From b7f4e3c8fd9b978709609d1a96e5ea038e8318a4 Mon Sep 17 00:00:00 2001 From: HanXinzi-AI Date: Fri, 26 Aug 2022 04:22:38 +0000 Subject: [PATCH 1/2] Update best-of list for version 2022.08.26 --- README.md | 8878 +++++++++++++++---------------- history/2022-08-26_changes.md | 20 + history/2022-08-26_projects.csv | 822 +++ latest-changes.md | 20 +- 4 files changed, 5291 insertions(+), 4449 deletions(-) create mode 100644 history/2022-08-26_changes.md create mode 100644 history/2022-08-26_projects.csv diff --git a/README.md b/README.md index 9583ca9..9c99ba2 100644 --- a/README.md +++ b/README.md @@ -14,286 +14,298 @@

-本资源清单包含820个python机器学习相关的开源工具资源，这些热门工具总共分成32个不同的子板块，这些项目目前在github上已经收到3.1M个点赞。所有的工具资源每周会自动从GitHub和工具维护平台采集信息，并更新排行展示。本清单参考[best-of模板](https://github.com/best-of-lists/best-of)完成，内容参考了[awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)，欢迎大家提PR丰富本清单。 -## 目录 - -- [机器学习框架](#机器学习框架) _54 个项目_ -- [数据可视化](#数据可视化) _49 个项目_ -- [文本数据和NLP](#文本数据和NLP) _82 个项目_ -- [图像数据与CV](#图像数据与CV) _49 个项目_ -- [图数据处理](#图数据处理) _29 个项目_ -- [音频处理](#音频处理) _23 个项目_ -- [地理Geo处理](#地理Geo处理) _22 个项目_ -- [金融数据处理](#金融数据处理) _23 个项目_ -- [时间序列](#时间序列) _20 个项目_ -- [医疗领域](#医疗领域) _19 个项目_ -- [光学字符识别OCR](#光学字符识别OCR) _11 个项目_ -- [数据容器和结构](#数据容器和结构) _28 个项目_ -- [数据读写与提取](#数据读写与提取) _23 个项目_ -- [网页抓取和爬虫](#网页抓取和爬虫) _1 个项目_ -- [数据管道和流处理](#数据管道和流处理) _36 个项目_ -- [分布式机器学习](#分布式机器学习) _26 个项目_ -- [超参数优化和AutoML](#超参数优化和AutoML) _45 个项目_ -- [强化学习](#强化学习) _19 个项目_ -- [推荐系统](#推荐系统) _13 个项目_ -- [隐私机器学习](#隐私机器学习) _6 个项目_ -- [工作流程和实验跟踪](#工作流程和实验跟踪) _35 个项目_ -- [模型序列化和转换](#模型序列化和转换) _11 个项目_ -- [模型的可解释性](#模型的可解释性) _46 个项目_ -- [向量相似度搜索（ANN）](#向量相似度搜索（ANN）) _12 个项目_ -- [概率统计](#概率统计) _21 个项目_ -- [对抗学习与鲁棒性](#对抗学习与鲁棒性) _7 个项目_ -- [GPU实用程序](#GPU实用程序) _18 个项目_ -- [Tensorflow实用程序](#Tensorflow实用程序) _13 个项目_ -- [Sklearn实用程序](#Sklearn实用程序) _17 个项目_ -- [Pytorch实用程序](#Pytorch实用程序) _27 个项目_ -- [数据库客户端](#数据库客户端) _1 个项目_ -- [中文自然语言处理](#中文自然语言处理) _2 个项目_ -- [Others](#Others) _33 个项目_ - -## 图标解释 -- 🥇🥈🥉  综合项目质量分 -- ⭐️  github上star的数量 -- 🐣  小于6个月的新项目 -- 💤  非活跃项目(6个月未更新) -- 💀  沉寂项目(12个月未更新) -- 📈📉  项目趋势(向上or向下) -- ➕  最近添加的项目 -- ❗️  警告(例如 项目没有license) -- 👨‍💻  项目的开发贡献者数量 -- 🔀  项目被fork的数量 -- 📋  项目issue的数量 -- ⏱️  项目包上次更新时间 -- 📥  工具库被下载次数 -- 📦  项目依赖的工具库数量 --   Tensorflow相关项目 --   Sklearn相关项目 --   pytorch相关项目 --   MxNet相关项目 --   Apache Spark相关项目 --   Jupyter相关项目 --   PaddlePaddle相关项目 --   Pandas相关项目 +本资源清单包含820个python机器学习相关的开源工具资源，这些热门工具总共分成32个不同的子板块，这些项目目前在github上已经收到3.5M个点赞。所有的工具资源每周会自动从GitHub和工具维护平台采集信息，并更新排行展示。本清单参考[best-of模板](https://github.com/best-of-lists/best-of)完成，内容参考了[awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)，欢迎大家提PR丰富本清单。 +## Contents + +- [Machine Learning Frameworks](#machine-learning-frameworks) _54 projects_ +- [Data Visualization](#data-visualization) _49 projects_ +- [Text Data & NLP](#text-data--nlp) _82 projects_ +- [Image Data](#image-data) _49 projects_ +- [Graph Data](#graph-data) _29 projects_ +- [Audio Data](#audio-data) _23 projects_ +- [Geospatial Data](#geospatial-data) _22 projects_ +- [Financial Data](#financial-data) _23 projects_ +- [Time Series Data](#time-series-data) _20 projects_ +- [Medical Data](#medical-data) _19 projects_ +- [Optical Character Recognition](#optical-character-recognition) _11 projects_ +- [Data Containers & Structures](#data-containers--structures) _28 projects_ +- [Data Loading & Extraction](#data-loading--extraction) _23 projects_ +- [Web Scraping & Crawling](#web-scraping--crawling) _1 projects_ +- [Data Pipelines & Streaming](#data-pipelines--streaming) _36 projects_ +- [Distributed Machine Learning](#distributed-machine-learning) _26 projects_ +- [Hyperparameter Optimization & AutoML](#hyperparameter-optimization--automl) _45 projects_ +- [Reinforcement Learning](#reinforcement-learning) _19 projects_ +- [Recommender Systems](#recommender-systems) _13 projects_ +- [Privacy Machine Learning](#privacy-machine-learning) _6 projects_ +- [Workflow & Experiment Tracking](#workflow--experiment-tracking) _35 projects_ +- [Model Serialization & Conversion](#model-serialization--conversion) _11 projects_ +- [Model Interpretability](#model-interpretability) _46 projects_ +- [Vector Similarity Search (ANN)](#vector-similarity-search-ann) _12 projects_ +- [Probabilistics & Statistics](#probabilistics--statistics) _21 projects_ +- [Adversarial Robustness](#adversarial-robustness) _7 projects_ +- [GPU Utilities](#gpu-utilities) _18 projects_ +- [Tensorflow Utilities](#tensorflow-utilities) _13 projects_ +- [Sklearn Utilities](#sklearn-utilities) _17 projects_ +- [Pytorch Utilities](#pytorch-utilities) _27 projects_ +- [Database Clients](#database-clients) _1 projects_ +- [Chinese NLP](#chinese-nlp) _2 projects_ +- [Others](#others) _33 projects_ + +## Explanation +- 🥇🥈🥉  Combined project-quality score +- ⭐️  Star count from GitHub +- 🐣  New project _(less than 6 months old)_ +- 💤  Inactive project _(6 months no activity)_ +- 💀  Dead project _(12 months no activity)_ +- 📈📉  Project is trending up or down +- ➕  Project was recently added +- ❗️  Warning _(e.g. missing/risky license)_ +- 👨‍💻  Contributors count from GitHub +- 🔀  Fork count from GitHub +- 📋  Issue count from GitHub +- ⏱️  Last update timestamp on package manager +- 📥  Download count from package manager +- 📦  Number of dependent projects +-   Tensorflow related project +-   Sklearn related project +-   PyTorch related project +-   MxNet related project +-   Apache Spark related project +-   Jupyter related project +-   PaddlePaddle related project +-   Pandas related project
-## 机器学习框架 +## Machine Learning Frameworks -Back to top +Back to top -_通用机器学习和深度学习框架。_ +_General-purpose machine learning and deep learning frameworks._ -
Tensorflow (🥇44 · ⭐ 160K) - 适用于所有人的开源机器学习框架。Apache-2 +
Tensorflow (🥇44 · ⭐ 170K) - An Open Source Machine Learning Framework for Everyone. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 3.9K · 🔀 69K · 📦 170K · 📋 34K - 7% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 4.1K · 🔀 70K · 📦 210K · 📋 35K - 5% open · ⏱️ 26.08.2022): ``` git clone https://github.com/tensorflow/tensorflow ``` -- [PyPi](https://pypi.org/project/tensorflow) (📥 15M / month): +- [PyPi](https://pypi.org/project/tensorflow) (📥 14M / month): ``` pip install tensorflow ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow) (📥 2.9M · ⏱️ 08.12.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow) (📥 3.6M · ⏱️ 20.07.2022): ``` conda install -c conda-forge tensorflow ``` -- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (📥 63M · ⭐ 2K · ⏱️ 16.12.2021): +- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (📥 67M · ⭐ 2K · ⏱️ 25.08.2022): ``` docker pull tensorflow/tensorflow ```
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scikit-learn (🥇38 · ⭐ 48K) - scikit-learn：基于Python的机器学习工具库。BSD-3 +
scikit-learn (🥇39 · ⭐ 51K) - scikit-learn: machine learning in Python. BSD-3 -- [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.4K · 🔀 22K · 📥 760 · 📦 290K · 📋 9K - 18% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.7K · 🔀 23K · 📥 810 · 📦 390K · 📋 9.6K - 16% open · ⏱️ 26.08.2022): ``` git clone https://github.com/scikit-learn/scikit-learn ``` -- [PyPi](https://pypi.org/project/scikit-learn) (📥 25M / month): +- [PyPi](https://pypi.org/project/scikit-learn) (📥 31M / month): ``` pip install scikit-learn ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn) (📥 11M · ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-learn) (📥 15M · ⏱️ 05.08.2022): ``` conda install -c conda-forge scikit-learn ```
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XGBoost (🥇37 · ⭐ 22K) - 可扩展，高效和分布式梯度增强（GBDT，GBRT等）的boosting工具库。Apache-2 +
XGBoost (🥇37 · ⭐ 23K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 -- [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 540 · 🔀 7.7K · 📥 3.5K · 📦 25K · 📋 4.2K - 6% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 570 · 🔀 7.9K · 📥 5K · 📦 35K · 📋 4.5K - 5% open · ⏱️ 25.08.2022): ``` git clone https://github.com/dmlc/xgboost ``` -- [PyPi](https://pypi.org/project/xgboost) (📥 8.8M / month): +- [PyPi](https://pypi.org/project/xgboost) (📥 8.3M / month): ``` pip install xgboost ``` -- [Conda](https://anaconda.org/conda-forge/xgboost) (📥 2.2M · ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/xgboost) (📥 2.9M · ⏱️ 12.08.2022): ``` conda install -c conda-forge xgboost ```
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LightGBM (🥇36 · ⭐ 13K) - 快速，分布式，高性能梯度提升（GBT，GBDT，GBRT等）的boosting工具库。MIT +
LightGBM (🥇35 · ⭐ 14K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT -- [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 250 · 🔀 3.4K · 📥 130K · 📦 10K · 📋 2.5K - 5% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 270 · 🔀 3.5K · 📥 160K · 📦 15K · 📋 2.8K - 7% open · ⏱️ 25.08.2022): ``` git clone https://github.com/microsoft/LightGBM ``` -- [PyPi](https://pypi.org/project/lightgbm) (📥 11M / month): +- [PyPi](https://pypi.org/project/lightgbm) (📥 6M / month): ``` pip install lightgbm ``` -- [Conda](https://anaconda.org/conda-forge/lightgbm) (📥 830K · ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/lightgbm) (📥 1.2M · ⏱️ 08.01.2022): ``` conda install -c conda-forge lightgbm ```
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pytorch-lightning (🥇35 · ⭐ 17K) - 轻巧而具备高性能的PyTorch上层封装工具库。Apache-2 +
Fastai (🥇34 · ⭐ 23K) - The fastai deep learning library. Apache-2 -- [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (👨‍💻 590 · 🔀 2K · 📥 4.9K · 📦 6K · 📋 4.3K - 8% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/fastai/fastai) (👨‍💻 210 · 🔀 7.1K · 📦 11K · 📋 1.7K - 6% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/PyTorchLightning/pytorch-lightning - ``` -- [PyPi](https://pypi.org/project/pytorch-lightning) (📥 870K / month): - ``` - pip install pytorch-lightning + git clone https://github.com/fastai/fastai ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (📥 380K · ⏱️ 16.12.2021): +- [PyPi](https://pypi.org/project/fastai) (📥 280K / month): ``` - conda install -c conda-forge pytorch-lightning + pip install fastai ```
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Thinc (🥇34 · ⭐ 2.4K) - 深度学习工具库。MIT +
Thinc (🥇34 · ⭐ 2.6K) - A refreshing functional take on deep learning, compatible with your favorite.. MIT -- [GitHub](https://github.com/explosion/thinc) (👨‍💻 42 · 🔀 220 · 📦 18K · 📋 110 - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/explosion/thinc) (👨‍💻 53 · 🔀 240 · 📦 23K · 📋 120 - 11% open · ⏱️ 05.08.2022): ``` git clone https://github.com/explosion/thinc ``` -- [PyPi](https://pypi.org/project/thinc) (📥 5.7M / month): +- [PyPi](https://pypi.org/project/thinc) (📥 4.1M / month): ``` pip install thinc ``` -- [Conda](https://anaconda.org/conda-forge/thinc) (📥 1.8M · ⏱️ 08.12.2021): +- [Conda](https://anaconda.org/conda-forge/thinc) (📥 2.2M · ⏱️ 08.07.2022): ``` conda install -c conda-forge thinc ```
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PyTorch (🥈33 · ⭐ 53K) - 具有强大GPU的Python中的张量和动态神经网络构建工具库。BSD-3 +
PyTorch (🥈33 · ⭐ 58K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 -- [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 3K · 🔀 14K · 📥 600 · 📋 24K - 31% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 3.5K · 🔀 16K · 📥 5.6K · 📋 28K - 32% open · ⏱️ 26.08.2022): ``` git clone https://github.com/pytorch/pytorch ``` -- [PyPi](https://pypi.org/project/torch) (📥 6.3M / month): +- [PyPi](https://pypi.org/project/torch) (📥 8.5M / month): ``` pip install torch ``` -- [Conda](https://anaconda.org/pytorch/pytorch) (📥 14M · ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/pytorch/pytorch) (📥 19M · ⏱️ 04.08.2022): ``` conda install -c pytorch pytorch ```
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StatsModels (🥈33 · ⭐ 6.9K) - Statsmodels：Python中的统计建模和计量经济学工具库。BSD-3 +
dlib (🥈33 · ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 -- [GitHub](https://github.com/statsmodels/statsmodels) (👨‍💻 350 · 🔀 2.2K · 📥 26 · 📦 55K · 📋 4.5K - 46% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/davisking/dlib) (👨‍💻 180 · 🔀 2.7K · 📥 25K · 📦 16K · 📋 2.1K - 1% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/statsmodels/statsmodels + git clone https://github.com/davisking/dlib ``` -- [PyPi](https://pypi.org/project/statsmodels) (📥 7.5M / month): +- [PyPi](https://pypi.org/project/dlib) (📥 91K / month): ``` - pip install statsmodels + pip install dlib ``` -- [Conda](https://anaconda.org/conda-forge/statsmodels) (📥 5.4M · ⏱️ 13.11.2021): +- [Conda](https://anaconda.org/conda-forge/dlib) (📥 460K · ⏱️ 08.05.2022): ``` - conda install -c conda-forge statsmodels + conda install -c conda-forge dlib ```
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PaddlePaddle (🥈32 · ⭐ 17K) - paddlepaddle机器学习与深度学习工具库。Apache-2 +
Keras (🥈32 · ⭐ 56K) - Deep Learning for humans. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 670 · 🔀 4K · 📥 15K · 📦 83 · 📋 14K - 14% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/keras-team/keras) (👨‍💻 1.1K · 🔀 18K · 📋 11K - 2% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/PaddlePaddle/Paddle + git clone https://github.com/keras-team/keras ``` -- [PyPi](https://pypi.org/project/paddlepaddle) (📥 110K / month): +- [PyPi](https://pypi.org/project/keras) (📥 8.4M / month): ``` - pip install paddlepaddle + pip install keras + ``` +- [Conda](https://anaconda.org/conda-forge/keras) (📥 2.5M · ⏱️ 19.05.2022): + ``` + conda install -c conda-forge keras ```
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PySpark (🥈31 · ⭐ 32K) - Apache Spark Python API。Apache-2 +
PySpark (🥈32 · ⭐ 34K) - Apache Spark Python API. Apache-2 -- [GitHub](https://github.com/apache/spark) (👨‍💻 2.6K · 🔀 24K · ⏱️ 16.12.2021): +- [GitHub](https://github.com/apache/spark) (👨‍💻 2.7K · 🔀 25K · ⏱️ 26.08.2022): ``` git clone https://github.com/apache/spark ``` -- [PyPi](https://pypi.org/project/pyspark) (📥 15M / month): +- [PyPi](https://pypi.org/project/pyspark) (📥 25M / month): ``` pip install pyspark ``` -- [Conda](https://anaconda.org/conda-forge/pyspark) (📥 1.4M · ⏱️ 18.10.2021): +- [Conda](https://anaconda.org/conda-forge/pyspark) (📥 1.9M · ⏱️ 27.07.2022): ``` conda install -c conda-forge pyspark ```
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dlib (🥈31 · ⭐ 11K) - 进行现实世界机器学习和数据分析的工具包。❗️BSL-1.0 +
PaddlePaddle (🥈32 · ⭐ 19K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- [GitHub](https://github.com/davisking/dlib) (👨‍💻 170 · 🔀 2.6K · 📥 25K · 📦 12K · 📋 2K - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 810 · 🔀 4.5K · 📥 15K · 📦 140 · 📋 15K - 14% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/davisking/dlib + git clone https://github.com/PaddlePaddle/Paddle ``` -- [PyPi](https://pypi.org/project/dlib) (📥 130K / month): +- [PyPi](https://pypi.org/project/paddlepaddle) (📥 79K / month): ``` - pip install dlib + pip install paddlepaddle ``` -- [Conda](https://anaconda.org/conda-forge/dlib) (📥 380K · ⏱️ 03.04.2021): +
+
Jina (🥈32 · ⭐ 16K) - An easier way to build neural search on the cloud. Apache-2 + +- [GitHub](https://github.com/jina-ai/jina) (👨‍💻 150 · 🔀 1.9K · 📦 350 · 📋 1.6K - 1% open · ⏱️ 25.08.2022): + ``` - conda install -c conda-forge dlib + git clone https://github.com/jina-ai/jina + ``` +- [PyPi](https://pypi.org/project/jina) (📥 88K / month): + ``` + pip install jina + ``` +- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (📥 1.1M · ⭐ 7 · ⏱️ 23.08.2022): + ``` + docker pull jinaai/jina ```
-
Theano (🥈31 · ⭐ 9.5K) - Theano是一个Python神经网络工具库。❗Unlicensed +
StatsModels (🥈32 · ⭐ 7.7K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 -- [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 12K · 📋 2.7K - 21% open · ⏱️ 23.11.2021): +- [GitHub](https://github.com/statsmodels/statsmodels) (👨‍💻 380 · 🔀 2.4K · 📥 26 · 📦 68K · 📋 4.8K - 46% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/Theano/Theano + git clone https://github.com/statsmodels/statsmodels ``` -- [PyPi](https://pypi.org/project/theano) (📥 230K / month): +- [PyPi](https://pypi.org/project/statsmodels) (📥 8.8M / month): ``` - pip install theano + pip install statsmodels ``` -- [Conda](https://anaconda.org/conda-forge/theano) (📥 1.8M · ⏱️ 10.11.2021): +- [Conda](https://anaconda.org/conda-forge/statsmodels) (📥 7M · ⏱️ 09.06.2022): ``` - conda install -c conda-forge theano + conda install -c conda-forge statsmodels ```
-
jax (🥈30 · ⭐ 16K) - Python + NumPy程序工具库。Apache-2 +
jax (🥈31 · ⭐ 20K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 -- [GitHub](https://github.com/google/jax) (👨‍💻 340 · 🔀 1.4K · 📦 3.1K · 📋 2.8K - 28% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/google/jax) (👨‍💻 440 · 🔀 1.8K · 📦 5.3K · 📋 3.4K - 24% open · ⏱️ 26.08.2022): ``` git clone https://github.com/google/jax ``` -- [PyPi](https://pypi.org/project/jax) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/jax) (📥 610K / month): ``` pip install jax ``` -- [Conda](https://anaconda.org/conda-forge/jaxlib) (📥 250K · ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/jaxlib) (📥 410K · ⏱️ 25.08.2022): ``` conda install -c conda-forge jaxlib ```
-
Chainer (🥈30 · ⭐ 5.7K) - 灵活的深度学习神经网络框架。MIT +
Chainer (🥈31 · ⭐ 5.7K) - A flexible framework of neural networks for deep learning. MIT -- [GitHub](https://github.com/chainer/chainer) (👨‍💻 320 · 🔀 1.3K · 📦 2.4K · 📋 2K - 0% open · ⏱️ 10.06.2021): +- [GitHub](https://github.com/chainer/chainer) (👨‍💻 320 · 🔀 1.3K · 📦 2.7K · 📋 2K - 0% open · ⏱️ 29.06.2022): ``` git clone https://github.com/chainer/chainer @@ -303,362 +315,362 @@ _通用机器学习和深度学习框架。_ pip install chainer ```
-
Keras (🥈29 · ⭐ 53K) - 易上手的深度学习工具库。❗Unlicensed +
Theano (🥈30 · ⭐ 9.6K · 💤) - Theano is a Python library that allows you to define,.. ❗Unlicensed -- [GitHub](https://github.com/keras-team/keras) (👨‍💻 1K · 🔀 18K · 📋 11K - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 13K · 📋 2.7K - 21% open · ⏱️ 23.11.2021): ``` - git clone https://github.com/keras-team/keras + git clone https://github.com/Theano/Theano ``` -- [PyPi](https://pypi.org/project/keras) (📥 7.6M / month): +- [PyPi](https://pypi.org/project/theano) (📥 270K / month): ``` - pip install keras + pip install theano ``` -- [Conda](https://anaconda.org/conda-forge/keras) (📥 2M · ⏱️ 25.11.2021): +- [Conda](https://anaconda.org/conda-forge/theano) (📥 2.1M · ⏱️ 16.03.2022): ``` - conda install -c conda-forge keras + conda install -c conda-forge theano ```
-
Jina (🥈29 · ⭐ 13K) - 在云端构建神经搜索的简便方法库。Apache-2 +
einops (🥈30 · ⭐ 5.5K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT -- [GitHub](https://github.com/jina-ai/jina) (👨‍💻 130 · 🔀 1.7K · 📦 190 · 📋 1.2K - 5% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/arogozhnikov/einops) (👨‍💻 20 · 🔀 240 · 📦 3.9K · 📋 120 - 28% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/jina-ai/jina + git clone https://github.com/arogozhnikov/einops ``` -- [PyPi](https://pypi.org/project/jina) (📥 13K / month): +- [PyPi](https://pypi.org/project/einops) (📥 1M / month): ``` - pip install jina + pip install einops ``` -- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (📥 990K · ⭐ 6 · ⏱️ 16.12.2021): +- [Conda](https://anaconda.org/conda-forge/einops) (📥 25K · ⏱️ 04.03.2022): ``` - docker pull jinaai/jina + conda install -c conda-forge einops ```
-
Catboost (🥈29 · ⭐ 6.3K) - 快速，可扩展，高性能的梯度决策提升工具库。Apache-2 +
MXNet (🥈29 · ⭐ 20K) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning.. Apache-2 -- [GitHub](https://github.com/catboost/catboost) (👨‍💻 930 · 🔀 910 · 📥 70K · 📋 1.7K - 19% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/apache/incubator-mxnet) (👨‍💻 980 · 🔀 6.5K · 📥 25K · 📋 9.5K - 18% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/catboost/catboost + git clone https://github.com/apache/incubator-mxnet ``` -- [PyPi](https://pypi.org/project/catboost) (📥 3.3M / month): +- [PyPi](https://pypi.org/project/mxnet) (📥 410K / month): ``` - pip install catboost + pip install mxnet ``` -- [Conda](https://anaconda.org/conda-forge/catboost) (📥 880K · ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/anaconda/mxnet) (📥 8K · ⏱️ 02.05.2022): ``` - conda install -c conda-forge catboost + conda install -c anaconda mxnet ```
-
einops (🥈29 · ⭐ 4K) - 重塑了深度学习操作（用于pytorch，tensorflow，jax等）的工具库。MIT +
pytorch-lightning (🥈29 · ⭐ 20K · 📉) - The lightweight PyTorch wrapper for high-performance.. Apache-2 -- [GitHub](https://github.com/arogozhnikov/einops) (👨‍💻 13 · 🔀 160 · 📦 1.6K · 📋 87 - 33% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/Lightning-AI/lightning) (👨‍💻 740 · 🔀 2.5K · 📥 8K · 📋 5.3K - 8% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/arogozhnikov/einops + git clone https://github.com/PyTorchLightning/pytorch-lightning ``` -- [PyPi](https://pypi.org/project/einops) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/pytorch-lightning) (📥 1.8M / month): ``` - pip install einops + pip install pytorch-lightning ``` -- [Conda](https://anaconda.org/conda-forge/einops) (📥 9.3K · ⏱️ 31.08.2021): +- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (📥 520K · ⏱️ 18.08.2022): ``` - conda install -c conda-forge einops + conda install -c conda-forge pytorch-lightning ```
-
Fastai (🥈28 · ⭐ 22K) - Fastai深度学习库。Apache-2 +
Vowpal Wabbit (🥈28 · ⭐ 8K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 -- [GitHub](https://github.com/fastai/fastai) (👨‍💻 180 · 🔀 7K · 📋 1.5K - 5% open · ⏱️ 29.11.2021): +- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 320 · 🔀 1.7K · 📋 1.2K - 10% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/fastai/fastai + git clone https://github.com/VowpalWabbit/vowpal_wabbit ``` -- [PyPi](https://pypi.org/project/fastai) (📥 240K / month): +- [PyPi](https://pypi.org/project/vowpalwabbit) (📥 92K / month): ``` - pip install fastai + pip install vowpalwabbit ```
-
MXNet (🥈28 · ⭐ 20K) - 轻巧，灵活的分布式/移动深度学习工具库。Apache-2 +
Catboost (🥈28 · ⭐ 6.7K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 -- [GitHub](https://github.com/apache/incubator-mxnet) (👨‍💻 970 · 🔀 6.5K · 📥 24K · 📋 9.4K - 18% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/catboost/catboost) (👨‍💻 1K · 🔀 990 · 📥 86K · 📋 1.9K - 21% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/apache/incubator-mxnet + git clone https://github.com/catboost/catboost ``` -- [PyPi](https://pypi.org/project/mxnet) (📥 340K / month): +- [PyPi](https://pypi.org/project/catboost) (📥 2.7M / month): ``` - pip install mxnet + pip install catboost ``` -- [Conda](https://anaconda.org/anaconda/mxnet) (📥 6.8K · ⏱️ 29.02.2020): +- [Conda](https://anaconda.org/conda-forge/catboost) (📥 1.1M · ⏱️ 19.05.2022): ``` - conda install -c anaconda mxnet + conda install -c conda-forge catboost ```
-
tensorpack (🥈28 · ⭐ 6.1K) - TensorFlow上的神经网络训练接口。Apache-2 +
Flax (🥈28 · ⭐ 3.5K) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax -- [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 58 · 🔀 1.8K · 📥 130 · 📦 920 · 📋 1.3K - 0% open · ⏱️ 27.11.2021): +- [GitHub](https://github.com/google/flax) (👨‍💻 170 · 🔀 380 · 📥 42 · 📦 1.3K · 📋 550 - 17% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/tensorpack/tensorpack + git clone https://github.com/google/flax ``` -- [PyPi](https://pypi.org/project/tensorpack) (📥 27K / month): +- [PyPi](https://pypi.org/project/flax) (📥 310K / month): ``` - pip install tensorpack + pip install flax ```
-
PyFlink (🥈27 · ⭐ 18K) - Apache Flink Python API。Apache-2 +
dyNET (🥈28 · ⭐ 3.3K) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 -- [GitHub](https://github.com/apache/flink) (👨‍💻 1.4K · 🔀 9.8K · ⏱️ 16.12.2021): +- [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 6.9K · 📦 220 · 📋 920 - 27% open · ⏱️ 14.08.2022): ``` - git clone https://github.com/apache/flink + git clone https://github.com/clab/dynet ``` -- [PyPi](https://pypi.org/project/apache-flink) (📥 8.2K / month): +- [PyPi](https://pypi.org/project/dyNET) (📥 20K / month): ``` - pip install apache-flink + pip install dyNET ```
-
Sonnet (🥈27 · ⭐ 9.1K) - 基于TensorFlow的神经网络库。Apache-2 +
PyFlink (🥉27 · ⭐ 20K) - Apache Flink Python API. Apache-2 -- [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 53 · 🔀 1.2K · 📦 730 · 📋 170 - 11% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/apache/flink) (👨‍💻 1.6K · 🔀 11K · ⏱️ 26.08.2022): ``` - git clone https://github.com/deepmind/sonnet - ``` -- [PyPi](https://pypi.org/project/dm-sonnet) (📥 380K / month): - ``` - pip install dm-sonnet + git clone https://github.com/apache/flink ``` -- [Conda](https://anaconda.org/conda-forge/sonnet) (📥 13K · ⏱️ 14.11.2020): +- [PyPi](https://pypi.org/project/apache-flink) (📥 54K / month): ``` - conda install -c conda-forge sonnet + pip install apache-flink ```
-
Vowpal Wabbit (🥈27 · ⭐ 7.8K) - Vowpal Wabbit是一个推动机器学习的机器学习系统。BSD-3 +
TFlearn (🥉27 · ⭐ 9.6K · 💀) - Deep learning library featuring a higher-level API for.. ❗Unlicensed -- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 310 · 🔀 1.7K · 📋 1.1K - 12% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/tflearn/tflearn) (👨‍💻 130 · 🔀 2.3K · 📦 4.1K · 📋 910 - 60% open · ⏱️ 30.11.2020): ``` - git clone https://github.com/VowpalWabbit/vowpal_wabbit + git clone https://github.com/tflearn/tflearn ``` -- [PyPi](https://pypi.org/project/vowpalwabbit) (📥 54K / month): +- [PyPi](https://pypi.org/project/tflearn) (📥 16K / month): ``` - pip install vowpalwabbit + pip install tflearn ```
-
skorch (🥈27 · ⭐ 4.2K) - 封装成scikit-learn接口模式的神经网络库。BSD-3 +
Sonnet (🥉27 · ⭐ 9.4K) - TensorFlow-based neural network library. Apache-2 -- [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 47 · 🔀 290 · 📦 420 · 📋 420 - 11% open · ⏱️ 28.11.2021): +- [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 54 · 🔀 1.2K · 📦 900 · 📋 180 - 14% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/skorch-dev/skorch + git clone https://github.com/deepmind/sonnet ``` -- [PyPi](https://pypi.org/project/skorch) (📥 19K / month): +- [PyPi](https://pypi.org/project/dm-sonnet) (📥 24K / month): ``` - pip install skorch + pip install dm-sonnet ``` -- [Conda](https://anaconda.org/conda-forge/skorch) (📥 490K · ⏱️ 30.11.2021): +- [Conda](https://anaconda.org/conda-forge/sonnet) (📥 16K · ⏱️ 14.11.2020): ``` - conda install -c conda-forge skorch + conda install -c conda-forge sonnet ```
-
dyNET (🥈27 · ⭐ 3.3K · 💤) - DyNet：动态神经网络工具包。Apache-2 +
Ludwig (🥉27 · ⭐ 8.5K) - Ludwig is a toolbox that allows to train and evaluate deep.. Apache-2 -- [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 4.3K · 📦 200 · 📋 920 - 27% open · ⏱️ 27.01.2021): +- [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 130 · 🔀 960 · 📦 130 · 📋 820 - 23% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/clab/dynet + git clone https://github.com/ludwig-ai/ludwig ``` -- [PyPi](https://pypi.org/project/dyNET) (📥 20K / month): +- [PyPi](https://pypi.org/project/ludwig) (📥 1.8K / month): ``` - pip install dyNET + pip install ludwig ```
-
Flax (🥈27 · ⭐ 2.4K · 📈) - Flax是专为.NET设计的用于JAX的神经网络库。Apache-2 jax +
tensorpack (🥉27 · ⭐ 6.2K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 -- [GitHub](https://github.com/google/flax) (👨‍💻 120 · 🔀 270 · 📥 31 · 📦 560 · 📋 410 - 32% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 58 · 🔀 1.8K · 📥 140 · 📦 1.1K · 📋 1.3K - 0% open · ⏱️ 04.05.2022): ``` - git clone https://github.com/google/flax + git clone https://github.com/tensorpack/tensorpack ``` -- [PyPi](https://pypi.org/project/flax) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/tensorpack) (📥 19K / month): ``` - pip install flax + pip install tensorpack ```
-
TFlearn (🥉26 · ⭐ 9.6K · 💀) - 深度学习库，基于TensorFlow构建上层简单易用的API。❗Unlicensed +
skorch (🥉26 · ⭐ 4.6K) - A scikit-learn compatible neural network library that wraps.. BSD-3 -- [GitHub](https://github.com/tflearn/tflearn) (👨‍💻 130 · 🔀 2.3K · 📦 3.7K · 📋 910 - 60% open · ⏱️ 30.11.2020): +- [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 50 · 🔀 310 · 📦 550 · 📋 440 - 9% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/tflearn/tflearn + git clone https://github.com/skorch-dev/skorch ``` -- [PyPi](https://pypi.org/project/tflearn) (📥 13K / month): +- [PyPi](https://pypi.org/project/skorch) (📥 31K / month): ``` - pip install tflearn + pip install skorch + ``` +- [Conda](https://anaconda.org/conda-forge/skorch) (📥 610K · ⏱️ 30.11.2021): + ``` + conda install -c conda-forge skorch ```
-
Ignite (🥉26 · ⭐ 3.8K) - 用于训练和评估神经等一系列操作的高级深度学习工具库。BSD-3 +
Ignite (🥉26 · ⭐ 4K) - High-level library to help with training and evaluating neural.. BSD-3 -- [GitHub](https://github.com/pytorch/ignite) (👨‍💻 160 · 🔀 500 · 📋 950 - 11% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/pytorch/ignite) (👨‍💻 180 · 🔀 540 · 📋 1.1K - 10% open · ⏱️ 25.08.2022): ``` git clone https://github.com/pytorch/ignite ``` -- [PyPi](https://pypi.org/project/pytorch-ignite) (📥 76K / month): +- [PyPi](https://pypi.org/project/pytorch-ignite) (📥 150K / month): ``` pip install pytorch-ignite ``` -- [Conda](https://anaconda.org/pytorch/ignite) (📥 75K · ⏱️ 19.10.2021): +- [Conda](https://anaconda.org/pytorch/ignite) (📥 99K · ⏱️ 04.05.2022): ``` conda install -c pytorch ignite ```
-
ktrain (🥉26 · ⭐ 930) - ktrain是一个Python库，可以使深度学习和AI更简单。Apache-2 +
ktrain (🥉26 · ⭐ 1K) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 -- [GitHub](https://github.com/amaiya/ktrain) (👨‍💻 12 · 🔀 220 · 📦 240 · 📋 380 - 1% open · ⏱️ 23.11.2021): +- [GitHub](https://github.com/amaiya/ktrain) (👨‍💻 15 · 🔀 240 · 📦 330 · 📋 420 - 0% open · ⏱️ 04.08.2022): ``` git clone https://github.com/amaiya/ktrain ``` -- [PyPi](https://pypi.org/project/ktrain) (📥 26K / month): +- [PyPi](https://pypi.org/project/ktrain) (📥 20K / month): ``` pip install ktrain ```
-
Turi Create (🥉25 · ⭐ 11K) - Turi Create简化了自定义机器学习的开发。BSD-3 +
Turi Create (🥉25 · ⭐ 11K · 💤) - Turi Create simplifies the development of custom machine.. BSD-3 -- [GitHub](https://github.com/apple/turicreate) (👨‍💻 82 · 🔀 1.1K · 📥 4.9K · 📦 280 · 📋 1.8K - 26% open · ⏱️ 29.11.2021): +- [GitHub](https://github.com/apple/turicreate) (👨‍💻 85 · 🔀 1.1K · 📥 6.8K · 📦 320 · 📋 1.8K - 27% open · ⏱️ 29.11.2021): ``` git clone https://github.com/apple/turicreate ``` -- [PyPi](https://pypi.org/project/turicreate) (📥 26K / month): +- [PyPi](https://pypi.org/project/turicreate) (📥 20K / month): ``` pip install turicreate ```
-
Ludwig (🥉24 · ⭐ 8K) - 路德维希（Ludwig）是一个工具箱，可用于深度学习训练和评估。Apache-2 +
xLearn (🥉25 · ⭐ 3K) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 -- [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 110 · 🔀 910 · 📦 98 · 📋 630 - 23% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 3.4K · 📦 93 · 📋 300 - 61% open · ⏱️ 05.06.2022): ``` - git clone https://github.com/ludwig-ai/ludwig + git clone https://github.com/aksnzhy/xlearn ``` -- [PyPi](https://pypi.org/project/ludwig) (📥 3.8K / month): +- [PyPi](https://pypi.org/project/xlearn) (📥 5.2K / month): ``` - pip install ludwig + pip install xlearn ```
-
NuPIC (🥉24 · ⭐ 6.3K · 💀) - Numenta智能计算平台。❗️AGPL-3.0 +
NuPIC (🥉24 · ⭐ 6.3K · 💀) - Numenta Platform for Intelligent Computing is an implementation.. ❗️AGPL-3.0 - [GitHub](https://github.com/numenta/nupic) (👨‍💻 120 · 🔀 1.6K · 📦 110 · 📋 1.8K - 25% open · ⏱️ 23.10.2019): ``` git clone https://github.com/numenta/nupic ``` -- [PyPi](https://pypi.org/project/nupic) (📥 3.3K / month): +- [PyPi](https://pypi.org/project/nupic) (📥 1.4K / month): ``` pip install nupic ```
-
xLearn (🥉24 · ⭐ 3K · 💀) - 高性能，易于使用且可扩展的机器学习（ML）工具库。Apache-2 +
fklearn (🥉24 · ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 -- [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 3K · 📦 72 · 📋 300 - 62% open · ⏱️ 03.03.2020): +- [GitHub](https://github.com/nubank/fklearn) (👨‍💻 47 · 🔀 160 · 📦 13 · 📋 48 - 54% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/aksnzhy/xlearn + git clone https://github.com/nubank/fklearn ``` -- [PyPi](https://pypi.org/project/xlearn) (📥 2.9K / month): +- [PyPi](https://pypi.org/project/fklearn) (📥 12K / month): ``` - pip install xlearn + pip install fklearn ```
-
tensorflow-upstream (🥉24 · ⭐ 580) - TensorFlow ROCm端口。Apache-2 +
tensorflow-upstream (🥉24 · ⭐ 610) - TensorFlow ROCm port. Apache-2 -- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 3.9K · 🔀 66 · 📥 17 · 📋 310 - 15% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 4.1K · 🔀 71 · 📥 20 · 📋 330 - 16% open · ⏱️ 23.08.2022): ``` git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` -- [PyPi](https://pypi.org/project/tensorflow-rocm) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/tensorflow-rocm) (📥 1.7K / month): ``` pip install tensorflow-rocm ```
-
mlpack (🥉23 · ⭐ 3.9K) - mlpack：可扩展的C++机器学习库-。❗Unlicensed +
mlpack (🥉23 · ⭐ 4.1K) - mlpack: a scalable C++ machine learning library --. ❗Unlicensed -- [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 280 · 🔀 1.4K · 📋 1.4K - 3% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 290 · 🔀 1.4K · 📋 1.4K - 2% open · ⏱️ 18.08.2022): ``` git clone https://github.com/mlpack/mlpack ``` -- [PyPi](https://pypi.org/project/mlpack) (📥 270 / month): +- [PyPi](https://pypi.org/project/mlpack) (📥 630 / month): ``` pip install mlpack ``` -- [Conda](https://anaconda.org/conda-forge/mlpack) (📥 96K · ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/conda-forge/mlpack) (📥 110K · ⏱️ 09.11.2021): ``` conda install -c conda-forge mlpack ```
-
Neural Network Libraries (🥉23 · ⭐ 2.5K) - 神经网络工具库。Apache-2 +
Neural Network Libraries (🥉23 · ⭐ 2.6K) - Neural Network Libraries. Apache-2 -- [GitHub](https://github.com/sony/nnabla) (👨‍💻 63 · 🔀 300 · 📥 530 · 📋 61 - 27% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/sony/nnabla) (👨‍💻 67 · 🔀 310 · 📥 540 · 📋 72 - 31% open · ⏱️ 25.08.2022): ``` git clone https://github.com/sony/nnabla ``` -- [PyPi](https://pypi.org/project/nnabla) (📥 3.5K / month): +- [PyPi](https://pypi.org/project/nnabla) (📥 2.8K / month): ``` pip install nnabla ```
-
fklearn (🥉23 · ⭐ 1.4K) - fklearn：机器学习工具库。Apache-2 +
Neural Tangents (🥉23 · ⭐ 1.8K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 -- [GitHub](https://github.com/nubank/fklearn) (👨‍💻 40 · 🔀 150 · 📦 10 · 📋 40 - 47% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/google/neural-tangents) (👨‍💻 23 · 🔀 200 · 📥 240 · 📦 47 · 📋 120 - 34% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/nubank/fklearn + git clone https://github.com/google/neural-tangents ``` -- [PyPi](https://pypi.org/project/fklearn) (📥 4K / month): +- [PyPi](https://pypi.org/project/neural-tangents) (📥 1.5K / month): ``` - pip install fklearn + pip install neural-tangents ```
-
CNTK (🥉22 · ⭐ 17K · 💀) - Microsoft认知工具包（CNTK），一种开源的深度学习工具包。❗Unlicensed +
CNTK (🥉22 · ⭐ 17K · 💀) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning.. ❗Unlicensed - [GitHub](https://github.com/microsoft/CNTK) (👨‍💻 270 · 🔀 4.3K · 📥 14K · 📋 3.3K - 22% open · ⏱️ 31.03.2020): ``` git clone https://github.com/microsoft/CNTK ``` -- [PyPi](https://pypi.org/project/cntk) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/cntk) (📥 730 / month): ``` pip install cntk ```
-
Lasagne (🥉22 · ⭐ 3.8K · 💀) - 轻量级的库，用于在Theano中构建和训练神经网络。❗Unlicensed +
Lasagne (🥉22 · ⭐ 3.8K · 💀) - Lightweight library to build and train neural networks in.. ❗Unlicensed -- [GitHub](https://github.com/Lasagne/Lasagne) (👨‍💻 72 · 🔀 940 · 📦 880 · 📋 520 - 22% open · ⏱️ 20.11.2019): +- [GitHub](https://github.com/Lasagne/Lasagne) (👨‍💻 72 · 🔀 930 · 📦 920 · 📋 520 - 22% open · ⏱️ 20.11.2019): ``` git clone https://github.com/Lasagne/Lasagne ``` -- [PyPi](https://pypi.org/project/lasagne) (📥 3K / month): +- [PyPi](https://pypi.org/project/lasagne) (📥 1.4K / month): ``` pip install lasagne ```
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SHOGUN (🥉22 · ⭐ 2.9K · 💤) - 统一高效的机器学习。BSD-3 +
SHOGUN (🥉22 · ⭐ 2.9K · 💀) - Unified and efficient Machine Learning. BSD-3 - [GitHub](https://github.com/shogun-toolbox/shogun) (👨‍💻 250 · 🔀 1K · 📋 1.5K - 27% open · ⏱️ 08.12.2020): ``` git clone https://github.com/shogun-toolbox/shogun ``` -- [Conda](https://anaconda.org/conda-forge/shogun) (📥 110K · ⏱️ 25.06.2018): +- [Conda](https://anaconda.org/conda-forge/shogun) (📥 120K · ⏱️ 25.06.2018): ``` conda install -c conda-forge shogun ``` @@ -667,141 +679,129 @@ _通用机器学习和深度学习框架。_ docker pull shogun/shogun ```
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NeuPy (🥉21 · ⭐ 700 · 💀) - NeuPy是一个基于Tensorflow的python库，用于原型设计和构建。MIT +
NeuPy (🥉22 · ⭐ 710 · 💀) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT -- [GitHub](https://github.com/itdxer/neupy) (👨‍💻 7 · 🔀 150 · 📦 120 · 📋 260 - 11% open · ⏱️ 02.09.2019): +- [GitHub](https://github.com/itdxer/neupy) (👨‍💻 7 · 🔀 150 · 📦 130 · 📋 270 - 12% open · ⏱️ 02.09.2019): ``` git clone https://github.com/itdxer/neupy ``` -- [PyPi](https://pypi.org/project/neupy) (📥 3K / month): +- [PyPi](https://pypi.org/project/neupy) (📥 3.5K / month): ``` pip install neupy ```
-
mace (🥉20 · ⭐ 4.5K) - MACE是针对移动设备优化的深度学习推理框架。Apache-2 +
Haiku (🥉21 · ⭐ 2.1K) - JAX-based neural network library. Apache-2 -- [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 63 · 🔀 770 · 📥 1.4K · 📋 650 - 5% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 63 · 🔀 170 · 📦 540 · 📋 180 - 26% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/XiaoMi/mace + git clone https://github.com/deepmind/dm-haiku ```
-
Haiku (🥉20 · ⭐ 1.6K) - 基于JAX的神经网络库。Apache-2 +
mace (🥉20 · ⭐ 4.7K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 -- [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 53 · 🔀 120 · 📦 270 · 📋 120 - 20% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 64 · 🔀 790 · 📥 1.4K · 📋 660 - 7% open · ⏱️ 30.05.2022): ``` - git clone https://github.com/deepmind/dm-haiku + git clone https://github.com/XiaoMi/mace ```
-
Objax (🥉20 · ⭐ 660) - Objax是加速研究与应用的开源深度学习框架。Apache-2 jax +
Objax (🥉20 · ⭐ 720) - Objax is a machine learning framework that provides an Object.. Apache-2 jax -- [GitHub](https://github.com/google/objax) (👨‍💻 22 · 🔀 56 · 📦 17 · 📋 93 - 39% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/google/objax) (👨‍💻 23 · 🔀 60 · 📦 25 · 📋 98 - 38% open · ⏱️ 12.07.2022): ``` git clone https://github.com/google/objax ``` -- [PyPi](https://pypi.org/project/objax) (📥 2.5K / month): +- [PyPi](https://pypi.org/project/objax) (📥 440 / month): ``` pip install objax ```
-
MindsDB (🥉19 · ⭐ 4.2K) - 为各种现有数据库提供预测性AI层。❗️GPL-3.0 +
MindsDB (🥉19 · ⭐ 9.7K) - Predictive AI layer for existing databases. ❗️GPL-3.0 -- [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 89 · 🔀 550 · 📋 780 - 10% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 130 · 🔀 1K · 📋 1.2K - 11% open · ⏱️ 25.08.2022): ``` git clone https://github.com/mindsdb/mindsdb ``` -- [PyPi](https://pypi.org/project/mindsdb) (📥 3.2K / month): +- [PyPi](https://pypi.org/project/mindsdb) (📥 2.9K / month): ``` pip install mindsdb ```
-
neon (🥉19 · ⭐ 3.9K · 💀) - 英特尔Nervana深度学习框架。Apache-2 +
neon (🥉19 · ⭐ 3.9K · 💀) - Intel Nervana reference deep learning framework committed to best.. Apache-2 -- [GitHub](https://github.com/NervanaSystems/neon) (👨‍💻 110 · 🔀 810 · 📥 320 · 📋 390 - 21% open · ⏱️ 22.05.2019): +- [GitHub](https://github.com/NervanaSystems/neon) (👨‍💻 110 · 🔀 800 · 📥 340 · 📋 390 - 21% open · ⏱️ 22.05.2019): ``` git clone https://github.com/NervanaSystems/neon ``` -- [PyPi](https://pypi.org/project/nervananeon) (📥 99 / month): +- [PyPi](https://pypi.org/project/nervananeon) (📥 32 / month): ``` pip install nervananeon ```
-
Neural Tangents (🥉19 · ⭐ 1.6K) - Python中的快速简便的无限神经网络。Apache-2 - -- [GitHub](https://github.com/google/neural-tangents) (👨‍💻 21 · 🔀 180 · 📥 180 · 📦 27 · 📋 100 - 29% open · ⏱️ 14.12.2021): - - ``` - git clone https://github.com/google/neural-tangents - ``` -- [PyPi](https://pypi.org/project/neural-tangents): - ``` - pip install neural-tangents - ``` -
-
ThunderSVM (🥉19 · ⭐ 1.4K · 💤) - ThunderSVM：在GPU和CPU上的快速SVM库。Apache-2 +
ThunderSVM (🥉19 · ⭐ 1.4K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 -- [GitHub](https://github.com/Xtra-Computing/thundersvm) (👨‍💻 33 · 🔀 180 · 📥 2.3K · 📋 200 - 28% open · ⏱️ 10.02.2021): +- [GitHub](https://github.com/Xtra-Computing/thundersvm) (👨‍💻 34 · 🔀 190 · 📥 2.5K · 📋 210 - 29% open · ⏱️ 09.04.2022): ``` git clone https://github.com/Xtra-Computing/thundersvm ``` -- [PyPi](https://pypi.org/project/thundersvm) (📥 730 / month): +- [PyPi](https://pypi.org/project/thundersvm) (📥 350 / month): ``` pip install thundersvm ```
-
Torchbearer (🥉19 · ⭐ 620 · 💤) - torchbearer：PyTorch的模型拟合库。MIT +
Torchbearer (🥉19 · ⭐ 630 · 💀) - torchbearer: A model fitting library for PyTorch. MIT -- [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 68 · 📦 56 · 📋 240 - 3% open · ⏱️ 26.03.2021): +- [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 66 · 📦 64 · 📋 250 - 4% open · ⏱️ 26.03.2021): ``` git clone https://github.com/pytorchbearer/torchbearer ``` -- [PyPi](https://pypi.org/project/torchbearer) (📥 560 / month): +- [PyPi](https://pypi.org/project/torchbearer) (📥 700 / month): ``` pip install torchbearer ```
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ThunderGBM (🥉16 · ⭐ 620 · 💤) - ThunderGBM：GPU上的快速GBDT和随机森林。Apache-2 +
elegy (🥉18 · ⭐ 400) - Elegy is a framework-agnostic Trainer interface for the Jax.. MIT jax -- [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 80 · 📋 60 - 50% open · ⏱️ 05.01.2021): +- [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 17 · 🔀 26 · 📋 100 - 34% open · ⏱️ 23.05.2022): ``` - git clone https://github.com/Xtra-Computing/thundergbm + git clone https://github.com/poets-ai/elegy ``` -- [PyPi](https://pypi.org/project/thundergbm) (📥 81 / month): +- [PyPi](https://pypi.org/project/elegy) (📥 1K / month): ``` - pip install thundergbm + pip install elegy ```
-
elegy (🥉16 · ⭐ 300) - Elegy是Jax的与框架无关的Trainer工具。MIT jax +
ThunderGBM (🥉17 · ⭐ 640) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 -- [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 14 · 🔀 21 · 📋 80 - 22% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 82 · 📋 74 - 50% open · ⏱️ 09.08.2022): ``` - git clone https://github.com/poets-ai/elegy + git clone https://github.com/Xtra-Computing/thundergbm ``` -- [PyPi](https://pypi.org/project/elegy): +- [PyPi](https://pypi.org/project/thundergbm) (📥 240 / month): ``` - pip install elegy + pip install thundergbm ```
-
NeoML (🥉15 · ⭐ 660) - neoml是可以用于深度学习和传统机器学习的工具库。Apache-2 +
NeoML (🥉15 · ⭐ 690) - Machine learning framework for both deep learning and traditional.. Apache-2 -- [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 25 · 🔀 97 · 📋 50 - 48% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 32 · 🔀 110 · 📋 62 - 22% open · ⏱️ 24.08.2022): ``` git clone https://github.com/neoml-lib/neoml ```
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StarSpace (🥉13 · ⭐ 3.7K · 💀) - 学习embedding嵌入用于分类，检索和排序。MIT +
StarSpace (🥉12 · ⭐ 3.8K · 💀) - Learning embeddings for classification, retrieval and ranking. MIT -- [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 500 · 📋 200 - 24% open · ⏱️ 13.12.2019): +- [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 510 · 📋 200 - 24% open · ⏱️ 13.12.2019): ``` git clone https://github.com/facebookresearch/StarSpace @@ -809,979 +809,963 @@ _通用机器学习和深度学习框架。_

-## 数据可视化 - -Back to top - -_通用和特定于任务的数据可视化库。_ +## Data Visualization -
Seaborn (🥇35 · ⭐ 9K) - 使用matplotlib进行统计数据可视化。BSD-3 +Back to top -- [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 160 · 🔀 1.5K · 📥 210 · 📦 130K · 📋 1.9K - 4% open · ⏱️ 27.11.2021): +_General-purpose and task-specific data visualization libraries._ - ``` - git clone https://github.com/mwaskom/seaborn - ``` -- [PyPi](https://pypi.org/project/seaborn): - ``` - pip install seaborn - ``` -- [Conda](https://anaconda.org/conda-forge/seaborn) (📥 3.2M · ⏱️ 16.08.2021): - ``` - conda install -c conda-forge seaborn - ``` -
-
Matplotlib (🥇33 · ⭐ 15K · 📉) - matplotlib：Python绘图工具库。❗Unlicensed +
Matplotlib (🥇36 · ⭐ 16K) - matplotlib: plotting with Python. ❗Unlicensed -- [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.3K · 🔀 6K · 📦 470K · 📋 8.2K - 17% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.4K · 🔀 6.3K · 📦 610K · 📋 8.8K - 17% open · ⏱️ 26.08.2022): ``` git clone https://github.com/matplotlib/matplotlib ``` -- [PyPi](https://pypi.org/project/matplotlib): +- [PyPi](https://pypi.org/project/matplotlib) (📥 28M / month): ``` pip install matplotlib ``` -- [Conda](https://anaconda.org/conda-forge/matplotlib) (📥 11M · ⏱️ 13.12.2021): +- [Conda](https://anaconda.org/conda-forge/matplotlib) (📥 13M · ⏱️ 25.08.2022): ``` conda install -c conda-forge matplotlib ```
-
pandas-profiling (🥇33 · ⭐ 8.3K) - 从pandas DataFrame创建HTML分析报告。MIT +
pandas-profiling (🥇33 · ⭐ 9.4K) - Create HTML profiling reports from pandas DataFrame.. MIT -- [GitHub](https://github.com/pandas-profiling/pandas-profiling) (👨‍💻 83 · 🔀 1.2K · 📦 6.1K · 📋 530 - 17% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/ydataai/pandas-profiling) (👨‍💻 92 · 🔀 1.3K · 📦 8.8K · 📋 580 - 19% open · ⏱️ 25.08.2022): ``` git clone https://github.com/pandas-profiling/pandas-profiling ``` -- [PyPi](https://pypi.org/project/pandas-profiling) (📥 2.3M / month): +- [PyPi](https://pypi.org/project/pandas-profiling) (📥 1.2M / month): ``` pip install pandas-profiling ``` -- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (📥 180K · ⏱️ 28.09.2021): +- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (📥 270K · ⏱️ 02.05.2022): ``` conda install -c conda-forge pandas-profiling ```
-
Altair (🥇33 · ⭐ 7.1K) - 用于Python的声明式统计可视化库。BSD-3 +
Altair (🥇33 · ⭐ 7.7K) - Declarative statistical visualization library for Python. BSD-3 -- [GitHub](https://github.com/altair-viz/altair) (👨‍💻 130 · 🔀 600 · 📦 20K · 📋 1.6K - 14% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/altair-viz/altair) (👨‍💻 140 · 🔀 650 · 📦 32K · 📋 1.6K - 13% open · ⏱️ 23.08.2022): ``` git clone https://github.com/altair-viz/altair ``` -- [PyPi](https://pypi.org/project/altair) (📥 4M / month): +- [PyPi](https://pypi.org/project/altair) (📥 7.3M / month): ``` pip install altair ``` -- [Conda](https://anaconda.org/conda-forge/altair) (📥 1M · ⏱️ 01.04.2020): +- [Conda](https://anaconda.org/conda-forge/altair) (📥 1.3M · ⏱️ 29.12.2021): ``` conda install -c conda-forge altair ```
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UMAP (🥇32 · ⭐ 5.3K) - 均匀流形逼近和投影。BSD-3 - -- [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 94 · 🔀 560 · 📦 4.2K · 📋 580 - 50% open · ⏱️ 03.12.2021): - - ``` - git clone https://github.com/lmcinnes/umap - ``` -- [PyPi](https://pypi.org/project/umap-learn) (📥 1.6M / month): - ``` - pip install umap-learn - ``` -
-
Bokeh (🥈31 · ⭐ 16K) - 浏览器中的Python交互式数据可视化。BSD-3 - -- [GitHub](https://github.com/bokeh/bokeh) (👨‍💻 590 · 🔀 3.8K · 📦 42K · 📋 6.8K - 10% open · ⏱️ 16.12.2021): - - ``` - git clone https://github.com/bokeh/bokeh - ``` -- [PyPi](https://pypi.org/project/bokeh) (📥 2.1M / month): - ``` - pip install bokeh - ``` -- [Conda](https://anaconda.org/conda-forge/bokeh) (📥 6.2M · ⏱️ 22.11.2021): - ``` - conda install -c conda-forge bokeh - ``` -
-
dash (🥈31 · ⭐ 16K) - 适用于Python，R，Julia和Jupyter的分析型Web应用程序。MIT +
dash (🥇32 · ⭐ 17K) - Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript.. MIT -- [GitHub](https://github.com/plotly/dash) (👨‍💻 100 · 🔀 1.6K · 📦 160 · 📋 1.1K - 46% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/plotly/dash) (👨‍💻 120 · 🔀 1.7K · 📦 220 · 📋 1.3K - 47% open · ⏱️ 19.08.2022): ``` git clone https://github.com/plotly/dash ``` -- [PyPi](https://pypi.org/project/dash) (📥 840K / month): +- [PyPi](https://pypi.org/project/dash) (📥 1M / month): ``` pip install dash ``` -- [Conda](https://anaconda.org/conda-forge/dash) (📥 330K · ⏱️ 21.09.2021): +- [Conda](https://anaconda.org/conda-forge/dash) (📥 590K · ⏱️ 03.08.2022): ``` conda install -c conda-forge dash ```
-
pyecharts (🥈29 · ⭐ 12K) - Python Echarts绘图库。MIT - -- [GitHub](https://github.com/pyecharts/pyecharts) (👨‍💻 30 · 🔀 2.6K · 📦 1.9K · 📋 1.5K - 1% open · ⏱️ 16.11.2021): - - ``` - git clone https://github.com/pyecharts/pyecharts - ``` -- [PyPi](https://pypi.org/project/pyecharts) (📥 87K / month): - ``` - pip install pyecharts - ``` -
-
Plotly (🥈29 · ⭐ 11K) - 适用于Python的交互式图形库（包括Plotly Express）。MIT +
Plotly (🥇32 · ⭐ 12K) - The interactive graphing library for Python (includes Plotly Express). MIT -- [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 190 · 🔀 2K · 📦 9 · 📋 2.1K - 46% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 200 · 🔀 2.1K · 📦 12 · 📋 2.4K - 49% open · ⏱️ 11.08.2022): ``` git clone https://github.com/plotly/plotly.py ``` -- [PyPi](https://pypi.org/project/plotly): +- [PyPi](https://pypi.org/project/plotly) (📥 8.6M / month): ``` pip install plotly ``` -- [Conda](https://anaconda.org/conda-forge/plotly) (📥 2.1M · ⏱️ 15.11.2021): +- [Conda](https://anaconda.org/conda-forge/plotly) (📥 3M · ⏱️ 14.08.2022): ``` conda install -c conda-forge plotly ``` -- [NPM](https://www.npmjs.com/package/plotlywidget) (📥 59K / month): +- [NPM](https://www.npmjs.com/package/plotlywidget) (📥 46K / month): ``` npm install plotlywidget ```
-
missingno (🥈29 · ⭐ 3K) - 在缺失值和混乱数据下，用于数据可视化的python模块。MIT +
UMAP (🥇32 · ⭐ 5.7K) - Uniform Manifold Approximation and Projection. BSD-3 -- [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 380 · 📦 5.7K · 📋 110 - 9% open · ⏱️ 04.07.2021): +- [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 100 · 🔀 630 · 📦 6K · 📋 640 - 52% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/ResidentMario/missingno - ``` -- [PyPi](https://pypi.org/project/missingno) (📥 720K / month): - ``` - pip install missingno + git clone https://github.com/lmcinnes/umap ``` -- [Conda](https://anaconda.org/conda-forge/missingno) (📥 140K · ⏱️ 15.02.2020): +- [PyPi](https://pypi.org/project/umap-learn) (📥 650K / month): ``` - conda install -c conda-forge missingno + pip install umap-learn ```
-
plotnine (🥈27 · ⭐ 2.9K) - Python的图形语法。❗️GPL-2.0 +
Graphviz (🥈30 · ⭐ 1.3K) - Simple Python interface for Graphviz. MIT -- [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 89 · 🔀 150 · 📦 2.8K · 📋 460 - 16% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 19 · 🔀 180 · 📦 34K · 📋 140 - 4% open · ⏱️ 27.07.2022): ``` - git clone https://github.com/has2k1/plotnine - ``` -- [PyPi](https://pypi.org/project/plotnine) (📥 190K / month): - ``` - pip install plotnine + git clone https://github.com/xflr6/graphviz ``` -- [Conda](https://anaconda.org/conda-forge/plotnine) (📥 140K · ⏱️ 25.03.2021): +- [PyPi](https://pypi.org/project/graphviz) (📥 10M / month): ``` - conda install -c conda-forge plotnine + pip install graphviz ```
-
datashader (🥈27 · ⭐ 2.7K) - 快速准确地渲染大数据。❗Unlicensed +
Seaborn (🥈29 · ⭐ 9.7K · 📉) - Statistical data visualization using matplotlib. BSD-3 -- [GitHub](https://github.com/holoviz/datashader) (👨‍💻 45 · 🔀 330 · 📦 900 · 📋 480 - 26% open · ⏱️ 29.11.2021): +- [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 170 · 🔀 1.6K · 📥 230 · 📋 2.1K - 4% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/holoviz/datashader + git clone https://github.com/mwaskom/seaborn ``` -- [PyPi](https://pypi.org/project/datashader) (📥 63K / month): +- [PyPi](https://pypi.org/project/seaborn) (📥 7.6M / month): ``` - pip install datashader + pip install seaborn ``` -- [Conda](https://anaconda.org/conda-forge/datashader) (📥 250K · ⏱️ 10.06.2021): +- [Conda](https://anaconda.org/conda-forge/seaborn) (📥 4.5M · ⏱️ 16.08.2021): ``` - conda install -c conda-forge datashader + conda install -c conda-forge seaborn ```
-
Cufflinks (🥈27 · ⭐ 2.4K · 💤) - Plotly + Pandas的生产力工具。MIT +
datashader (🥈29 · ⭐ 2.8K) - Quickly and accurately render even the largest data. BSD-3 -- [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 560 · 📦 4.8K · 📋 200 - 39% open · ⏱️ 25.02.2021): +- [GitHub](https://github.com/holoviz/datashader) (👨‍💻 49 · 🔀 340 · 📦 1.3K · 📋 500 - 23% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/santosjorge/cufflinks + git clone https://github.com/holoviz/datashader ``` -- [PyPi](https://pypi.org/project/cufflinks) (📥 280K / month): +- [PyPi](https://pypi.org/project/datashader) (📥 42K / month): ``` - pip install cufflinks + pip install datashader + ``` +- [Conda](https://anaconda.org/conda-forge/datashader) (📥 370K · ⏱️ 10.08.2022): + ``` + conda install -c conda-forge datashader ```
-
PyVista (🥈27 · ⭐ 1K) - 通过简化的界面进行3D绘图和网格分析。MIT +
Bokeh (🥈28 · ⭐ 17K) - Interactive Data Visualization in the browser, from Python. BSD-3 -- [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 64 · 🔀 200 · 📥 380 · 📦 540 · 📋 640 - 27% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/bokeh/bokeh) (👨‍💻 610 · 🔀 3.9K · 📦 150 · 📋 7K - 9% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/pyvista/pyvista + git clone https://github.com/bokeh/bokeh ``` -- [PyPi](https://pypi.org/project/pyvista) (📥 36K / month): +- [PyPi](https://pypi.org/project/bokeh) (📥 3.7M / month): ``` - pip install pyvista + pip install bokeh ``` -- [Conda](https://anaconda.org/conda-forge/pyvista) (📥 130K · ⏱️ 12.09.2021): +- [Conda](https://anaconda.org/conda-forge/bokeh) (📥 8.3M · ⏱️ 15.08.2022): ``` - conda install -c conda-forge pyvista + conda install -c conda-forge bokeh ```
-
hvPlot (🥈27 · ⭐ 490) - 用于构建的pandas，dask，xarray和networkx的高级绘图API。BSD-3 +
pyecharts (🥈28 · ⭐ 13K) - Python Echarts Plotting Library. MIT -- [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 33 · 🔀 62 · 📦 940 · 📋 400 - 34% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pyecharts/pyecharts) (👨‍💻 30 · 🔀 2.7K · 📦 2.4K · 📋 1.6K - 1% open · ⏱️ 25.04.2022): ``` - git clone https://github.com/holoviz/hvplot - ``` -- [PyPi](https://pypi.org/project/hvplot) (📥 80K / month): - ``` - pip install hvplot + git clone https://github.com/pyecharts/pyecharts ``` -- [Conda](https://anaconda.org/conda-forge/hvplot) (📥 140K · ⏱️ 23.07.2021): +- [PyPi](https://pypi.org/project/pyecharts) (📥 44K / month): ``` - conda install -c conda-forge hvplot + pip install pyecharts ```
-
wordcloud (🥈26 · ⭐ 8.5K) - Python中的词云生成器。MIT +
missingno (🥈28 · ⭐ 3.3K) - Missing data visualization module for Python. MIT -- [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 64 · 🔀 2.1K · 📋 450 - 20% open · ⏱️ 13.11.2021): +- [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 410 · 📦 8.3K · 📋 120 - 6% open · ⏱️ 27.02.2022): ``` - git clone https://github.com/amueller/word_cloud + git clone https://github.com/ResidentMario/missingno ``` -- [PyPi](https://pypi.org/project/wordcloud) (📥 680K / month): +- [PyPi](https://pypi.org/project/missingno) (📥 1M / month): ``` - pip install wordcloud + pip install missingno ``` -- [Conda](https://anaconda.org/conda-forge/wordcloud) (📥 250K · ⏱️ 15.11.2021): +- [Conda](https://anaconda.org/conda-forge/missingno) (📥 210K · ⏱️ 15.02.2020): ``` - conda install -c conda-forge wordcloud + conda install -c conda-forge missingno ```
-
Facets Overview (🥈26 · ⭐ 6.7K · 💤) - 机器学习数据集的可视化。Apache-2 +
D-Tale (🥈27 · ⭐ 3.6K) - Visualizer for pandas data structures. ❗️LGPL-2.1 -- [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 820 · 📦 92 · 📋 150 - 50% open · ⏱️ 06.05.2021): +- [GitHub](https://github.com/man-group/dtale) (👨‍💻 27 · 🔀 290 · 📦 460 · 📋 470 - 8% open · ⏱️ 07.08.2022): ``` - git clone https://github.com/pair-code/facets + git clone https://github.com/man-group/dtale ``` -- [PyPi](https://pypi.org/project/facets-overview) (📥 150K / month): +- [PyPi](https://pypi.org/project/dtale) (📥 100K / month): ``` - pip install facets-overview + pip install dtale + ``` +- [Conda](https://anaconda.org/conda-forge/dtale) (📥 150K · ⏱️ 07.08.2022): + ``` + conda install -c conda-forge dtale ```
-
bqplot (🥈26 · ⭐ 3.2K) - 用于IPython / Jupyter笔记本的绘图库。Apache-2 +
bqplot (🥈27 · ⭐ 3.3K) - Plotting library for IPython/Jupyter notebooks. Apache-2 -- [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 55 · 🔀 430 · 📦 28 · 📋 550 - 35% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 59 · 🔀 440 · 📦 34 · 📋 570 - 36% open · ⏱️ 22.08.2022): ``` git clone https://github.com/bqplot/bqplot ``` -- [PyPi](https://pypi.org/project/bqplot): +- [PyPi](https://pypi.org/project/bqplot) (📥 81K / month): ``` pip install bqplot ``` -- [Conda](https://anaconda.org/conda-forge/bqplot) (📥 910K · ⏱️ 01.10.2021): +- [Conda](https://anaconda.org/conda-forge/bqplot) (📥 1M · ⏱️ 22.08.2022): ``` conda install -c conda-forge bqplot ``` -- [NPM](https://www.npmjs.com/package/bqplot) (📥 26K / month): +- [NPM](https://www.npmjs.com/package/bqplot) (📥 9.3K / month): ``` npm install bqplot ```
-
D-Tale (🥈25 · ⭐ 2.9K) - pandas数据结构的可视化工具。❗️LGPL-2.1 +
data-validation (🥈27 · ⭐ 660) - Library for exploring and validating machine learning.. Apache-2 -- [GitHub](https://github.com/man-group/dtale) (👨‍💻 18 · 🔀 220 · 📦 270 · 📋 440 - 8% open · ⏱️ 12.12.2021): +- [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 24 · 🔀 130 · 📥 370 · 📦 540 · 📋 150 - 16% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/man-group/dtale - ``` -- [PyPi](https://pypi.org/project/dtale) (📥 48K / month): - ``` - pip install dtale + git clone https://github.com/tensorflow/data-validation ``` -- [Conda](https://anaconda.org/conda-forge/dtale) (📥 100K · ⏱️ 18.11.2021): +- [PyPi](https://pypi.org/project/tensorflow-data-validation) (📥 1.1M / month): ``` - conda install -c conda-forge dtale + pip install tensorflow-data-validation ```
-
HoloViews (🥈25 · ⭐ 2.1K) - 使用Holoviews，您的数据可以可视化。BSD-3 +
hvPlot (🥈27 · ⭐ 620) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 -- [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 120 · 🔀 330 · 📋 2.7K - 29% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 37 · 🔀 73 · 📦 1.6K · 📋 480 - 37% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/holoviz/holoviews + git clone https://github.com/holoviz/hvplot ``` -- [PyPi](https://pypi.org/project/holoviews): +- [PyPi](https://pypi.org/project/hvplot) (📥 160K / month): ``` - pip install holoviews + pip install hvplot ``` -- [Conda](https://anaconda.org/conda-forge/holoviews) (📥 620K · ⏱️ 17.09.2021): +- [Conda](https://anaconda.org/conda-forge/hvplot) (📥 210K · ⏱️ 09.05.2022): ``` - conda install -c conda-forge holoviews + conda install -c conda-forge hvplot ``` -- [NPM](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (📥 3.2K / month): +
+
wordcloud (🥈26 · ⭐ 8.9K) - A little word cloud generator in Python. MIT + +- [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 65 · 🔀 2.2K · 📋 470 - 20% open · ⏱️ 27.06.2022): + ``` - npm install @pyviz/jupyterlab_pyviz + git clone https://github.com/amueller/word_cloud + ``` +- [PyPi](https://pypi.org/project/wordcloud) (📥 690K / month): + ``` + pip install wordcloud + ``` +- [Conda](https://anaconda.org/conda-forge/wordcloud) (📥 310K · ⏱️ 25.08.2022): + ``` + conda install -c conda-forge wordcloud ```
-
Perspective (🥉24 · ⭐ 4K) - 通过WebAssembly进行流式透视显示。Apache-2 +
Cufflinks (🥈26 · ⭐ 2.6K · 💀) - Productivity Tools for Plotly + Pandas. MIT -- [GitHub](https://github.com/finos/perspective) (👨‍💻 65 · 🔀 410 · 📦 220 · 📋 470 - 12% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 600 · 📦 6.5K · 📋 210 - 41% open · ⏱️ 25.02.2021): ``` - git clone https://github.com/finos/perspective + git clone https://github.com/santosjorge/cufflinks ``` -- [PyPi](https://pypi.org/project/perspective-python) (📥 5.5K / month): +- [PyPi](https://pypi.org/project/cufflinks) (📥 310K / month): ``` - pip install perspective-python + pip install cufflinks ``` -- [NPM](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (📥 2.2K / month): +
+
HoloViews (🥈26 · ⭐ 2.3K) - With Holoviews, your data visualizes itself. BSD-3 + +- [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 120 · 🔀 350 · 📋 2.8K - 31% open · ⏱️ 22.08.2022): + ``` - npm install @finos/perspective-jupyterlab + git clone https://github.com/holoviz/holoviews + ``` +- [PyPi](https://pypi.org/project/holoviews) (📥 380K / month): + ``` + pip install holoviews + ``` +- [Conda](https://anaconda.org/conda-forge/holoviews) (📥 850K · ⏱️ 07.07.2022): + ``` + conda install -c conda-forge holoviews + ``` +- [NPM](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (📥 840 / month): + ``` + npm install @pyviz/jupyterlab_pyviz ```
-
VisPy (🥉24 · ⭐ 2.8K) - 高性能交互式2D / 3D数据可视化库。❗Unlicensed +
PyVista (🥈26 · ⭐ 1.4K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT -- [GitHub](https://github.com/vispy/vispy) (👨‍💻 170 · 🔀 570 · 📦 650 · 📋 1.3K - 20% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 100 · 🔀 280 · 📥 660 · 📦 900 · 📋 920 - 28% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/vispy/vispy + git clone https://github.com/pyvista/pyvista ``` -- [PyPi](https://pypi.org/project/vispy) (📥 45K / month): +- [PyPi](https://pypi.org/project/pyvista) (📥 46K / month): ``` - pip install vispy + pip install pyvista ``` -- [Conda](https://anaconda.org/conda-forge/vispy) (📥 200K · ⏱️ 24.11.2021): +- [Conda](https://anaconda.org/conda-forge/pyvista) (📥 210K · ⏱️ 01.08.2022): ``` - conda install -c conda-forge vispy + conda install -c conda-forge pyvista + ``` +
+
Facets Overview (🥉25 · ⭐ 7K · 💀) - Visualizations for machine learning datasets. Apache-2 + +- [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 850 · 📦 130 · 📋 150 - 50% open · ⏱️ 06.05.2021): + ``` -- [NPM](https://www.npmjs.com/package/vispy) (📥 11 / month): + git clone https://github.com/pair-code/facets ``` - npm install vispy +- [PyPi](https://pypi.org/project/facets-overview) (📥 300K / month): + ``` + pip install facets-overview ```
-
HyperTools (🥉23 · ⭐ 1.7K) - 一个Python工具箱，用于获得对高维的几何洞察力。MIT +
Chartify (🥉25 · ⭐ 3.2K · 💀) - Python library that makes it easy for data scientists to create.. Apache-2 -- [GitHub](https://github.com/ContextLab/hypertools) (👨‍💻 21 · 🔀 160 · 📥 8 · 📦 160 · 📋 190 - 35% open · ⏱️ 19.07.2021): +- [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 280 · 📦 65 · 📋 72 - 56% open · ⏱️ 05.02.2021): ``` - git clone https://github.com/ContextLab/hypertools + git clone https://github.com/spotify/chartify ``` -- [PyPi](https://pypi.org/project/hypertools) (📥 990 / month): +- [PyPi](https://pypi.org/project/chartify) (📥 10K / month): ``` - pip install hypertools + pip install chartify + ``` +- [Conda](https://anaconda.org/conda-forge/chartify) (📥 21K · ⏱️ 07.11.2020): + ``` + conda install -c conda-forge chartify ```
-
Graphviz (🥉23 · ⭐ 1.1K) - Graphviz的简单Python界面。MIT +
VisPy (🥉24 · ⭐ 2.9K) - High-performance interactive 2D/3D data visualization library. ❗Unlicensed -- [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 17 · 🔀 160 · 📦 26K · 📋 120 - 3% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/vispy/vispy) (👨‍💻 180 · 🔀 580 · 📦 820 · 📋 1.3K - 20% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/xflr6/graphviz + git clone https://github.com/vispy/vispy ``` -- [PyPi](https://pypi.org/project/graphviz): +- [PyPi](https://pypi.org/project/vispy) (📥 51K / month): ``` - pip install graphviz + pip install vispy + ``` +- [Conda](https://anaconda.org/conda-forge/vispy) (📥 270K · ⏱️ 05.07.2022): + ``` + conda install -c conda-forge vispy + ``` +- [NPM](https://www.npmjs.com/package/vispy) (📥 10 / month): + ``` + npm install vispy ```
-
Pandas-Bokeh (🥉23 · ⭐ 740 · 💤) - pandas和GeoPandas的Bokeh绘图后端。MIT +
HyperTools (🥉24 · ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT -- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 12 · 🔀 93 · 📦 260 · 📋 93 - 29% open · ⏱️ 10.05.2021): +- [GitHub](https://github.com/ContextLab/hypertools) (👨‍💻 21 · 🔀 150 · 📥 20 · 📦 210 · 📋 190 - 35% open · ⏱️ 12.02.2022): ``` - git clone https://github.com/PatrikHlobil/Pandas-Bokeh + git clone https://github.com/ContextLab/hypertools ``` -- [PyPi](https://pypi.org/project/pandas-bokeh) (📥 11K / month): +- [PyPi](https://pypi.org/project/hypertools) (📥 550 / month): ``` - pip install pandas-bokeh + pip install hypertools ```
-
python-ternary (🥉23 · ⭐ 500) - 带有matplotlib的python三元绘图库。MIT +
pythreejs (🥉24 · ⭐ 830) - A Jupyter - Three.js bridge. ❗Unlicensed -- [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 130 · 📥 17 · 📦 76 · 📋 120 - 21% open · ⏱️ 21.10.2021): +- [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 30 · 🔀 170 · 📦 21 · 📋 220 - 23% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/marcharper/python-ternary + git clone https://github.com/jupyter-widgets/pythreejs ``` -- [PyPi](https://pypi.org/project/python-ternary) (📥 21K / month): +- [PyPi](https://pypi.org/project/pythreejs) (📥 64K / month): ``` - pip install python-ternary + pip install pythreejs ``` -- [Conda](https://anaconda.org/conda-forge/python-ternary) (📥 60K · ⏱️ 17.02.2021): +- [Conda](https://anaconda.org/conda-forge/pythreejs) (📥 410K · ⏱️ 25.08.2022): ``` - conda install -c conda-forge python-ternary + conda install -c conda-forge pythreejs + ``` +- [NPM](https://www.npmjs.com/package/jupyter-threejs) (📥 4.6K / month): + ``` + npm install jupyter-threejs ```
-
Chartify (🥉22 · ⭐ 3.1K · 💤) - Python库，使数据科学家可以轻松创建。Apache-2 +
PyQtGraph (🥉23 · ⭐ 2.9K) - Fast data visualization and GUI tools for scientific /.. ❗Unlicensed -- [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 270 · 📦 61 · 📋 71 - 56% open · ⏱️ 05.02.2021): +- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (👨‍💻 230 · 🔀 930 · 📋 1K - 31% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/spotify/chartify + git clone https://github.com/pyqtgraph/pyqtgraph ``` -- [PyPi](https://pypi.org/project/chartify): +- [PyPi](https://pypi.org/project/pyqtgraph) (📥 100K / month): ``` - pip install chartify + pip install pyqtgraph ``` -- [Conda](https://anaconda.org/conda-forge/chartify) (📥 17K · ⏱️ 07.11.2020): +- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (📥 280K · ⏱️ 05.03.2022): ``` - conda install -c conda-forge chartify + conda install -c conda-forge pyqtgraph ```
-
PandasGUI (🥉22 · ⭐ 2.5K) - pandas Dataframe的GUI。MIT +
FiftyOne (🥉23 · ⭐ 1.8K) - Visualize, create, and debug image and video datasets.. Apache-2 -- [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 10 · 🔀 150 · 📦 120 · 📋 140 - 22% open · ⏱️ 25.09.2021): +- [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 46 · 🔀 220 · 📦 160 · 📋 890 - 31% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/adamerose/pandasgui + git clone https://github.com/voxel51/fiftyone ``` -- [PyPi](https://pypi.org/project/pandasgui) (📥 9.3K / month): +- [PyPi](https://pypi.org/project/fiftyone) (📥 21K / month): ``` - pip install pandasgui + pip install fiftyone ```
-
openTSNE (🥉22 · ⭐ 930) - t-SNE的可扩展并行实现。BSD-3 +
openTSNE (🥉23 · ⭐ 1K) - Extensible, parallel implementations of t-SNE. BSD-3 -- [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 97 · 📦 270 · 📋 98 - 3% open · ⏱️ 25.10.2021): +- [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 120 · 📦 380 · 📋 110 - 5% open · ⏱️ 18.03.2022): ``` git clone https://github.com/pavlin-policar/openTSNE ``` -- [PyPi](https://pypi.org/project/opentsne): +- [PyPi](https://pypi.org/project/opentsne) (📥 21K / month): ``` pip install opentsne ``` -- [Conda](https://anaconda.org/conda-forge/opentsne) (📥 130K · ⏱️ 13.11.2021): +- [Conda](https://anaconda.org/conda-forge/opentsne) (📥 150K · ⏱️ 27.05.2022): ``` conda install -c conda-forge opentsne ```
-
PyQtGraph (🥉21 · ⭐ 2.7K) - 用于科学/工程的快速数据可视化和GUI工具。❗Unlicensed +
python-ternary (🥉23 · ⭐ 580) - Ternary plotting library for python with matplotlib. MIT -- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (👨‍💻 210 · 🔀 880 · 📋 950 - 29% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 140 · 📥 18 · 📦 100 · 📋 130 - 25% open · ⏱️ 27.02.2022): ``` - git clone https://github.com/pyqtgraph/pyqtgraph + git clone https://github.com/marcharper/python-ternary ``` -- [PyPi](https://pypi.org/project/pyqtgraph): +- [PyPi](https://pypi.org/project/python-ternary) (📥 27K / month): ``` - pip install pyqtgraph + pip install python-ternary ``` -- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (📥 210K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/python-ternary) (📥 66K · ⏱️ 17.02.2021): ``` - conda install -c conda-forge pyqtgraph + conda install -c conda-forge python-ternary ```
-
pythreejs (🥉21 · ⭐ 780) - Jupyter-Three.js桥。❗Unlicensed +
Sweetviz (🥉22 · ⭐ 2.1K) - Visualize and compare datasets, target values and associations, with one.. MIT -- [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 29 · 🔀 160 · 📦 19 · 📋 210 - 31% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 210 · 📋 100 - 28% open · ⏱️ 08.06.2022): ``` - git clone https://github.com/jupyter-widgets/pythreejs + git clone https://github.com/fbdesignpro/sweetviz ``` -- [PyPi](https://pypi.org/project/pythreejs) (📥 39K / month): +- [PyPi](https://pypi.org/project/sweetviz) (📥 64K / month): ``` - pip install pythreejs + pip install sweetviz ``` -- [Conda](https://anaconda.org/conda-forge/pythreejs) (📥 360K · ⏱️ 02.03.2021): +
+
lets-plot (🥉22 · ⭐ 780) - An open-source plotting library for statistical data. MIT + +- [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 17 · 🔀 34 · 📥 300 · 📦 17 · 📋 270 - 27% open · ⏱️ 23.08.2022): + ``` - conda install -c conda-forge pythreejs + git clone https://github.com/JetBrains/lets-plot ``` -- [NPM](https://www.npmjs.com/package/jupyter-threejs) (📥 6.1K / month): +- [PyPi](https://pypi.org/project/lets-plot) (📥 1.8K / month): ``` - npm install jupyter-threejs + pip install lets-plot ```
-
data-validation (🥉21 · ⭐ 600) - 用于探索和验证机器学习的库。Apache-2 +
PDPbox (🥉22 · ⭐ 700 · 💀) - python partial dependence plot toolbox. MIT -- [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 23 · 🔀 110 · 📥 290 · 📦 360 · 📋 140 - 19% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 110 · 📦 510 · 📋 60 - 36% open · ⏱️ 14.03.2021): ``` - git clone https://github.com/tensorflow/data-validation + git clone https://github.com/SauceCat/PDPbox ``` -- [PyPi](https://pypi.org/project/tensorflow-data-validation): +- [PyPi](https://pypi.org/project/pdpbox) (📥 34K / month): ``` - pip install tensorflow-data-validation + pip install pdpbox + ``` +- [Conda](https://anaconda.org/conda-forge/pdpbox) (📥 13K · ⏱️ 14.03.2021): + ``` + conda install -c conda-forge pdpbox ```
-
HiPlot (🥉20 · ⭐ 2.2K) - HiPlot使理解高维数据变得容易。MIT +
Perspective (🥉21 · ⭐ 4.8K) - Streaming pivot visualization via WebAssembly. Apache-2 -- [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 7 · 🔀 100 · 📦 3 · 📋 71 - 14% open · ⏱️ 05.11.2021): +- [GitHub](https://github.com/finos/perspective) (👨‍💻 72 · 🔀 490 · 📦 4 · 📋 540 - 14% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/facebookresearch/hiplot + git clone https://github.com/finos/perspective ``` -- [PyPi](https://pypi.org/project/hiplot) (📥 10K / month): +- [PyPi](https://pypi.org/project/perspective-python) (📥 3K / month): ``` - pip install hiplot + pip install perspective-python ``` -- [Conda](https://anaconda.org/conda-forge/hiplot) (📥 73K · ⏱️ 05.11.2021): +- [NPM](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (📥 1.4K / month): ``` - conda install -c conda-forge hiplot + npm install @finos/perspective-jupyterlab ```
-
Sweetviz (🥉20 · ⭐ 1.8K) - 可视化和比较数据集，目标值和相关性。MIT +
plotnine (🥉21 · ⭐ 3.2K) - A grammar of graphics for Python. MIT -- [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 180 · 📋 90 - 22% open · ⏱️ 08.07.2021): +- [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 96 · 🔀 170 · 📋 500 - 13% open · ⏱️ 01.07.2022): ``` - git clone https://github.com/fbdesignpro/sweetviz + git clone https://github.com/has2k1/plotnine ``` -- [PyPi](https://pypi.org/project/sweetviz) (📥 60K / month): +- [PyPi](https://pypi.org/project/plotnine) (📥 350K / month): ``` - pip install sweetviz + pip install plotnine + ``` +- [Conda](https://anaconda.org/conda-forge/plotnine) (📥 190K · ⏱️ 02.07.2022): + ``` + conda install -c conda-forge plotnine ```
-
Multicore-TSNE (🥉20 · ⭐ 1.7K · 💀) - 使用Python和Torch并行执行t-SNE。BSD-3 +
Multicore-TSNE (🥉21 · ⭐ 1.7K · 💀) - Parallel t-SNE implementation with Python and Torch.. BSD-3 -- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 190 · 📦 260 · 📋 55 - 61% open · ⏱️ 19.08.2020): +- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 200 · 📦 310 · 📋 58 - 63% open · ⏱️ 19.08.2020): ``` git clone https://github.com/DmitryUlyanov/Multicore-TSNE ``` -- [PyPi](https://pypi.org/project/MulticoreTSNE): +- [PyPi](https://pypi.org/project/MulticoreTSNE) (📥 19K / month): ``` pip install MulticoreTSNE ``` -- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (📥 12K · ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (📥 18K · ⏱️ 09.11.2021): ``` conda install -c conda-forge multicore-tsne ```
-
PDPbox (🥉20 · ⭐ 640 · 💤) - python部分依赖图工具箱。MIT +
AutoViz (🥉20 · ⭐ 890) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 -- [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 100 · 📦 460 · 📋 55 - 30% open · ⏱️ 14.03.2021): +- [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 12 · 🔀 120 · 📦 240 · 📋 59 - 5% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/SauceCat/PDPbox - ``` -- [PyPi](https://pypi.org/project/pdpbox): - ``` - pip install pdpbox + git clone https://github.com/AutoViML/AutoViz ``` -- [Conda](https://anaconda.org/conda-forge/pdpbox) (📥 10K · ⏱️ 14.03.2021): +- [PyPi](https://pypi.org/project/autoviz) (📥 52K / month): ``` - conda install -c conda-forge pdpbox + pip install autoviz ```
-
PyWaffle (🥉19 · ⭐ 460) - 用Python作图。MIT +
PyWaffle (🥉20 · ⭐ 500) - Make Waffle Charts in Python. MIT -- [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 80 · 📦 100 · 📋 14 - 21% open · ⏱️ 28.07.2021): +- [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 92 · 📦 150 · 📋 18 - 22% open · ⏱️ 08.06.2022): ``` git clone https://github.com/gyli/PyWaffle ``` -- [PyPi](https://pypi.org/project/pywaffle) (📥 2.6K / month): +- [PyPi](https://pypi.org/project/pywaffle) (📥 8.3K / month): ``` pip install pywaffle ```
-
pivottablejs (🥉19 · ⭐ 450 · 💀) - Jupyter/IPython的Dragndrop数据透视表和图表。❗Unlicensed +
PandasGUI (🥉19 · ⭐ 2.7K) - A GUI for Pandas DataFrames. ❗️MIT-0 -- [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 61 · 📦 210 · 📋 56 - 28% open · ⏱️ 04.12.2018): +- [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 13 · 🔀 180 · 📦 170 · 📋 160 - 27% open · ⏱️ 16.03.2022): ``` - git clone https://github.com/nicolaskruchten/jupyter_pivottablejs + git clone https://github.com/adamerose/pandasgui ``` -- [PyPi](https://pypi.org/project/pivottablejs) (📥 17K / month): +- [PyPi](https://pypi.org/project/pandasgui) (📥 3.7K / month): ``` - pip install pivottablejs + pip install pandasgui ```
-
ivis (🥉19 · ⭐ 250) - 使用算法对非常大的数据集进行降维。Apache-2 +
HiPlot (🥉19 · ⭐ 2.3K) - HiPlot makes understanding high dimensional data easy. MIT -- [GitHub](https://github.com/beringresearch/ivis) (👨‍💻 10 · 🔀 26 · 📦 19 · 📋 53 - 5% open · ⏱️ 08.11.2021): +- [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 8 · 🔀 120 · 📦 5 · 📋 80 - 15% open · ⏱️ 05.07.2022): ``` - git clone https://github.com/beringresearch/ivis + git clone https://github.com/facebookresearch/hiplot ``` -- [PyPi](https://pypi.org/project/ivis) (📥 890 / month): +- [PyPi](https://pypi.org/project/hiplot) (📥 27K / month): ``` - pip install ivis + pip install hiplot + ``` +- [Conda](https://anaconda.org/conda-forge/hiplot) (📥 98K · ⏱️ 31.05.2022): + ``` + conda install -c conda-forge hiplot ```
-
FiftyOne (🥉18 · ⭐ 860) - 可视化，创建和调试图像和视频数据集。❗Unlicensed +
pivottablejs (🥉19 · ⭐ 470 · 💀) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. ❗Unlicensed -- [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 20 · 🔀 98 · 📦 64 · 📋 600 - 30% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 62 · 📦 260 · 📋 58 - 29% open · ⏱️ 04.12.2018): ``` - git clone https://github.com/voxel51/fiftyone + git clone https://github.com/nicolaskruchten/jupyter_pivottablejs ``` -- [PyPi](https://pypi.org/project/fiftyone): +- [PyPi](https://pypi.org/project/pivottablejs) (📥 14K / month): ``` - pip install fiftyone + pip install pivottablejs ```
-
animatplot (🥉18 · ⭐ 380 · 💀) - 用于在patpliblib上构建动画图的python程序包。MIT +
joypy (🥉19 · ⭐ 440 · 💤) - Joyplots in Python with matplotlib & pandas. MIT -- [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 35 · 📦 29 · 📋 30 - 43% open · ⏱️ 05.10.2020): +- [GitHub](https://github.com/leotac/joypy) (👨‍💻 6 · 🔀 47 · 📦 190 · 📋 47 - 21% open · ⏱️ 19.12.2021): ``` - git clone https://github.com/t-makaro/animatplot + git clone https://github.com/sbebo/joypy ``` -- [PyPi](https://pypi.org/project/animatplot) (📥 270 / month): +- [PyPi](https://pypi.org/project/joypy) (📥 13K / month): ``` - pip install animatplot + pip install joypy ``` -- [Conda](https://anaconda.org/conda-forge/animatplot) (📥 7.2K · ⏱️ 06.10.2020): +- [Conda](https://anaconda.org/conda-forge/joypy) (📥 15K · ⏱️ 28.12.2020): ``` - conda install -c conda-forge animatplot + conda install -c conda-forge joypy ```
-
joypy (🥉18 · ⭐ 370) - 带有matplotlib和pandas的Python中的Joyplots。MIT +
ivis (🥉19 · ⭐ 280) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 -- [GitHub](https://github.com/leotac/joypy) (👨‍💻 5 · 🔀 43 · 📦 110 · 📋 45 - 20% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/beringresearch/ivis) (👨‍💻 10 · 🔀 35 · 📦 26 · 📋 57 - 5% open · ⏱️ 29.07.2022): ``` - git clone https://github.com/sbebo/joypy + git clone https://github.com/beringresearch/ivis ``` -- [PyPi](https://pypi.org/project/joypy): +- [PyPi](https://pypi.org/project/ivis) (📥 330 / month): ``` - pip install joypy + pip install ivis + ``` +
+
Pandas-Bokeh (🥉18 · ⭐ 800) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT + +- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 14 · 🔀 100 · 📋 98 - 31% open · ⏱️ 25.03.2022): + ``` -- [Conda](https://anaconda.org/conda-forge/joypy) (📥 12K · ⏱️ 28.12.2020): + git clone https://github.com/PatrikHlobil/Pandas-Bokeh ``` - conda install -c conda-forge joypy +- [PyPi](https://pypi.org/project/pandas-bokeh) (📥 14K / month): + ``` + pip install pandas-bokeh ```
-
vega (🥉18 · ⭐ 320) - 适用于Vega和Vega-Lite的IPython/Jupyter笔记本模块。BSD-3 +
animatplot (🥉18 · ⭐ 400 · 💀) - A python package for animating plots build on matplotlib. MIT -- [GitHub](https://github.com/vega/ipyvega) (👨‍💻 10 · 🔀 52 · 📋 92 - 11% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 34 · 📦 35 · 📋 30 - 43% open · ⏱️ 05.10.2020): ``` - git clone https://github.com/vega/ipyvega + git clone https://github.com/t-makaro/animatplot ``` -- [PyPi](https://pypi.org/project/vega) (📥 21K / month): +- [PyPi](https://pypi.org/project/animatplot) (📥 260 / month): ``` - pip install vega + pip install animatplot ``` -- [Conda](https://anaconda.org/conda-forge/vega) (📥 470K · ⏱️ 18.11.2021): +- [Conda](https://anaconda.org/conda-forge/animatplot) (📥 9K · ⏱️ 06.10.2020): ``` - conda install -c conda-forge vega + conda install -c conda-forge animatplot ```
-
lets-plot (🥉17 · ⭐ 700) - 一个用于统计数据的开源绘图库。❗Unlicensed +
vega (🥉18 · ⭐ 330) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 -- [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 16 · 🔀 29 · 📥 140 · 📦 12 · 📋 220 - 32% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/vega/ipyvega) (👨‍💻 11 · 🔀 55 · 📋 95 - 13% open · ⏱️ 01.08.2022): ``` - git clone https://github.com/JetBrains/lets-plot + git clone https://github.com/vega/ipyvega ``` -- [PyPi](https://pypi.org/project/lets-plot): +- [PyPi](https://pypi.org/project/vega) (📥 7.3K / month): ``` - pip install lets-plot + pip install vega + ``` +- [Conda](https://anaconda.org/conda-forge/vega) (📥 500K · ⏱️ 10.02.2022): + ``` + conda install -c conda-forge vega ```
-
pdvega (🥉16 · ⭐ 340 · 💀) - 使用Vega-Lite交互式绘制pandas数据图。MIT +
pdvega (🥉16 · ⭐ 340 · 💀) - Interactive plotting for Pandas using Vega-Lite. MIT -- [GitHub](https://github.com/altair-viz/pdvega) (👨‍💻 9 · 🔀 30 · 📦 59 · 📋 26 - 61% open · ⏱️ 29.03.2019): +- [GitHub](https://github.com/altair-viz/pdvega) (👨‍💻 9 · 🔀 31 · 📦 67 · 📋 26 - 61% open · ⏱️ 29.03.2019): ``` git clone https://github.com/altair-viz/pdvega ``` -- [PyPi](https://pypi.org/project/pdvega) (📥 140 / month): +- [PyPi](https://pypi.org/project/pdvega) (📥 56 / month): ``` pip install pdvega ```
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AutoViz (🥉15 · ⭐ 580) - 自动显示任意行的任何大小的任何数据集。Apache-2 +
data-describe (🥉14 · ⭐ 290 · 💤) - datadescribe: Pythonic EDA Accelerator for Data.. ❗Unlicensed -- [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 11 · 🔀 86 · 📦 120 · 📋 41 - 17% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/data-describe/data-describe) (👨‍💻 14 · 🔀 18 · 📋 240 - 28% open · ⏱️ 19.11.2021): ``` - git clone https://github.com/AutoViML/AutoViz + git clone https://github.com/data-describe/data-describe ``` -- [PyPi](https://pypi.org/project/autoviz): +- [PyPi](https://pypi.org/project/data-describe) (📥 2.6K / month): ``` - pip install autoviz + pip install data-describe ```
-
nx-altair (🥉15 · ⭐ 180 · 💀) - 使用Altair绘制交互式NetworkX图形。MIT +
nx-altair (🥉14 · ⭐ 200 · 💀) - Draw interactive NetworkX graphs with Altair. MIT -- [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 22 · 📋 10 - 60% open · ⏱️ 02.06.2020): +- [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 23 · 📋 10 - 60% open · ⏱️ 02.06.2020): ``` git clone https://github.com/Zsailer/nx_altair ``` -- [PyPi](https://pypi.org/project/nx-altair) (📥 3.1K / month): +- [PyPi](https://pypi.org/project/nx-altair) (📥 1.5K / month): ``` pip install nx-altair ```
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data-describe (🥉13 · ⭐ 290) - 数据描述：Pythonic EDA数据科学加速器。❗Unlicensed - -- [GitHub](https://github.com/data-describe/data-describe) (👨‍💻 14 · 🔀 15 · 📋 240 - 28% open · ⏱️ 19.11.2021): - - ``` - git clone https://github.com/data-describe/data-describe - ``` -- [PyPi](https://pypi.org/project/data-describe) (📥 310 / month): - ``` - pip install data-describe - ``` -
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nptsne (🥉11 · ⭐ 27 · 💤) - nptsne是numpy兼容的python二进制包。Apache-2 +
nptsne (🥉11 · ⭐ 29 · 💀) - nptsne is a numpy compatible python binary package that offers a.. Apache-2 -- [GitHub](https://github.com/biovault/nptsne) (👨‍💻 3 · 🔀 2 · 📦 3 · 📋 12 - 58% open · ⏱️ 03.02.2021): +- [GitHub](https://github.com/biovault/nptsne) (👨‍💻 3 · 🔀 2 · 📦 4 · 📋 13 - 53% open · ⏱️ 03.02.2021): ``` git clone https://github.com/biovault/nptsne ``` -- [PyPi](https://pypi.org/project/nptsne): +- [PyPi](https://pypi.org/project/nptsne) (📥 70 / month): ``` pip install nptsne ```

-## 文本数据和NLP +## Text Data & NLP -Back to top +Back to top -_用于处理，清理，处理和分析文本数据的库，以及用于NLP任务的库，例如语言检测，模糊匹配，文本分类，seq2seq学习，智能对话，关键字提取和机器翻译。_ +_Libraries for processing, cleaning, manipulating, and analyzing text data as well as libraries for NLP tasks such as language detection, fuzzy matching, classification, seq2seq learning, conversational AI, keyword extraction, and translation._ -
transformers (🥇38 · ⭐ 56K) - transformers：先进的自然语言模型库。Apache-2 +
spaCy (🥇38 · ⭐ 24K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT -- [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1.1K · 🔀 13K · 📥 1.4K · 📦 20K · 📋 8.3K - 3% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/explosion/spaCy) (👨‍💻 700 · 🔀 3.8K · 📥 3.1K · 📦 43K · 📋 5.2K - 1% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/huggingface/transformers + git clone https://github.com/explosion/spaCy ``` -- [PyPi](https://pypi.org/project/transformers) (📥 3.2M / month): +- [PyPi](https://pypi.org/project/spacy) (📥 4.7M / month): ``` - pip install transformers + pip install spacy ``` -- [Conda](https://anaconda.org/conda-forge/transformers) (📥 87K · ⏱️ 16.12.2021): +- [Conda](https://anaconda.org/conda-forge/spacy) (📥 2.8M · ⏱️ 27.07.2022): ``` - conda install -c conda-forge transformers + conda install -c conda-forge spacy ```
-
spaCy (🥇38 · ⭐ 22K) - Python中的工业级自然语言处理（NLP）工具包。MIT +
transformers (🥇37 · ⭐ 69K) - Transformers: State-of-the-art Natural Language.. Apache-2 -- [GitHub](https://github.com/explosion/spaCy) (👨‍💻 640 · 🔀 3.6K · 📥 3.1K · 📦 33K · 📋 5K - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1.4K · 🔀 15K · 📥 1.5K · 📦 34K · 📋 9.9K - 4% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/explosion/spaCy + git clone https://github.com/huggingface/transformers ``` -- [PyPi](https://pypi.org/project/spacy) (📥 5.9M / month): +- [PyPi](https://pypi.org/project/transformers) (📥 6.1M / month): ``` - pip install spacy + pip install transformers ``` -- [Conda](https://anaconda.org/conda-forge/spacy) (📥 2.5M · ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/transformers) (📥 370K · ⏱️ 25.08.2022): ``` - conda install -c conda-forge spacy + conda install -c conda-forge transformers ```
-
gensim (🥇36 · ⭐ 13K) - 主题模型工具库。❗️LGPL-2.1 +
gensim (🥇36 · ⭐ 13K) - Topic Modelling for Humans. ❗️LGPL-2.1 -- [GitHub](https://github.com/RaRe-Technologies/gensim) (👨‍💻 420 · 🔀 3.9K · 📥 3.5K · 📦 29K · 📋 1.7K - 20% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/RaRe-Technologies/gensim) (👨‍💻 430 · 🔀 4K · 📥 3.8K · 📦 36K · 📋 1.8K - 20% open · ⏱️ 22.08.2022): ``` git clone https://github.com/RaRe-Technologies/gensim ``` -- [PyPi](https://pypi.org/project/gensim) (📥 10M / month): +- [PyPi](https://pypi.org/project/gensim) (📥 4.9M / month): ``` pip install gensim ``` -- [Conda](https://anaconda.org/conda-forge/gensim) (📥 760K · ⏱️ 09.11.2021): +- [Conda](https://anaconda.org/conda-forge/gensim) (📥 860K · ⏱️ 29.07.2022): ``` conda install -c conda-forge gensim ```
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nltk (🥇33 · ⭐ 10K) - 用于符号和统计自然的库和程序套件。Apache-2 +
sentence-transformers (🥇34 · ⭐ 8.3K) - Sentence Embeddings with BERT & XLNet. Apache-2 -- [GitHub](https://github.com/nltk/nltk) (👨‍💻 410 · 🔀 2.4K · 📦 120K · 📋 1.6K - 12% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 93 · 🔀 1.6K · 📦 4K · 📋 1.5K - 51% open · ⏱️ 15.08.2022): ``` - git clone https://github.com/nltk/nltk - ``` -- [PyPi](https://pypi.org/project/nltk) (📥 9.5M / month): - ``` - pip install nltk + git clone https://github.com/UKPLab/sentence-transformers ``` -- [Conda](https://anaconda.org/conda-forge/nltk) (📥 1.1M · ⏱️ 11.10.2021): +- [PyPi](https://pypi.org/project/sentence-transformers) (📥 1.5M / month): ``` - conda install -c conda-forge nltk + pip install sentence-transformers ```
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AllenNLP (🥇32 · ⭐ 11K) - 基于PyTorch的开源NLP研究库。Apache-2 +
AllenNLP (🥇33 · ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 -- [GitHub](https://github.com/allenai/allennlp) (👨‍💻 250 · 🔀 2.1K · 📥 43 · 📦 2.1K · 📋 2.5K - 3% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/allenai/allennlp) (👨‍💻 260 · 🔀 2.1K · 📥 47 · 📦 2.7K · 📋 2.5K - 3% open · ⏱️ 24.08.2022): ``` git clone https://github.com/allenai/allennlp ``` -- [PyPi](https://pypi.org/project/allennlp) (📥 37K / month): +- [PyPi](https://pypi.org/project/allennlp) (📥 72K / month): ``` pip install allennlp ```
-
fastText (🥇31 · ⭐ 23K · 💀) - 用于快速文本表示和分类的库。MIT +
nltk (🥇33 · ⭐ 11K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 -- [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 58 · 🔀 4.3K · 📦 2.4K · 📋 1K - 40% open · ⏱️ 18.07.2020): +- [GitHub](https://github.com/nltk/nltk) (👨‍💻 430 · 🔀 2.5K · 📦 150K · 📋 1.6K - 13% open · ⏱️ 29.07.2022): ``` - git clone https://github.com/facebookresearch/fastText + git clone https://github.com/nltk/nltk ``` -- [PyPi](https://pypi.org/project/fasttext) (📥 470K / month): +- [PyPi](https://pypi.org/project/nltk) (📥 12M / month): ``` - pip install fasttext + pip install nltk ``` -- [Conda](https://anaconda.org/conda-forge/fasttext) (📥 25K · ⏱️ 08.11.2021): +- [Conda](https://anaconda.org/conda-forge/nltk) (📥 1.4M · ⏱️ 29.12.2021): ``` - conda install -c conda-forge fasttext + conda install -c conda-forge nltk ```
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ChatterBot (🥇31 · ⭐ 12K) - ChatterBot是机器学习的对话引擎。BSD-3 +
sentencepiece (🥇33 · ⭐ 6.1K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 -- [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 3.8K · 📦 4K · 📋 1.5K - 18% open · ⏱️ 01.06.2021): +- [GitHub](https://github.com/google/sentencepiece) (👨‍💻 68 · 🔀 810 · 📥 22K · 📦 17K · 📋 540 - 2% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/gunthercox/ChatterBot + git clone https://github.com/google/sentencepiece ``` -- [PyPi](https://pypi.org/project/chatterbot) (📥 33K / month): +- [PyPi](https://pypi.org/project/sentencepiece) (📥 5.6M / month): ``` - pip install chatterbot + pip install sentencepiece + ``` +- [Conda](https://anaconda.org/conda-forge/sentencepiece) (📥 220K · ⏱️ 08.04.2022): + ``` + conda install -c conda-forge sentencepiece ```
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fuzzywuzzy (🥇31 · ⭐ 8.6K) - Python中的模糊字符串匹配。❗️GPL-2.0 +
ChatterBot (🥇32 · ⭐ 12K · 💀) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 -- [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 860 · 📦 11K · 📋 180 - 43% open · ⏱️ 09.09.2021): +- [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 4K · 📦 4.5K · 📋 1.6K - 19% open · ⏱️ 01.06.2021): ``` - git clone https://github.com/seatgeek/fuzzywuzzy - ``` -- [PyPi](https://pypi.org/project/fuzzywuzzy) (📥 5.3M / month): - ``` - pip install fuzzywuzzy + git clone https://github.com/gunthercox/ChatterBot ``` -- [Conda](https://anaconda.org/conda-forge/fuzzywuzzy) (📥 340K · ⏱️ 18.11.2020): +- [PyPi](https://pypi.org/project/chatterbot) (📥 71K / month): ``` - conda install -c conda-forge fuzzywuzzy + pip install chatterbot ```
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sentence-transformers (🥇31 · ⭐ 6.7K) - BERT和XLNet的句子嵌入。Apache-2 +
fastText (🥇31 · ⭐ 24K) - Library for fast text representation and classification. MIT -- [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 67 · 🔀 1.3K · 📦 2.1K · 📋 1.2K - 49% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 59 · 🔀 4.3K · 📦 3.2K · 📋 1K - 41% open · ⏱️ 04.03.2022): ``` - git clone https://github.com/UKPLab/sentence-transformers + git clone https://github.com/facebookresearch/fastText ``` -- [PyPi](https://pypi.org/project/sentence-transformers) (📥 560K / month): +- [PyPi](https://pypi.org/project/fasttext) (📥 810K / month): ``` - pip install sentence-transformers + pip install fasttext + ``` +- [Conda](https://anaconda.org/conda-forge/fasttext) (📥 36K · ⏱️ 16.04.2022): + ``` + conda install -c conda-forge fasttext ```
-
sentencepiece (🥇31 · ⭐ 5.5K) - 用于基于神经网络的文本的预处理器。Apache-2 +
TextBlob (🥇31 · ⭐ 8.3K · 💤) - Simple, Pythonic, text processing--Sentiment analysis, part-of-.. MIT -- [GitHub](https://github.com/google/sentencepiece) (👨‍💻 57 · 🔀 730 · 📥 19K · 📦 12K · 📋 490 - 9% open · ⏱️ 02.07.2021): +- [GitHub](https://github.com/sloria/TextBlob) (👨‍💻 35 · 🔀 1K · 📥 100 · 📦 22K · 📋 250 - 37% open · ⏱️ 22.10.2021): ``` - git clone https://github.com/google/sentencepiece + git clone https://github.com/sloria/TextBlob ``` -- [PyPi](https://pypi.org/project/sentencepiece) (📥 3.3M / month): +- [PyPi](https://pypi.org/project/textblob) (📥 860K / month): ``` - pip install sentencepiece + pip install textblob ``` -- [Conda](https://anaconda.org/conda-forge/sentencepiece) (📥 130K · ⏱️ 05.11.2021): +- [Conda](https://anaconda.org/conda-forge/textblob) (📥 170K · ⏱️ 24.02.2019): ``` - conda install -c conda-forge sentencepiece + conda install -c conda-forge textblob ```
-
flair (🥈30 · ⭐ 11K) - 一个用于最先进的自然语言处理的非常简单的框架。❗Unlicensed +
flair (🥈30 · ⭐ 12K) - A very simple framework for state-of-the-art Natural Language.. ❗Unlicensed -- [GitHub](https://github.com/flairNLP/flair) (👨‍💻 210 · 🔀 1.5K · 📦 1.1K · 📋 1.7K - 4% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/flairNLP/flair) (👨‍💻 230 · 🔀 1.6K · 📦 1.6K · 📋 1.9K - 6% open · ⏱️ 18.08.2022): ``` git clone https://github.com/flairNLP/flair ``` -- [PyPi](https://pypi.org/project/flair) (📥 67K / month): +- [PyPi](https://pypi.org/project/flair) (📥 170K / month): ``` pip install flair ```
-
TextBlob (🥈30 · ⭐ 8K) - 包含情感分析、词性标注等等功能的NLP工具库。MIT +
fuzzywuzzy (🥈30 · ⭐ 8.7K · 💤) - Fuzzy String Matching in Python. ❗️GPL-2.0 -- [GitHub](https://github.com/sloria/TextBlob) (👨‍💻 35 · 🔀 1K · 📥 97 · 📦 16K · 📋 240 - 36% open · ⏱️ 22.10.2021): +- [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 870 · 📦 14K · 📋 180 - 43% open · ⏱️ 09.09.2021): ``` - git clone https://github.com/sloria/TextBlob - ``` -- [PyPi](https://pypi.org/project/textblob) (📥 820K / month): - ``` - pip install textblob - ``` -- [Conda](https://anaconda.org/conda-forge/textblob) (📥 150K · ⏱️ 24.02.2019): - ``` - conda install -c conda-forge textblob + git clone https://github.com/seatgeek/fuzzywuzzy ``` -
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ParlAI (🥈29 · ⭐ 8.5K) - 一个用于训练和评估AI模型的框架。MIT - -- [GitHub](https://github.com/facebookresearch/ParlAI) (👨‍💻 170 · 🔀 1.7K · 📦 54 · 📋 1.2K - 7% open · ⏱️ 15.12.2021): - +- [PyPi](https://pypi.org/project/fuzzywuzzy) (📥 7.3M / month): ``` - git clone https://github.com/facebookresearch/ParlAI + pip install fuzzywuzzy ``` -- [PyPi](https://pypi.org/project/parlai) (📥 2.3K / month): +- [Conda](https://anaconda.org/conda-forge/fuzzywuzzy) (📥 380K · ⏱️ 18.11.2020): ``` - pip install parlai + conda install -c conda-forge fuzzywuzzy ```
-
DeepPavlov (🥈28 · ⭐ 5.5K) - 一个用于深度学习端到端对话的开源库。Apache-2 +
fairseq (🥈29 · ⭐ 19K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT -- [GitHub](https://github.com/deepmipt/DeepPavlov) (👨‍💻 67 · 🔀 970 · 📦 240 · 📋 600 - 16% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/facebookresearch/fairseq) (👨‍💻 400 · 🔀 4.7K · 📥 260 · 📦 920 · 📋 3.5K - 18% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/deepmipt/DeepPavlov + git clone https://github.com/pytorch/fairseq ``` -- [PyPi](https://pypi.org/project/deeppavlov) (📥 11K / month): +- [PyPi](https://pypi.org/project/fairseq) (📥 40K / month): ``` - pip install deeppavlov + pip install fairseq ```
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Tokenizers (🥈28 · ⭐ 5.1K) - 针对研究和应用进行了优化的快速最先进的分词器。Apache-2 +
TextDistance (🥈29 · ⭐ 2.9K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT -- [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 46 · 🔀 410 · 📦 38 · 📋 530 - 27% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/life4/textdistance) (👨‍💻 12 · 🔀 230 · 📥 830 · 📦 2.6K · ⏱️ 21.08.2022): ``` - git clone https://github.com/huggingface/tokenizers + git clone https://github.com/life4/textdistance ``` -- [PyPi](https://pypi.org/project/tokenizers) (📥 3.8M / month): +- [PyPi](https://pypi.org/project/textdistance) (📥 640K / month): ``` - pip install tokenizers + pip install textdistance ``` -- [Conda](https://anaconda.org/conda-forge/tokenizers) (📥 110K · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/textdistance) (📥 180K · ⏱️ 21.08.2022): ``` - conda install -c conda-forge tokenizers + conda install -c conda-forge textdistance ```
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ftfy (🥈28 · ⭐ 3.1K · 💤) - 修复Unicode文本中的故障功能的工具库。MIT +
TensorFlow Text (🥈29 · ⭐ 980) - Making text a first-class citizen in TensorFlow. Apache-2 -- [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 100 · 📦 4.5K · 📋 120 - 9% open · ⏱️ 17.05.2021): +- [GitHub](https://github.com/tensorflow/text) (👨‍💻 91 · 🔀 230 · 📦 2.2K · 📋 180 - 18% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/LuminosoInsight/python-ftfy - ``` -- [PyPi](https://pypi.org/project/ftfy) (📥 970K / month): - ``` - pip install ftfy + git clone https://github.com/tensorflow/text ``` -- [Conda](https://anaconda.org/conda-forge/ftfy) (📥 130K · ⏱️ 25.05.2021): +- [PyPi](https://pypi.org/project/tensorflow-text) (📥 2.2M / month): ``` - conda install -c conda-forge ftfy + pip install tensorflow-text ```
-
GluonNLP (🥈27 · ⭐ 2.3K) - 可轻松进行文本预处理，数据集加载和处理的工具包。Apache-2 +
GluonNLP (🥈28 · ⭐ 2.4K · 💤) - Toolkit that enables easy text preprocessing, datasets.. Apache-2 -- [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 680 · 📋 530 - 44% open · ⏱️ 24.08.2021): +- [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 920 · 📋 530 - 44% open · ⏱️ 24.08.2021): ``` git clone https://github.com/dmlc/gluon-nlp @@ -1791,1821 +1775,1837 @@ _用于处理，清理，处理和分析文本数据的库，以及用于NLP任 pip install gluonnlp ```
-
Dedupe (🥈26 · ⭐ 3.2K) - 一个用于准确和可扩展的模糊匹配的python库。MIT +
DeepPavlov (🥈27 · ⭐ 5.8K) - An open source library for deep learning end-to-end dialog.. Apache-2 -- [GitHub](https://github.com/dedupeio/dedupe) (👨‍💻 61 · 🔀 440 · 📦 210 · 📋 670 - 9% open · ⏱️ 14.10.2021): +- [GitHub](https://github.com/deepmipt/DeepPavlov) (👨‍💻 67 · 🔀 1K · 📦 280 · 📋 620 - 8% open · ⏱️ 31.05.2022): ``` - git clone https://github.com/dedupeio/dedupe + git clone https://github.com/deepmipt/DeepPavlov ``` -- [PyPi](https://pypi.org/project/dedupe) (📥 250K / month): +- [PyPi](https://pypi.org/project/deeppavlov) (📥 8K / month): ``` - pip install dedupe + pip install deeppavlov ```
-
TextDistance (🥈26 · ⭐ 2.6K) - 计算序列之间的距离，包含30多种算法。MIT +
OpenNMT (🥈27 · ⭐ 5.7K) - Open Source Neural Machine Translation in PyTorch. MIT -- [GitHub](https://github.com/life4/textdistance) (👨‍💻 11 · 🔀 200 · 📥 410 · 📦 1.4K · ⏱️ 29.11.2021): +- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 180 · 🔀 2K · 📦 150 · 📋 1.3K - 6% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/life4/textdistance + git clone https://github.com/OpenNMT/OpenNMT-py ``` -- [PyPi](https://pypi.org/project/textdistance) (📥 280K / month): +- [PyPi](https://pypi.org/project/OpenNMT-py) (📥 5.2K / month): ``` - pip install textdistance + pip install OpenNMT-py ``` -- [Conda](https://anaconda.org/conda-forge/textdistance) (📥 67K · ⏱️ 27.10.2021): +
+
spark-nlp (🥈27 · ⭐ 2.9K) - State of the Art Natural Language Processing. Apache-2 + +- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 130 · 🔀 570 · 📋 700 - 5% open · ⏱️ 24.08.2022): + ``` - conda install -c conda-forge textdistance + git clone https://github.com/JohnSnowLabs/spark-nlp + ``` +- [PyPi](https://pypi.org/project/spark-nlp) (📥 2.4M / month): + ``` + pip install spark-nlp ```
-
spacy-transformers (🥈26 · ⭐ 1.1K) - 使用经过预训练的transformer模型，例如BERT，XLNet和GPT-2。MIT spacy +
spacy-transformers (🥈27 · ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy -- [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 18 · 🔀 130 · 📦 340 · ⏱️ 16.12.2021): +- [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 18 · 🔀 140 · 📦 610 · ⏱️ 23.08.2022): ``` git clone https://github.com/explosion/spacy-transformers ``` -- [PyPi](https://pypi.org/project/spacy-transformers) (📥 85K / month): +- [PyPi](https://pypi.org/project/spacy-transformers) (📥 100K / month): ``` pip install spacy-transformers ```
-
Rasa (🥈25 · ⭐ 13K) - 开源机器学习框架，可处理文本和语音多场景问题。Apache-2 +
ParlAI (🥈26 · ⭐ 9.4K) - A framework for training and evaluating AI models on a variety of.. MIT -- [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 520 · 🔀 3.7K · 📋 6.3K - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/facebookresearch/ParlAI) (👨‍💻 200 · 🔀 1.8K · 📦 87 · 📋 1.4K - 5% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/RasaHQ/rasa + git clone https://github.com/facebookresearch/ParlAI ``` -- [PyPi](https://pypi.org/project/rasa) (📥 230K / month): +- [PyPi](https://pypi.org/project/parlai) (📥 3.4K / month): ``` - pip install rasa + pip install parlai ```
-
OpenNMT (🥈25 · ⭐ 5.4K) - PyTorch中的开源神经机器翻译。MIT +
Tokenizers (🥈26 · ⭐ 5.8K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 -- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 170 · 🔀 1.9K · 📦 120 · 📋 1.3K - 6% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 59 · 🔀 480 · 📦 51 · 📋 650 - 30% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/OpenNMT/OpenNMT-py + git clone https://github.com/huggingface/tokenizers ``` -- [PyPi](https://pypi.org/project/OpenNMT-py): +- [PyPi](https://pypi.org/project/tokenizers) (📥 5.9M / month): ``` - pip install OpenNMT-py + pip install tokenizers + ``` +- [Conda](https://anaconda.org/conda-forge/tokenizers) (📥 330K · ⏱️ 21.05.2022): + ``` + conda install -c conda-forge tokenizers ```
-
haystack (🥈25 · ⭐ 3.4K) - 用于构建自然语言搜索的端到端Python框架。Apache-2 +
Sumy (🥈26 · ⭐ 2.9K) - Module for automatic summarization of text documents and HTML pages. Apache-2 -- [GitHub](https://github.com/deepset-ai/haystack) (👨‍💻 87 · 🔀 580 · 📦 94 · 📋 1K - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 23 · 🔀 470 · 📦 1.4K · 📋 110 - 15% open · ⏱️ 31.07.2022): ``` - git clone https://github.com/deepset-ai/haystack + git clone https://github.com/miso-belica/sumy ``` -- [PyPi](https://pypi.org/project/haystack) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/sumy) (📥 21K / month): ``` - pip install haystack + pip install sumy ```
-
neuralcoref (🥈25 · ⭐ 2.5K) - 基于SpaCy的神经网络实现快速共指解析。MIT +
jellyfish (🥈26 · ⭐ 1.7K · 💤) - a python library for doing approximate and phonetic matching of.. BSD-2 -- [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 420 · 📥 300 · 📦 430 · 📋 290 - 20% open · ⏱️ 22.06.2021): +- [GitHub](https://github.com/jamesturk/jellyfish) (👨‍💻 25 · 🔀 140 · 📦 4.1K · 📋 110 - 10% open · ⏱️ 07.01.2022): ``` - git clone https://github.com/huggingface/neuralcoref + git clone https://github.com/jamesturk/jellyfish ``` -- [PyPi](https://pypi.org/project/neuralcoref) (📥 53K / month): +- [PyPi](https://pypi.org/project/jellyfish) (📥 2.6M / month): ``` - pip install neuralcoref + pip install jellyfish ``` -- [Conda](https://anaconda.org/conda-forge/neuralcoref) (📥 10K · ⏱️ 21.02.2020): +- [Conda](https://anaconda.org/conda-forge/jellyfish) (📥 300K · ⏱️ 08.04.2022): ``` - conda install -c conda-forge neuralcoref + conda install -c conda-forge jellyfish ```
-
fastNLP (🥈25 · ⭐ 2.4K) - fastNLP：模块化和可扩展的NLP框架。Apache-2 +
Rasa (🥈25 · ⭐ 15K) - Open source machine learning framework to automate text- and voice-.. Apache-2 -- [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 54 · 🔀 400 · 📥 65 · 📦 52 · 📋 180 - 19% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 550 · 🔀 4K · 📋 6.6K - 12% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/fastnlp/fastNLP + git clone https://github.com/RasaHQ/rasa ``` -- [PyPi](https://pypi.org/project/fastnlp) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/rasa) (📥 170K / month): ``` - pip install fastnlp + pip install rasa ```
-
jellyfish (🥈25 · ⭐ 1.6K) - 一个python库，用于进行文本相似度和距离计算。BSD-2 +
stanza (🥈25 · ⭐ 6.2K) - Official Stanford NLP Python Library for Many Human Languages. ❗Unlicensed -- [GitHub](https://github.com/jamesturk/jellyfish) (👨‍💻 25 · 🔀 140 · 📦 3K · 📋 110 - 8% open · ⏱️ 16.11.2021): +- [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 48 · 🔀 790 · 📦 1.2K · 📋 720 - 11% open · ⏱️ 23.04.2022): ``` - git clone https://github.com/jamesturk/jellyfish + git clone https://github.com/stanfordnlp/stanza ``` -- [PyPi](https://pypi.org/project/jellyfish) (📥 1.7M / month): +- [PyPi](https://pypi.org/project/stanza) (📥 330K / month): ``` - pip install jellyfish + pip install stanza ``` -- [Conda](https://anaconda.org/conda-forge/jellyfish) (📥 160K · ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/stanfordnlp/stanza) (📥 5.6K · ⏱️ 23.04.2022): ``` - conda install -c conda-forge jellyfish + conda install -c stanfordnlp stanza ```
-
Ciphey (🥈24 · ⭐ 9.1K) - 在不知道密钥或密码的情况下自动解密加密。MIT +
ftfy (🥈25 · ⭐ 3.3K) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT -- [GitHub](https://github.com/Ciphey/Ciphey) (👨‍💻 46 · 🔀 560 · 📋 270 - 15% open · ⏱️ 03.11.2021): +- [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 110 · 📦 6.6K · 📋 130 - 9% open · ⏱️ 09.02.2022): ``` - git clone https://github.com/Ciphey/Ciphey + git clone https://github.com/LuminosoInsight/python-ftfy ``` -- [PyPi](https://pypi.org/project/ciphey) (📥 15K / month): +- [PyPi](https://pypi.org/project/ftfy) (📥 2.1M / month): ``` - pip install ciphey + pip install ftfy ``` -- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (📥 14K · ⭐ 5 · ⏱️ 16.11.2021): +- [Conda](https://anaconda.org/conda-forge/ftfy) (📥 180K · ⏱️ 13.03.2022): ``` - docker pull remnux/ciphey + conda install -c conda-forge ftfy ```
-
stanza (🥈24 · ⭐ 5.9K) - 斯坦福NLP官方Python语言库，支持多种语言。❗Unlicensed +
fastNLP (🥈25 · ⭐ 2.7K) - fastNLP: A Modularized and Extensible NLP Framework. Currently still.. Apache-2 -- [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 41 · 🔀 740 · 📦 780 · 📋 610 - 11% open · ⏱️ 18.11.2021): +- [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 59 · 🔀 420 · 📥 66 · 📦 90 · 📋 190 - 22% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/stanfordnlp/stanza - ``` -- [PyPi](https://pypi.org/project/stanza) (📥 250K / month): - ``` - pip install stanza + git clone https://github.com/fastnlp/fastNLP ``` -- [Conda](https://anaconda.org/stanfordnlp/stanza) (📥 4.5K · ⏱️ 05.10.2021): +- [PyPi](https://pypi.org/project/fastnlp) (📥 2.5K / month): ``` - conda install -c stanfordnlp stanza + pip install fastnlp ```
-
torchtext (🥈24 · ⭐ 2.9K) - 文本和NLP的数据加载器和抽象。BSD-3 +
neuralcoref (🥈25 · ⭐ 2.6K · 💀) - Fast Coreference Resolution in spaCy with Neural Networks. MIT -- [GitHub](https://github.com/pytorch/text) (👨‍💻 120 · 🔀 640 · 📋 590 - 43% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 440 · 📥 450 · 📦 520 · 📋 300 - 16% open · ⏱️ 22.06.2021): ``` - git clone https://github.com/pytorch/text + git clone https://github.com/huggingface/neuralcoref ``` -- [PyPi](https://pypi.org/project/torchtext) (📥 120K / month): +- [PyPi](https://pypi.org/project/neuralcoref) (📥 270K / month): ``` - pip install torchtext + pip install neuralcoref + ``` +- [Conda](https://anaconda.org/conda-forge/neuralcoref) (📥 12K · ⏱️ 21.02.2020): + ``` + conda install -c conda-forge neuralcoref ```
-
PyTextRank (🥈24 · ⭐ 1.7K) - TextRank的Python实现。MIT +
PyTextRank (🥈25 · ⭐ 1.9K) - Python implementation of TextRank for phrase extraction and.. MIT -- [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 17 · 🔀 290 · 📦 220 · 📋 79 - 27% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 18 · 🔀 300 · 📦 280 · 📋 89 - 19% open · ⏱️ 27.07.2022): ``` git clone https://github.com/DerwenAI/pytextrank ``` -- [PyPi](https://pypi.org/project/pytextrank) (📥 18K / month): +- [PyPi](https://pypi.org/project/pytextrank) (📥 70K / month): ``` pip install pytextrank ```
-
pyahocorasick (🥈24 · ⭐ 660) - Python文本工具库。BSD-3 +
SciSpacy (🥈25 · ⭐ 1.2K) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 + +- [GitHub](https://github.com/allenai/scispacy) (👨‍💻 24 · 🔀 160 · 📦 500 · 📋 260 - 10% open · ⏱️ 04.08.2022): + + ``` + git clone https://github.com/allenai/scispacy + ``` +- [PyPi](https://pypi.org/project/scispacy) (📥 21K / month): + ``` + pip install scispacy + ``` +
+
pyahocorasick (🥈25 · ⭐ 740) - Python module (C extension and plain python) implementing Aho-.. BSD-3 -- [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 23 · 🔀 95 · 📦 840 · 📋 110 - 34% open · ⏱️ 22.11.2021): +- [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 24 · 🔀 110 · 📦 1.2K · 📋 120 - 20% open · ⏱️ 04.05.2022): ``` git clone https://github.com/WojciechMula/pyahocorasick ``` -- [PyPi](https://pypi.org/project/pyahocorasick) (📥 320K / month): +- [PyPi](https://pypi.org/project/pyahocorasick) (📥 400K / month): ``` pip install pyahocorasick ``` -- [Conda](https://anaconda.org/conda-forge/pyahocorasick) (📥 140K · ⏱️ 13.10.2020): +- [Conda](https://anaconda.org/conda-forge/pyahocorasick) (📥 150K · ⏱️ 15.04.2022): ``` conda install -c conda-forge pyahocorasick ```
-
fairseq (🥈23 · ⭐ 15K) - 用Python编写的Facebook AI Research Sequence-to-Sequence工具包。MIT +
Ciphey (🥈24 · ⭐ 11K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT -- [GitHub](https://github.com/pytorch/fairseq) (👨‍💻 370 · 🔀 3.8K · 📥 160 · 📦 610 · 📋 3.1K - 34% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Ciphey/Ciphey) (👨‍💻 46 · 🔀 650 · 📋 290 - 15% open · ⏱️ 28.06.2022): ``` - git clone https://github.com/pytorch/fairseq + git clone https://github.com/Ciphey/Ciphey ``` -- [PyPi](https://pypi.org/project/fairseq): +- [PyPi](https://pypi.org/project/ciphey) (📥 23K / month): ``` - pip install fairseq + pip install ciphey + ``` +- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (📥 16K · ⭐ 8 · ⏱️ 27.05.2022): + ``` + docker pull remnux/ciphey ```
-
flashtext (🥈23 · ⭐ 5K · 💀) - 从句子中提取关键字或替换句子中的关键字。MIT +
vaderSentiment (🥈24 · ⭐ 3.7K) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary and.. MIT -- [GitHub](https://github.com/vi3k6i5/flashtext) (👨‍💻 7 · 🔀 550 · 📦 650 · 📋 96 - 46% open · ⏱️ 03.05.2020): +- [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 11 · 🔀 880 · 📦 4.1K · 📋 110 - 31% open · ⏱️ 01.04.2022): ``` - git clone https://github.com/vi3k6i5/flashtext + git clone https://github.com/cjhutto/vaderSentiment ``` -- [PyPi](https://pypi.org/project/flashtext) (📥 460K / month): +- [PyPi](https://pypi.org/project/vadersentiment) (📥 190K / month): ``` - pip install flashtext + pip install vadersentiment ```
-
vaderSentiment (🥈23 · ⭐ 3.3K · 💤) - VADER情感分析。MIT +
torchtext (🥈24 · ⭐ 3.1K) - Data loaders and abstractions for text and NLP. BSD-3 -- [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 10 · 🔀 820 · 📦 3.3K · 📋 100 - 28% open · ⏱️ 15.03.2021): +- [GitHub](https://github.com/pytorch/text) (👨‍💻 140 · 🔀 700 · 📋 670 - 33% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/cjhutto/vaderSentiment + git clone https://github.com/pytorch/text ``` -- [PyPi](https://pypi.org/project/vadersentiment) (📥 220K / month): +- [PyPi](https://pypi.org/project/torchtext) (📥 270K / month): ``` - pip install vadersentiment + pip install torchtext ```
-
pytorch-nlp (🥈23 · ⭐ 2K) - PyTorch自然语言处理（NLP）的基本实用程序。BSD-3 +
pytorch-nlp (🥈24 · ⭐ 2.1K · 💀) - Basic Utilities for PyTorch Natural Language Processing.. BSD-3 -- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (👨‍💻 18 · 🔀 240 · 📦 310 · 📋 66 - 25% open · ⏱️ 10.07.2021): +- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (👨‍💻 18 · 🔀 250 · 📦 410 · 📋 67 - 26% open · ⏱️ 10.07.2021): ``` git clone https://github.com/PetrochukM/PyTorch-NLP ``` -- [PyPi](https://pypi.org/project/pytorch-nlp) (📥 7.9K / month): +- [PyPi](https://pypi.org/project/pytorch-nlp) (📥 6K / month): ``` pip install pytorch-nlp ```
-
polyglot (🥈23 · ⭐ 1.9K · 💀) - 多语言文本（NLP）处理工具包。❗️GPL-3.0 +
CLTK (🥈24 · ⭐ 740) - The Classical Language Toolkit. MIT -- [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 300 · 📦 620 · 📋 200 - 68% open · ⏱️ 22.09.2020): +- [GitHub](https://github.com/cltk/cltk) (👨‍💻 120 · 🔀 310 · 📥 25 · 📦 210 · 📋 530 - 5% open · ⏱️ 20.07.2022): ``` - git clone https://github.com/aboSamoor/polyglot + git clone https://github.com/cltk/cltk ``` -- [PyPi](https://pypi.org/project/polyglot) (📥 86K / month): +- [PyPi](https://pypi.org/project/cltk) (📥 480 / month): ``` - pip install polyglot + pip install cltk ```
-
scattertext (🥈23 · ⭐ 1.7K) - 文件之间语言分布的漂亮可视化效果。Apache-2 +
flashtext (🥉23 · ⭐ 5.2K · 💀) - Extract Keywords from sentence or Replace keywords in sentences. MIT -- [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 12 · 🔀 230 · 📦 250 · 📋 82 - 20% open · ⏱️ 15.11.2021): +- [GitHub](https://github.com/vi3k6i5/flashtext) (👨‍💻 7 · 🔀 570 · 📦 850 · 📋 100 - 49% open · ⏱️ 03.05.2020): ``` - git clone https://github.com/JasonKessler/scattertext - ``` -- [PyPi](https://pypi.org/project/scattertext) (📥 3.2K / month): - ``` - pip install scattertext + git clone https://github.com/vi3k6i5/flashtext ``` -- [Conda](https://anaconda.org/conda-forge/scattertext) (📥 59K · ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/flashtext) (📥 730K / month): ``` - conda install -c conda-forge scattertext + pip install flashtext ```
-
TensorFlow Text (🥈23 · ⭐ 860) - TensorFlow文本处理。Apache-2 +
Dedupe (🥉23 · ⭐ 3.5K) - A python library for accurate and scalable fuzzy matching, record.. MIT -- [GitHub](https://github.com/tensorflow/text) (👨‍💻 66 · 🔀 160 · 📦 1.2K · 📋 140 - 17% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/dedupeio/dedupe) (👨‍💻 64 · 🔀 460 · 📦 230 · 📋 760 - 7% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/tensorflow/text + git clone https://github.com/dedupeio/dedupe ``` -- [PyPi](https://pypi.org/project/tensorflow-text): +- [PyPi](https://pypi.org/project/dedupe) (📥 330K / month): ``` - pip install tensorflow-text + pip install dedupe ```
-
snowballstemmer (🥈23 · ⭐ 530) - Snowball编译器和词干算法。BSD-3 +
snowballstemmer (🥉23 · ⭐ 580 · 💤) - Snowball compiler and stemming algorithms. BSD-3 -- [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 28 · 🔀 140 · 📦 4 · 📋 57 - 22% open · ⏱️ 16.11.2021): +- [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 28 · 🔀 160 · 📦 4 · 📋 60 - 26% open · ⏱️ 17.12.2021): ``` git clone https://github.com/snowballstem/snowball ``` -- [PyPi](https://pypi.org/project/snowballstemmer) (📥 5.7M / month): +- [PyPi](https://pypi.org/project/snowballstemmer) (📥 7.6M / month): ``` pip install snowballstemmer ``` -- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (📥 3.5M · ⏱️ 17.11.2021): +- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (📥 4.9M · ⏱️ 17.11.2021): ``` conda install -c conda-forge snowballstemmer ```
-
T5 (🥉22 · ⭐ 3.8K) - 探索迁移学习的论文源码Apache-2 +
pySBD (🥉23 · ⭐ 470 · 💀) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT -- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 44 · 🔀 530 · 📦 72 · 📋 370 - 10% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 58 · 📦 390 · 📋 65 - 21% open · ⏱️ 11.02.2021): ``` - git clone https://github.com/google-research/text-to-text-transfer-transformer + git clone https://github.com/nipunsadvilkar/pySBD ``` -- [PyPi](https://pypi.org/project/t5) (📥 8.1K / month): +- [PyPi](https://pypi.org/project/pysbd) (📥 52K / month): ``` - pip install t5 + pip install pysbd ```
-
Snips NLU (🥉22 · ⭐ 3.6K · 💤) - 从文本中提取含义的Python库。Apache-2 +
stop-words (🥉23 · ⭐ 140 · 💀) - Get list of common stop words in various languages in Python. BSD-3 -- [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 480 · 📋 250 - 21% open · ⏱️ 03.05.2021): +- [GitHub](https://github.com/Alir3z4/python-stop-words) (👨‍💻 8 · 🔀 26 · 📦 1.6K · 📋 12 - 25% open · ⏱️ 23.07.2018): ``` - git clone https://github.com/snipsco/snips-nlu + git clone https://github.com/Alir3z4/python-stop-words ``` -- [PyPi](https://pypi.org/project/snips-nlu) (📥 4.5K / month): +- [PyPi](https://pypi.org/project/stop-words) (📥 550K / month): ``` - pip install snips-nlu + pip install stop-words ```
-
Sumy (🥉22 · ⭐ 2.7K) - 自动汇总文本文档和HTML页面的模块。Apache-2 +
textgenrnn (🥉22 · ⭐ 4.7K · 💀) - Easily train your own text-generating neural network.. ❗Unlicensed -- [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 21 · 🔀 450 · 📦 1K · 📋 93 - 13% open · ⏱️ 23.11.2021): +- [GitHub](https://github.com/minimaxir/textgenrnn) (👨‍💻 19 · 🔀 720 · 📥 740 · 📦 1K · 📋 220 - 57% open · ⏱️ 14.07.2020): ``` - git clone https://github.com/miso-belica/sumy + git clone https://github.com/minimaxir/textgenrnn ``` -- [PyPi](https://pypi.org/project/sumy): +- [PyPi](https://pypi.org/project/textgenrnn) (📥 460 / month): ``` - pip install sumy + pip install textgenrnn ```
-
Texar (🥉22 · ⭐ 2.2K · 💀) - 机器学习，自然语言处理等工具包。Apache-2 +
NeMo (🥉22 · ⭐ 4.6K) - NeMo: a toolkit for conversational AI. Apache-2 -- [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 17 · 📋 160 - 19% open · ⏱️ 29.07.2020): +- [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 170 · 🔀 1.1K · 📥 15K · 📋 1.2K - 3% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/asyml/texar + git clone https://github.com/NVIDIA/NeMo ``` -- [PyPi](https://pypi.org/project/texar) (📥 180 / month): +- [PyPi](https://pypi.org/project/nemo-toolkit) (📥 18K / month): ``` - pip install texar + pip install nemo-toolkit ```
-
langid (🥉22 · ⭐ 1.9K · 💀) - 独立的语言识别系统。❗Unlicensed +
T5 (🥉22 · ⭐ 4.4K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 -- [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 280 · 📦 870 · 📋 71 - 36% open · ⏱️ 15.07.2017): +- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 50 · 🔀 590 · 📦 110 · 📋 390 - 12% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/saffsd/langid.py + git clone https://github.com/google-research/text-to-text-transfer-transformer ``` -- [PyPi](https://pypi.org/project/langid) (📥 330K / month): +- [PyPi](https://pypi.org/project/t5) (📥 11K / month): ``` - pip install langid + pip install t5 ```
-
sense2vec (🥉22 · ⭐ 1.3K) - 上下文相关性构建词向量。MIT +
phonenumbers (🥉22 · ⭐ 3.1K) - Python port of Google's libphonenumber. Apache-2 -- [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 220 · 📥 23K · 📦 100 · 📋 100 - 15% open · ⏱️ 16.08.2021): +- [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 26 · 🔀 370 · 📋 150 - 2% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/explosion/sense2vec + git clone https://github.com/daviddrysdale/python-phonenumbers ``` -- [PyPi](https://pypi.org/project/sense2vec): +- [PyPi](https://pypi.org/project/phonenumbers) (📥 4.6M / month): ``` - pip install sense2vec + pip install phonenumbers ``` -- [Conda](https://anaconda.org/conda-forge/sense2vec) (📥 24K · ⏱️ 14.07.2021): +- [Conda](https://anaconda.org/conda-forge/phonenumbers) (📥 610K · ⏱️ 19.08.2022): ``` - conda install -c conda-forge sense2vec + conda install -c conda-forge phonenumbers ```
-
pySBD (🥉22 · ⭐ 390 · 💤) - pySBD（Python句子边界歧义消除）。MIT +
langid (🥉22 · ⭐ 2K · 💀) - Stand-alone language identification system. ❗Unlicensed -- [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 42 · 📦 250 · 📋 60 - 20% open · ⏱️ 11.02.2021): +- [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 280 · 📦 1.1K · 📋 71 - 35% open · ⏱️ 15.07.2017): ``` - git clone https://github.com/nipunsadvilkar/pySBD + git clone https://github.com/saffsd/langid.py ``` -- [PyPi](https://pypi.org/project/pysbd) (📥 39K / month): +- [PyPi](https://pypi.org/project/langid) (📥 380K / month): ``` - pip install pysbd + pip install langid ```
-
stop-words (🥉22 · ⭐ 130 · 💀) - 获取Python中各种语言的常用停用词表。BSD-3 +
scattertext (🥉22 · ⭐ 1.9K) - Beautiful visualizations of how language differs among document.. Apache-2 -- [GitHub](https://github.com/Alir3z4/python-stop-words) (👨‍💻 8 · 🔀 24 · 📦 1.4K · 📋 12 - 25% open · ⏱️ 23.07.2018): +- [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 12 · 🔀 250 · 📦 310 · 📋 89 - 17% open · ⏱️ 26.03.2022): ``` - git clone https://github.com/Alir3z4/python-stop-words - ``` -- [PyPi](https://pypi.org/project/stop-words) (📥 200K / month): - ``` - pip install stop-words + git clone https://github.com/JasonKessler/scattertext ``` -
-
textgenrnn (🥉21 · ⭐ 4.6K · 💀) - 轻松地训练自己的文本生成神经网络。❗Unlicensed - -- [GitHub](https://github.com/minimaxir/textgenrnn) (👨‍💻 19 · 🔀 710 · 📥 620 · 📦 950 · 📋 200 - 57% open · ⏱️ 14.07.2020): - +- [PyPi](https://pypi.org/project/scattertext) (📥 2.4K / month): ``` - git clone https://github.com/minimaxir/textgenrnn + pip install scattertext ``` -- [PyPi](https://pypi.org/project/textgenrnn) (📥 850 / month): +- [Conda](https://anaconda.org/conda-forge/scattertext) (📥 66K · ⏱️ 26.03.2022): ``` - pip install textgenrnn + conda install -c conda-forge scattertext ```
-
MatchZoo (🥉21 · ⭐ 3.6K) - 便于深层设计，比较和共享的工具库。Apache-2 +
anaGo (🥉22 · ⭐ 1.5K · 💀) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT -- [GitHub](https://github.com/NTMC-Community/MatchZoo) (👨‍💻 36 · 🔀 890 · 📦 10 · 📋 460 - 6% open · ⏱️ 02.06.2021): +- [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 30 · 📋 110 - 33% open · ⏱️ 01.04.2021): ``` - git clone https://github.com/NTMC-Community/MatchZoo + git clone https://github.com/Hironsan/anago ``` -- [PyPi](https://pypi.org/project/matchzoo) (📥 200 / month): +- [PyPi](https://pypi.org/project/anago) (📥 1.2K / month): ``` - pip install matchzoo + pip install anago ```
-
phonenumbers (🥉21 · ⭐ 2.9K) - Google的libphonenumber的Python端口。Apache-2 +
sense2vec (🥉22 · ⭐ 1.4K · 💤) - Contextually-keyed word vectors. MIT -- [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 25 · 🔀 350 · 📋 130 - 2% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 220 · 📥 36K · 📦 170 · 📋 110 - 18% open · ⏱️ 16.08.2021): ``` - git clone https://github.com/daviddrysdale/python-phonenumbers + git clone https://github.com/explosion/sense2vec ``` -- [PyPi](https://pypi.org/project/phonenumbers) (📥 2.7M / month): +- [PyPi](https://pypi.org/project/sense2vec) (📥 3.5K / month): ``` - pip install phonenumbers + pip install sense2vec ``` -- [Conda](https://anaconda.org/conda-forge/phonenumbers) (📥 500K · ⏱️ 07.12.2021): +- [Conda](https://anaconda.org/conda-forge/sense2vec) (📥 27K · ⏱️ 14.07.2021): ``` - conda install -c conda-forge phonenumbers + conda install -c conda-forge sense2vec ```
-
spark-nlp (🥉21 · ⭐ 2.5K) - 最先进的自然语言处理。Apache-2 +
Snips NLU (🥉21 · ⭐ 3.7K · 💀) - Snips Python library to extract meaning from text. Apache-2 -- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 100 · 🔀 510 · 📋 600 - 12% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 490 · 📋 260 - 23% open · ⏱️ 03.05.2021): ``` - git clone https://github.com/JohnSnowLabs/spark-nlp + git clone https://github.com/snipsco/snips-nlu ``` -- [PyPi](https://pypi.org/project/spark-nlp): +- [PyPi](https://pypi.org/project/snips-nlu) (📥 2.3K / month): ``` - pip install spark-nlp + pip install snips-nlu ```
-
Texthero (🥉21 · ⭐ 2.4K) - 文本预处理，表示和可视化从入门到精通。MIT +
Texthero (🥉21 · ⭐ 2.5K) - Text preprocessing, representation and visualization from zero to hero. MIT -- [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 18 · 🔀 200 · 📥 87 · 📋 110 - 44% open · ⏱️ 19.07.2021): +- [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 19 · 🔀 220 · 📥 92 · 📋 110 - 45% open · ⏱️ 19.07.2022): ``` git clone https://github.com/jbesomi/texthero ``` -- [PyPi](https://pypi.org/project/texthero) (📥 18K / month): +- [PyPi](https://pypi.org/project/texthero) (📥 23K / month): ``` pip install texthero ```
-
FARM (🥉21 · ⭐ 1.4K) - NLP的快速和轻松迁移学习。Apache-2 +
Texar (🥉21 · ⭐ 2.3K · 💀) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 -- [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 36 · 🔀 210 · 📋 400 - 3% open · ⏱️ 23.11.2021): +- [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 26 · 📋 160 - 19% open · ⏱️ 29.07.2020): ``` - git clone https://github.com/deepset-ai/FARM + git clone https://github.com/asyml/texar ``` -- [PyPi](https://pypi.org/project/farm) (📥 5.7K / month): +- [PyPi](https://pypi.org/project/texar) (📥 65 / month): ``` - pip install farm + pip install texar ```
-
SciSpacy (🥉21 · ⭐ 1.1K) - 完整的科学/生物医学的SpaCy应用案例。Apache-2 +
polyglot (🥉21 · ⭐ 2K · 💀) - Multilingual text (NLP) processing toolkit. ❗Unlicensed -- [GitHub](https://github.com/allenai/scispacy) (👨‍💻 21 · 🔀 140 · 📦 370 · 📋 230 - 15% open · ⏱️ 15.07.2021): +- [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 310 · 📦 750 · 📋 210 - 68% open · ⏱️ 22.09.2020): ``` - git clone https://github.com/allenai/scispacy + git clone https://github.com/aboSamoor/polyglot ``` -- [PyPi](https://pypi.org/project/scispacy) (📥 28K / month): +- [PyPi](https://pypi.org/project/polyglot) (📥 53K / month): ``` - pip install scispacy + pip install polyglot ```
-
CLTK (🥉21 · ⭐ 700) - 古典语言工具包。MIT +
YouTokenToMe (🥉21 · ⭐ 820 · 💀) - Unsupervised text tokenizer focused on computational efficiency. MIT -- [GitHub](https://github.com/cltk/cltk) (👨‍💻 110 · 🔀 300 · 📥 22 · 📦 180 · 📋 510 - 4% open · ⏱️ 21.10.2021): +- [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 61 · 📦 290 · 📋 54 - 55% open · ⏱️ 28.01.2021): ``` - git clone https://github.com/cltk/cltk + git clone https://github.com/vkcom/youtokentome ``` -- [PyPi](https://pypi.org/project/cltk): +- [PyPi](https://pypi.org/project/youtokentome) (📥 30K / month): ``` - pip install cltk + pip install youtokentome ```
-
PyText (🥉20 · ⭐ 6.3K) - 基于PyTorch的自然语言建模框架。❗Unlicensed +
inflect (🥉21 · ⭐ 690) - Correctly generate plurals, ordinals, indefinite articles; convert numbers.. MIT -- [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 220 · 🔀 790 · 📥 280 · 📦 100 · 📋 130 - 44% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/jaraco/inflect) (👨‍💻 45 · 🔀 74 · 📋 91 - 18% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/facebookresearch/pytext + git clone https://github.com/jaraco/inflect ``` -- [PyPi](https://pypi.org/project/pytext-nlp) (📥 240 / month): +- [PyPi](https://pypi.org/project/inflect) (📥 2.5M / month): ``` - pip install pytext-nlp + pip install inflect + ``` +- [Conda](https://anaconda.org/conda-forge/inflect) (📥 240K · ⏱️ 31.07.2022): + ``` + conda install -c conda-forge inflect ```
-
NeMo (🥉20 · ⭐ 3.7K) - NeMo：用于智能对话的工具包。Apache-2 +
PyText (🥉20 · ⭐ 6.4K) - A natural language modeling framework based on PyTorch. ❗Unlicensed -- [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 120 · 🔀 790 · 📥 17K · 📋 870 - 4% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 230 · 🔀 790 · 📥 300 · 📦 110 · 📋 140 - 45% open · ⏱️ 11.08.2022): ``` - git clone https://github.com/NVIDIA/NeMo + git clone https://github.com/facebookresearch/pytext ``` -- [PyPi](https://pypi.org/project/nemo-toolkit) (📥 6.9K / month): +- [PyPi](https://pypi.org/project/pytext-nlp) (📥 180 / month): ``` - pip install nemo-toolkit + pip install pytext-nlp ```
-
Kashgari (🥉20 · ⭐ 2.2K) - Kashgari是工业级的NLP迁移学习框架。Apache-2 +
MatchZoo (🥉20 · ⭐ 3.7K · 💀) - Facilitating the design, comparison and sharing of deep.. Apache-2 -- [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 420 · 📦 49 · 📋 360 - 9% open · ⏱️ 09.07.2021): +- [GitHub](https://github.com/NTMC-Community/MatchZoo) (👨‍💻 36 · 🔀 900 · 📦 11 · 📋 460 - 7% open · ⏱️ 02.06.2021): ``` - git clone https://github.com/BrikerMan/Kashgari + git clone https://github.com/NTMC-Community/MatchZoo ``` -- [PyPi](https://pypi.org/project/kashgari-tf) (📥 73 / month): +- [PyPi](https://pypi.org/project/matchzoo) (📥 63 / month): ``` - pip install kashgari-tf + pip install matchzoo ```
-
DELTA (🥉20 · ⭐ 1.5K · 💤) - DELTA是一个基于深度学习的自然语言和语音处理平台。Apache-2 +
NLP Architect (🥉20 · ⭐ 2.9K) - A model library for exploring state-of-the-art deep learning.. Apache-2 -- [GitHub](https://github.com/Delta-ML/delta) (👨‍💻 41 · 🔀 290 · 📋 75 - 1% open · ⏱️ 17.12.2020): +- [GitHub](https://github.com/IntelLabs/nlp-architect) (👨‍💻 37 · 🔀 430 · 📦 8 · 📋 130 - 11% open · ⏱️ 29.06.2022): ``` - git clone https://github.com/Delta-ML/delta - ``` -- [PyPi](https://pypi.org/project/delta-nlp) (📥 20 / month): - ``` - pip install delta-nlp + git clone https://github.com/IntelLabs/nlp-architect ``` -- [Docker Hub](https://hub.docker.com/r/zh794390558/delta) (📥 13K · ⏱️ 03.08.2021): +- [PyPi](https://pypi.org/project/nlp-architect) (📥 170 / month): ``` - docker pull zh794390558/delta + pip install nlp-architect ```
-
anaGo (🥉20 · ⭐ 1.4K · 💤) - 双向LSTM-CRF和ELMo实现，可用于命名实体识别和文本分类等任务。MIT +
FARM (🥉20 · ⭐ 1.6K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 -- [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 27 · 📋 110 - 33% open · ⏱️ 01.04.2021): +- [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 37 · 🔀 220 · 📋 400 - 0% open · ⏱️ 25.04.2022): ``` - git clone https://github.com/Hironsan/anago + git clone https://github.com/deepset-ai/FARM ``` -- [PyPi](https://pypi.org/project/anago) (📥 490 / month): +- [PyPi](https://pypi.org/project/farm) (📥 4.4K / month): ``` - pip install anago + pip install farm ```
-
inflect (🥉20 · ⭐ 590 · 💤) - 辅助功能，正确生成复数，序数，不定冠词，转换数字。MIT +
DELTA (🥉20 · ⭐ 1.5K · 💀) - DELTA is a deep learning based natural language and speech.. Apache-2 -- [GitHub](https://github.com/jaraco/inflect) (👨‍💻 29 · 🔀 65 · 📋 80 - 21% open · ⏱️ 23.03.2021): +- [GitHub](https://github.com/Delta-ML/delta) (👨‍💻 41 · 🔀 290 · 📋 75 - 1% open · ⏱️ 17.12.2020): ``` - git clone https://github.com/jaraco/inflect + git clone https://github.com/Delta-ML/delta ``` -- [PyPi](https://pypi.org/project/inflect) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/delta-nlp) (📥 14 / month): ``` - pip install inflect + pip install delta-nlp ``` -- [Conda](https://anaconda.org/conda-forge/inflect) (📥 190K · ⏱️ 02.11.2021): +- [Docker Hub](https://hub.docker.com/r/zh794390558/delta) (📥 13K · ⏱️ 03.08.2021): ``` - conda install -c conda-forge inflect + docker pull zh794390558/delta ```
-
pyfasttext (🥉20 · ⭐ 230 · 💀) - fastText的另一个Python接口。❗️GPL-3.0 +
pyfasttext (🥉20 · ⭐ 230 · 💀) - Yet another Python binding for fastText. ❗️GPL-3.0 -- [GitHub](https://github.com/vrasneur/pyfasttext) (👨‍💻 4 · 🔀 30 · 📥 340 · 📦 200 · 📋 49 - 42% open · ⏱️ 08.12.2018): +- [GitHub](https://github.com/vrasneur/pyfasttext) (👨‍💻 4 · 🔀 30 · 📥 350 · 📦 240 · 📋 49 - 42% open · ⏱️ 08.12.2018): ``` git clone https://github.com/vrasneur/pyfasttext ``` -- [PyPi](https://pypi.org/project/pyfasttext) (📥 5.6K / month): +- [PyPi](https://pypi.org/project/pyfasttext) (📥 3.4K / month): ``` pip install pyfasttext ```
-
NLP Architect (🥉19 · ⭐ 2.8K) - 用于探索最先进的深度学习的模型库。Apache-2 +
haystack (🥉19 · ⭐ 5.2K) - End-to-end Python framework for building natural language search.. Apache-2 -- [GitHub](https://github.com/IntelLabs/nlp-architect) (👨‍💻 37 · 🔀 420 · 📦 8 · 📋 130 - 11% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/deepset-ai/haystack) (👨‍💻 140 · 🔀 830 · 📥 15 · 📋 1.5K - 14% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/IntelLabs/nlp-architect + git clone https://github.com/deepset-ai/haystack ``` -- [PyPi](https://pypi.org/project/nlp-architect) (📥 480 / month): +- [PyPi](https://pypi.org/project/haystack) (📥 870 / month): ``` - pip install nlp-architect + pip install haystack ```
-
textacy (🥉19 · ⭐ 1.8K) - spaCy之前和之后的NLP。❗Unlicensed +
Kashgari (🥉19 · ⭐ 2.3K · 💀) - Kashgari is a production-level NLP Transfer learning.. Apache-2 -- [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 31 · 🔀 230 · 📋 240 - 10% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 440 · 📦 54 · 📋 370 - 11% open · ⏱️ 09.07.2021): ``` - git clone https://github.com/chartbeat-labs/textacy - ``` -- [PyPi](https://pypi.org/project/textacy) (📥 36K / month): - ``` - pip install textacy + git clone https://github.com/BrikerMan/Kashgari ``` -- [Conda](https://anaconda.org/conda-forge/textacy) (📥 100K · ⏱️ 13.04.2021): +- [PyPi](https://pypi.org/project/kashgari-tf) (📥 44 / month): ``` - conda install -c conda-forge textacy + pip install kashgari-tf ```
-
gpt-2-simple (🥉18 · ⭐ 2.8K) - 可轻松重新训练OpenAI的GPT-2文本模型的Python软件包。❗Unlicensed +
fast-bert (🥉19 · ⭐ 1.8K) - Super easy library for BERT based NLP models. Apache-2 -- [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 18 · 🔀 570 · 📥 280 · 📋 230 - 60% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/utterworks/fast-bert) (👨‍💻 36 · 🔀 330 · 📋 250 - 61% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/minimaxir/gpt-2-simple + git clone https://github.com/kaushaltrivedi/fast-bert ``` -- [PyPi](https://pypi.org/project/gpt-2-simple) (📥 6.4K / month): +- [PyPi](https://pypi.org/project/fast-bert) (📥 1.4K / month): ``` - pip install gpt-2-simple + pip install fast-bert ```
-
fast-bert (🥉18 · ⭐ 1.7K) - 用于基于BERT的NLP模型的简单易用工具库。Apache-2 +
Sockeye (🥉19 · ⭐ 1.1K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 -- [GitHub](https://github.com/utterworks/fast-bert) (👨‍💻 35 · 🔀 320 · 📋 240 - 60% open · ⏱️ 31.08.2021): +- [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 57 · 🔀 300 · 📥 15 · 📋 280 - 2% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/kaushaltrivedi/fast-bert + git clone https://github.com/awslabs/sockeye ``` -- [PyPi](https://pypi.org/project/fast-bert) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/sockeye) (📥 370 / month): ``` - pip install fast-bert + pip install sockeye ```
-
Sockeye (🥉18 · ⭐ 1K) - 序列到序列框架。Apache-2 +
gpt-2-simple (🥉18 · ⭐ 3K) - Python package to easily retrain OpenAI's GPT-2 text-.. ❗Unlicensed -- [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 54 · 🔀 280 · 📥 12 · 📋 260 - 1% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 21 · 🔀 600 · 📥 340 · 📋 250 - 61% open · ⏱️ 22.05.2022): ``` - git clone https://github.com/awslabs/sockeye + git clone https://github.com/minimaxir/gpt-2-simple ``` -- [PyPi](https://pypi.org/project/sockeye) (📥 470 / month): +- [PyPi](https://pypi.org/project/gpt-2-simple) (📥 3.8K / month): ``` - pip install sockeye + pip install gpt-2-simple ```
-
finetune (🥉18 · ⭐ 660) - 针对NLP的Scikit风格模型微调。MPL-2.0 +
textacy (🥉18 · ⭐ 2K) - NLP, before and after spaCy. ❗Unlicensed -- [GitHub](https://github.com/IndicoDataSolutions/finetune) (👨‍💻 19 · 🔀 69 · 📦 9 · 📋 140 - 15% open · ⏱️ 18.11.2021): +- [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 32 · 🔀 230 · 📋 250 - 11% open · ⏱️ 06.03.2022): ``` - git clone https://github.com/IndicoDataSolutions/finetune + git clone https://github.com/chartbeat-labs/textacy ``` -- [PyPi](https://pypi.org/project/finetune) (📥 75 / month): +- [PyPi](https://pypi.org/project/textacy) (📥 38K / month): ``` - pip install finetune + pip install textacy + ``` +- [Conda](https://anaconda.org/conda-forge/textacy) (📥 110K · ⏱️ 06.02.2022): + ``` + conda install -c conda-forge textacy ```
-
textpipe (🥉17 · ⭐ 290) - Textpipe：从文本中清理并提取元数据。MIT +
finetune (🥉18 · ⭐ 660) - Scikit-learn style model finetuning for NLP. MPL-2.0 -- [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 22 · 📦 8 · 📋 40 - 37% open · ⏱️ 09.06.2021): +- [GitHub](https://github.com/IndicoDataSolutions/finetune) (👨‍💻 19 · 🔀 71 · 📦 9 · 📋 140 - 15% open · ⏱️ 16.06.2022): ``` - git clone https://github.com/textpipe/textpipe + git clone https://github.com/IndicoDataSolutions/finetune ``` -- [PyPi](https://pypi.org/project/textpipe) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/finetune) (📥 96 / month): ``` - pip install textpipe + pip install finetune ```
-
YouTokenToMe (🥉16 · ⭐ 780 · 💤) - 用于基于神经网络的文本的预处理器。MIT +
skift (🥉18 · ⭐ 230) - scikit-learn wrappers for Python fastText. MIT -- [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 55 · 📦 180 · 📋 50 - 54% open · ⏱️ 28.01.2021): +- [GitHub](https://github.com/shaypal5/skift) (👨‍💻 9 · 🔀 23 · 📦 12 · 📋 11 - 9% open · ⏱️ 07.06.2022): ``` - git clone https://github.com/vkcom/youtokentome + git clone https://github.com/shaypal5/skift ``` -- [PyPi](https://pypi.org/project/youtokentome): +- [PyPi](https://pypi.org/project/skift) (📥 1.1K / month): ``` - pip install youtokentome + pip install skift ```
-
DeepMatcher (🥉16 · ⭐ 380) - 用于实体和文本匹配的Python包。BSD-3 +
DeepMatcher (🥉17 · ⭐ 440 · 💀) - Python package for performing Entity and Text Matching using.. BSD-3 -- [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 88 · 📦 14 · 📋 76 - 71% open · ⏱️ 13.06.2021): +- [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 98 · 📦 21 · 📋 86 - 72% open · ⏱️ 13.06.2021): ``` git clone https://github.com/anhaidgroup/deepmatcher ``` -- [PyPi](https://pypi.org/project/deepmatcher) (📥 480 / month): +- [PyPi](https://pypi.org/project/deepmatcher) (📥 1.1K / month): ``` pip install deepmatcher ```
-
Camphr (🥉16 · ⭐ 340) - 适用于Transformers，Udify，ELmo等的spaCy插件。Apache-2 spacy +
Camphr (🥉16 · ⭐ 340 · 💤) - spaCy plugin for Transformers , Udify, ELmo, etc. Apache-2 spacy -- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (👨‍💻 7 · 🔀 17 · 📋 27 - 7% open · ⏱️ 18.08.2021): +- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (👨‍💻 7 · 🔀 16 · 📋 28 - 7% open · ⏱️ 18.08.2021): ``` git clone https://github.com/PKSHATechnology-Research/camphr ``` -- [PyPi](https://pypi.org/project/camphr) (📥 200 / month): +- [PyPi](https://pypi.org/project/camphr) (📥 75 / month): ``` pip install camphr ```
-
OpenNRE (🥉15 · ⭐ 3.4K) - 神经关系提取（NRE）的开源软件包。MIT +
textpipe (🥉16 · ⭐ 300 · 💀) - Textpipe: clean and extract metadata from text. MIT -- [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 10 · 🔀 900 · 📋 330 - 3% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 23 · 📦 8 · 📋 40 - 37% open · ⏱️ 09.06.2021): ``` - git clone https://github.com/thunlp/OpenNRE + git clone https://github.com/textpipe/textpipe + ``` +- [PyPi](https://pypi.org/project/textpipe) (📥 150 / month): + ``` + pip install textpipe ```
-
Translate (🥉15 · ⭐ 720) - Translate-PyTorch NLP库。BSD-3 +
NeuroNER (🥉15 · ⭐ 1.6K · 💀) - Named-entity recognition using neural networks. Easy-to-use and.. MIT -- [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 170 · 📋 38 - 28% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 460 · 📋 150 - 55% open · ⏱️ 02.10.2019): ``` - git clone https://github.com/pytorch/translate + git clone https://github.com/Franck-Dernoncourt/NeuroNER ``` -- [PyPi](https://pypi.org/project/pytorch-translate): +- [PyPi](https://pypi.org/project/pyneuroner) (📥 100 / month): ``` - pip install pytorch-translate + pip install pyneuroner ```
-
NeuralQA (🥉15 · ⭐ 220 · 💤) - NeuralQA：用于对大型数据集进行问答构建。MIT +
Translate (🥉15 · ⭐ 760) - Translate - a PyTorch Language Library. BSD-3 -- [GitHub](https://github.com/victordibia/neuralqa) (👨‍💻 3 · 🔀 31 · 📦 3 · 📋 28 - 71% open · ⏱️ 16.12.2020): +- [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 180 · 📋 38 - 28% open · ⏱️ 10.06.2022): ``` - git clone https://github.com/victordibia/neuralqa + git clone https://github.com/pytorch/translate ``` -- [PyPi](https://pypi.org/project/neuralqa) (📥 87 / month): +- [PyPi](https://pypi.org/project/pytorch-translate) (📥 10 / month): ``` - pip install neuralqa + pip install pytorch-translate ```
-
ONNX-T5 (🥉15 · ⭐ 190 · 💤) - 文本摘要，翻译，情感分析，文本生成等实现。Apache-2 +
NeuralQA (🥉15 · ⭐ 220 · 💀) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT -- [GitHub](https://github.com/abelriboulot/onnxt5) (👨‍💻 3 · 🔀 24 · 📋 14 - 42% open · ⏱️ 28.01.2021): +- [GitHub](https://github.com/victordibia/neuralqa) (👨‍💻 3 · 🔀 30 · 📦 4 · 📋 28 - 71% open · ⏱️ 16.12.2020): ``` - git clone https://github.com/abelriboulot/onnxt5 + git clone https://github.com/victordibia/neuralqa ``` -- [PyPi](https://pypi.org/project/onnxt5) (📥 170 / month): +- [PyPi](https://pypi.org/project/neuralqa) (📥 68 / month): ``` - pip install onnxt5 + pip install neuralqa ```
-
NeuroNER (🥉14 · ⭐ 1.6K · 💀) - 使用神经网络的命名实体识别。MIT +
OpenNRE (🥉14 · ⭐ 3.8K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT -- [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 450 · 📋 150 - 55% open · ⏱️ 02.10.2019): +- [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 10 · 🔀 950 · 📋 350 - 2% open · ⏱️ 06.04.2022): ``` - git clone https://github.com/Franck-Dernoncourt/NeuroNER - ``` -- [PyPi](https://pypi.org/project/pyneuroner): - ``` - pip install pyneuroner + git clone https://github.com/thunlp/OpenNRE ```
-
TransferNLP (🥉14 · ⭐ 290 · 💀) - 用于可重复的实验的NLP库。MIT +
TransferNLP (🥉14 · ⭐ 290 · 💀) - NLP library designed for reproducible experimentation.. MIT - [GitHub](https://github.com/feedly/transfer-nlp) (👨‍💻 7 · 🔀 17 · 📋 23 - 13% open · ⏱️ 28.05.2020): ``` git clone https://github.com/feedly/transfer-nlp ``` -- [PyPi](https://pypi.org/project/transfer-nlp) (📥 81 / month): +- [PyPi](https://pypi.org/project/transfer-nlp) (📥 100 / month): ``` pip install transfer-nlp ```
-
skift (🥉14 · ⭐ 220) - 适用于Python fastText的scikit-learn包装器。❗Unlicensed +
ONNX-T5 (🥉14 · ⭐ 200 · 💀) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 -- [GitHub](https://github.com/shaypal5/skift) (👨‍💻 8 · 🔀 21 · 📦 10 · 📋 11 - 18% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/abelriboulot/onnxt5) (👨‍💻 3 · 🔀 23 · 📦 1 · 📋 15 - 46% open · ⏱️ 28.01.2021): ``` - git clone https://github.com/shaypal5/skift + git clone https://github.com/abelriboulot/onnxt5 ``` -- [PyPi](https://pypi.org/project/skift): +- [PyPi](https://pypi.org/project/onnxt5) (📥 57 / month): ``` - pip install skift + pip install onnxt5 ```
-
VizSeq (🥉12 · ⭐ 370) - 用于自然语言生成的分析工具包。MIT +
textvec (🥉14 · ⭐ 180) - Text vectorization tool to outperform TFIDF for classification tasks. MIT -- [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 43 · 📦 3 · 📋 15 - 40% open · ⏱️ 02.09.2021): +- [GitHub](https://github.com/textvec/textvec) (👨‍💻 10 · 🔀 23 · 📦 4 · 📋 9 - 33% open · ⏱️ 05.07.2022): ``` - git clone https://github.com/facebookresearch/vizseq + git clone https://github.com/textvec/textvec ``` -- [PyPi](https://pypi.org/project/vizseq) (📥 68 / month): +- [PyPi](https://pypi.org/project/textvec) (📥 26 / month): ``` - pip install vizseq + pip install textvec ```
-
textvec (🥉12 · ⭐ 180 · 💤) - 胜过TF-IDF文本向量化工具。MIT +
VizSeq (🥉13 · ⭐ 400) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT -- [GitHub](https://github.com/textvec/textvec) (👨‍💻 4 · 🔀 21 · 📦 4 · 📋 9 - 33% open · ⏱️ 03.12.2020): +- [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 49 · 📦 6 · 📋 15 - 40% open · ⏱️ 20.07.2022): ``` - git clone https://github.com/textvec/textvec + git clone https://github.com/facebookresearch/vizseq ``` -- [PyPi](https://pypi.org/project/textvec): +- [PyPi](https://pypi.org/project/vizseq) (📥 59 / month): ``` - pip install textvec + pip install vizseq ```
-
Headliner (🥉11 · ⭐ 230 · 💀) - 轻松训练和部署seq2seq模型。❗Unlicensed +
Headliner (🥉11 · ⭐ 230 · 💀) - Easy training and deployment of seq2seq models. ❗Unlicensed -- [GitHub](https://github.com/as-ideas/headliner) (👨‍💻 2 · 🔀 40 · 📦 3 · 📋 14 - 7% open · ⏱️ 14.02.2020): +- [GitHub](https://github.com/as-ideas/headliner) (👨‍💻 2 · 🔀 41 · 📦 3 · 📋 14 - 7% open · ⏱️ 14.02.2020): ``` git clone https://github.com/as-ideas/headliner ``` -- [PyPi](https://pypi.org/project/headliner) (📥 130 / month): +- [PyPi](https://pypi.org/project/headliner) (📥 120 / month): ``` pip install headliner ```

-## 图像数据与CV +## Image Data -Back to top +Back to top -_用于图像和视频处理，操纵和扩充的库，以及用于计算机视觉任务（例如面部识别，对象检测和图像分类）的库。_ +_Libraries for image & video processing, manipulation, and augmentation as well as libraries for computer vision tasks such as facial recognition, object detection, and classification._ -
imgaug (🥇32 · ⭐ 12K · 💀) - 用于机器学习实验的图像增强。MIT +
Pillow (🥇36 · ⭐ 10K · 📈) - The friendly PIL fork (Python Imaging Library). ❗️PIL -- [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.2K · 📦 8.4K · 📋 480 - 53% open · ⏱️ 01.06.2020): +- [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 410 · 🔀 1.7K · 📦 820K · 📋 2.6K - 3% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/aleju/imgaug + git clone https://github.com/python-pillow/Pillow ``` -- [PyPi](https://pypi.org/project/imgaug) (📥 260K / month): +- [PyPi](https://pypi.org/project/Pillow) (📥 45M / month): ``` - pip install imgaug + pip install Pillow ``` -- [Conda](https://anaconda.org/conda-forge/imgaug) (📥 59K · ⏱️ 14.02.2020): +- [Conda](https://anaconda.org/conda-forge/pillow) (📥 18M · ⏱️ 13.08.2022): ``` - conda install -c conda-forge imgaug + conda install -c conda-forge pillow ```
-
Albumentations (🥇32 · ⭐ 9.3K) - 快速的图像增强库和易于使用的包装器。MIT +
MoviePy (🥇34 · ⭐ 9.5K) - Video editing with Python. MIT -- [GitHub](https://github.com/albumentations-team/albumentations) (👨‍💻 98 · 🔀 1.2K · 📦 6K · 📋 540 - 39% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 150 · 🔀 1.2K · 📦 18K · 📋 1.2K - 24% open · ⏱️ 01.06.2022): ``` - git clone https://github.com/albumentations-team/albumentations + git clone https://github.com/Zulko/moviepy ``` -- [PyPi](https://pypi.org/project/albumentations) (📥 210K / month): +- [PyPi](https://pypi.org/project/moviepy) (📥 2.5M / month): ``` - pip install albumentations + pip install moviepy ``` -- [Conda](https://anaconda.org/conda-forge/albumentations) (📥 29K · ⏱️ 15.07.2021): +- [Conda](https://anaconda.org/conda-forge/moviepy) (📥 130K · ⏱️ 16.04.2022): ``` - conda install -c conda-forge albumentations + conda install -c conda-forge moviepy ```
-
MoviePy (🥇32 · ⭐ 8.8K) - 使用Python进行视频编辑。MIT +
imageio (🥇33 · ⭐ 1.1K) - Python library for reading and writing image data. BSD-2 -- [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 140 · 🔀 1.1K · 📦 12K · 📋 1.1K - 29% open · ⏱️ 12.11.2021): +- [GitHub](https://github.com/imageio/imageio) (👨‍💻 91 · 🔀 220 · 📥 360 · 📦 67K · 📋 470 - 12% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/Zulko/moviepy + git clone https://github.com/imageio/imageio ``` -- [PyPi](https://pypi.org/project/moviepy) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/imageio) (📥 12M / month): ``` - pip install moviepy + pip install imageio ``` -- [Conda](https://anaconda.org/conda-forge/moviepy) (📥 99K · ⏱️ 23.02.2020): +- [Conda](https://anaconda.org/conda-forge/imageio) (📥 3.5M · ⏱️ 08.08.2022): ``` - conda install -c conda-forge moviepy + conda install -c conda-forge imageio ```
-
PyTorch Image Models (🥇30 · ⭐ 15K) - PyTorch图像模型，脚本，预训练权重。Apache-2 +
imgaug (🥇32 · ⭐ 13K · 💀) - Image augmentation for machine learning experiments. MIT -- [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 62 · 🔀 2.4K · 📥 780K · 📦 1.6K · 📋 420 - 10% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.3K · 📦 11K · 📋 490 - 55% open · ⏱️ 01.06.2020): ``` - git clone https://github.com/rwightman/pytorch-image-models + git clone https://github.com/aleju/imgaug + ``` +- [PyPi](https://pypi.org/project/imgaug) (📥 390K / month): + ``` + pip install imgaug + ``` +- [Conda](https://anaconda.org/conda-forge/imgaug) (📥 83K · ⏱️ 31.12.2021): + ``` + conda install -c conda-forge imgaug ```
-
imageio (🥇30 · ⭐ 960) - 用于读取和写入图像数据的Python库。BSD-2 +
Albumentations (🥇32 · ⭐ 11K) - Fast image augmentation library and an easy-to-use wrapper.. MIT -- [GitHub](https://github.com/imageio/imageio) (👨‍💻 83 · 🔀 190 · 📥 45 · 📦 53K · 📋 400 - 17% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/albumentations-team/albumentations) (👨‍💻 110 · 🔀 1.4K · 📦 9.1K · 📋 660 - 41% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/imageio/imageio + git clone https://github.com/albumentations-team/albumentations ``` -- [PyPi](https://pypi.org/project/imageio): +- [PyPi](https://pypi.org/project/albumentations) (📥 370K / month): ``` - pip install imageio + pip install albumentations ``` -- [Conda](https://anaconda.org/conda-forge/imageio) (📥 2.4M · ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/albumentations) (📥 49K · ⏱️ 12.07.2022): ``` - conda install -c conda-forge imageio + conda install -c conda-forge albumentations ```
-
GluonCV (🥈29 · ⭐ 5K) - Gluon CV工具包。Apache-2 +
Kornia (🥇32 · ⭐ 7K) - Open Source Differentiable Computer Vision Library for PyTorch. Apache-2 -- [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 110 · 🔀 1.1K · 📦 640 · 📋 790 - 6% open · ⏱️ 14.11.2021): +- [GitHub](https://github.com/kornia/kornia) (👨‍💻 170 · 🔀 680 · 📥 430 · 📦 1.7K · 📋 600 - 26% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/dmlc/gluon-cv + git clone https://github.com/kornia/kornia ``` -- [PyPi](https://pypi.org/project/gluoncv) (📥 540K / month): +- [PyPi](https://pypi.org/project/kornia) (📥 470K / month): ``` - pip install gluoncv + pip install kornia ```
-
scikit-image (🥈29 · ⭐ 4.7K) - Python中的图像处理。❗Unlicensed +
scikit-image (🥇32 · ⭐ 5K) - Image processing in Python. ❗Unlicensed -- [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 540 · 🔀 1.8K · 📦 88K · 📋 2.2K - 6% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 560 · 🔀 2K · 📦 110K · 📋 2.3K - 19% open · ⏱️ 23.08.2022): ``` git clone https://github.com/scikit-image/scikit-image ``` -- [PyPi](https://pypi.org/project/scikit-image): +- [PyPi](https://pypi.org/project/scikit-image) (📥 5.3M / month): ``` pip install scikit-image ``` -- [Conda](https://anaconda.org/conda-forge/scikit-image) (📥 3.1M · ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-image) (📥 3.8M · ⏱️ 10.08.2022): ``` conda install -c conda-forge scikit-image ```
-
ImageHash (🥈29 · ⭐ 2.2K) - Python感知图像哈希模块。BSD-2 +
Wand (🥇32 · ⭐ 1.2K) - The ctypes-based simple ImageMagick binding for Python. MIT -- [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 280 · 📦 3.9K · 📋 100 - 10% open · ⏱️ 07.09.2021): +- [GitHub](https://github.com/emcconville/wand) (👨‍💻 100 · 🔀 190 · 📥 8.5K · 📦 12K · 📋 380 - 4% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/JohannesBuchner/imagehash - ``` -- [PyPi](https://pypi.org/project/ImageHash) (📥 1.2M / month): - ``` - pip install ImageHash + git clone https://github.com/emcconville/wand ``` -- [Conda](https://anaconda.org/conda-forge/imagehash) (📥 160K · ⏱️ 15.07.2021): +- [PyPi](https://pypi.org/project/wand) (📥 450K / month): ``` - conda install -c conda-forge imagehash + pip install wand ```
-
imutils (🥈28 · ⭐ 3.9K · 💤) - 图像处理库。MIT +
PyTorch Image Models (🥈31 · ⭐ 21K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 -- [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 20 · 🔀 930 · 📦 21K · 📋 160 - 52% open · ⏱️ 15.01.2021): +- [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 79 · 🔀 3.3K · 📥 1.7M · 📦 4.3K · 📋 570 - 9% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/jrosebr1/imutils - ``` -- [PyPi](https://pypi.org/project/imutils) (📥 470K / month): - ``` - pip install imutils - ``` -- [Conda](https://anaconda.org/conda-forge/imutils) (📥 74K · ⏱️ 09.12.2021): - ``` - conda install -c conda-forge imutils + git clone https://github.com/rwightman/pytorch-image-models ```
-
MMDetection (🥈27 · ⭐ 18K) - OpenMMLab检测工具箱。Apache-2 +
GluonCV (🥈29 · ⭐ 5.3K) - Gluon CV Toolkit. Apache-2 -- [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 290 · 🔀 5.8K · 📦 200 · 📋 4.9K - 7% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 120 · 🔀 1.2K · 📦 840 · 📋 810 - 5% open · ⏱️ 11.08.2022): ``` - git clone https://github.com/open-mmlab/mmdetection + git clone https://github.com/dmlc/gluon-cv + ``` +- [PyPi](https://pypi.org/project/gluoncv) (📥 570K / month): + ``` + pip install gluoncv ```
-
glfw (🥈27 · ⭐ 8.4K) - 一个用于OpenGL，Op​​enGL ES，Vulkan，窗口和输入的多平台库。❗️Zlib +
ImageHash (🥈29 · ⭐ 2.5K · 💤) - A Python Perceptual Image Hashing Module. BSD-2 -- [GitHub](https://github.com/glfw/glfw) (👨‍💻 180 · 🔀 3K · 📥 2.6M · 📦 1 · 📋 1.5K - 27% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 300 · 📦 5.8K · 📋 110 - 13% open · ⏱️ 07.09.2021): ``` - git clone https://github.com/glfw/glfw + git clone https://github.com/JohannesBuchner/imagehash ``` -- [PyPi](https://pypi.org/project/glfw) (📥 80K / month): +- [PyPi](https://pypi.org/project/ImageHash) (📥 1.4M / month): ``` - pip install glfw + pip install ImageHash ``` -- [Conda](https://anaconda.org/conda-forge/glfw) (📥 42K · ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/imagehash) (📥 230K · ⏱️ 15.07.2021): ``` - conda install -c conda-forge glfw + conda install -c conda-forge imagehash ```
-
Kornia (🥈27 · ⭐ 5.6K) - PyTorch的开源可微分计算机视觉库。❗Unlicensed +
imutils (🥈28 · ⭐ 4.2K · 💤) - A series of convenience functions to make basic image processing.. MIT -- [GitHub](https://github.com/kornia/kornia) (👨‍💻 140 · 🔀 540 · 📥 160 · 📦 830 · 📋 490 - 22% open · ⏱️ 12.12.2021): +- [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 21 · 🔀 980 · 📦 27K · 📋 160 - 53% open · ⏱️ 27.01.2022): ``` - git clone https://github.com/kornia/kornia - ``` -- [PyPi](https://pypi.org/project/kornia) (📥 180K / month): - ``` - pip install kornia + git clone https://github.com/jrosebr1/imutils ``` -
-
Wand (🥈27 · ⭐ 1.1K) - 用于Python的基于ctypes的简单ImageMagick接口。MIT - -- [GitHub](https://github.com/emcconville/wand) (👨‍💻 97 · 🔀 190 · 📥 5.3K · 📦 7.9K · 📋 360 - 3% open · ⏱️ 20.11.2021): - +- [PyPi](https://pypi.org/project/imutils) (📥 330K / month): ``` - git clone https://github.com/emcconville/wand + pip install imutils ``` -- [PyPi](https://pypi.org/project/wand): +- [Conda](https://anaconda.org/conda-forge/imutils) (📥 97K · ⏱️ 26.08.2022): ``` - pip install wand + conda install -c conda-forge imutils ```
-
detectron2 (🥈26 · ⭐ 19K) - Detectron2是Facebook FAIR的高级目标检测平台。Apache-2 +
MMDetection (🥈27 · ⭐ 21K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 -- [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 200 · 🔀 4.9K · 📦 440 · 📋 2.8K - 4% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 350 · 🔀 6.9K · 📦 550 · 📋 6.2K - 9% open · ⏱️ 28.07.2022): ``` - git clone https://github.com/facebookresearch/detectron2 - ``` -- [Conda](https://anaconda.org/conda-forge/detectron2) (📥 36K · ⏱️ 30.07.2021): - ``` - conda install -c conda-forge detectron2 + git clone https://github.com/open-mmlab/mmdetection ```
-
InsightFace (🥈26 · ⭐ 11K) - MXNet和PyTorch上的人脸分析项目。MIT +
torchvision (🥈27 · ⭐ 12K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 -- [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 31 · 🔀 3.5K · 📦 120 · 📋 1.8K - 53% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/pytorch/vision) (👨‍💻 500 · 🔀 6K · 📥 11K · 📋 2.5K - 23% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/deepinsight/insightface - ``` -- [PyPi](https://pypi.org/project/insightface) (📥 23K / month): - ``` - pip install insightface + git clone https://github.com/pytorch/vision ``` -
-
imageai (🥈26 · ⭐ 6.7K · 💤) - python库旨在使开发人员能够构建应用程序。MIT - -- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (👨‍💻 15 · 🔀 1.8K · 📥 680K · 📦 1K · 📋 660 - 35% open · ⏱️ 08.05.2021): - +- [PyPi](https://pypi.org/project/torchvision) (📥 3.9M / month): ``` - git clone https://github.com/OlafenwaMoses/ImageAI + pip install torchvision ``` -- [PyPi](https://pypi.org/project/imageai): +- [Conda](https://anaconda.org/conda-forge/torchvision) (📥 340K · ⏱️ 24.07.2022): ``` - pip install imageai + conda install -c conda-forge torchvision ```
-
Face Recognition (🥈25 · ⭐ 43K) - 简单的面部识别API。MIT +
glfw (🥈27 · ⭐ 9.5K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib -- [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 47 · 🔀 12K · 📥 450 · 📋 1.2K - 53% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/glfw/glfw) (👨‍💻 180 · 🔀 3.5K · 📥 2.9M · 📦 1 · 📋 1.6K - 25% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/ageitgey/face_recognition + git clone https://github.com/glfw/glfw ``` -- [PyPi](https://pypi.org/project/face_recognition) (📥 52K / month): +- [PyPi](https://pypi.org/project/glfw) (📥 220K / month): ``` - pip install face_recognition + pip install glfw + ``` +- [Conda](https://anaconda.org/conda-forge/glfw) (📥 68K · ⏱️ 23.07.2022): + ``` + conda install -c conda-forge glfw ```
-
Pillow (🥈24 · ⭐ 9.2K · 📉) - 友好的PIL分支（Python Imaging Library）。❗️PIL +
InsightFace (🥈26 · ⭐ 12K) - Face Analysis Project on MXNet and PyTorch. MIT -- [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 380 · 🔀 1.6K · 📋 2.4K - 5% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 46 · 🔀 3.9K · 📦 180 · 📋 2K - 55% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/python-pillow/Pillow - ``` -- [PyPi](https://pypi.org/project/Pillow): - ``` - pip install Pillow + git clone https://github.com/deepinsight/insightface ``` -- [Conda](https://anaconda.org/conda-forge/pillow) (📥 12M · ⏱️ 10.11.2021): +- [PyPi](https://pypi.org/project/insightface) (📥 21K / month): ``` - conda install -c conda-forge pillow + pip install insightface ```
-
facenet-pytorch (🥈24 · ⭐ 2.6K) - 预训练的Pytorch人脸检测（MTCNN）和识别。MIT +
imageai (🥈26 · ⭐ 7.2K · 💀) - A python library built to empower developers to build applications.. MIT -- [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 550 · 📥 180K · 📦 570 · 📋 140 - 36% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (👨‍💻 15 · 🔀 1.9K · 📥 780K · 📦 1.2K · 📋 690 - 37% open · ⏱️ 08.05.2021): ``` - git clone https://github.com/timesler/facenet-pytorch + git clone https://github.com/OlafenwaMoses/ImageAI ``` -- [PyPi](https://pypi.org/project/facenet-pytorch): +- [PyPi](https://pypi.org/project/imageai) (📥 8.9K / month): ``` - pip install facenet-pytorch + pip install imageai ```
-
torchvision (🥈23 · ⭐ 11K) - 计算机视觉的数据集，转换和模型。BSD-3 +
Face Recognition (🥈25 · ⭐ 46K) - The world's simplest facial recognition api for.. MIT -- [GitHub](https://github.com/pytorch/vision) (👨‍💻 440 · 🔀 5.3K · 📋 2K - 23% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 54 · 🔀 12K · 📥 470 · 📋 1.2K - 53% open · ⏱️ 10.06.2022): ``` - git clone https://github.com/pytorch/vision - ``` -- [PyPi](https://pypi.org/project/torchvision): - ``` - pip install torchvision + git clone https://github.com/ageitgey/face_recognition ``` -- [Conda](https://anaconda.org/conda-forge/torchvision) (📥 160K · ⏱️ 27.09.2021): +- [PyPi](https://pypi.org/project/face_recognition) (📥 39K / month): ``` - conda install -c conda-forge torchvision + pip install face_recognition ```
-
mtcnn (🥈23 · ⭐ 1.7K) - TensorFlow的MTCNN人脸检测实现。MIT +
detectron2 (🥈25 · ⭐ 22K) - Detectron2 is FAIR's next-generation platform for object.. Apache-2 -- [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 430 · 📦 1.7K · 📋 97 - 61% open · ⏱️ 09.07.2021): +- [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 210 · 🔀 5.7K · 📦 710 · 📋 3.1K - 7% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/ipazc/mtcnn + git clone https://github.com/facebookresearch/detectron2 ``` -- [PyPi](https://pypi.org/project/mtcnn) (📥 33K / month): +- [Conda](https://anaconda.org/conda-forge/detectron2) (📥 78K · ⏱️ 25.04.2022): ``` - pip install mtcnn + conda install -c conda-forge detectron2 ```
-
Image Deduplicator (🥉22 · ⭐ 3.9K · 💀) - 图像查重。Apache-2 +
vit-pytorch (🥈25 · ⭐ 11K) - Implementation of Vision Transformer, a simple way to.. MIT -- [GitHub](https://github.com/idealo/imagededup) (👨‍💻 10 · 🔀 330 · 📦 21 · 📋 87 - 32% open · ⏱️ 23.11.2020): +- [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 15 · 🔀 1.8K · 📦 140 · 📋 190 - 47% open · ⏱️ 27.07.2022): ``` - git clone https://github.com/idealo/imagededup + git clone https://github.com/lucidrains/vit-pytorch ``` -- [PyPi](https://pypi.org/project/imagededup) (📥 2.8K / month): +- [PyPi](https://pypi.org/project/vit-pytorch) (📥 19K / month): ``` - pip install imagededup + pip install vit-pytorch ```
-
Image Super-Resolution (🥉22 · ⭐ 3.3K) - 图像超精度变换。Apache-2 +
facenet-pytorch (🥈25 · ⭐ 3K · 💤) - Pretrained Pytorch face detection (MTCNN) and.. MIT -- [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 570 · 📦 68 · 📋 190 - 42% open · ⏱️ 02.06.2021): +- [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 650 · 📥 390K · 📦 850 · 📋 150 - 39% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/idealo/image-super-resolution - ``` -- [PyPi](https://pypi.org/project/ISR) (📥 5.8K / month): - ``` - pip install ISR + git clone https://github.com/timesler/facenet-pytorch ``` -- [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (📥 190 · ⏱️ 01.04.2019): +- [PyPi](https://pypi.org/project/facenet-pytorch) (📥 18K / month): ``` - docker pull idealo/image-super-resolution-gpu + pip install facenet-pytorch ```
-
Torch Points 3D (🥉22 · ⭐ 1.6K) - 用于在点云上进行深度学习的Pytorch框架。BSD-3 +
opencv-python (🥈25 · ⭐ 2.9K · 📈) - Automated CI toolchain to produce precompiled opencv-python,.. MIT -- [GitHub](https://github.com/nicolas-chaulet/torch-points3d) (👨‍💻 29 · 🔀 260 · 📦 4 · 📋 300 - 29% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 39 · 🔀 580 · 📋 570 - 7% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/nicolas-chaulet/torch-points3d + git clone https://github.com/skvark/opencv-python ``` -- [PyPi](https://pypi.org/project/torch-points3d) (📥 1K / month): +- [PyPi](https://pypi.org/project/opencv-python) (📥 5.6M / month): ``` - pip install torch-points3d + pip install opencv-python ```
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chainercv (🥉22 · ⭐ 1.5K · 💀) - ChainerCV：一个用于计算机视觉深度学习的库。MIT +
chainercv (🥈25 · ⭐ 1.5K · 💀) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT -- [GitHub](https://github.com/chainer/chainercv) (👨‍💻 39 · 🔀 310 · 📦 270 · 📋 200 - 18% open · ⏱️ 07.01.2020): +- [GitHub](https://github.com/chainer/chainercv) (👨‍💻 39 · 🔀 300 · 📦 300 · 📋 200 - 18% open · ⏱️ 07.01.2020): ``` git clone https://github.com/chainer/chainercv ``` -- [PyPi](https://pypi.org/project/chainercv): +- [PyPi](https://pypi.org/project/chainercv) (📥 3.2K / month): ``` pip install chainercv ```
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mahotas (🥉22 · ⭐ 720) - Python中的计算机视觉。❗Unlicensed +
mahotas (🥈25 · ⭐ 770) - Computer Vision in Python. ❗Unlicensed -- [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 32 · 🔀 140 · 📦 720 · 📋 76 - 19% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 32 · 🔀 140 · 📦 870 · 📋 79 - 20% open · ⏱️ 28.06.2022): ``` git clone https://github.com/luispedro/mahotas ``` -- [PyPi](https://pypi.org/project/mahotas): +- [PyPi](https://pypi.org/project/mahotas) (📥 11K / month): ``` pip install mahotas ``` -- [Conda](https://anaconda.org/conda-forge/mahotas) (📥 310K · ⏱️ 17.11.2021): +- [Conda](https://anaconda.org/conda-forge/mahotas) (📥 330K · ⏱️ 28.07.2022): ``` conda install -c conda-forge mahotas ```
-
segmentation_models (🥉21 · ⭐ 3.6K · 💀) - Segmentation models with pretrained backbones. Keras.. MIT +
vidgear (🥉24 · ⭐ 2.4K) - High-performance cross-platform Video Processing Python framework.. Apache-2 -- [GitHub](https://github.com/qubvel/segmentation_models) (👨‍💻 14 · 🔀 840 · 📋 450 - 44% open · ⏱️ 17.04.2020): +- [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 13 · 🔀 190 · 📥 640 · 📦 230 · 📋 230 - 1% open · ⏱️ 06.07.2022): ``` - git clone https://github.com/qubvel/segmentation_models + git clone https://github.com/abhiTronix/vidgear ``` -- [PyPi](https://pypi.org/project/segmentation_models) (📥 57K / month): +- [PyPi](https://pypi.org/project/vidgear) (📥 6.5K / month): ``` - pip install segmentation_models + pip install vidgear ```
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PyTorch3D (🥉20 · ⭐ 5.5K) - PyTorch3D是FAIR的深度学习可重用组件库。❗Unlicensed +
PyTorch3D (🥉23 · ⭐ 6.4K) - PyTorch3D is FAIR's library of reusable components for.. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 75 · 🔀 750 · 📦 130 · 📋 840 - 9% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 96 · 🔀 940 · 📦 270 · 📋 1.1K - 7% open · ⏱️ 25.08.2022): ``` git clone https://github.com/facebookresearch/pytorch3d ``` -- [PyPi](https://pypi.org/project/pytorch3d): +- [PyPi](https://pypi.org/project/pytorch3d) (📥 14K / month): ``` pip install pytorch3d ``` -- [Conda](https://anaconda.org/pytorch3d/pytorch3d) (📥 26K · ⏱️ 13.12.2021): +- [Conda](https://anaconda.org/pytorch3d/pytorch3d) (📥 60K · ⏱️ 14.08.2022): ``` conda install -c pytorch3d pytorch3d ```
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Augmentor (🥉20 · ⭐ 4.6K) - Python中的图像增强库，用于机器学习。MIT +
Face Alignment (🥉23 · ⭐ 5.8K · 💤) - 2D and 3D Face alignment library build using pytorch. BSD-3 -- [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 810 · 📦 390 · 📋 180 - 61% open · ⏱️ 15.10.2021): +- [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.2K · 📋 280 - 21% open · ⏱️ 04.08.2021): ``` - git clone https://github.com/mdbloice/Augmentor + git clone https://github.com/1adrianb/face-alignment ``` -- [PyPi](https://pypi.org/project/Augmentor): +- [PyPi](https://pypi.org/project/face-alignment) (📥 9.6K / month): ``` - pip install Augmentor + pip install face-alignment ```
-
vidgear (🥉20 · ⭐ 2K) - 高性能跨平台视频处理Python框架。Apache-2 +
Augmentor (🥉23 · ⭐ 4.8K) - Image augmentation library in Python for machine learning. MIT -- [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 9 · 🔀 150 · 📥 500 · 📦 160 · 📋 190 - 1% open · ⏱️ 05.12.2021): +- [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 820 · 📦 480 · 📋 190 - 61% open · ⏱️ 24.05.2022): ``` - git clone https://github.com/abhiTronix/vidgear + git clone https://github.com/mdbloice/Augmentor ``` -- [PyPi](https://pypi.org/project/vidgear): +- [PyPi](https://pypi.org/project/Augmentor) (📥 16K / month): ``` - pip install vidgear + pip install Augmentor ```
-
Classy Vision (🥉20 · ⭐ 1.4K) - 用于图像和视频的端到端PyTorch框架。MIT +
mtcnn (🥉23 · ⭐ 1.8K · 💀) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT -- [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 66 · 🔀 240 · 📋 74 - 17% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 460 · 📦 2.6K · 📋 100 - 62% open · ⏱️ 09.07.2021): ``` - git clone https://github.com/facebookresearch/ClassyVision - ``` -- [PyPi](https://pypi.org/project/classy_vision) (📥 1.4K / month): - ``` - pip install classy_vision + git clone https://github.com/ipazc/mtcnn ``` -- [Conda](https://anaconda.org/conda-forge/classy_vision) (📥 11K · ⏱️ 11.12.2020): +- [PyPi](https://pypi.org/project/mtcnn) (📥 23K / month): ``` - conda install -c conda-forge classy_vision + pip install mtcnn ```
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CellProfiler (🥉20 · ⭐ 630) - 生物图像分析的开源应用程序。❗Unlicensed +
lightly (🥉23 · ⭐ 1.7K) - A python library for self-supervised learning on images. MIT -- [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 120 · 🔀 290 · 📥 2K · 📦 5 · 📋 3K - 6% open · ⏱️ 05.11.2021): +- [GitHub](https://github.com/lightly-ai/lightly) (👨‍💻 19 · 🔀 140 · 📦 46 · 📋 330 - 20% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/CellProfiler/CellProfiler + git clone https://github.com/lightly-ai/lightly ``` -- [PyPi](https://pypi.org/project/cellprofiler): +- [PyPi](https://pypi.org/project/lightly) (📥 3.3K / month): ``` - pip install cellprofiler + pip install lightly ```
-
Caer (🥉20 · ⭐ 580) - 轻量级的计算机视觉库。MIT +
Image Deduplicator (🥉22 · ⭐ 4.1K · 💀) - Finding duplicate images made easy!. Apache-2 -- [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 8 · 🔀 63 · 📥 19 · 📋 15 - 13% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/idealo/imagededup) (👨‍💻 10 · 🔀 370 · 📦 26 · 📋 93 - 36% open · ⏱️ 23.11.2020): ``` - git clone https://github.com/jasmcaus/caer + git clone https://github.com/idealo/imagededup ``` -- [PyPi](https://pypi.org/project/caer) (📥 4.1K / month): +- [PyPi](https://pypi.org/project/imagededup) (📥 1.3K / month): ``` - pip install caer + pip install imagededup ```
-
pyvips (🥉20 · ⭐ 370) - 使用cffi的libvips的python接口。MIT +
pyvips (🥉22 · ⭐ 440) - python binding for libvips using cffi. MIT -- [GitHub](https://github.com/libvips/pyvips) (👨‍💻 12 · 🔀 32 · 📦 250 · 📋 260 - 36% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/libvips/pyvips) (👨‍💻 14 · 🔀 40 · 📦 350 · 📋 300 - 36% open · ⏱️ 13.08.2022): ``` git clone https://github.com/libvips/pyvips ``` -- [PyPi](https://pypi.org/project/pyvips): +- [PyPi](https://pypi.org/project/pyvips) (📥 19K / month): ``` pip install pyvips ``` -- [Conda](https://anaconda.org/conda-forge/pyvips) (📥 14K · ⏱️ 22.11.2021): +- [Conda](https://anaconda.org/conda-forge/pyvips) (📥 29K · ⏱️ 24.07.2022): ``` conda install -c conda-forge pyvips ```
-
vit-pytorch (🥉19 · ⭐ 7.2K) - 实现视觉transformer，一种简单的方法。MIT +
PaddleDetection (🥉21 · ⭐ 8.3K) - Object detection and instance segmentation toolkit.. Apache-2 -- [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 12 · 🔀 1.1K · 📦 59 · 📋 150 - 47% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 100 · 🔀 2.1K · 📦 30 · 📋 3.8K - 20% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/lucidrains/vit-pytorch - ``` -- [PyPi](https://pypi.org/project/vit-pytorch): - ``` - pip install vit-pytorch + git clone https://github.com/PaddlePaddle/PaddleDetection ```
-
PaddleDetection (🥉19 · ⭐ 5.8K) - 对象检测和实例分割工具箱。Apache-2 +
segmentation_models (🥉21 · ⭐ 4K) - Segmentation models with pretrained backbones. Keras.. MIT -- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 75 · 🔀 1.4K · 📦 6 · 📋 2.7K - 28% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/qubvel/segmentation_models) (👨‍💻 14 · 🔀 910 · 📋 480 - 46% open · ⏱️ 29.07.2022): ``` - git clone https://github.com/PaddlePaddle/PaddleDetection + git clone https://github.com/qubvel/segmentation_models + ``` +- [PyPi](https://pypi.org/project/segmentation_models) (📥 26K / month): + ``` + pip install segmentation_models ```
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Face Alignment (🥉19 · ⭐ 5.4K) - 使用pytorch构建2D和3D人脸对齐库。BSD-3 +
Image Super-Resolution (🥉21 · ⭐ 3.8K · 💀) - Super-scale your images and run experiments with.. Apache-2 -- [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.1K · 📋 260 - 18% open · ⏱️ 04.08.2021): +- [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 630 · 📦 97 · 📋 200 - 45% open · ⏱️ 02.06.2021): ``` - git clone https://github.com/1adrianb/face-alignment + git clone https://github.com/idealo/image-super-resolution ``` -- [PyPi](https://pypi.org/project/face-alignment): +- [PyPi](https://pypi.org/project/ISR) (📥 4.5K / month): ``` - pip install face-alignment + pip install ISR + ``` +- [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (📥 220 · ⏱️ 01.04.2019): + ``` + docker pull idealo/image-super-resolution-gpu ```
-
Luminoth (🥉19 · ⭐ 2.4K · 💀) - 用于计算机视觉的深度学习工具包。BSD-3 +
Norfair (🥉21 · ⭐ 1.6K) - Lightweight Python library for adding real-time 2D object tracking to.. BSD-3 -- [GitHub](https://github.com/tryolabs/luminoth) (👨‍💻 15 · 🔀 400 · 📥 12K · 📦 39 · 📋 180 - 28% open · ⏱️ 07.01.2020): +- [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 18 · 🔀 150 · 📥 200 · 📋 75 - 16% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/tryolabs/luminoth + git clone https://github.com/tryolabs/norfair ``` -- [PyPi](https://pypi.org/project/luminoth) (📥 850 / month): +- [PyPi](https://pypi.org/project/norfair) (📥 7.3K / month): ``` - pip install luminoth + pip install norfair ```
-
lightly (🥉19 · ⭐ 1.3K) - 一个用于对图像进行自监督学习的python库。MIT +
CellProfiler (🥉21 · ⭐ 700) - An open-source application for biological image analysis. ❗Unlicensed -- [GitHub](https://github.com/lightly-ai/lightly) (👨‍💻 14 · 🔀 86 · 📦 25 · 📋 290 - 21% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 130 · 🔀 320 · 📥 3.4K · 📦 9 · 📋 3.1K - 5% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/lightly-ai/lightly + git clone https://github.com/CellProfiler/CellProfiler ``` -- [PyPi](https://pypi.org/project/lightly): +- [PyPi](https://pypi.org/project/cellprofiler) (📥 900 / month): ``` - pip install lightly + pip install cellprofiler ```
-
MMF (🥉18 · ⭐ 4.7K) - 来自视觉和语言多模态研究的模块化框架。BSD-3 +
MMF (🥉20 · ⭐ 5K) - A modular framework for vision & language multimodal research from.. BSD-3 -- [GitHub](https://github.com/facebookresearch/mmf) (👨‍💻 89 · 🔀 780 · 📦 10 · 📋 570 - 26% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/facebookresearch/mmf) (👨‍💻 100 · 🔀 840 · 📦 12 · 📋 620 - 30% open · ⏱️ 11.08.2022): ``` git clone https://github.com/facebookresearch/mmf ``` -- [PyPi](https://pypi.org/project/mmf): +- [PyPi](https://pypi.org/project/mmf) (📥 240 / month): ``` pip install mmf ```
-
tensorflow-graphics (🥉17 · ⭐ 2.6K) - TensorFlow图神经网络：可微分的图layerApache-2 +
tensorflow-graphics (🥉20 · ⭐ 2.7K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 -- [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 34 · 🔀 320 · 📋 160 - 43% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 36 · 🔀 340 · 📋 160 - 45% open · ⏱️ 04.04.2022): ``` git clone https://github.com/tensorflow/graphics ``` -- [PyPi](https://pypi.org/project/tensorflow-graphics): +- [PyPi](https://pypi.org/project/tensorflow-graphics) (📥 2.7K / month): ``` pip install tensorflow-graphics ```
-
Norfair (🥉17 · ⭐ 1.2K) - 轻量级Python库，用于向其中添加实时2D对象跟踪。BSD-3 +
nude.py (🥉20 · ⭐ 860 · 💀) - Nudity detection with Python. MIT -- [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 9 · 🔀 88 · 📋 39 - 20% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 2.6K · 📋 10 - 70% open · ⏱️ 23.11.2020): ``` - git clone https://github.com/tryolabs/norfair + git clone https://github.com/hhatto/nude.py ``` -- [PyPi](https://pypi.org/project/norfair): +- [PyPi](https://pypi.org/project/nudepy) (📥 9.5K / month): ``` - pip install norfair + pip install nudepy ```
-
DE⫶TR (🥉16 · ⭐ 8.1K) - End-to-End Object Detection with Transformers. Apache-2 +
Luminoth (🥉19 · ⭐ 2.4K · 💀) - Deep Learning toolkit for Computer Vision. BSD-3 -- [GitHub](https://github.com/facebookresearch/detr) (👨‍💻 24 · 🔀 1.4K · 📋 400 - 32% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/tryolabs/luminoth) (👨‍💻 15 · 🔀 400 · 📥 13K · 📦 41 · 📋 180 - 28% open · ⏱️ 07.01.2020): ``` - git clone https://github.com/facebookresearch/detr + git clone https://github.com/tryolabs/luminoth + ``` +- [PyPi](https://pypi.org/project/luminoth) (📥 610 / month): + ``` + pip install luminoth ```
-
opencv-python (🥉16 · ⭐ 2.4K) - 自动化的CI工具链可生成预编译的opencv-python。❗Unlicensed +
Classy Vision (🥉19 · ⭐ 1.5K) - An end-to-end PyTorch framework for image and video.. MIT -- [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 36 · 🔀 470 · 📋 490 - 5% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 76 · 🔀 260 · 📋 76 - 17% open · ⏱️ 03.08.2022): ``` - git clone https://github.com/skvark/opencv-python + git clone https://github.com/facebookresearch/ClassyVision ``` -- [PyPi](https://pypi.org/project/opencv-python): +- [PyPi](https://pypi.org/project/classy_vision) (📥 2K / month): ``` - pip install opencv-python + pip install classy_vision + ``` +- [Conda](https://anaconda.org/conda-forge/classy_vision) (📥 14K · ⏱️ 22.03.2022): + ``` + conda install -c conda-forge classy_vision ```
-
Pillow-SIMD (🥉16 · ⭐ 1.7K · 💀) - 友好的PIL fork。❗️PIL +
Caer (🥉18 · ⭐ 630 · 💤) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT -- [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 310 · 🔀 70 · 📦 500 · 📋 69 - 17% open · ⏱️ 02.06.2020): +- [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 8 · 🔀 74 · 📥 19 · 📋 15 - 13% open · ⏱️ 13.10.2021): ``` - git clone https://github.com/uploadcare/pillow-simd + git clone https://github.com/jasmcaus/caer ``` -- [PyPi](https://pypi.org/project/pillow-simd): +- [PyPi](https://pypi.org/project/caer) (📥 3K / month): ``` - pip install pillow-simd + pip install caer ```
-
nude.py (🥉16 · ⭐ 820 · 💀) - 使用Python进行裸露检测。MIT +
DE⫶TR (🥉17 · ⭐ 9.6K) - End-to-End Object Detection with Transformers. Apache-2 -- [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 1.3K · 📋 10 - 70% open · ⏱️ 23.11.2020): +- [GitHub](https://github.com/facebookresearch/detr) (👨‍💻 25 · 🔀 1.7K · 📋 440 - 38% open · ⏱️ 07.03.2022): ``` - git clone https://github.com/hhatto/nude.py + git clone https://github.com/facebookresearch/detr + ``` +
+
Pillow-SIMD (🥉17 · ⭐ 1.9K · 💤) - The friendly PIL fork. ❗️PIL + +- [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 380 · 🔀 74 · 📋 77 - 14% open · ⏱️ 17.01.2022): + + ``` + git clone https://github.com/uploadcare/pillow-simd ``` -- [PyPi](https://pypi.org/project/nudepy): +- [PyPi](https://pypi.org/project/pillow-simd) (📥 51K / month): ``` - pip install nudepy + pip install pillow-simd ```
-
PySlowFast (🥉15 · ⭐ 4.4K) - PySlowFast：来自FAIR的视频理解代码库。Apache-2 +
PySlowFast (🥉16 · ⭐ 5K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 -- [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 25 · 🔀 820 · 📦 5 · 📋 470 - 49% open · ⏱️ 28.10.2021): +- [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 28 · 🔀 960 · 📦 10 · 📋 550 - 52% open · ⏱️ 25.08.2022): ``` git clone https://github.com/facebookresearch/SlowFast ```
-
pycls (🥉15 · ⭐ 1.8K) - 用PyTorch编写的图像分类研究代码库。MIT +
image-match (🥉16 · ⭐ 2.8K · 💤) - Quickly search over billions of images. ❗Unlicensed + +- [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 380 · 📋 100 - 53% open · ⏱️ 21.09.2021): + + ``` + git clone https://github.com/EdjoLabs/image-match + ``` +- [PyPi](https://pypi.org/project/image_match) (📥 590 / month): + ``` + pip install image_match + ``` +
+
pycls (🥉15 · ⭐ 2K) - Codebase for Image Classification Research, written in PyTorch. MIT -- [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 13 · 🔀 200 · 📦 4 · 📋 77 - 28% open · ⏱️ 19.08.2021): +- [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 17 · 🔀 230 · 📦 6 · 📋 78 - 28% open · ⏱️ 12.07.2022): ``` git clone https://github.com/facebookresearch/pycls ```
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image-match (🥉14 · ⭐ 2.7K) - 快速搜索数十亿张图像。❗Unlicensed +
Torch Points 3D (🥉14 · ⭐ 93 · 💤) - Pytorch framework for doing deep learning on point.. BSD-3 -- [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 370 · 📋 99 - 51% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/nicolas-chaulet/torch-points3d) (👨‍💻 29 · 🔀 19 · ⏱️ 10.12.2021): ``` - git clone https://github.com/EdjoLabs/image-match + git clone https://github.com/nicolas-chaulet/torch-points3d ``` -- [PyPi](https://pypi.org/project/image_match): +- [PyPi](https://pypi.org/project/torch-points3d) (📥 570 / month): ``` - pip install image_match + pip install torch-points3d ```

-## 图数据处理 +## Graph Data -Back to top +Back to top -_用于图数据处理，聚类，图嵌入和机器学习任务的库。_ +_Libraries for graph processing, clustering, embedding, and machine learning tasks._ -
networkx (🥇32 · ⭐ 10K) - Python中的网络分析。❗Unlicensed +
networkx (🥇32 · ⭐ 11K) - Network Analysis in Python. ❗Unlicensed -- [GitHub](https://github.com/networkx/networkx) (👨‍💻 560 · 🔀 2.4K · 📥 57 · 📦 93K · 📋 2.6K - 6% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/networkx/networkx) (👨‍💻 610 · 🔀 2.6K · 📥 60 · 📦 120K · 📋 2.8K - 5% open · ⏱️ 23.08.2022): ``` git clone https://github.com/networkx/networkx ``` -- [PyPi](https://pypi.org/project/networkx) (📥 17M / month): +- [PyPi](https://pypi.org/project/networkx) (📥 19M / month): ``` pip install networkx ``` -- [Conda](https://anaconda.org/conda-forge/networkx) (📥 5.2M · ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/networkx) (📥 7.8M · ⏱️ 22.08.2022): ``` conda install -c conda-forge networkx ```
-
dgl (🥇28 · ⭐ 8.6K) - 在现有基础之上构建的Python软件包，用于简化图上的深度学习。Apache-2 +
dgl (🥇29 · ⭐ 10K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 -- [GitHub](https://github.com/dmlc/dgl) (👨‍💻 180 · 🔀 1.9K · 📋 1.3K - 21% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/dmlc/dgl) (👨‍💻 230 · 🔀 2.4K · 📦 30 · 📋 1.7K - 13% open · ⏱️ 25.08.2022): ``` git clone https://github.com/dmlc/dgl ``` -- [PyPi](https://pypi.org/project/dgl) (📥 68K / month): +- [PyPi](https://pypi.org/project/dgl) (📥 32K / month): ``` pip install dgl ```
-
igraph (🥇27 · ⭐ 900) - Igraph的Python接口。❗️GPL-2.0 - -- [GitHub](https://github.com/igraph/python-igraph) (👨‍💻 56 · 🔀 210 · 📥 300K · 📦 380 · 📋 360 - 8% open · ⏱️ 13.12.2021): - - ``` - git clone https://github.com/igraph/python-igraph - ``` -- [PyPi](https://pypi.org/project/python-igraph) (📥 220K / month): - ``` - pip install python-igraph - ``` -- [Conda](https://anaconda.org/conda-forge/igraph) (📥 260K · ⏱️ 12.11.2021): - ``` - conda install -c conda-forge igraph - ``` -
-
PyTorch Geometric (🥈23 · ⭐ 13K) - PyTorch的几何深度学习扩展库。MIT +
PyTorch Geometric (🥇28 · ⭐ 15K) - Geometric Deep Learning Extension Library for PyTorch. MIT -- [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 230 · 🔀 2.3K · 📋 2.3K - 37% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 300 · 🔀 2.7K · 📋 2.6K - 35% open · ⏱️ 25.08.2022): ``` git clone https://github.com/rusty1s/pytorch_geometric ``` -- [PyPi](https://pypi.org/project/torch-geometric): +- [PyPi](https://pypi.org/project/torch-geometric) (📥 92K / month): ``` pip install torch-geometric ```
-
Karate Club (🥈23 · ⭐ 1.5K) - 面向API的开源Python框架。❗️GPL-3.0 +
ogb (🥇28 · ⭐ 1.4K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT -- [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 13 · 🔀 170 · 📦 65 · 📋 65 - 1% open · ⏱️ 21.11.2021): +- [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 23 · 🔀 310 · 📦 380 · 📋 230 - 0% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/benedekrozemberczki/karateclub + git clone https://github.com/snap-stanford/ogb ``` -- [PyPi](https://pypi.org/project/karateclub) (📥 5.2K / month): +- [PyPi](https://pypi.org/project/ogb) (📥 80K / month): ``` - pip install karateclub + pip install ogb ```
-
StellarGraph (🥈22 · ⭐ 2.2K) - StellarGraph-图机器学习库。Apache-2 +
igraph (🥈27 · ⭐ 1K) - Python interface for igraph. ❗️GPL-2.0 -- [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 320 · 📦 100 · 📋 980 - 25% open · ⏱️ 29.10.2021): +- [GitHub](https://github.com/igraph/python-igraph) (👨‍💻 61 · 🔀 220 · 📥 460K · 📦 850 · 📋 410 - 9% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/stellargraph/stellargraph + git clone https://github.com/igraph/python-igraph ``` -- [PyPi](https://pypi.org/project/stellargraph): +- [PyPi](https://pypi.org/project/python-igraph) (📥 260K / month): ``` - pip install stellargraph + pip install python-igraph + ``` +- [Conda](https://anaconda.org/conda-forge/igraph) (📥 320K · ⏱️ 13.06.2022): + ``` + conda install -c conda-forge igraph ```
-
ogb (🥈22 · ⭐ 1.2K) - 用于图机器学习的基准数据集，数据加载器和评估器。MIT +
StellarGraph (🥈25 · ⭐ 2.5K · 💤) - StellarGraph - Machine Learning on Graphs. Apache-2 -- [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 18 · 🔀 240 · 📦 190 · ⏱️ 06.12.2021): +- [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 380 · 📦 160 · 📋 1K - 27% open · ⏱️ 29.10.2021): ``` - git clone https://github.com/snap-stanford/ogb + git clone https://github.com/stellargraph/stellargraph ``` -- [PyPi](https://pypi.org/project/ogb): +- [PyPi](https://pypi.org/project/stellargraph) (📥 22K / month): ``` - pip install ogb + pip install stellargraph ```
-
Spektral (🥈21 · ⭐ 1.9K) - 使用Keras和Tensorflow 2的图神经网络。MIT +
Spektral (🥈25 · ⭐ 2.1K) - Graph Neural Networks with Keras and Tensorflow 2. MIT -- [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 19 · 🔀 260 · 📦 87 · 📋 200 - 18% open · ⏱️ 26.10.2021): +- [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 24 · 🔀 300 · 📦 140 · 📋 230 - 16% open · ⏱️ 22.07.2022): ``` git clone https://github.com/danielegrattarola/spektral ``` -- [PyPi](https://pypi.org/project/spektral) (📥 4.4K / month): +- [PyPi](https://pypi.org/project/spektral) (📥 6.8K / month): ``` pip install spektral ```
-
Node2Vec (🥈21 · ⭐ 820) - node2vec算法的实现。MIT +
Karate Club (🥈23 · ⭐ 1.7K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 -- [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 9 · 🔀 180 · 📋 69 - 1% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 15 · 🔀 210 · 📦 100 · ⏱️ 20.08.2022): ``` - git clone https://github.com/eliorc/node2vec - ``` -- [PyPi](https://pypi.org/project/node2vec) (📥 130K / month): - ``` - pip install node2vec + git clone https://github.com/benedekrozemberczki/karateclub ``` -- [Conda](https://anaconda.org/conda-forge/node2vec) (📥 20K · ⏱️ 25.04.2020): +- [PyPi](https://pypi.org/project/karateclub) (📥 2.8K / month): ``` - conda install -c conda-forge node2vec + pip install karateclub ```
-
pytorch_geometric_temporal (🥈20 · ⭐ 1.2K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT +
pytorch_geometric_temporal (🥈23 · ⭐ 1.7K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT -- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (👨‍💻 12 · 🔀 160 · 📋 70 - 2% open · ⏱️ 21.11.2021): +- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (👨‍💻 23 · 🔀 250 · 📋 120 - 5% open · ⏱️ 02.08.2022): ``` git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal ``` -- [PyPi](https://pypi.org/project/torch-geometric-temporal) (📥 1K / month): +- [PyPi](https://pypi.org/project/torch-geometric-temporal) (📥 1.8K / month): ``` pip install torch-geometric-temporal ```
-
Paddle Graph Learning (🥈20 · ⭐ 1.2K) - paddle图机器学习。Apache-2 +
AmpliGraph (🥈22 · ⭐ 1.8K · 💀) - Python library for Representation Learning on Knowledge.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 21 · 🔀 190 · 📦 23 · 📋 96 - 35% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 210 · 📦 25 · 📋 210 - 12% open · ⏱️ 25.05.2021): ``` - git clone https://github.com/PaddlePaddle/PGL + git clone https://github.com/Accenture/AmpliGraph ``` -- [PyPi](https://pypi.org/project/pgl) (📥 980 / month): +- [PyPi](https://pypi.org/project/ampligraph) (📥 1.2K / month): ``` - pip install pgl + pip install ampligraph ```
-
PyKEEN (🥈20 · ⭐ 630) - 一个用于学习和评估知识图嵌入的Python库。MIT +
Paddle Graph Learning (🥈22 · ⭐ 1.4K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 -- [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 24 · 🔀 90 · 📥 92 · 📋 300 - 31% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 28 · 🔀 270 · 📦 33 · 📋 150 - 35% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/pykeen/pykeen + git clone https://github.com/PaddlePaddle/PGL ``` -- [PyPi](https://pypi.org/project/pykeen) (📥 900 / month): +- [PyPi](https://pypi.org/project/pgl) (📥 1.8K / month): ``` - pip install pykeen + pip install pgl ```
-
pygal (🥉19 · ⭐ 2.4K) - PYthon svg GrAph绘图库。❗️LGPL-3.0 +
pygal (🥈21 · ⭐ 2.5K · 💤) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 -- [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 380 · 📋 400 - 38% open · ⏱️ 24.11.2021): +- [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 390 · 📋 400 - 39% open · ⏱️ 24.11.2021): ``` git clone https://github.com/Kozea/pygal ``` -- [PyPi](https://pypi.org/project/pygal): +- [PyPi](https://pypi.org/project/pygal) (📥 120K / month): ``` pip install pygal ``` -- [Conda](https://anaconda.org/conda-forge/pygal) (📥 9.5K · ⏱️ 04.06.2019): +- [Conda](https://anaconda.org/conda-forge/pygal) (📥 20K · ⏱️ 04.06.2019): ``` conda install -c conda-forge pygal ```
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DeepWalk (🥉19 · ⭐ 2.4K · 💀) - DeepWalk-图的深度学习。❗️GPL-3.0 +
PyKEEN (🥈21 · ⭐ 960) - A Python library for learning and evaluating knowledge graph embeddings. MIT -- [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 780 · 📦 46 · 📋 100 - 23% open · ⏱️ 02.04.2020): +- [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 31 · 🔀 130 · 📥 140 · 📋 420 - 13% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/phanein/deepwalk + git clone https://github.com/pykeen/pykeen ``` -- [PyPi](https://pypi.org/project/deepwalk) (📥 2.5K / month): +- [PyPi](https://pypi.org/project/pykeen) (📥 1.4K / month): ``` - pip install deepwalk + pip install pykeen ```
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AmpliGraph (🥉18 · ⭐ 1.7K · 💤) - 用于知识表示学习的Python库。Apache-2 +
Node2Vec (🥈21 · ⭐ 950) - Implementation of the node2vec algorithm. MIT -- [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 190 · 📦 16 · 📋 200 - 9% open · ⏱️ 25.05.2021): +- [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 11 · 🔀 200 · ⏱️ 01.08.2022): ``` - git clone https://github.com/Accenture/AmpliGraph + git clone https://github.com/eliorc/node2vec ``` -- [PyPi](https://pypi.org/project/ampligraph): +- [PyPi](https://pypi.org/project/node2vec) (📥 78K / month): ``` - pip install ampligraph + pip install node2vec + ``` +- [Conda](https://anaconda.org/conda-forge/node2vec) (📥 22K · ⏱️ 25.04.2020): + ``` + conda install -c conda-forge node2vec ```
-
pyRDF2Vec (🥉17 · ⭐ 140) - RDF2Vec的Python实现和扩展。MIT +
torch-cluster (🥈21 · ⭐ 560) - PyTorch Extension Library of Optimized Graph Cluster.. MIT -- [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 5 · 🔀 24 · 📋 44 - 6% open · ⏱️ 08.11.2021): +- [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 25 · 🔀 100 · 📋 110 - 17% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/IBCNServices/pyRDF2Vec + git clone https://github.com/rusty1s/pytorch_cluster ``` -- [PyPi](https://pypi.org/project/pyrdf2vec) (📥 170 / month): +- [PyPi](https://pypi.org/project/torch-cluster) (📥 27K / month): ``` - pip install pyrdf2vec + pip install torch-cluster ```
-
PyTorch-BigGraph (🥉16 · ⭐ 3K) - 从大型图网络结构生成embedding嵌入。❗Unlicensed +
PyTorch-BigGraph (🥉19 · ⭐ 3.1K) - Generate embeddings from large-scale graph-structured.. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 24 · 🔀 400 · 📥 120 · 📋 170 - 30% open · ⏱️ 27.10.2021): +- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 27 · 🔀 410 · 📥 140 · 📋 190 - 26% open · ⏱️ 05.07.2022): ``` git clone https://github.com/facebookresearch/PyTorch-BigGraph ``` -- [PyPi](https://pypi.org/project/torchbiggraph) (📥 810 / month): +- [PyPi](https://pypi.org/project/torchbiggraph) (📥 320K / month): ``` pip install torchbiggraph ```
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GraphEmbedding (🥉16 · ⭐ 2.5K · 💀) - 图嵌入算法的实现和实验。MIT +
DeepWalk (🥉19 · ⭐ 2.5K · 💀) - DeepWalk - Deep Learning for Graphs. ❗Unlicensed -- [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 8 · 🔀 740 · 📦 12 · 📋 52 - 73% open · ⏱️ 18.10.2020): +- [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 810 · 📦 56 · 📋 110 - 24% open · ⏱️ 02.04.2020): ``` - git clone https://github.com/shenweichen/GraphEmbedding + git clone https://github.com/phanein/deepwalk + ``` +- [PyPi](https://pypi.org/project/deepwalk) (📥 3.1K / month): + ``` + pip install deepwalk ```
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kglib (🥉16 · ⭐ 480) - Grakn知识图库（ML R＆D）。Apache-2 +
kglib (🥉17 · ⭐ 520) - Grakn Knowledge Graph Library (ML R&D). Apache-2 -- [GitHub](https://github.com/vaticle/kglib) (👨‍💻 7 · 🔀 86 · 📥 210 · 📋 58 - 15% open · ⏱️ 22.10.2021): +- [GitHub](https://github.com/vaticle/typedb-ml) (👨‍💻 9 · 🔀 88 · 📥 210 · 📋 60 - 16% open · ⏱️ 01.08.2022): ``` git clone https://github.com/graknlabs/kglib ``` -- [PyPi](https://pypi.org/project/grakn-kglib) (📥 73 / month): +- [PyPi](https://pypi.org/project/grakn-kglib) (📥 26 / month): ``` pip install grakn-kglib ```
-
torch-cluster (🥉15 · ⭐ 450) - 优化图聚类的PyTorch扩展库MIT +
GraphEmbedding (🥉16 · ⭐ 3K) - Implementation and experiments of graph embedding algorithms. MIT -- [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 19 · 🔀 84 · 📋 91 - 9% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 9 · 🔀 860 · 📦 21 · 📋 57 - 59% open · ⏱️ 21.06.2022): ``` - git clone https://github.com/rusty1s/pytorch_cluster - ``` -- [PyPi](https://pypi.org/project/torch-cluster): - ``` - pip install torch-cluster + git clone https://github.com/shenweichen/GraphEmbedding ```
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DeepGraph (🥉15 · ⭐ 250) - 使用基于pandas的网络分析数据。❗Unlicensed +
graph-nets (🥉15 · ⭐ 5.2K · 💀) - Build Graph Nets in Tensorflow. Apache-2 -- [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 36 · 📦 2 · 📋 14 - 64% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 770 · 📋 120 - 2% open · ⏱️ 04.12.2020): ``` - git clone https://github.com/deepgraph/deepgraph - ``` -- [PyPi](https://pypi.org/project/deepgraph) (📥 300 / month): - ``` - pip install deepgraph + git clone https://github.com/deepmind/graph_nets ``` -- [Conda](https://anaconda.org/conda-forge/deepgraph) (📥 110K · ⏱️ 08.11.2021): +- [PyPi](https://pypi.org/project/graph-nets) (📥 1K / month): ``` - conda install -c conda-forge deepgraph + pip install graph-nets ```
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Euler (🥉14 · ⭐ 2.7K · 💀) - 分布式图深度学习框架。Apache-2 +
Euler (🥉15 · ⭐ 2.8K · 💀) - A distributed graph deep learning framework. Apache-2 -- [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 540 · 📋 320 - 67% open · ⏱️ 29.07.2020): +- [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 550 · 📋 320 - 67% open · ⏱️ 29.07.2020): ``` git clone https://github.com/alibaba/euler ``` -- [PyPi](https://pypi.org/project/euler-gl) (📥 11 / month): +- [PyPi](https://pypi.org/project/euler-gl) (📥 15 / month): ``` pip install euler-gl ```
-
AutoGL (🥉14 · ⭐ 720) - 用于图上机器学习的autoML框架和工具包。Apache-2 +
DeepGraph (🥉15 · ⭐ 260 · 💀) - Analyze Data with Pandas-based Networks... ❗Unlicensed -- [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 9 · 🔀 72 · 📋 14 - 21% open · ⏱️ 23.11.2021): +- [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 38 · 📦 5 · 📋 14 - 64% open · ⏱️ 14.06.2021): ``` - git clone https://github.com/THUMNLab/AutoGL + git clone https://github.com/deepgraph/deepgraph ``` -- [PyPi](https://pypi.org/project/auto-graph-learning) (📥 28 / month): +- [PyPi](https://pypi.org/project/deepgraph) (📥 290 / month): ``` - pip install auto-graph-learning + pip install deepgraph + ``` +- [Conda](https://anaconda.org/conda-forge/deepgraph) (📥 130K · ⏱️ 19.04.2022): + ``` + conda install -c conda-forge deepgraph ```
-
graph-nets (🥉13 · ⭐ 5K · 💤) - 在Tensorflow中构建图神经网络。Apache-2 +
pyRDF2Vec (🥉15 · ⭐ 160) - Python Implementation and Extension of RDF2Vec. MIT -- [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 760 · 📋 120 - 2% open · ⏱️ 04.12.2020): +- [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 6 · 🔀 32 · 📋 61 - 14% open · ⏱️ 06.05.2022): ``` - git clone https://github.com/deepmind/graph_nets + git clone https://github.com/IBCNServices/pyRDF2Vec ``` -- [PyPi](https://pypi.org/project/graph-nets): +- [PyPi](https://pypi.org/project/pyrdf2vec) (📥 300 / month): ``` - pip install graph-nets + pip install pyrdf2vec ```
-
GraphSAGE (🥉13 · ⭐ 2.6K · 💀) - 大型图上的表示学习。MIT +
GraphSAGE (🥉14 · ⭐ 2.8K · 💀) - Representation learning on large graphs using stochastic.. MIT -- [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 720 · 📋 150 - 60% open · ⏱️ 19.09.2018): +- [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 770 · 📋 160 - 62% open · ⏱️ 19.09.2018): ``` git clone https://github.com/williamleif/GraphSAGE ```
-
OpenNE (🥉13 · ⭐ 1.5K · 💀) - 神经关系提取（NRE）的开源软件包。MIT +
OpenNE (🥉14 · ⭐ 1.6K · 💀) - An Open-Source Package for Network Embedding (NE). MIT -- [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 470 · 📋 96 - 2% open · ⏱️ 12.08.2019): +- [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 480 · 📋 97 - 1% open · ⏱️ 12.08.2019): ``` git clone https://github.com/thunlp/OpenNE ```
-
Sematch (🥉13 · ⭐ 370 · 💀) - 知识图的语义相似性框架。Apache-2 +
AutoGL (🥉14 · ⭐ 840) - An autoML framework & toolkit for machine learning on graphs. Apache-2 + +- [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 13 · 🔀 98 · 📋 23 - 34% open · ⏱️ 19.04.2022): + + ``` + git clone https://github.com/THUMNLab/AutoGL + ``` +- [PyPi](https://pypi.org/project/auto-graph-learning): + ``` + pip install auto-graph-learning + ``` +
+
Sematch (🥉14 · ⭐ 400 · 💀) - semantic similarity framework for knowledge graph. Apache-2 -- [GitHub](https://github.com/gsi-upm/sematch) (👨‍💻 5 · 🔀 100 · 📦 29 · 📋 31 - 38% open · ⏱️ 27.03.2019): +- [GitHub](https://github.com/gsi-upm/sematch) (👨‍💻 5 · 🔀 100 · 📦 34 · 📋 33 - 42% open · ⏱️ 27.03.2019): ``` git clone https://github.com/gsi-upm/sematch ``` -- [PyPi](https://pypi.org/project/sematch): +- [PyPi](https://pypi.org/project/sematch) (📥 130 / month): ``` pip install sematch ```
-
GraphVite (🥉12 · ⭐ 980 · 💤) - GraphVite：通用的高性能图形嵌入系统。Apache-2 +
GraphVite (🥉12 · ⭐ 1.1K · 💀) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 -- [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 130 · 📋 91 - 38% open · ⏱️ 14.01.2021): +- [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 140 · 📋 100 - 42% open · ⏱️ 14.01.2021): ``` git clone https://github.com/DeepGraphLearning/graphvite ``` -- [Conda](https://anaconda.org/milagraph/graphvite) (📥 4.1K · ⏱️ 19.03.2020): +- [Conda](https://anaconda.org/milagraph/graphvite) (📥 4.4K · ⏱️ 19.03.2020): ``` conda install -c milagraph graphvite ```
-
OpenKE (🥉11 · ⭐ 2.8K · 💤) - 神经关系提取（NRE）的开源软件包。❗Unlicensed +
OpenKE (🥉11 · ⭐ 3.2K · 💀) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed -- [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 830 · 📋 330 - 5% open · ⏱️ 06.04.2021): +- [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 900 · 📋 350 - 1% open · ⏱️ 06.04.2021): ``` git clone https://github.com/thunlp/OpenKE @@ -3613,915 +3613,915 @@ _用于图数据处理，聚类，图嵌入和机器学习任务的库。_

-## 音频处理 +## Audio Data -Back to top +Back to top -_用于音频分析，处理，转换和提取以及语音识别和音乐生成任务的库。_ +_Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks._ -
DeepSpeech (🥇30 · ⭐ 19K · 📈) - DeepSpeech是开源的语音转文本引擎。MPL-2.0 +
DeepSpeech (🥇30 · ⭐ 20K · 💤) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -- [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 160 · 🔀 3.2K · 📥 770K · 📦 640 · 📋 2K - 5% open · ⏱️ 17.11.2021): +- [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 160 · 🔀 3.4K · 📥 880K · 📦 800 · 📋 2.1K - 5% open · ⏱️ 17.11.2021): ``` git clone https://github.com/mozilla/DeepSpeech ``` -- [PyPi](https://pypi.org/project/deepspeech): +- [PyPi](https://pypi.org/project/deepspeech) (📥 9.4K / month): ``` pip install deepspeech ```
-
Pydub (🥇30 · ⭐ 5.8K) - 使用简单易用的高级界面处理音频。MIT +
Pydub (🥇30 · ⭐ 6.3K) - Manipulate audio with a simple and easy high level interface. MIT -- [GitHub](https://github.com/jiaaro/pydub) (👨‍💻 90 · 🔀 770 · 📦 9.9K · 📋 450 - 43% open · ⏱️ 08.06.2021): +- [GitHub](https://github.com/jiaaro/pydub) (👨‍💻 92 · 🔀 840 · 📦 14K · 📋 490 - 46% open · ⏱️ 14.05.2022): ``` git clone https://github.com/jiaaro/pydub ``` -- [PyPi](https://pypi.org/project/pydub) (📥 920K / month): +- [PyPi](https://pypi.org/project/pydub) (📥 1.6M / month): ``` pip install pydub ``` -- [Conda](https://anaconda.org/conda-forge/pydub) (📥 20K · ⏱️ 13.03.2021): +- [Conda](https://anaconda.org/conda-forge/pydub) (📥 28K · ⏱️ 13.03.2021): ``` conda install -c conda-forge pydub ```
-
audioread (🥇27 · ⭐ 380) - 跨库（GStreamer + Core Audio + MAD + FFmpeg）音频编解码。MIT +
espnet (🥇29 · ⭐ 5.4K) - End-to-End Speech Processing Toolkit. Apache-2 -- [GitHub](https://github.com/beetbox/audioread) (👨‍💻 21 · 🔀 89 · 📦 6.9K · 📋 75 - 38% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/espnet/espnet) (👨‍💻 280 · 🔀 1.6K · 📥 76 · 📦 67 · 📋 1.9K - 15% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/beetbox/audioread - ``` -- [PyPi](https://pypi.org/project/audioread) (📥 540K / month): - ``` - pip install audioread + git clone https://github.com/espnet/espnet ``` -- [Conda](https://anaconda.org/conda-forge/audioread) (📥 370K · ⏱️ 07.11.2021): +- [PyPi](https://pypi.org/project/espnet) (📥 11K / month): ``` - conda install -c conda-forge audioread + pip install espnet ```
-
Magenta (🥈26 · ⭐ 17K) - 借助机器智能进行音乐和艺术创作。Apache-2 +
Magenta (🥈27 · ⭐ 18K) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 -- [GitHub](https://github.com/magenta/magenta) (👨‍💻 150 · 🔀 3.5K · 📦 330 · 📋 860 - 33% open · ⏱️ 30.06.2021): +- [GitHub](https://github.com/magenta/magenta) (👨‍💻 150 · 🔀 3.5K · 📦 380 · 📋 890 - 34% open · ⏱️ 08.08.2022): ``` git clone https://github.com/magenta/magenta ``` -- [PyPi](https://pypi.org/project/magenta) (📥 7.5K / month): +- [PyPi](https://pypi.org/project/magenta) (📥 3.9K / month): ``` pip install magenta ```
-
aubio (🥈26 · ⭐ 2.6K · 💤) - 用于音频和音乐分析的库。❗️GPL-3.0 +
torchaudio (🥈27 · ⭐ 1.8K) - Data manipulation and transformation for audio signal.. BSD-2 -- [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 330 · 📦 280 · 📋 300 - 40% open · ⏱️ 19.01.2021): +- [GitHub](https://github.com/pytorch/audio) (👨‍💻 170 · 🔀 450 · 📋 640 - 20% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/aubio/aubio - ``` -- [PyPi](https://pypi.org/project/aubio): - ``` - pip install aubio + git clone https://github.com/pytorch/audio ``` -- [Conda](https://anaconda.org/conda-forge/aubio) (📥 480K · ⏱️ 09.11.2021): +- [PyPi](https://pypi.org/project/torchaudio) (📥 730K / month): ``` - conda install -c conda-forge aubio + pip install torchaudio ```
-
torchaudio (🥈25 · ⭐ 1.5K) - 音频信号的数据处理和转换。BSD-2 +
aubio (🥈26 · ⭐ 2.8K · 💤) - a library for audio and music analysis. ❗️GPL-3.0 -- [GitHub](https://github.com/pytorch/audio) (👨‍💻 140 · 🔀 360 · 📋 550 - 20% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 340 · 📦 310 · 📋 310 - 41% open · ⏱️ 25.01.2022): ``` - git clone https://github.com/pytorch/audio + git clone https://github.com/aubio/aubio ``` -- [PyPi](https://pypi.org/project/torchaudio) (📥 380K / month): +- [PyPi](https://pypi.org/project/aubio) (📥 1.5K / month): ``` - pip install torchaudio + pip install aubio + ``` +- [Conda](https://anaconda.org/conda-forge/aubio) (📥 540K · ⏱️ 13.07.2022): + ``` + conda install -c conda-forge aubio ```
-
spleeter (🥈24 · ⭐ 18K) - Deezer源分离库，包括预训练的模型。MIT +
spleeter (🥈24 · ⭐ 20K) - Deezer source separation library including pretrained models. MIT -- [GitHub](https://github.com/deezer/spleeter) (👨‍💻 18 · 🔀 1.9K · 📥 1.3M · 📋 600 - 17% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/deezer/spleeter) (👨‍💻 19 · 🔀 2.2K · 📥 1.8M · 📋 680 - 21% open · ⏱️ 10.06.2022): ``` git clone https://github.com/deezer/spleeter ``` -- [PyPi](https://pypi.org/project/spleeter): +- [PyPi](https://pypi.org/project/spleeter) (📥 10K / month): ``` pip install spleeter ``` -- [Conda](https://anaconda.org/conda-forge/spleeter) (📥 61K · ⏱️ 30.06.2020): +- [Conda](https://anaconda.org/conda-forge/spleeter) (📥 68K · ⏱️ 30.06.2020): ``` conda install -c conda-forge spleeter ```
-
Essentia (🥈24 · ⭐ 2K) - C++库，用于音频和音乐分析，描述等。❗️AGPL-3.0 +
SpeechRecognition (🥈24 · ⭐ 6.5K) - Speech recognition module for Python, supporting.. BSD-3 -- [GitHub](https://github.com/MTG/essentia) (👨‍💻 73 · 🔀 420 · 📦 260 · 📋 920 - 34% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 47 · 🔀 2K · 📋 510 - 44% open · ⏱️ 02.08.2022): ``` - git clone https://github.com/MTG/essentia + git clone https://github.com/Uberi/speech_recognition ``` -- [PyPi](https://pypi.org/project/essentia) (📥 2.3K / month): +- [PyPi](https://pypi.org/project/SpeechRecognition) (📥 330K / month): ``` - pip install essentia + pip install SpeechRecognition + ``` +- [Conda](https://anaconda.org/conda-forge/speechrecognition) (📥 140K · ⏱️ 13.12.2021): + ``` + conda install -c conda-forge speechrecognition ```
-
espnet (🥈23 · ⭐ 4.5K) - 端到端语音处理工具包。Apache-2 +
pyAudioAnalysis (🥈24 · ⭐ 4.9K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 -- [GitHub](https://github.com/espnet/espnet) (👨‍💻 210 · 🔀 1.3K · 📥 74 · 📦 25 · 📋 1.6K - 14% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 26 · 🔀 1.1K · 📦 290 · 📋 290 - 59% open · ⏱️ 19.04.2022): ``` - git clone https://github.com/espnet/espnet + git clone https://github.com/tyiannak/pyAudioAnalysis ``` -- [PyPi](https://pypi.org/project/espnet): +- [PyPi](https://pypi.org/project/pyAudioAnalysis) (📥 21K / month): ``` - pip install espnet + pip install pyAudioAnalysis ```
-
kapre (🥈23 · ⭐ 790) - kapre：Keras音频预处理器。MIT +
Essentia (🥈24 · ⭐ 2.2K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 -- [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 140 · 📥 19 · 📦 1.2K · 📋 93 - 11% open · ⏱️ 14.11.2021): +- [GitHub](https://github.com/MTG/essentia) (👨‍💻 74 · 🔀 460 · 📦 320 · 📋 950 - 36% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/keunwoochoi/kapre + git clone https://github.com/MTG/essentia ``` -- [PyPi](https://pypi.org/project/kapre) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/essentia) (📥 3.9K / month): ``` - pip install kapre + pip install essentia ```
-
SpeechRecognition (🥉22 · ⭐ 6K) - 适用于Python的语音识别模块。❗Unlicensed +
librosa (🥉23 · ⭐ 5.4K) - Python library for audio and music analysis. ISC -- [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 41 · 🔀 1.9K · 📋 490 - 43% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/librosa/librosa) (👨‍💻 110 · 🔀 810 · 📋 1K - 4% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/Uberi/speech_recognition + git clone https://github.com/librosa/librosa ``` -- [PyPi](https://pypi.org/project/SpeechRecognition) (📥 240K / month): +- [PyPi](https://pypi.org/project/librosa) (📥 1.2M / month): ``` - pip install SpeechRecognition + pip install librosa ``` -- [Conda](https://anaconda.org/conda-forge/speechrecognition) (📥 130K · ⏱️ 13.12.2021): +- [Conda](https://anaconda.org/conda-forge/librosa) (📥 510K · ⏱️ 27.06.2022): ``` - conda install -c conda-forge speechrecognition + conda install -c conda-forge librosa ```
-
librosa (🥉22 · ⭐ 4.9K) - 用于音频和音乐分析的Python库。ISC +
tinytag (🥉23 · ⭐ 560) - Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and.. MIT -- [GitHub](https://github.com/librosa/librosa) (👨‍💻 92 · 🔀 760 · 📋 920 - 3% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/devsnd/tinytag) (👨‍💻 22 · 🔀 88 · 📦 580 · 📋 93 - 12% open · ⏱️ 13.08.2022): ``` - git clone https://github.com/librosa/librosa - ``` -- [PyPi](https://pypi.org/project/librosa) (📥 560K / month): - ``` - pip install librosa + git clone https://github.com/devsnd/tinytag ``` -- [Conda](https://anaconda.org/conda-forge/librosa) (📥 420K · ⏱️ 26.05.2021): +- [PyPi](https://pypi.org/project/tinytag) (📥 85K / month): ``` - conda install -c conda-forge librosa + pip install tinytag ```
-
python_speech_features (🥉21 · ⭐ 2K · 💤) - This library provides common speech features for ASR.. MIT +
kapre (🥉22 · ⭐ 850) - kapre: Keras Audio Preprocessors. MIT -- [GitHub](https://github.com/jameslyons/python_speech_features) (👨‍💻 19 · 🔀 570 · 📋 70 - 27% open · ⏱️ 31.12.2020): +- [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 140 · 📥 22 · 📦 1.8K · 📋 94 - 12% open · ⏱️ 04.07.2022): ``` - git clone https://github.com/jameslyons/python_speech_features + git clone https://github.com/keunwoochoi/kapre ``` -- [PyPi](https://pypi.org/project/python_speech_features) (📥 130K / month): +- [PyPi](https://pypi.org/project/kapre) (📥 3.6K / month): ``` - pip install python_speech_features + pip install kapre ```
-
Madmom (🥉21 · ⭐ 840) - Python音频和音乐信号处理库。❗Unlicensed +
Porcupine (🥉21 · ⭐ 2.8K) - On-device wake word detection powered by deep learning. Apache-2 -- [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 150 · 📦 170 · 📋 240 - 21% open · ⏱️ 23.08.2021): +- [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 31 · 🔀 380 · 📦 9 · 📋 390 - 0% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/CPJKU/madmom + git clone https://github.com/Picovoice/Porcupine ``` -- [PyPi](https://pypi.org/project/madmom) (📥 11K / month): +- [PyPi](https://pypi.org/project/pvporcupine) (📥 1.2K / month): ``` - pip install madmom + pip install pvporcupine ```
-
tinytag (🥉21 · ⭐ 500) - 读取音乐元数据和MP3，OGG，OPUS，MP4，M4A，FLAC，WMA等的长度。MIT +
DDSP (🥉21 · ⭐ 2.2K) - DDSP: Differentiable Digital Signal Processing. Apache-2 -- [GitHub](https://github.com/devsnd/tinytag) (👨‍💻 20 · 🔀 82 · 📦 450 · 📋 85 - 11% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/magenta/ddsp) (👨‍💻 31 · 🔀 250 · 📦 28 · 📋 140 - 18% open · ⏱️ 16.05.2022): ``` - git clone https://github.com/devsnd/tinytag + git clone https://github.com/magenta/ddsp ``` -- [PyPi](https://pypi.org/project/tinytag) (📥 11K / month): +- [PyPi](https://pypi.org/project/ddsp) (📥 3K / month): ``` - pip install tinytag + pip install ddsp ```
-
pyAudioAnalysis (🥉20 · ⭐ 4.5K) - Python音频分析库。Apache-2 +
python-soundfile (🥉21 · ⭐ 470) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 -- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 25 · 🔀 1K · 📦 240 · 📋 280 - 58% open · ⏱️ 12.11.2021): +- [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 24 · 🔀 75 · 📥 4K · 📋 170 - 39% open · ⏱️ 23.02.2022): ``` - git clone https://github.com/tyiannak/pyAudioAnalysis + git clone https://github.com/bastibe/python-soundfile ``` -- [PyPi](https://pypi.org/project/pyAudioAnalysis): +- [PyPi](https://pypi.org/project/soundfile) (📥 1.1M / month): ``` - pip install pyAudioAnalysis + pip install soundfile ```
-
Porcupine (🥉19 · ⭐ 2.6K) - 深度学习支持的设备上唤醒词识别。Apache-2 +
python_speech_features (🥉20 · ⭐ 2.1K · 💀) - This library provides common speech features for ASR.. MIT -- [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 30 · 🔀 360 · 📦 6 · 📋 340 - 1% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/jameslyons/python_speech_features) (👨‍💻 19 · 🔀 590 · 📋 71 - 28% open · ⏱️ 31.12.2020): ``` - git clone https://github.com/Picovoice/Porcupine + git clone https://github.com/jameslyons/python_speech_features ``` -- [PyPi](https://pypi.org/project/pvporcupine): +- [PyPi](https://pypi.org/project/python_speech_features) (📥 150K / month): ``` - pip install pvporcupine + pip install python_speech_features ```
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DDSP (🥉19 · ⭐ 2K) - DDSP：微分数字信号处理。Apache-2 +
TTS (🥉19 · ⭐ 6.2K · 💀) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 -- [GitHub](https://github.com/magenta/ddsp) (👨‍💻 29 · 🔀 210 · 📦 18 · 📋 120 - 16% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 930 · 📥 2.6K · 📋 540 - 0% open · ⏱️ 12.02.2021): ``` - git clone https://github.com/magenta/ddsp - ``` -- [PyPi](https://pypi.org/project/ddsp): - ``` - pip install ddsp + git clone https://github.com/mozilla/TTS ```
-
TTS (🥉18 · ⭐ 5.4K · 💤) - 文本到语音的深度学习。MPL-2.0 +
Dejavu (🥉19 · ⭐ 5.8K · 💀) - Audio fingerprinting and recognition in Python. MIT -- [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 850 · 📥 1.5K · 📋 520 - 2% open · ⏱️ 12.02.2021): +- [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 22 · 🔀 1.3K · 📦 23 · 📋 210 - 39% open · ⏱️ 03.06.2020): ``` - git clone https://github.com/mozilla/TTS + git clone https://github.com/worldveil/dejavu + ``` +- [PyPi](https://pypi.org/project/PyDejavu) (📥 67 / month): + ``` + pip install PyDejavu ```
-
Muda (🥉18 · ⭐ 200 · 💤) - 用于扩充带注释的音频数据的库。ISC +
Madmom (🥉19 · ⭐ 950 · 💤) - Python audio and music signal processing library. ❗Unlicensed -- [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 34 · 📦 13 · 📋 49 - 10% open · ⏱️ 03.05.2021): +- [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 150 · 📦 210 · 📋 240 - 16% open · ⏱️ 06.01.2022): ``` - git clone https://github.com/bmcfee/muda + git clone https://github.com/CPJKU/madmom ``` -- [PyPi](https://pypi.org/project/muda) (📥 160 / month): +- [PyPi](https://pypi.org/project/madmom) (📥 1.7K / month): ``` - pip install muda + pip install madmom ```
-
Dejavu (🥉17 · ⭐ 5.6K · 💀) - Python中的音频指纹识别。MIT +
audioread (🥉19 · ⭐ 410 · 📉) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT -- [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 23 · 🔀 1.2K · 📦 19 · 📋 200 - 36% open · ⏱️ 03.06.2020): +- [GitHub](https://github.com/beetbox/audioread) (👨‍💻 22 · 🔀 94 · 📋 80 - 38% open · ⏱️ 12.08.2022): ``` - git clone https://github.com/worldveil/dejavu + git clone https://github.com/beetbox/audioread ``` -- [PyPi](https://pypi.org/project/PyDejavu): +- [PyPi](https://pypi.org/project/audioread) (📥 1.2M / month): ``` - pip install PyDejavu + pip install audioread + ``` +- [Conda](https://anaconda.org/conda-forge/audioread) (📥 480K · ⏱️ 14.08.2022): + ``` + conda install -c conda-forge audioread ```
-
python-soundfile (🥉16 · ⭐ 430) - SoundFile是基于libsndfile，CFFI等的音频库。BSD-3 +
Muda (🥉17 · ⭐ 210 · 💀) - A library for augmenting annotated audio data. ISC -- [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 23 · 🔀 57 · 📥 2.8K · 📋 160 - 37% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 32 · 📦 15 · 📋 50 - 12% open · ⏱️ 03.05.2021): ``` - git clone https://github.com/bastibe/python-soundfile + git clone https://github.com/bmcfee/muda ``` -- [PyPi](https://pypi.org/project/soundfile): +- [PyPi](https://pypi.org/project/muda) (📥 110 / month): ``` - pip install soundfile + pip install muda ```
-
Julius (🥉15 · ⭐ 240) - 基于PyTorch的快速DSP，用于音频和一维信号。MIT +
Julius (🥉15 · ⭐ 280 · 💤) - Fast PyTorch based DSP for audio and 1D signals. MIT -- [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 12 · 📦 49 · 📋 9 - 11% open · ⏱️ 20.10.2021): +- [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 18 · 📦 120 · ⏱️ 28.01.2022): ``` git clone https://github.com/adefossez/julius ``` -- [PyPi](https://pypi.org/project/julius) (📥 8.1K / month): +- [PyPi](https://pypi.org/project/julius) (📥 24K / month): ``` pip install julius ```

-## 地理Geo处理 +## Geospatial Data -Back to top +Back to top -_用于加载，处理，分析和写入geo地理数据的库，以及用于空间分析，地图可视化和地理编码的库。_ +_Libraries to load, process, analyze, and write geographic data as well as libraries for spatial analysis, map visualization, and geocoding._ -
pydeck (🥇34 · ⭐ 9.3K) - WebGL2支持的地理空间可视化图层。MIT +
pydeck (🥇35 · ⭐ 10K) - WebGL2 powered geospatial visualization layers. MIT -- [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 180 · 🔀 1.6K · 📦 2.1K · 📋 2.3K - 4% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 200 · 🔀 1.7K · 📦 4.5K · 📋 2.5K - 5% open · ⏱️ 24.08.2022): ``` git clone https://github.com/visgl/deck.gl ``` -- [PyPi](https://pypi.org/project/pydeck) (📥 660K / month): +- [PyPi](https://pypi.org/project/pydeck) (📥 790K / month): ``` pip install pydeck ``` -- [Conda](https://anaconda.org/conda-forge/pydeck) (📥 63K · ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/pydeck) (📥 170K · ⏱️ 26.10.2021): ``` conda install -c conda-forge pydeck ``` -- [NPM](https://www.npmjs.com/package/deck.gl) (📥 240K / month): +- [NPM](https://www.npmjs.com/package/deck.gl) (📥 320K / month): ``` npm install deck.gl ```
-
geopy (🥇33 · ⭐ 3.5K) - 适用于Python的地址解析库。MIT +
geopy (🥇32 · ⭐ 3.7K) - Geocoding library for Python. MIT -- [GitHub](https://github.com/geopy/geopy) (👨‍💻 120 · 🔀 540 · 📦 30K · 📋 250 - 9% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/geopy/geopy) (👨‍💻 130 · 🔀 580 · 📦 41K · 📋 260 - 7% open · ⏱️ 07.08.2022): ``` git clone https://github.com/geopy/geopy ``` -- [PyPi](https://pypi.org/project/geopy) (📥 3.8M / month): +- [PyPi](https://pypi.org/project/geopy) (📥 5M / month): ``` pip install geopy ``` -- [Conda](https://anaconda.org/conda-forge/geopy) (📥 630K · ⏱️ 12.07.2021): +- [Conda](https://anaconda.org/conda-forge/geopy) (📥 780K · ⏱️ 12.07.2021): ``` conda install -c conda-forge geopy ```
-
GeoPandas (🥇33 · ⭐ 2.9K) - 用于地理数据的Python工具。BSD-3 - -- [GitHub](https://github.com/geopandas/geopandas) (👨‍💻 160 · 🔀 620 · 📥 1.3K · 📦 11K · 📋 1.2K - 28% open · ⏱️ 11.12.2021): - - ``` - git clone https://github.com/geopandas/geopandas - ``` -- [PyPi](https://pypi.org/project/geopandas) (📥 2M / month): - ``` - pip install geopandas - ``` -- [Conda](https://anaconda.org/conda-forge/geopandas) (📥 1.3M · ⏱️ 01.12.2021): - ``` - conda install -c conda-forge geopandas - ``` -
-
Shapely (🥈31 · ⭐ 2.6K) - 操作和分析几何对象。BSD-3 +
Shapely (🥇31 · ⭐ 2.9K) - Manipulation and analysis of geometric objects. BSD-3 -- [GitHub](https://github.com/shapely/shapely) (👨‍💻 130 · 🔀 440 · 📦 25K · 📋 800 - 17% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/shapely/shapely) (👨‍💻 130 · 🔀 460 · 📥 220 · 📦 32K · 📋 910 - 17% open · ⏱️ 23.08.2022): ``` git clone https://github.com/Toblerity/Shapely ``` -- [PyPi](https://pypi.org/project/shapely) (📥 6.1M / month): +- [PyPi](https://pypi.org/project/shapely) (📥 8M / month): ``` pip install shapely ``` -- [Conda](https://anaconda.org/conda-forge/shapely) (📥 3.1M · ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/shapely) (📥 4.3M · ⏱️ 18.08.2022): ``` conda install -c conda-forge shapely ```
-
Geocoder (🥈30 · ⭐ 1.4K · 💀) - Python Geocoder。MIT +
Geocoder (🥇31 · ⭐ 1.5K · 💀) - Python Geocoder. MIT -- [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 74 · 🔀 260 · 📦 4.2K · 📋 290 - 24% open · ⏱️ 12.10.2018): +- [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 73 · 🔀 260 · 📦 5.3K · 📋 290 - 25% open · ⏱️ 12.10.2018): ``` git clone https://github.com/DenisCarriere/geocoder ``` -- [PyPi](https://pypi.org/project/geocoder) (📥 2.1M / month): +- [PyPi](https://pypi.org/project/geocoder) (📥 580K / month): ``` pip install geocoder ``` -- [Conda](https://anaconda.org/conda-forge/geocoder) (📥 95K · ⏱️ 27.06.2019): +- [Conda](https://anaconda.org/conda-forge/geocoder) (📥 110K · ⏱️ 27.06.2019): ``` conda install -c conda-forge geocoder ```
-
folium (🥈29 · ⭐ 5.5K) - Leaflet.js地图的Python数据。MIT +
GeoPandas (🥈30 · ⭐ 3.3K) - Python tools for geographic data. BSD-3 -- [GitHub](https://github.com/python-visualization/folium) (👨‍💻 120 · 🔀 2K · 📦 13K · 📋 890 - 19% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/geopandas/geopandas) (👨‍💻 180 · 🔀 700 · 📥 1.6K · 📦 15K · 📋 1.3K - 26% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/python-visualization/folium + git clone https://github.com/geopandas/geopandas ``` -- [PyPi](https://pypi.org/project/folium) (📥 710K / month): +- [PyPi](https://pypi.org/project/geopandas) (📥 2.9M / month): ``` - pip install folium + pip install geopandas ``` -- [Conda](https://anaconda.org/conda-forge/folium) (📥 480K · ⏱️ 03.12.2021): +- [Conda](https://anaconda.org/conda-forge/geopandas) (📥 1.9M · ⏱️ 24.07.2022): ``` - conda install -c conda-forge folium + conda install -c conda-forge geopandas ```
-
Rasterio (🥈29 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed +
ipyleaflet (🥈30 · ⭐ 1.3K) - A Jupyter - Leaflet.js bridge. MIT -- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 80 · 🔀 320 · 📦 2.6K · 📋 500 - 36% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/mapbox/rasterio + git clone https://github.com/jupyter-widgets/ipyleaflet ``` -- [PyPi](https://pypi.org/project/rasterio) (📥 720K / month): +- [PyPi](https://pypi.org/project/ipyleaflet) (📥 110K / month): ``` - pip install rasterio + pip install ipyleaflet ``` -- [Conda](https://anaconda.org/conda-forge/rasterio) (📥 1.4M · ⏱️ 03.12.2021): +- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (📥 870K · ⏱️ 23.08.2022): ``` - conda install -c conda-forge rasterio + conda install -c conda-forge ipyleaflet + ``` +- [NPM](https://www.npmjs.com/package/jupyter-leaflet) (📥 50K / month): + ``` + npm install jupyter-leaflet ```
-
ipyleaflet (🥈29 · ⭐ 1.2K) - Jupyter-Leaflet.js桥。MIT +
Fiona (🥈30 · ⭐ 940) - Fiona reads and writes geographic data files. BSD-3 -- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 72 · 🔀 300 · 📦 1.3K · 📋 460 - 38% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 66 · 🔀 170 · 📦 9.4K · 📋 680 - 10% open · ⏱️ 01.03.2022): ``` - git clone https://github.com/jupyter-widgets/ipyleaflet - ``` -- [PyPi](https://pypi.org/project/ipyleaflet) (📥 59K / month): - ``` - pip install ipyleaflet + git clone https://github.com/Toblerity/Fiona ``` -- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (📥 780K · ⏱️ 09.12.2021): +- [PyPi](https://pypi.org/project/fiona) (📥 3.1M / month): ``` - conda install -c conda-forge ipyleaflet + pip install fiona ``` -- [NPM](https://www.npmjs.com/package/jupyter-leaflet) (📥 47K / month): +- [Conda](https://anaconda.org/conda-forge/fiona) (📥 3.3M · ⏱️ 30.05.2022): ``` - npm install jupyter-leaflet + conda install -c conda-forge fiona ```
-
pyproj (🥈29 · ⭐ 690) - 与PROJ的Python界面（图形投影和坐标。MIT +
pyproj (🥈29 · ⭐ 780) - Python interface to PROJ (cartographic projections and coordinate.. MIT -- [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 44 · 🔀 170 · 📦 12K · 📋 460 - 1% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 52 · 🔀 180 · 📦 16K · 📋 500 - 1% open · ⏱️ 26.08.2022): ``` git clone https://github.com/pyproj4/pyproj ``` -- [PyPi](https://pypi.org/project/pyproj) (📥 3.9M / month): +- [PyPi](https://pypi.org/project/pyproj) (📥 5M / month): ``` pip install pyproj ``` -- [Conda](https://anaconda.org/conda-forge/pyproj) (📥 2.8M · ⏱️ 18.11.2021): +- [Conda](https://anaconda.org/conda-forge/pyproj) (📥 4M · ⏱️ 17.06.2022): ``` conda install -c conda-forge pyproj ```
-
Cartopy (🥉28 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed +
folium (🥈28 · ⭐ 5.9K) - Python Data. Leaflet.js Maps. MIT -- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/python-visualization/folium) (👨‍💻 130 · 🔀 2.1K · 📦 18K · 📋 940 - 22% open · ⏱️ 06.05.2022): ``` - git clone https://github.com/mapbox/rasterio + git clone https://github.com/python-visualization/folium ``` -- [PyPi](https://pypi.org/project/Cartopy) (📥 130K / month): +- [PyPi](https://pypi.org/project/folium) (📥 820K / month): ``` - pip install Cartopy + pip install folium ``` -- [Conda](https://anaconda.org/conda-forge/cartopy) (📥 1.9M · ⏱️ 20.11.2021): +- [Conda](https://anaconda.org/conda-forge/folium) (📥 1.1M · ⏱️ 03.12.2021): ``` - conda install -c conda-forge cartopy + conda install -c conda-forge folium ```
-
Fiona (🥉27 · ⭐ 870) - Fiona读写地理数据文件。❗Unlicensed +
Rasterio (🥉27 · ⭐ 1.8K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed -- [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 65 · 🔀 170 · 📦 7.3K · 📋 640 - 11% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 130 · 🔀 470 · 📥 760 · 📦 5.4K · 📋 1.6K - 8% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/Toblerity/Fiona + git clone https://github.com/mapbox/rasterio ``` -- [PyPi](https://pypi.org/project/fiona) (📥 2.3M / month): +- [PyPi](https://pypi.org/project/rasterio) (📥 600K / month): ``` - pip install fiona + pip install rasterio ``` -- [Conda](https://anaconda.org/conda-forge/fiona) (📥 2.4M · ⏱️ 01.12.2021): +- [Conda](https://anaconda.org/conda-forge/rasterio) (📥 1.7M · ⏱️ 19.08.2022): ``` - conda install -c conda-forge fiona + conda install -c conda-forge rasterio ```
-
geojson (🥉27 · ⭐ 680) - GeoJSON的Python接口。BSD-3 +
geojson (🥉27 · ⭐ 740) - Python bindings and utilities for GeoJSON. BSD-3 -- [GitHub](https://github.com/jazzband/geojson) (👨‍💻 45 · 🔀 85 · 📦 8.2K · 📋 77 - 24% open · ⏱️ 11.11.2021): +- [GitHub](https://github.com/jazzband/geojson) (👨‍💻 48 · 🔀 93 · 📦 10K · 📋 85 - 25% open · ⏱️ 07.05.2022): ``` git clone https://github.com/jazzband/geojson ``` -- [PyPi](https://pypi.org/project/geojson) (📥 690K / month): +- [PyPi](https://pypi.org/project/geojson) (📥 780K / month): ``` pip install geojson ``` -- [Conda](https://anaconda.org/conda-forge/geojson) (📥 460K · ⏱️ 11.08.2019): +- [Conda](https://anaconda.org/conda-forge/geojson) (📥 560K · ⏱️ 11.08.2019): ``` conda install -c conda-forge geojson ```
-
ArcGIS API (🥉24 · ⭐ 1.2K) - ArcGIS API for Python的文档和示例。Apache-2 +
Cartopy (🥉26 · ⭐ 1.8K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed + +- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 130 · 🔀 470 · 📥 760 · 📦 5.4K · 📋 1.6K - 8% open · ⏱️ 18.08.2022): + + ``` + git clone https://github.com/mapbox/rasterio + ``` +- [PyPi](https://pypi.org/project/Cartopy) (📥 120K / month): + ``` + pip install Cartopy + ``` +- [Conda](https://anaconda.org/conda-forge/cartopy) (📥 2.3M · ⏱️ 25.08.2022): + ``` + conda install -c conda-forge cartopy + ``` +
+
GeoViews (🥉25 · ⭐ 430) - Simple, concise geographical visualization in Python. BSD-3 + +- [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 28 · 🔀 66 · 📦 470 · 📋 300 - 34% open · ⏱️ 24.08.2022): + + ``` + git clone https://github.com/holoviz/geoviews + ``` +- [PyPi](https://pypi.org/project/geoviews) (📥 7.7K / month): + ``` + pip install geoviews + ``` +- [Conda](https://anaconda.org/conda-forge/geoviews) (📥 120K · ⏱️ 08.03.2022): + ``` + conda install -c conda-forge geoviews + ``` +
+
ArcGIS API (🥉24 · ⭐ 1.4K) - Documentation and samples for ArcGIS API for Python. Apache-2 -- [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 73 · 🔀 820 · 📥 1K · 📋 380 - 24% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 81 · 🔀 910 · 📥 5.2K · 📋 470 - 8% open · ⏱️ 17.08.2022): ``` git clone https://github.com/Esri/arcgis-python-api ``` -- [PyPi](https://pypi.org/project/arcgis) (📥 57K / month): +- [PyPi](https://pypi.org/project/arcgis) (📥 45K / month): ``` pip install arcgis ``` -- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (📥 5.4K · ⭐ 33 · ⏱️ 05.10.2021): +- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (📥 7.2K · ⭐ 35 · ⏱️ 17.06.2022): ``` docker pull esridocker/arcgis-api-python-notebook ```
-
PySAL (🥉23 · ⭐ 950) - PySAL：Python空间分析库元包。BSD-3 +
PySAL (🥉23 · ⭐ 1.1K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 -- [GitHub](https://github.com/pysal/pysal) (👨‍💻 73 · 🔀 250 · 📋 600 - 1% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/pysal/pysal) (👨‍💻 77 · 🔀 260 · 📋 610 - 1% open · ⏱️ 23.07.2022): ``` git clone https://github.com/pysal/pysal ``` -- [PyPi](https://pypi.org/project/pysal) (📥 22K / month): +- [PyPi](https://pypi.org/project/pysal) (📥 30K / month): ``` pip install pysal ``` -- [Conda](https://anaconda.org/conda-forge/pysal) (📥 430K · ⏱️ 02.08.2021): +- [Conda](https://anaconda.org/conda-forge/pysal) (📥 450K · ⏱️ 01.08.2022): ``` conda install -c conda-forge pysal ```
-
Sentinelsat (🥉23 · ⭐ 700) - 搜索和下载哥白尼前哨卫星图像。❗️GPL-3.0 +
Sentinelsat (🥉22 · ⭐ 790) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 -- [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 42 · 🔀 190 · 📥 230 · 📦 260 · 📋 310 - 2% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 42 · 🔀 200 · 📥 230 · 📦 350 · 📋 330 - 2% open · ⏱️ 01.08.2022): ``` git clone https://github.com/sentinelsat/sentinelsat ``` -- [PyPi](https://pypi.org/project/sentinelsat) (📥 23K / month): +- [PyPi](https://pypi.org/project/sentinelsat) (📥 13K / month): ``` pip install sentinelsat ```
-
Satpy (🥉21 · ⭐ 780) - 用于地球观测卫星数据处理的Python软件包。❗️GPL-3.0 +
Mapbox GL (🥉22 · ⭐ 620 · 💀) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT -- [GitHub](https://github.com/pytroll/satpy) (👨‍💻 120 · 🔀 220 · 📦 54 · 📋 700 - 40% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 21 · 🔀 130 · 📦 140 · 📋 99 - 32% open · ⏱️ 19.04.2021): ``` - git clone https://github.com/pytroll/satpy - ``` -- [PyPi](https://pypi.org/project/satpy) (📥 1.7K / month): - ``` - pip install satpy + git clone https://github.com/mapbox/mapboxgl-jupyter ``` -- [Conda](https://anaconda.org/conda-forge/satpy) (📥 79K · ⏱️ 11.12.2021): +- [PyPi](https://pypi.org/project/mapboxgl) (📥 11K / month): ``` - conda install -c conda-forge satpy + pip install mapboxgl ```
-
GeoViews (🥉21 · ⭐ 380) - 使用Python进行简单，简洁的地理可视化。BSD-3 +
Satpy (🥉21 · ⭐ 850) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 -- [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 25 · 🔀 65 · 📋 290 - 35% open · ⏱️ 01.12.2021): +- [GitHub](https://github.com/pytroll/satpy) (👨‍💻 130 · 🔀 240 · 📦 72 · 📋 790 - 38% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/holoviz/geoviews + git clone https://github.com/pytroll/satpy ``` -- [PyPi](https://pypi.org/project/geoviews) (📥 8.1K / month): +- [PyPi](https://pypi.org/project/satpy) (📥 1.1K / month): ``` - pip install geoviews + pip install satpy ``` -- [Conda](https://anaconda.org/conda-forge/geoviews) (📥 88K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/satpy) (📥 100K · ⏱️ 15.08.2022): ``` - conda install -c conda-forge geoviews + conda install -c conda-forge satpy ```
-
EarthPy (🥉21 · ⭐ 310) - 使用开放源代码处理空间数据。BSD-3 +
EarthPy (🥉21 · ⭐ 380 · 💤) - A package built to support working with spatial data using open.. BSD-3 -- [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 120 · 📦 110 · 📋 220 - 7% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 140 · 📦 160 · 📋 230 - 8% open · ⏱️ 20.12.2021): ``` git clone https://github.com/earthlab/earthpy ``` -- [PyPi](https://pypi.org/project/earthpy) (📥 4.5K / month): +- [PyPi](https://pypi.org/project/earthpy) (📥 8.4K / month): ``` pip install earthpy ``` -- [Conda](https://anaconda.org/conda-forge/earthpy) (📥 40K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/earthpy) (📥 49K · ⏱️ 04.10.2021): ``` conda install -c conda-forge earthpy ```
-
geoplotlib (🥉20 · ⭐ 940 · 💀) - python工具箱，用于可视化地理数据和制作地图。MIT +
geoplotlib (🥉19 · ⭐ 970 · 💀) - python toolbox for visualizing geographical data and making maps. MIT -- [GitHub](https://github.com/andrea-cuttone/geoplotlib) (👨‍💻 8 · 🔀 150 · 📦 120 · 📋 43 - 58% open · ⏱️ 06.05.2019): +- [GitHub](https://github.com/andrea-cuttone/geoplotlib) (👨‍💻 8 · 🔀 160 · 📦 150 · 📋 44 - 56% open · ⏱️ 06.05.2019): ``` git clone https://github.com/andrea-cuttone/geoplotlib ``` -- [PyPi](https://pypi.org/project/geoplotlib) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/geoplotlib) (📥 880 / month): ``` pip install geoplotlib ```
-
Mapbox GL (🥉19 · ⭐ 590 · 💤) - 使用Mapbox GL JS可视化Python Jupyter笔记本中的数据。MIT +
gmaps (🥉18 · ⭐ 740 · 💀) - Google maps for Jupyter notebooks. BSD-3 -- [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 21 · 🔀 120 · 📦 120 · 📋 98 - 31% open · ⏱️ 19.04.2021): +- [GitHub](https://github.com/pbugnion/gmaps) (👨‍💻 16 · 🔀 140 · 📦 1 · 📋 200 - 32% open · ⏱️ 22.07.2019): ``` - git clone https://github.com/mapbox/mapboxgl-jupyter - ``` -- [PyPi](https://pypi.org/project/mapboxgl): - ``` - pip install mapboxgl + git clone https://github.com/pbugnion/gmaps ``` -
-
pymap3d (🥉18 · ⭐ 220) - 纯Python实现（Numpy可选）的3D坐标转换。BSD-2 - -- [GitHub](https://github.com/geospace-code/pymap3d) (👨‍💻 10 · 🔀 58 · 📋 32 - 6% open · ⏱️ 28.11.2021): - +- [PyPi](https://pypi.org/project/gmaps) (📥 9K / month): ``` - git clone https://github.com/geospace-code/pymap3d + pip install gmaps ``` -- [PyPi](https://pypi.org/project/pymap3d) (📥 43K / month): +- [Conda](https://anaconda.org/conda-forge/gmaps) (📥 270K · ⏱️ 02.08.2019): ``` - pip install pymap3d + conda install -c conda-forge gmaps ``` -- [Conda](https://anaconda.org/conda-forge/pymap3d) (📥 16K · ⏱️ 19.10.2021): +- [NPM](https://www.npmjs.com/package/jupyter-gmaps) (📥 1.8K / month): ``` - conda install -c conda-forge pymap3d + npm install jupyter-gmaps ```
-
gmaps (🥉17 · ⭐ 730 · 💀) - Google为Jupyter笔记本电脑映射。BSD-3 +
pymap3d (🥉18 · ⭐ 270) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 -- [GitHub](https://github.com/pbugnion/gmaps) (👨‍💻 16 · 🔀 140 · 📦 1 · 📋 200 - 31% open · ⏱️ 22.07.2019): +- [GitHub](https://github.com/geospace-code/pymap3d) (👨‍💻 11 · 🔀 68 · 📋 38 - 2% open · ⏱️ 03.07.2022): ``` - git clone https://github.com/pbugnion/gmaps - ``` -- [PyPi](https://pypi.org/project/gmaps): - ``` - pip install gmaps + git clone https://github.com/geospace-code/pymap3d ``` -- [Conda](https://anaconda.org/conda-forge/gmaps) (📥 250K · ⏱️ 02.08.2019): +- [PyPi](https://pypi.org/project/pymap3d) (📥 50K / month): ``` - conda install -c conda-forge gmaps + pip install pymap3d ``` -- [NPM](https://www.npmjs.com/package/jupyter-gmaps) (📥 1.9K / month): +- [Conda](https://anaconda.org/conda-forge/pymap3d) (📥 29K · ⏱️ 04.07.2022): ``` - npm install jupyter-gmaps + conda install -c conda-forge pymap3d ```

-## 金融数据处理 +## Financial Data -Back to top +Back to top -_用于算法股票/加密交易，风险分析，回测，技术分析以及其他金融数据任务的库。_ +_Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data._ -
zipline (🥇29 · ⭐ 15K · 💀) - Zipline，一个Pythonic算法交易库。Apache-2 +
zipline (🥇30 · ⭐ 15K · 💀) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 -- [GitHub](https://github.com/quantopian/zipline) (👨‍💻 150 · 🔀 3.9K · 📦 800 · 📋 960 - 32% open · ⏱️ 14.10.2020): +- [GitHub](https://github.com/quantopian/zipline) (👨‍💻 160 · 🔀 4K · 📦 880 · 📋 970 - 32% open · ⏱️ 14.10.2020): ``` git clone https://github.com/quantopian/zipline ``` -- [PyPi](https://pypi.org/project/zipline) (📥 4.3K / month): +- [PyPi](https://pypi.org/project/zipline) (📥 3.1K / month): ``` pip install zipline ```
-
yfinance (🥇29 · ⭐ 6.1K) - Yahoo! 金融市场数据下载器（+更快的Pandas数据加载读取器）。Apache-2 +
yfinance (🥇30 · ⭐ 7.5K) - Yahoo! Finance market data downloader (+faster Pandas Datareader). Apache-2 -- [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 49 · 🔀 1.4K · 📦 8.4K · 📋 700 - 54% open · ⏱️ 21.11.2021): +- [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 60 · 🔀 1.6K · 📦 13K · 📋 810 - 56% open · ⏱️ 11.07.2022): ``` git clone https://github.com/ranaroussi/yfinance ``` -- [PyPi](https://pypi.org/project/yfinance) (📥 320K / month): +- [PyPi](https://pypi.org/project/yfinance) (📥 500K / month): ``` pip install yfinance ``` -- [Conda](https://anaconda.org/ranaroussi/yfinance) (📥 20K · ⏱️ 10.07.2021): +- [Conda](https://anaconda.org/ranaroussi/yfinance) (📥 51K · ⏱️ 10.07.2021): ``` conda install -c ranaroussi yfinance ```
-
pyfolio (🥇26 · ⭐ 4.2K · 💀) - Python中的投资组合和风险分析。Apache-2 +
backtrader (🥇27 · ⭐ 9.2K · 💀) - Python Backtesting library for trading strategies. ❗️GPL-3.0 + +- [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.7K · 📦 1.1K · ⏱️ 17.07.2021): + + ``` + git clone https://github.com/mementum/backtrader + ``` +- [PyPi](https://pypi.org/project/backtrader) (📥 13K / month): + ``` + pip install backtrader + ``` +
+
pyfolio (🥈26 · ⭐ 4.5K · 💀) - Portfolio and risk analytics in Python. Apache-2 -- [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 55 · 🔀 1.3K · 📦 340 · 📋 400 - 33% open · ⏱️ 15.07.2020): +- [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 56 · 🔀 1.4K · 📦 450 · 📋 400 - 34% open · ⏱️ 15.07.2020): ``` git clone https://github.com/quantopian/pyfolio ``` -- [PyPi](https://pypi.org/project/pyfolio) (📥 5.6K / month): +- [PyPi](https://pypi.org/project/pyfolio) (📥 6.5K / month): ``` pip install pyfolio ``` -- [Conda](https://anaconda.org/conda-forge/pyfolio) (📥 7.8K · ⏱️ 16.05.2020): +- [Conda](https://anaconda.org/conda-forge/pyfolio) (📥 9.3K · ⏱️ 16.05.2020): ``` conda install -c conda-forge pyfolio ```
-
backtrader (🥈25 · ⭐ 7.8K) - 用于交易策略的Python Backtesting库。❗️GPL-3.0 +
ta (🥈26 · ⭐ 3.2K) - Technical Analysis Library using Pandas and Numpy. MIT -- [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.3K · 📦 840 · ⏱️ 17.07.2021): +- [GitHub](https://github.com/bukosabino/ta) (👨‍💻 29 · 🔀 720 · 📦 1.4K · 📋 200 - 51% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/mementum/backtrader + git clone https://github.com/bukosabino/ta ``` -- [PyPi](https://pypi.org/project/backtrader) (📥 15K / month): +- [PyPi](https://pypi.org/project/ta) (📥 71K / month): ``` - pip install backtrader + pip install ta ```
-
Alphalens (🥈25 · ⭐ 2.1K · 💀) - 股票因子预测分析。Apache-2 +
ffn (🥈26 · ⭐ 1.3K) - ffn - a financial function library for Python. MIT -- [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 790 · 📦 470 · 📋 180 - 20% open · ⏱️ 27.04.2020): +- [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 28 · 🔀 220 · 📦 220 · 📋 100 - 20% open · ⏱️ 01.07.2022): ``` - git clone https://github.com/quantopian/alphalens - ``` -- [PyPi](https://pypi.org/project/alphalens) (📥 2.3K / month): - ``` - pip install alphalens + git clone https://github.com/pmorissette/ffn ``` -- [Conda](https://anaconda.org/conda-forge/alphalens) (📥 14K · ⏱️ 16.05.2020): +- [PyPi](https://pypi.org/project/ffn) (📥 37K / month): ``` - conda install -c conda-forge alphalens + pip install ffn ```
-
bt (🥈24 · ⭐ 1.2K · 💤) - bt-Python的灵活回测。MIT +
Alphalens (🥈25 · ⭐ 2.4K · 💀) - Performance analysis of predictive (alpha) stock factors. Apache-2 -- [GitHub](https://github.com/pmorissette/bt) (👨‍💻 24 · 🔀 290 · 📦 88 · 📋 270 - 17% open · ⏱️ 15.05.2021): +- [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 880 · 📦 570 · 📋 180 - 20% open · ⏱️ 27.04.2020): ``` - git clone https://github.com/pmorissette/bt + git clone https://github.com/quantopian/alphalens ``` -- [PyPi](https://pypi.org/project/bt) (📥 10K / month): +- [PyPi](https://pypi.org/project/alphalens) (📥 13K / month): ``` - pip install bt + pip install alphalens + ``` +- [Conda](https://anaconda.org/conda-forge/alphalens) (📥 16K · ⏱️ 16.05.2020): + ``` + conda install -c conda-forge alphalens ```
-
empyrical (🥈24 · ⭐ 870 · 💀) - 常见的金融风险和绩效指标。Apache-2 +
empyrical (🥈25 · ⭐ 970 · 💀) - Common financial risk and performance metrics. Used by zipline.. Apache-2 -- [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 270 · 📦 760 · 📋 49 - 46% open · ⏱️ 14.10.2020): +- [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 300 · 📦 940 · 📋 49 - 46% open · ⏱️ 14.10.2020): ``` git clone https://github.com/quantopian/empyrical ``` -- [PyPi](https://pypi.org/project/empyrical) (📥 33K / month): +- [PyPi](https://pypi.org/project/empyrical) (📥 28K / month): ``` pip install empyrical ``` -- [Conda](https://anaconda.org/conda-forge/empyrical) (📥 14K · ⏱️ 14.10.2020): +- [Conda](https://anaconda.org/conda-forge/empyrical) (📥 18K · ⏱️ 14.10.2020): ``` conda install -c conda-forge empyrical ```
-
arch (🥈24 · ⭐ 840) - Python中的ARCH模型。❗️NCSA +
Qlib (🥈24 · ⭐ 9.5K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT -- [GitHub](https://github.com/bashtage/arch) (👨‍💻 30 · 🔀 190 · 📦 420 · 📋 160 - 7% open · ⏱️ 19.11.2021): +- [GitHub](https://github.com/microsoft/qlib) (👨‍💻 100 · 🔀 1.7K · 📥 330 · 📦 27 · 📋 600 - 27% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/bashtage/arch + git clone https://github.com/microsoft/qlib ``` -- [PyPi](https://pypi.org/project/arch) (📥 180K / month): +- [PyPi](https://pypi.org/project/pyqlib) (📥 2.4K / month): ``` - pip install arch + pip install pyqlib ```
-
ffn (🥈23 · ⭐ 1K · 💤) - ffn-Python的金融函数库。MIT +
bt (🥈24 · ⭐ 1.5K) - bt - flexible backtesting for Python. MIT -- [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 26 · 🔀 190 · 📦 160 · 📋 96 - 16% open · ⏱️ 24.04.2021): +- [GitHub](https://github.com/pmorissette/bt) (👨‍💻 27 · 🔀 320 · 📦 130 · 📋 300 - 20% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/pmorissette/ffn + git clone https://github.com/pmorissette/bt ``` -- [PyPi](https://pypi.org/project/ffn) (📥 42K / month): +- [PyPi](https://pypi.org/project/bt) (📥 5.5K / month): ``` - pip install ffn + pip install bt ```
-
Qlib (🥉22 · ⭐ 7.6K) - Qlib是一个面向AI的量化投资平台。MIT +
FinTA (🥉23 · ⭐ 1.7K) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 -- [GitHub](https://github.com/microsoft/qlib) (👨‍💻 72 · 🔀 1.2K · 📥 270 · 📦 8 · 📋 370 - 33% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/peerchemist/finta) (👨‍💻 28 · 🔀 550 · 📦 260 · 📋 85 - 24% open · ⏱️ 24.07.2022): ``` - git clone https://github.com/microsoft/qlib + git clone https://github.com/peerchemist/finta ``` -- [PyPi](https://pypi.org/project/pyqlib) (📥 3.2K / month): +- [PyPi](https://pypi.org/project/finta) (📥 7.7K / month): ``` - pip install pyqlib + pip install finta + ``` +
+
arch (🥉23 · ⭐ 970) - ARCH models in Python. ❗Unlicensed + +- [GitHub](https://github.com/bashtage/arch) (👨‍💻 31 · 🔀 210 · 📦 620 · 📋 180 - 8% open · ⏱️ 17.08.2022): + + ``` + git clone https://github.com/bashtage/arch + ``` +- [PyPi](https://pypi.org/project/arch) (📥 320K / month): + ``` + pip install arch ```
-
TensorTrade (🥉22 · ⭐ 3.6K) - 一个开放源代码的强化学习框架。Apache-2 +
TensorTrade (🥉22 · ⭐ 3.9K) - An open source reinforcement learning framework for training,.. Apache-2 -- [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 57 · 🔀 820 · 📦 27 · 📋 190 - 11% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 61 · 🔀 890 · 📦 36 · 📋 230 - 16% open · ⏱️ 23.08.2022): ``` git clone https://github.com/tensortrade-org/tensortrade ``` -- [PyPi](https://pypi.org/project/tensortrade) (📥 1K / month): +- [PyPi](https://pypi.org/project/tensortrade) (📥 490 / month): ``` pip install tensortrade ```
-
PyAlgoTrade (🥉22 · ⭐ 3.6K · 💀) - Python算法交易库。Apache-2 +
PyAlgoTrade (🥉22 · ⭐ 3.7K · 💀) - Python Algorithmic Trading Library. Apache-2 -- [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 98 · 📋 120 - 30% open · ⏱️ 21.08.2018): +- [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 110 · 📋 120 - 31% open · ⏱️ 21.08.2018): ``` git clone https://github.com/gbeced/pyalgotrade ``` -- [PyPi](https://pypi.org/project/pyalgotrade) (📥 980 / month): +- [PyPi](https://pypi.org/project/pyalgotrade) (📥 480 / month): ``` pip install pyalgotrade ```
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Alpha Vantage (🥉22 · ⭐ 3.6K) - 用于金融数据的Alpha Vantage API的python包装器。MIT +
Alpha Vantage (🥉21 · ⭐ 3.7K · 💀) - A python wrapper for Alpha Vantage API for financial data. MIT -- [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 630 · 📋 250 - 1% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 640 · 📋 260 - 2% open · ⏱️ 14.06.2021): ``` git clone https://github.com/RomelTorres/alpha_vantage ``` -- [PyPi](https://pypi.org/project/alpha_vantage) (📥 23K / month): +- [PyPi](https://pypi.org/project/alpha_vantage) (📥 17K / month): ``` pip install alpha_vantage ```
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FinTA (🥉22 · ⭐ 1.4K) - 基于pandas实现的通用金融技术指标。❗️LGPL-3.0 +
Enigma Catalyst (🥉21 · ⭐ 2.4K · 💤) - An Algorithmic Trading Library for Crypto-Assets in.. Apache-2 -- [GitHub](https://github.com/peerchemist/finta) (👨‍💻 27 · 🔀 440 · 📦 140 · 📋 80 - 21% open · ⏱️ 19.10.2021): +- [GitHub](https://github.com/scrtlabs/catalyst) (👨‍💻 150 · 🔀 700 · 📦 25 · 📋 480 - 25% open · ⏱️ 22.09.2021): ``` - git clone https://github.com/peerchemist/finta + git clone https://github.com/enigmampc/catalyst ``` -- [PyPi](https://pypi.org/project/finta) (📥 7.2K / month): +- [PyPi](https://pypi.org/project/enigma-catalyst) (📥 430 / month): ``` - pip install finta + pip install enigma-catalyst ```
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ta (🥉21 · ⭐ 2.6K) - 使用Pandas和Numpy的技术分析库。MIT +
tf-quant-finance (🥉20 · ⭐ 3.2K) - High-performance TensorFlow library for quantitative.. Apache-2 -- [GitHub](https://github.com/bukosabino/ta) (👨‍💻 24 · 🔀 630 · 📦 900 · 📋 180 - 51% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 41 · 🔀 420 · 📋 40 - 37% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/bukosabino/ta + git clone https://github.com/google/tf-quant-finance ``` -- [PyPi](https://pypi.org/project/ta): +- [PyPi](https://pypi.org/project/tf-quant-finance) (📥 4.8K / month): ``` - pip install ta + pip install tf-quant-finance ```
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IB-insync (🥉21 · ⭐ 1.6K) - 用于Interactive Brokers API的Python同步/异步框架。BSD-2 +
IB-insync (🥉20 · ⭐ 1.9K) - Python sync/async framework for Interactive Brokers API. BSD-2 -- [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 29 · 🔀 460 · 📋 360 - 2% open · ⏱️ 28.11.2021): +- [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 31 · 🔀 490 · 📋 420 - 1% open · ⏱️ 23.08.2022): ``` git clone https://github.com/erdewit/ib_insync ``` -- [PyPi](https://pypi.org/project/ib_insync) (📥 8.7K / month): +- [PyPi](https://pypi.org/project/ib_insync) (📥 7.4K / month): ``` pip install ib_insync ``` -- [Conda](https://anaconda.org/conda-forge/ib-insync) (📥 14K · ⏱️ 29.11.2021): +- [Conda](https://anaconda.org/conda-forge/ib-insync) (📥 20K · ⏱️ 29.11.2021): ``` conda install -c conda-forge ib-insync ```
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finmarketpy (🥉20 · ⭐ 2.8K) - Python库，用于回测交易策略和分析。Apache-2 - -- [GitHub](https://github.com/cuemacro/finmarketpy) (👨‍💻 14 · 🔀 420 · 📥 40 · 📦 4 · 📋 26 - 88% open · ⏱️ 07.10.2021): - - ``` - git clone https://github.com/cuemacro/finmarketpy - ``` -- [PyPi](https://pypi.org/project/finmarketpy) (📥 100 / month): - ``` - pip install finmarketpy - ``` -
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Enigma Catalyst (🥉20 · ⭐ 2.3K) - Python中加密资产的算法交易库。Apache-2 - -- [GitHub](https://github.com/scrtlabs/catalyst) (👨‍💻 150 · 🔀 670 · 📦 23 · 📋 480 - 25% open · ⏱️ 22.09.2021): - - ``` - git clone https://github.com/enigmampc/catalyst - ``` -- [PyPi](https://pypi.org/project/enigma-catalyst) (📥 970 / month): - ``` - pip install enigma-catalyst - ``` -
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Crypto Signals (🥉19 · ⭐ 3.7K) - CryptoSignal量化交易技术。MIT +
Crypto Signals (🥉19 · ⭐ 4.1K) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT -- [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 950 · 📋 250 - 19% open · ⏱️ 28.06.2021): +- [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 1.1K · 📋 260 - 20% open · ⏱️ 09.08.2022): ``` git clone https://github.com/CryptoSignal/crypto-signal @@ -4531,45 +4531,45 @@ _用于算法股票/加密交易，风险分析，回测，技术分析以及其 docker pull shadowreaver/crypto-signal ```
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tf-quant-finance (🥉19 · ⭐ 2.9K) - 用于量化投资的高性能TensorFlow库。Apache-2 +
stockstats (🥉19 · ⭐ 1K · 💤) - Supply a wrapper ``StockDataFrame`` based on the.. ❗Unlicensed -- [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 36 · 🔀 380 · 📋 32 - 43% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 260 · 📦 530 · 📋 87 - 11% open · ⏱️ 07.01.2022): ``` - git clone https://github.com/google/tf-quant-finance + git clone https://github.com/jealous/stockstats ``` -- [PyPi](https://pypi.org/project/tf-quant-finance) (📥 890 / month): +- [PyPi](https://pypi.org/project/stockstats) (📥 6.2K / month): ``` - pip install tf-quant-finance + pip install stockstats ```
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Backtesting.py (🥉18 · ⭐ 2K) - 回溯Python中的交易策略。❗️AGPL-3.0 +
finmarketpy (🥉18 · ⭐ 3K) - Python library for backtesting trading strategies & analyzing.. Apache-2 -- [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 410 · 📋 270 - 14% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/cuemacro/finmarketpy) (👨‍💻 14 · 🔀 440 · 📥 40 · 📦 5 · 📋 26 - 88% open · ⏱️ 05.04.2022): ``` - git clone https://github.com/kernc/backtesting.py + git clone https://github.com/cuemacro/finmarketpy ``` -- [PyPi](https://pypi.org/project/backtesting) (📥 13K / month): +- [PyPi](https://pypi.org/project/finmarketpy) (📥 100 / month): ``` - pip install backtesting + pip install finmarketpy ```
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stockstats (🥉17 · ⭐ 910) - 提供StockDataFrame包装器BSD-3 +
Backtesting.py (🥉17 · ⭐ 2.8K) - Backtest trading strategies in Python. ❗️AGPL-3.0 -- [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 240 · 📦 360 · 📋 72 - 41% open · ⏱️ 20.11.2021): +- [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 550 · 📋 330 - 17% open · ⏱️ 27.03.2022): ``` - git clone https://github.com/jealous/stockstats + git clone https://github.com/kernc/backtesting.py ``` -- [PyPi](https://pypi.org/project/stockstats): +- [PyPi](https://pypi.org/project/backtesting) (📥 7.4K / month): ``` - pip install stockstats + pip install backtesting ```
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surpriver (🥉12 · ⭐ 1.4K · 💀) - 使用机器学习在股票大波动之前找到它。❗️GPL-3.0 +
surpriver (🥉12 · ⭐ 1.5K · 💀) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 -- [GitHub](https://github.com/tradytics/surpriver) (👨‍💻 6 · 🔀 250 · 📋 15 - 60% open · ⏱️ 21.09.2020): +- [GitHub](https://github.com/tradytics/surpriver) (👨‍💻 6 · 🔀 280 · 📋 15 - 60% open · ⏱️ 21.09.2020): ``` git clone https://github.com/tradytics/surpriver @@ -4577,455 +4577,467 @@ _用于算法股票/加密交易，风险分析，回测，技术分析以及其

-## 时间序列 +## Time Series Data + +Back to top + +_Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._ -Back to top +
pmdarima (🥇30 · ⭐ 1.2K · 📈) - A statistical library designed to fill the void in Python's time.. MIT -_用于按时间序列和顺序数据进行预测，异常检测，特征提取和机器学习的库。_ +- [GitHub](https://github.com/alkaline-ml/pmdarima) (👨‍💻 21 · 🔀 210 · 📦 2.5K · 📋 280 - 9% open · ⏱️ 23.08.2022): -
sktime (🥇26 · ⭐ 4.7K) - 具有时间序列的机器学习的统一框架。BSD-3 + ``` + git clone https://github.com/alkaline-ml/pmdarima + ``` +- [PyPi](https://pypi.org/project/pmdarima) (📥 1.5M / month): + ``` + pip install pmdarima + ``` +
+
sktime (🥇27 · ⭐ 5.6K) - A unified framework for machine learning with time series. BSD-3 -- [GitHub](https://github.com/alan-turing-institute/sktime) (👨‍💻 130 · 🔀 700 · 📥 64 · 📦 310 · 📋 780 - 31% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/alan-turing-institute/sktime) (👨‍💻 190 · 🔀 890 · 📥 76 · 📦 560 · 📋 1.3K - 33% open · ⏱️ 25.08.2022): ``` git clone https://github.com/alan-turing-institute/sktime ``` -- [PyPi](https://pypi.org/project/sktime) (📥 140K / month): +- [PyPi](https://pypi.org/project/sktime) (📥 260K / month): ``` pip install sktime ```
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tslearn (🥇26 · ⭐ 1.9K) - 专门用于时间序列数据的机器学习工具包。BSD-2 +
STUMPY (🥈26 · ⭐ 2.4K) - STUMPY is a powerful and scalable Python library for computing a Matrix.. BSD-3 -- [GitHub](https://github.com/tslearn-team/tslearn) (👨‍💻 36 · 🔀 250 · 📦 360 · 📋 250 - 27% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 31 · 🔀 230 · 📦 260 · 📋 340 - 11% open · ⏱️ 04.08.2022): ``` - git clone https://github.com/tslearn-team/tslearn + git clone https://github.com/TDAmeritrade/stumpy + ``` +- [PyPi](https://pypi.org/project/stumpy) (📥 170K / month): + ``` + pip install stumpy ``` -- [PyPi](https://pypi.org/project/tslearn) (📥 120K / month): +- [Conda](https://anaconda.org/conda-forge/stumpy) (📥 48K · ⏱️ 31.03.2022): + ``` + conda install -c conda-forge stumpy + ``` +
+
Prophet (🥈25 · ⭐ 15K) - Tool for producing high quality forecasts for time series data that has.. MIT + +- [GitHub](https://github.com/facebook/prophet) (👨‍💻 150 · 🔀 4.2K · 📥 810 · 📋 1.9K - 13% open · ⏱️ 07.07.2022): + ``` - pip install tslearn + git clone https://github.com/facebook/prophet ``` -- [Conda](https://anaconda.org/conda-forge/tslearn) (📥 240K · ⏱️ 16.08.2021): +- [PyPi](https://pypi.org/project/fbprophet) (📥 1.7M / month): ``` - conda install -c conda-forge tslearn + pip install fbprophet ```
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Darts (🥈24 · ⭐ 3.2K) - 一个易于操作和预测时间序列的python库。Apache-2 +
Darts (🥈25 · ⭐ 4.6K) - A python library for easy manipulation and forecasting of time series. Apache-2 -- [GitHub](https://github.com/unit8co/darts) (👨‍💻 41 · 🔀 280 · 📦 22 · 📋 290 - 36% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/unit8co/darts) (👨‍💻 61 · 🔀 480 · 📦 92 · 📋 600 - 23% open · ⏱️ 25.08.2022): ``` git clone https://github.com/unit8co/darts ``` -- [PyPi](https://pypi.org/project/u8darts) (📥 3.7K / month): +- [PyPi](https://pypi.org/project/u8darts) (📥 6.4K / month): ``` pip install u8darts ``` -- [Docker Hub](https://hub.docker.com/r/unit8/darts) (📥 230 · ⏱️ 28.11.2021): +- [Docker Hub](https://hub.docker.com/r/unit8/darts) (📥 360 · ⏱️ 12.08.2022): ``` docker pull unit8/darts ```
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GluonTS (🥈24 · ⭐ 2.4K) - Python中的概率时间序列建模。Apache-2 +
tslearn (🥈25 · ⭐ 2.2K) - A machine learning toolkit dedicated to time-series data. BSD-2 -- [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 79 · 🔀 480 · 📋 640 - 34% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/tslearn-team/tslearn) (👨‍💻 39 · 🔀 280 · 📦 560 · 📋 280 - 32% open · ⏱️ 17.06.2022): ``` - git clone https://github.com/awslabs/gluon-ts + git clone https://github.com/tslearn-team/tslearn ``` -- [PyPi](https://pypi.org/project/gluonts) (📥 76K / month): +- [PyPi](https://pypi.org/project/tslearn) (📥 100K / month): ``` - pip install gluonts + pip install tslearn + ``` +- [Conda](https://anaconda.org/conda-forge/tslearn) (📥 270K · ⏱️ 15.01.2022): + ``` + conda install -c conda-forge tslearn ```
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Prophet (🥈23 · ⭐ 14K) - 产生具有时间序列数据的高质量预测的工具。MIT +
pytorch-forecasting (🥈25 · ⭐ 2.2K) - Time series forecasting with PyTorch. MIT -- [GitHub](https://github.com/facebook/prophet) (👨‍💻 140 · 🔀 3.9K · 📥 640 · 📋 1.7K - 9% open · ⏱️ 03.10.2021): +- [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 32 · 🔀 350 · 📋 510 - 49% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/facebook/prophet + git clone https://github.com/jdb78/pytorch-forecasting ``` -- [PyPi](https://pypi.org/project/fbprophet) (📥 1.2M / month): +- [PyPi](https://pypi.org/project/pytorch-forecasting) (📥 74K / month): ``` - pip install fbprophet + pip install pytorch-forecasting ```
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tsfresh (🥈23 · ⭐ 6.1K) - 从时间序列中自动提取相关特征。MIT +
tsfresh (🥈23 · ⭐ 6.6K · 💤) - Automatic extraction of relevant features from time series:. MIT -- [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 80 · 🔀 930 · 📋 470 - 8% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 82 · 🔀 1K · 📋 490 - 10% open · ⏱️ 21.12.2021): ``` git clone https://github.com/blue-yonder/tsfresh ``` -- [PyPi](https://pypi.org/project/tsfresh) (📥 260K / month): +- [PyPi](https://pypi.org/project/tsfresh) (📥 420K / month): ``` pip install tsfresh ``` -- [Conda](https://anaconda.org/conda-forge/tsfresh) (📥 71K · ⏱️ 07.03.2021): +- [Conda](https://anaconda.org/conda-forge/tsfresh) (📥 220K · ⏱️ 21.12.2021): ``` conda install -c conda-forge tsfresh ```
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STUMPY (🥈22 · ⭐ 2K) - STUMPY是一个功能强大且可扩展的Python库，用于矩阵计算。BSD-3 +
pyts (🥈23 · ⭐ 1.3K) - A Python package for time series classification. BSD-3 -- [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 26 · 🔀 190 · 📋 270 - 10% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 11 · 🔀 140 · 📦 240 · 📋 64 - 59% open · ⏱️ 16.06.2022): ``` - git clone https://github.com/TDAmeritrade/stumpy - ``` -- [PyPi](https://pypi.org/project/stumpy) (📥 320K / month): - ``` - pip install stumpy - ``` -- [Conda](https://anaconda.org/conda-forge/stumpy) (📥 34K · ⏱️ 15.12.2021): - ``` - conda install -c conda-forge stumpy + git clone https://github.com/johannfaouzi/pyts ``` -
-
pmdarima (🥈22 · ⭐ 1.1K) - 一个统计数据库，旨在填补Python时间序列中的空白。MIT - -- [GitHub](https://github.com/alkaline-ml/pmdarima) (👨‍💻 19 · 🔀 190 · 📦 1.6K · 📋 260 - 7% open · ⏱️ 28.11.2021): - +- [PyPi](https://pypi.org/project/pyts) (📥 140K / month): ``` - git clone https://github.com/alkaline-ml/pmdarima + pip install pyts ``` -- [PyPi](https://pypi.org/project/pmdarima): +- [Conda](https://anaconda.org/conda-forge/pyts) (📥 13K · ⏱️ 31.10.2021): ``` - pip install pmdarima + conda install -c conda-forge pyts ```
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Streamz (🥉21 · ⭐ 1K) - python的实时流处理。❗Unlicensed +
Streamz (🥈23 · ⭐ 1.1K) - Real-time stream processing for python. BSD-3 -- [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 44 · 🔀 130 · 📦 250 · 📋 240 - 38% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 45 · 🔀 140 · 📦 310 · 📋 240 - 39% open · ⏱️ 27.07.2022): ``` git clone https://github.com/python-streamz/streamz ``` -- [PyPi](https://pypi.org/project/streamz) (📥 10K / month): +- [PyPi](https://pypi.org/project/streamz) (📥 12K / month): ``` pip install streamz ``` -- [Conda](https://anaconda.org/conda-forge/streamz) (📥 230K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/streamz) (📥 380K · ⏱️ 28.07.2022): ``` conda install -c conda-forge streamz ```
-
pytorch-forecasting (🥉20 · ⭐ 1.6K) - 使用PyTorch进行时间序列预测。MIT +
GluonTS (🥉22 · ⭐ 2.9K) - Probabilistic time series modeling in Python. Apache-2 -- [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 27 · 🔀 230 · 📋 360 - 36% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 93 · 🔀 580 · 📋 740 - 31% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/jdb78/pytorch-forecasting + git clone https://github.com/awslabs/gluon-ts ``` -- [PyPi](https://pypi.org/project/pytorch-forecasting): +- [PyPi](https://pypi.org/project/gluonts) (📥 140K / month): ``` - pip install pytorch-forecasting + pip install gluonts ```
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pyts (🥉20 · ⭐ 1.1K) - 用于时间序列分类的Python软件包。BSD-3 +
PyFlux (🥉22 · ⭐ 2K · 💀) - Open source time series library for Python. BSD-3 -- [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 10 · 🔀 110 · 📦 160 · 📋 56 - 57% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 220 · 📋 150 - 56% open · ⏱️ 16.12.2018): ``` - git clone https://github.com/johannfaouzi/pyts - ``` -- [PyPi](https://pypi.org/project/pyts): - ``` - pip install pyts + git clone https://github.com/RJT1990/pyflux ``` -- [Conda](https://anaconda.org/conda-forge/pyts) (📥 9.7K · ⏱️ 31.10.2021): +- [PyPi](https://pypi.org/project/pyflux) (📥 150K / month): ``` - conda install -c conda-forge pyts + pip install pyflux ```
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luminol (🥉19 · ⭐ 980 · 💀) - 异常检测和相关库。Apache-2 +
luminol (🥉20 · ⭐ 1K · 💀) - Anomaly Detection and Correlation library. Apache-2 -- [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 190 · 📦 47 · 📋 36 - 66% open · ⏱️ 09.01.2018): +- [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 200 · 📦 66 · 📋 36 - 66% open · ⏱️ 09.01.2018): ``` git clone https://github.com/linkedin/luminol ``` -- [PyPi](https://pypi.org/project/luminol) (📥 41K / month): +- [PyPi](https://pypi.org/project/luminol) (📥 32K / month): ``` pip install luminol ```
-
tick (🥉18 · ⭐ 360 · 💀) - 统计学习模块。BSD-3 - -- [GitHub](https://github.com/X-DataInitiative/tick) (👨‍💻 16 · 🔀 81 · 📥 190 · 📦 46 · 📋 220 - 24% open · ⏱️ 15.06.2020): - - ``` - git clone https://github.com/X-DataInitiative/tick - ``` -- [PyPi](https://pypi.org/project/tick) (📥 890 / month): - ``` - pip install tick - ``` -
-
PyFlux (🥉17 · ⭐ 1.9K · 💀) - 适用于Python的开源时间序列库。BSD-3 +
ADTK (🥉18 · ⭐ 850 · 💀) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 -- [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 210 · 📋 150 - 55% open · ⏱️ 16.12.2018): +- [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 100 · 📋 67 - 46% open · ⏱️ 17.04.2020): ``` - git clone https://github.com/RJT1990/pyflux + git clone https://github.com/arundo/adtk ``` -- [PyPi](https://pypi.org/project/pyflux): +- [PyPi](https://pypi.org/project/adtk) (📥 280K / month): ``` - pip install pyflux + pip install adtk ```
-
ADTK (🥉17 · ⭐ 760 · 💀) - 一个Python工具包，用于基于规则的/无监督的异常检测。MPL-2.0 +
pydlm (🥉18 · ⭐ 420 · 💀) - A python library for Bayesian time series modeling. BSD-3 -- [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 94 · 📋 60 - 43% open · ⏱️ 17.04.2020): +- [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 91 · 📦 27 · 📋 43 - 81% open · ⏱️ 22.10.2019): ``` - git clone https://github.com/arundo/adtk + git clone https://github.com/wwrechard/pydlm ``` -- [PyPi](https://pypi.org/project/adtk) (📥 55K / month): +- [PyPi](https://pypi.org/project/pydlm) (📥 27K / month): ``` - pip install adtk + pip install pydlm ```
-
seglearn (🥉17 · ⭐ 480 · 💤) - 机器学习时间序列的Python模块。BSD-3 +
tick (🥉18 · ⭐ 400 · 💀) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 -- [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 13 · 🔀 52 · 📦 11 · 📋 28 - 17% open · ⏱️ 12.03.2021): +- [GitHub](https://github.com/X-DataInitiative/tick) (👨‍💻 16 · 🔀 84 · 📥 200 · 📦 66 · 📋 220 - 25% open · ⏱️ 15.06.2020): ``` - git clone https://github.com/dmbee/seglearn + git clone https://github.com/X-DataInitiative/tick ``` -- [PyPi](https://pypi.org/project/seglearn) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/tick) (📥 980 / month): ``` - pip install seglearn + pip install tick ```
-
Auto TS (🥉17 · ⭐ 350) - 自动实现ARIMA，SARIMAX，VAR，FB Prophet和XGBoost等模型时序建模。Apache-2 +
matrixprofile-ts (🥉17 · ⭐ 690 · 💀) - A Python library for detecting patterns and anomalies.. Apache-2 -- [GitHub](https://github.com/AutoViML/Auto_TS) (👨‍💻 6 · 🔀 65 · 📋 57 - 14% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 97 · 📦 19 · 📋 53 - 35% open · ⏱️ 25.04.2020): ``` - git clone https://github.com/AutoViML/Auto_TS + git clone https://github.com/target/matrixprofile-ts ``` -- [PyPi](https://pypi.org/project/auto-ts) (📥 2.6K / month): +- [PyPi](https://pypi.org/project/matrixprofile-ts) (📥 520 / month): ``` - pip install auto-ts + pip install matrixprofile-ts ```
-
matrixprofile-ts (🥉14 · ⭐ 670 · 💀) - 一个用于检测模式和异常的Python库。Apache-2 +
seglearn (🥉17 · ⭐ 520) - Python module for machine learning time series:. BSD-3 -- [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 92 · 📦 17 · 📋 53 - 35% open · ⏱️ 25.04.2020): +- [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 14 · 🔀 61 · 📦 11 · 📋 29 - 20% open · ⏱️ 16.06.2022): ``` - git clone https://github.com/target/matrixprofile-ts + git clone https://github.com/dmbee/seglearn ``` -- [PyPi](https://pypi.org/project/matrixprofile-ts): +- [PyPi](https://pypi.org/project/seglearn) (📥 970 / month): ``` - pip install matrixprofile-ts + pip install seglearn ```
-
pydlm (🥉14 · ⭐ 400 · 💀) - 用于贝叶斯时间序列建模的python库。BSD-3 +
Auto TS (🥉17 · ⭐ 470) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 -- [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 87 · 📦 24 · 📋 43 - 81% open · ⏱️ 22.10.2019): +- [GitHub](https://github.com/AutoViML/Auto_TS) (👨‍💻 6 · 🔀 86 · 📋 75 - 8% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/wwrechard/pydlm + git clone https://github.com/AutoViML/Auto_TS ``` -- [PyPi](https://pypi.org/project/pydlm): +- [PyPi](https://pypi.org/project/auto-ts) (📥 4.4K / month): ``` - pip install pydlm + pip install auto-ts ```
-
atspy (🥉10 · ⭐ 400) - AtsPy：Python中的自动时间序列模型。❗Unlicensed +
atspy (🥉13 · ⭐ 450 · 💤) - AtsPy: Automated Time Series Models in Python (by @firmai). ❗Unlicensed -- [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 78 · 📦 3 · 📋 20 - 90% open · ⏱️ 30.08.2021): +- [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 85 · 📦 6 · 📋 21 - 90% open · ⏱️ 18.12.2021): ``` git clone https://github.com/firmai/atspy ``` -- [PyPi](https://pypi.org/project/atspy): +- [PyPi](https://pypi.org/project/atspy) (📥 350 / month): ``` pip install atspy ```

-## 医疗领域 +## Medical Data -Back to top +Back to top -_用于处理和分析MRI，EEG，基因组数据和其他医学成像格式等医学数据的库。_ +_Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic data, and other medical imaging formats._ -
Lifelines (🥇29 · ⭐ 1.8K) - Python中的生存分析。MIT +
NIPYPE (🥇31 · ⭐ 640) - Workflows and interfaces for neuroimaging packages. Apache-2 + +- [GitHub](https://github.com/nipy/nipype) (👨‍💻 240 · 🔀 460 · 📦 1K · 📋 1.3K - 28% open · ⏱️ 22.08.2022): + + ``` + git clone https://github.com/nipy/nipype + ``` +- [PyPi](https://pypi.org/project/nipype) (📥 54K / month): + ``` + pip install nipype + ``` +- [Conda](https://anaconda.org/conda-forge/nipype) (📥 490K · ⏱️ 14.07.2022): + ``` + conda install -c conda-forge nipype + ``` +
+
Lifelines (🥇30 · ⭐ 1.9K) - Survival analysis in Python. MIT -- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 98 · 🔀 440 · 📦 730 · 📋 830 - 25% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 100 · 🔀 480 · 📦 1K · 📋 870 - 25% open · ⏱️ 17.07.2022): ``` git clone https://github.com/CamDavidsonPilon/lifelines ``` -- [PyPi](https://pypi.org/project/lifelines) (📥 320K / month): +- [PyPi](https://pypi.org/project/lifelines) (📥 370K / month): ``` pip install lifelines ``` -- [Conda](https://anaconda.org/conda-forge/lifelines) (📥 180K · ⏱️ 01.12.2021): +- [Conda](https://anaconda.org/conda-forge/lifelines) (📥 210K · ⏱️ 18.05.2022): ``` conda install -c conda-forge lifelines ```
-
NIPYPE (🥇29 · ⭐ 600) - 神经影像软件包的工作流程和接口。Apache-2 +
NiBabel (🥈28 · ⭐ 490) - Python package to access a cacophony of neuro-imaging file formats. ❗Unlicensed -- [GitHub](https://github.com/nipy/nipype) (👨‍💻 230 · 🔀 440 · 📦 810 · 📋 1.2K - 27% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/nipy/nibabel) (👨‍💻 94 · 🔀 230 · 📦 7.9K · 📋 440 - 26% open · ⏱️ 20.08.2022): ``` - git clone https://github.com/nipy/nipype + git clone https://github.com/nipy/nibabel ``` -- [PyPi](https://pypi.org/project/nipype) (📥 32K / month): +- [PyPi](https://pypi.org/project/nibabel) (📥 230K / month): ``` - pip install nipype + pip install nibabel ``` -- [Conda](https://anaconda.org/conda-forge/nipype) (📥 460K · ⏱️ 20.10.2021): +- [Conda](https://anaconda.org/conda-forge/nibabel) (📥 470K · ⏱️ 18.06.2022): ``` - conda install -c conda-forge nipype + conda install -c conda-forge nibabel ```
-
MNE (🥈27 · ⭐ 1.8K) - MNE：Python中的磁脑图（MEG）和脑电图（EEG）。BSD-3 +
MNE (🥈27 · ⭐ 2K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 -- [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 280 · 🔀 940 · 📦 1.3K · 📋 3.9K - 8% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 310 · 🔀 1K · 📦 1.8K · 📋 4.2K - 9% open · ⏱️ 25.08.2022): ``` git clone https://github.com/mne-tools/mne-python ``` -- [PyPi](https://pypi.org/project/mne) (📥 37K / month): +- [PyPi](https://pypi.org/project/mne) (📥 48K / month): ``` pip install mne ``` -- [Conda](https://anaconda.org/conda-forge/mne) (📥 180K · ⏱️ 02.12.2021): +- [Conda](https://anaconda.org/conda-forge/mne) (📥 220K · ⏱️ 24.08.2022): ``` conda install -c conda-forge mne ```
-
NiBabel (🥈27 · ⭐ 450) - Python软件包，用于访问神经影像文件格式。❗Unlicensed +
Hail (🥈27 · ⭐ 820) - Scalable genomic data analysis. MIT -- [GitHub](https://github.com/nipy/nibabel) (👨‍💻 93 · 🔀 220 · 📦 5.9K · 📋 410 - 25% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/hail-is/hail) (👨‍💻 81 · 🔀 210 · 📦 75 · 📋 2K - 0% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/nipy/nibabel - ``` -- [PyPi](https://pypi.org/project/nibabel) (📥 150K / month): - ``` - pip install nibabel + git clone https://github.com/hail-is/hail ``` -- [Conda](https://anaconda.org/conda-forge/nibabel) (📥 400K · ⏱️ 29.11.2020): +- [PyPi](https://pypi.org/project/hail) (📥 240K / month): ``` - conda install -c conda-forge nibabel + pip install hail ```
-
Hail (🥈26 · ⭐ 770) - 可扩展的基因组数据分析。MIT +
MONAI (🥈25 · ⭐ 3.3K) - AI Toolkit for Healthcare Imaging. Apache-2 -- [GitHub](https://github.com/hail-is/hail) (👨‍💻 76 · 🔀 200 · 📦 45 · 📋 2K - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 110 · 🔀 640 · 📦 460 · 📋 1.9K - 11% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/hail-is/hail + git clone https://github.com/Project-MONAI/MONAI ``` -- [PyPi](https://pypi.org/project/hail) (📥 20K / month): +- [PyPi](https://pypi.org/project/monai) (📥 48K / month): ``` - pip install hail + pip install monai ```
-
Nilearn (🥈24 · ⭐ 790) - Python中NeuroImaging的机器学习。❗Unlicensed +
Nilearn (🥈24 · ⭐ 880) - Machine learning for NeuroImaging in Python. ❗Unlicensed -- [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 180 · 🔀 420 · 📥 14 · 📦 1.3K · 📋 1.5K - 15% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 190 · 🔀 450 · 📥 64 · 📦 1.7K · 📋 1.6K - 14% open · ⏱️ 25.08.2022): ``` git clone https://github.com/nilearn/nilearn ``` -- [PyPi](https://pypi.org/project/nilearn) (📥 21K / month): +- [PyPi](https://pypi.org/project/nilearn) (📥 38K / month): ``` pip install nilearn ``` -- [Conda](https://anaconda.org/conda-forge/nilearn) (📥 130K · ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/conda-forge/nilearn) (📥 180K · ⏱️ 24.08.2022): ``` conda install -c conda-forge nilearn ```
-
DIPY (🥈24 · ⭐ 480) - DIPY是Python中的Paragon 3D/4D +影像库。❗Unlicensed +
DIPY (🥈24 · ⭐ 540) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed -- [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 320 · 📦 480 · 📋 740 - 13% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 340 · 📦 600 · 📋 780 - 14% open · ⏱️ 25.08.2022): ``` git clone https://github.com/dipy/dipy ``` -- [PyPi](https://pypi.org/project/dipy) (📥 8.6K / month): +- [PyPi](https://pypi.org/project/dipy) (📥 13K / month): ``` pip install dipy ``` -- [Conda](https://anaconda.org/conda-forge/dipy) (📥 270K · ⏱️ 06.05.2021): +- [Conda](https://anaconda.org/conda-forge/dipy) (📥 320K · ⏱️ 15.03.2022): ``` conda install -c conda-forge dipy ```
-
DeepVariant (🥈22 · ⭐ 2.4K) - DeepVariant是使用深度神经网络的分析管道。BSD-3 +
DeepVariant (🥉22 · ⭐ 2.6K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 -- [GitHub](https://github.com/google/deepvariant) (👨‍💻 21 · 🔀 580 · 📥 3.7K · 📋 450 - 0% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/google/deepvariant) (👨‍💻 24 · 🔀 620 · 📥 4.1K · 📋 500 - 1% open · ⏱️ 02.06.2022): ``` git clone https://github.com/google/deepvariant ``` -- [Conda](https://anaconda.org/bioconda/deepvariant) (📥 36K · ⏱️ 16.12.2021): +- [Conda](https://anaconda.org/bioconda/deepvariant) (📥 44K · ⏱️ 05.06.2022): ``` conda install -c bioconda deepvariant ```
-
NiftyNet (🥈22 · ⭐ 1.3K · 💀) - 开源医疗卷积神经网络工具库。Apache-2 +
NiftyNet (🥉22 · ⭐ 1.3K · 💀) - [unmaintained] An open-source convolutional neural.. Apache-2 -- [GitHub](https://github.com/NifTK/NiftyNet) (👨‍💻 58 · 🔀 390 · 📦 37 · 📋 320 - 30% open · ⏱️ 21.04.2020): +- [GitHub](https://github.com/NifTK/NiftyNet) (👨‍💻 59 · 🔀 390 · 📦 38 · 📋 320 - 30% open · ⏱️ 21.04.2020): ``` git clone https://github.com/NifTK/NiftyNet ``` -- [PyPi](https://pypi.org/project/niftynet) (📥 380 / month): +- [PyPi](https://pypi.org/project/niftynet) (📥 260 / month): ``` pip install niftynet ```
-
MedPy (🥉21 · ⭐ 380 · 💀) - Python中的医学图像处理。❗️GPL-3.0 +
MedPy (🥉22 · ⭐ 430 · 💀) - Medical image processing in Python. ❗️GPL-3.0 -- [GitHub](https://github.com/loli/medpy) (👨‍💻 13 · 🔀 110 · 📦 450 · 📋 78 - 14% open · ⏱️ 01.05.2020): +- [GitHub](https://github.com/loli/medpy) (👨‍💻 14 · 🔀 120 · 📦 700 · 📋 80 - 15% open · ⏱️ 01.05.2020): ``` git clone https://github.com/loli/medpy ``` -- [PyPi](https://pypi.org/project/MedPy) (📥 10K / month): +- [PyPi](https://pypi.org/project/MedPy) (📥 13K / month): ``` pip install MedPy ```
-
MONAI (🥉20 · ⭐ 2.6K) - 用于医疗成像的AI工具包。Apache-2 +
Glow (🥉22 · ⭐ 210) - An open-source toolkit for large-scale genomic analysis. Apache-2 -- [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 84 · 🔀 480 · 📦 160 · 📋 1.3K - 8% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/projectglow/glow) (👨‍💻 21 · 🔀 78 · 📋 130 - 40% open · ⏱️ 09.05.2022): ``` - git clone https://github.com/Project-MONAI/MONAI + git clone https://github.com/projectglow/glow ``` -- [PyPi](https://pypi.org/project/monai): +- [PyPi](https://pypi.org/project/glow.py) (📥 140K / month): ``` - pip install monai + pip install glow.py ```
-
Glow (🥉20 · ⭐ 180) - 一个用于大规模基因组分析的开源工具包。Apache-2 +
DLTK (🥉18 · ⭐ 1.3K · 💀) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 -- [GitHub](https://github.com/projectglow/glow) (👨‍💻 18 · 🔀 55 · 📋 120 - 36% open · ⏱️ 01.12.2021): +- [GitHub](https://github.com/DLTK/DLTK) (👨‍💻 9 · 🔀 390 · 📦 23 · 📋 31 - 22% open · ⏱️ 21.01.2019): ``` - git clone https://github.com/projectglow/glow + git clone https://github.com/DLTK/DLTK ``` -- [PyPi](https://pypi.org/project/glow.py) (📥 27K / month): +- [PyPi](https://pypi.org/project/dltk) (📥 100 / month): ``` - pip install glow.py + pip install dltk ```
-
NIPY (🥉19 · ⭐ 310 · 💤) - Python FMRI分析软件包中的Neuroimaging。BSD-3 +
NIPY (🥉18 · ⭐ 320 · 💀) - Neuroimaging in Python FMRI analysis package. BSD-3 -- [GitHub](https://github.com/nipy/nipy) (👨‍💻 63 · 🔀 130 · 📋 150 - 25% open · ⏱️ 29.03.2021): +- [GitHub](https://github.com/nipy/nipy) (👨‍💻 63 · 🔀 130 · 📋 150 - 26% open · ⏱️ 29.03.2021): ``` git clone https://github.com/nipy/nipy @@ -5034,102 +5046,90 @@ _用于处理和分析MRI，EEG，基因组数据和其他医学成像格式等 ``` pip install nipy ``` -- [Conda](https://anaconda.org/conda-forge/nipy) (📥 89K · ⏱️ 04.05.2020): +- [Conda](https://anaconda.org/conda-forge/nipy) (📥 95K · ⏱️ 04.05.2020): ``` conda install -c conda-forge nipy ```
-
Brainiak (🥉18 · ⭐ 260 · 💤) - 脑成像分析套件。Apache-2 +
Brainiak (🥉18 · ⭐ 280 · 💀) - Brain Imaging Analysis Kit. Apache-2 -- [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 33 · 🔀 120 · 📦 15 · 📋 190 - 35% open · ⏱️ 28.05.2021): +- [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 34 · 🔀 130 · 📦 16 · 📋 200 - 37% open · ⏱️ 28.05.2021): ``` git clone https://github.com/brainiak/brainiak ``` -- [PyPi](https://pypi.org/project/brainiak) (📥 190 / month): +- [PyPi](https://pypi.org/project/brainiak) (📥 180 / month): ``` pip install brainiak ``` -- [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (📥 680 · ⭐ 1 · ⏱️ 15.10.2020): +- [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (📥 760 · ⭐ 1 · ⏱️ 15.10.2020): ``` docker pull brainiak/brainiak ```
-
DLTK (🥉16 · ⭐ 1.3K · 💀) - 用于医学图像分析的深度学习工具包。Apache-2 - -- [GitHub](https://github.com/DLTK/DLTK) (👨‍💻 9 · 🔀 390 · 📦 21 · 📋 31 - 22% open · ⏱️ 21.01.2019): - - ``` - git clone https://github.com/DLTK/DLTK - ``` -- [PyPi](https://pypi.org/project/dltk): - ``` - pip install dltk - ``` -
-
MedicalTorch (🥉16 · ⭐ 760 · 💤) - Pytorch的医学成像框架。Apache-2 +
MedicalTorch (🥉15 · ⭐ 790 · 💀) - A medical imaging framework for Pytorch. Apache-2 -- [GitHub](https://github.com/perone/medicaltorch) (👨‍💻 8 · 🔀 110 · 📦 11 · 📋 22 - 59% open · ⏱️ 16.04.2021): +- [GitHub](https://github.com/perone/medicaltorch) (👨‍💻 8 · 🔀 110 · 📦 12 · 📋 22 - 59% open · ⏱️ 16.04.2021): ``` git clone https://github.com/perone/medicaltorch ``` -- [PyPi](https://pypi.org/project/medicaltorch) (📥 200 / month): +- [PyPi](https://pypi.org/project/medicaltorch) (📥 210 / month): ``` pip install medicaltorch ```
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MedicalNet (🥉13 · ⭐ 1.3K · 💀) - Transfer Learning for 3D Medical Image Analysis的论文实现。MIT +
MedicalNet (🥉14 · ⭐ 1.4K · 💀) - Many studies have shown that the performance on deep learning is.. MIT -- [GitHub](https://github.com/Tencent/MedicalNet) (🔀 330 · 📋 62 - 77% open · ⏱️ 27.08.2020): +- [GitHub](https://github.com/Tencent/MedicalNet) (🔀 370 · 📋 70 - 78% open · ⏱️ 27.08.2020): ``` git clone https://github.com/Tencent/MedicalNet ```
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Medical Detection Toolkit (🥉12 · ⭐ 1.1K) - Medical Detection Toolkit包含2D + 3D。Apache-2 +
Medical Detection Toolkit (🥉14 · ⭐ 1.1K) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 -- [GitHub](https://github.com/MIC-DKFZ/medicaldetectiontoolkit) (👨‍💻 3 · 🔀 270 · 📋 120 - 30% open · ⏱️ 09.09.2021): +- [GitHub](https://github.com/MIC-DKFZ/medicaldetectiontoolkit) (👨‍💻 3 · 🔀 280 · 📋 120 - 30% open · ⏱️ 04.04.2022): ``` git clone https://github.com/MIC-DKFZ/medicaldetectiontoolkit ```
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DeepNeuro (🥉12 · ⭐ 110 · 💀) - 用于神经影像数据的深度学习python软件包。MIT +
DeepNeuro (🥉11 · ⭐ 110 · 💀) - A deep learning python package for neuroimaging data. Made by:. MIT - [GitHub](https://github.com/QTIM-Lab/DeepNeuro) (👨‍💻 6 · 🔀 34 · 📦 1 · 📋 41 - 60% open · ⏱️ 24.06.2020): ``` git clone https://github.com/QTIM-Lab/DeepNeuro ``` -- [PyPi](https://pypi.org/project/deepneuro) (📥 33 / month): +- [PyPi](https://pypi.org/project/deepneuro) (📥 20 / month): ``` pip install deepneuro ```

-## 光学字符识别OCR +## Optical Character Recognition -Back to top +Back to top -_用于光学字符识别（OCR）和从图像或视频中提取文本的库。_ +_Libraries for optical character recognition (OCR) and text extraction from images or videos._ -
EasyOCR (🥇30 · ⭐ 13K) - 即用型OCR，具有80多种受支持的语言和所有流行的手写文字。Apache-2 +
EasyOCR (🥇31 · ⭐ 16K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 -- [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 90 · 🔀 1.7K · 📥 870K · 📦 750 · 📋 470 - 29% open · ⏱️ 15.10.2021): +- [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 110 · 🔀 2.2K · 📥 2M · 📦 1.5K · 📋 640 - 15% open · ⏱️ 25.08.2022): ``` git clone https://github.com/JaidedAI/EasyOCR ``` -- [PyPi](https://pypi.org/project/easyocr) (📥 120K / month): +- [PyPi](https://pypi.org/project/easyocr) (📥 84K / month): ``` pip install easyocr ```
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PaddleOCR (🥇26 · ⭐ 18K) - 基于PaddlePaddle的多语言OCR工具包。Apache-2 +
PaddleOCR (🥇27 · ⭐ 24K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 58 · 🔀 3.6K · 📦 450 · 📋 3.5K - 25% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 110 · 🔀 4.9K · 📦 780 · 📋 5.1K - 25% open · ⏱️ 26.08.2022): ``` git clone https://github.com/PaddlePaddle/PaddleOCR @@ -5139,113 +5139,113 @@ _用于光学字符识别（OCR）和从图像或视频中提取文本的库。_ pip install paddleocr ```
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tesserocr (🥈25 · ⭐ 1.6K) - 用于tesseract-ocr API的Python包装器。MIT +
tesserocr (🥈26 · ⭐ 1.7K) - A Python wrapper for the tesseract-ocr API. MIT -- [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 200 · 📦 580 · 📋 230 - 31% open · ⏱️ 09.11.2021): +- [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 220 · 📦 700 · 📋 250 - 31% open · ⏱️ 23.08.2022): ``` git clone https://github.com/sirfz/tesserocr ``` -- [PyPi](https://pypi.org/project/tesserocr): +- [PyPi](https://pypi.org/project/tesserocr) (📥 49K / month): ``` pip install tesserocr ``` -- [Conda](https://anaconda.org/conda-forge/tesserocr) (📥 62K · ⏱️ 13.01.2021): +- [Conda](https://anaconda.org/conda-forge/tesserocr) (📥 81K · ⏱️ 04.05.2022): ``` conda install -c conda-forge tesserocr ```
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Tesseract (🥈24 · ⭐ 3.9K) - Python-tesseract是一种光学字符识别（OCR）工具。Apache-2 +
Tesseract (🥈25 · ⭐ 4.4K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 -- [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 38 · 🔀 550 · 📋 280 - 3% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 41 · 🔀 600 · 📋 310 - 4% open · ⏱️ 16.08.2022): ``` git clone https://github.com/madmaze/pytesseract ``` -- [PyPi](https://pypi.org/project/pytesseract) (📥 850K / month): +- [PyPi](https://pypi.org/project/pytesseract) (📥 670K / month): ``` pip install pytesseract ``` -- [Conda](https://anaconda.org/conda-forge/pytesseract) (📥 480K · ⏱️ 05.06.2021): +- [Conda](https://anaconda.org/conda-forge/pytesseract) (📥 520K · ⏱️ 15.03.2022): ``` conda install -c conda-forge pytesseract ```
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OCRmyPDF (🥈22 · ⭐ 5.5K) - OCRmyPDF将OCR文本层添加到扫描的PDF文件中使用。MPL-2.0 +
OCRmyPDF (🥈22 · ⭐ 7K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 -- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 58 · 🔀 510 · 📋 780 - 11% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 74 · 🔀 590 · 📋 880 - 9% open · ⏱️ 15.08.2022): ``` git clone https://github.com/jbarlow83/OCRmyPDF ``` -- [PyPi](https://pypi.org/project/ocrmypdf) (📥 21K / month): +- [PyPi](https://pypi.org/project/ocrmypdf) (📥 25K / month): ``` pip install ocrmypdf ```
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attention-ocr (🥉21 · ⭐ 880) - 用于文本识别的Tensorflow模型。MIT +
pdftabextract (🥉19 · ⭐ 2K) - A set of tools for extracting tables from PDF files.. Apache-2 -- [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 18 · 📋 150 - 14% open · ⏱️ 29.10.2021): +- [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 3 · 🔀 350 · 📦 42 · 📋 21 - 14% open · ⏱️ 24.06.2022): ``` - git clone https://github.com/emedvedev/attention-ocr + git clone https://github.com/WZBSocialScienceCenter/pdftabextract ``` -- [PyPi](https://pypi.org/project/aocr) (📥 280 / month): +- [PyPi](https://pypi.org/project/pdftabextract) (📥 660 / month): ``` - pip install aocr + pip install pdftabextract ```
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keras-ocr (🥉19 · ⭐ 960) - CRAFT文本检测器。MIT +
calamari (🥉19 · ⭐ 940) - Line based ATR Engine based on OCRopy. Apache-2 -- [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 12 · 🔀 240 · 📥 200K · 📋 150 - 30% open · ⏱️ 24.11.2021): +- [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 190 · 📋 250 - 19% open · ⏱️ 10.06.2022): ``` - git clone https://github.com/faustomorales/keras-ocr + git clone https://github.com/Calamari-OCR/calamari ``` -- [PyPi](https://pypi.org/project/keras-ocr) (📥 4.9K / month): +- [PyPi](https://pypi.org/project/calamari_ocr) (📥 430 / month): ``` - pip install keras-ocr + pip install calamari_ocr ```
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doc2text (🥉17 · ⭐ 1.3K · 💤) - 批量检测文本块和OCR扫描不良的PDF。MIT +
attention-ocr (🥉19 · ⭐ 920 · 💤) - A Tensorflow model for text recognition (CNN + seq2seq.. MIT -- [GitHub](https://github.com/jlsutherland/doc2text) (👨‍💻 5 · 🔀 94 · 📦 50 · 📋 21 - 57% open · ⏱️ 01.12.2020): +- [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 20 · 📋 150 - 15% open · ⏱️ 29.10.2021): ``` - git clone https://github.com/jlsutherland/doc2text + git clone https://github.com/emedvedev/attention-ocr ``` -- [PyPi](https://pypi.org/project/doc2text) (📥 380 / month): +- [PyPi](https://pypi.org/project/aocr) (📥 96 / month): ``` - pip install doc2text + pip install aocr ```
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calamari (🥉17 · ⭐ 880) - 基于OCRopy的基于行的ATR引擎。Apache-2 +
doc2text (🥉18 · ⭐ 1.3K · 💀) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT -- [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 180 · 📋 230 - 16% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/jlsutherland/doc2text) (👨‍💻 5 · 🔀 95 · 📦 60 · 📋 21 - 57% open · ⏱️ 01.12.2020): ``` - git clone https://github.com/Calamari-OCR/calamari + git clone https://github.com/jlsutherland/doc2text ``` -- [PyPi](https://pypi.org/project/calamari_ocr): +- [PyPi](https://pypi.org/project/doc2text) (📥 1.8K / month): ``` - pip install calamari_ocr + pip install doc2text ```
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pdftabextract (🥉15 · ⭐ 2K · 💀) - 一组用于从PDF文件提取表格的工具。Apache-2 +
keras-ocr (🥉18 · ⭐ 1.1K) - A packaged and flexible version of the CRAFT text detector and.. MIT -- [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 2 · 🔀 340 · 📦 37 · 📋 21 - 14% open · ⏱️ 26.10.2018): +- [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 15 · 🔀 270 · 📥 300K · 📋 180 - 38% open · ⏱️ 19.05.2022): ``` - git clone https://github.com/WZBSocialScienceCenter/pdftabextract + git clone https://github.com/faustomorales/keras-ocr ``` -- [PyPi](https://pypi.org/project/pdftabextract): +- [PyPi](https://pypi.org/project/keras-ocr) (📥 5.8K / month): ``` - pip install pdftabextract + pip install keras-ocr ```
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Mozart (🥉10 · ⭐ 340 · 💤) - 光学音乐识别（OMR）系统。Apache-2 +
Mozart (🥉11 · ⭐ 400) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 -- [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 47 · 📋 9 - 33% open · ⏱️ 05.05.2021): +- [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 58 · 📋 12 - 25% open · ⏱️ 24.08.2022): ``` git clone https://github.com/aashrafh/Mozart @@ -5253,160 +5253,168 @@ _用于光学字符识别（OCR）和从图像或视频中提取文本的库。_

-## 数据容器和结构 +## Data Containers & Structures -Back to top +Back to top -_通用数据容器和结构以及pandas的实用程序和扩展。_ +_General-purpose data containers & structures as well as utilities & extensions for pandas._ -
pandas (🥇43 · ⭐ 32K) - 灵活而强大的数据分析/操作库。BSD-3 +
pandas (🥇39 · ⭐ 35K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 -- [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 2.9K · 🔀 13K · 📥 130K · 📦 600K · 📋 22K - 15% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 3.1K · 🔀 15K · 📥 160K · 📦 800K · 📋 23K - 14% open · ⏱️ 25.08.2022): ``` git clone https://github.com/pandas-dev/pandas ``` -- [PyPi](https://pypi.org/project/pandas) (📥 71M / month): +- [PyPi](https://pypi.org/project/pandas) (📥 100M / month): ``` pip install pandas ``` -- [Conda](https://anaconda.org/conda-forge/pandas) (📥 22M · ⏱️ 13.12.2021): +- [Conda](https://anaconda.org/conda-forge/pandas) (📥 29M · ⏱️ 24.08.2022): ``` conda install -c conda-forge pandas ```
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numpy (🥇38 · ⭐ 19K) - 使用Python进行科学计算的基本软件包。BSD-3 +
numpy (🥇38 · ⭐ 21K) - The fundamental package for scientific computing with Python. BSD-3 -- [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.4K · 🔀 6.1K · 📥 430K · 📦 910K · 📋 10K - 20% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.5K · 🔀 7K · 📥 560K · 📦 1.2M · 📋 11K - 18% open · ⏱️ 24.08.2022): ``` git clone https://github.com/numpy/numpy ``` -- [PyPi](https://pypi.org/project/numpy) (📥 90M / month): +- [PyPi](https://pypi.org/project/numpy) (📥 130M / month): ``` pip install numpy ``` -- [Conda](https://anaconda.org/conda-forge/numpy) (📥 27M · ⏱️ 05.11.2021): +- [Conda](https://anaconda.org/conda-forge/numpy) (📥 38M · ⏱️ 16.08.2022): ``` conda install -c conda-forge numpy ```
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h5py (🥇34 · ⭐ 1.6K) - 适用于Python的HDF5-h5py软件包，HDF5的Pythonic接口。BSD-3 +
h5py (🥇36 · ⭐ 1.8K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 -- [GitHub](https://github.com/h5py/h5py) (👨‍💻 170 · 🔀 420 · 📥 1.6K · 📦 140K · 📋 1.3K - 16% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/h5py/h5py) (👨‍💻 180 · 🔀 450 · 📥 2.1K · 📦 170K · 📋 1.3K - 16% open · ⏱️ 01.07.2022): ``` git clone https://github.com/h5py/h5py ``` -- [PyPi](https://pypi.org/project/h5py): +- [PyPi](https://pypi.org/project/h5py) (📥 12M / month): ``` pip install h5py ``` -- [Conda](https://anaconda.org/conda-forge/h5py) (📥 6.8M · ⏱️ 26.11.2021): +- [Conda](https://anaconda.org/conda-forge/h5py) (📥 8.8M · ⏱️ 14.08.2022): ``` conda install -c conda-forge h5py ```
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Arrow (🥈33 · ⭐ 8.8K) - Apache Arrow定义了一种在内存中表示tabular data的格式。Apache-2 +
Arrow (🥈33 · ⭐ 10K) - Apache Arrow is a cross-language development platform for in-.. Apache-2 -- [GitHub](https://github.com/apache/arrow) (👨‍💻 780 · 🔀 2K · 📦 57 · 📋 700 - 1% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/apache/arrow) (👨‍💻 930 · 🔀 2.4K · 📦 77 · 📋 840 - 6% open · ⏱️ 25.08.2022): ``` git clone https://github.com/apache/arrow ``` -- [PyPi](https://pypi.org/project/pyarrow) (📥 32M / month): +- [PyPi](https://pypi.org/project/pyarrow) (📥 68M / month): ``` pip install pyarrow ``` -- [Conda](https://anaconda.org/conda-forge/arrow) (📥 840K · ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/arrow) (📥 1.1M · ⏱️ 27.01.2022): ``` conda install -c conda-forge arrow ```
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xarray (🥈30 · ⭐ 2.4K) - Python中带有N-D标签的数组和数据集。Apache-2 +
Modin (🥈29 · ⭐ 7.7K) - Modin: Speed up your Pandas workflows by changing a single line of.. Apache-2 -- [GitHub](https://github.com/pydata/xarray) (👨‍💻 350 · 🔀 740 · 📦 8.5K · 📋 3K - 27% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/modin-project/modin) (👨‍💻 100 · 🔀 540 · 📥 200K · 📦 710 · 📋 2.9K - 30% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/pydata/xarray - ``` -- [PyPi](https://pypi.org/project/xarray) (📥 1.2M / month): - ``` - pip install xarray + git clone https://github.com/modin-project/modin ``` -- [Conda](https://anaconda.org/conda-forge/xarray) (📥 4.4M · ⏱️ 10.12.2021): +- [PyPi](https://pypi.org/project/modin) (📥 180K / month): ``` - conda install -c conda-forge xarray + pip install modin ```
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Koalas (🥈29 · ⭐ 3K) - Apache Spark上的pandas API。Apache-2 +
xarray (🥈29 · ⭐ 2.7K) - N-D labeled arrays and datasets in Python. Apache-2 -- [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 320 · 📥 1K · 📦 160 · 📋 570 - 15% open · ⏱️ 21.10.2021): +- [GitHub](https://github.com/pydata/xarray) (👨‍💻 390 · 🔀 800 · 📦 12K · 📋 3.4K - 26% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/databricks/koalas + git clone https://github.com/pydata/xarray ``` -- [PyPi](https://pypi.org/project/koalas) (📥 2.3M / month): +- [PyPi](https://pypi.org/project/xarray) (📥 1.6M / month): ``` - pip install koalas + pip install xarray ``` -- [Conda](https://anaconda.org/conda-forge/koalas) (📥 110K · ⏱️ 20.10.2021): +- [Conda](https://anaconda.org/conda-forge/xarray) (📥 5.7M · ⏱️ 26.07.2022): ``` - conda install -c conda-forge koalas + conda install -c conda-forge xarray ```
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sklearn-pandas (🥈28 · ⭐ 2.5K · 💤) - pandas与sklearn集成。❗️Zlib +
sklearn-pandas (🥈29 · ⭐ 2.6K) - Pandas integration with sklearn. ❗️Zlib -- [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 37 · 🔀 370 · 📦 3.2K · 📋 150 - 13% open · ⏱️ 08.05.2021): +- [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 39 · 🔀 380 · 📦 4.4K · 📋 150 - 16% open · ⏱️ 17.07.2022): ``` git clone https://github.com/scikit-learn-contrib/sklearn-pandas ``` -- [PyPi](https://pypi.org/project/sklearn-pandas) (📥 490K / month): +- [PyPi](https://pypi.org/project/sklearn-pandas) (📥 580K / month): ``` pip install sklearn-pandas ```
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zarr (🥈27 · ⭐ 820) - Python的分块，压缩N维数组的实现。MIT +
datasketch (🥈29 · ⭐ 1.8K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT -- [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 52 · 🔀 130 · 📦 970 · 📋 440 - 37% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 24 · 🔀 240 · 📥 19 · 📦 440 · 📋 140 - 25% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/zarr-developers/zarr-python - ``` -- [PyPi](https://pypi.org/project/zarr): - ``` - pip install zarr + git clone https://github.com/ekzhu/datasketch ``` -- [Conda](https://anaconda.org/conda-forge/zarr) (📥 1.2M · ⏱️ 19.11.2021): +- [PyPi](https://pypi.org/project/datasketch) (📥 720K / month): ``` - conda install -c conda-forge zarr + pip install datasketch ```
-
Bottleneck (🥈27 · ⭐ 680 · 💤) - 用C编写的快速NumPy数组函数。BSD-2 +
Bottleneck (🥈29 · ⭐ 780) - Fast NumPy array functions written in C. BSD-2 -- [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 21 · 🔀 74 · 📦 29K · 📋 220 - 17% open · ⏱️ 24.01.2021): +- [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 25 · 🔀 80 · 📦 35K · 📋 220 - 15% open · ⏱️ 02.07.2022): ``` git clone https://github.com/pydata/bottleneck ``` -- [PyPi](https://pypi.org/project/Bottleneck): +- [PyPi](https://pypi.org/project/Bottleneck) (📥 430K / month): ``` pip install Bottleneck ``` -- [Conda](https://anaconda.org/conda-forge/bottleneck) (📥 1.8M · ⏱️ 04.11.2021): +- [Conda](https://anaconda.org/conda-forge/bottleneck) (📥 2.5M · ⏱️ 03.07.2022): ``` conda install -c conda-forge bottleneck ```
-
Blaze (🥈26 · ⭐ 3K · 💀) - NumPy和Pandas连接到大数据。❗Unlicensed +
Koalas (🥈28 · ⭐ 3.2K · 💤) - Koalas: pandas API on Apache Spark. Apache-2 + +- [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 330 · 📥 1K · 📦 220 · 📋 580 - 16% open · ⏱️ 21.10.2021): + + ``` + git clone https://github.com/databricks/koalas + ``` +- [PyPi](https://pypi.org/project/koalas) (📥 1.6M / month): + ``` + pip install koalas + ``` +- [Conda](https://anaconda.org/conda-forge/koalas) (📥 180K · ⏱️ 20.10.2021): + ``` + conda install -c conda-forge koalas + ``` +
+
Blaze (🥈28 · ⭐ 3.1K · 💀) - NumPy and Pandas interface to Big Data. BSD-3 -- [GitHub](https://github.com/blaze/blaze) (👨‍💻 64 · 🔀 360 · 📦 8K · 📋 750 - 33% open · ⏱️ 15.08.2019): +- [GitHub](https://github.com/blaze/blaze) (👨‍💻 65 · 🔀 360 · 📦 8.3K · 📋 750 - 33% open · ⏱️ 15.08.2019): ``` git clone https://github.com/blaze/blaze ``` -- [PyPi](https://pypi.org/project/blaze) (📥 13K / month): +- [PyPi](https://pypi.org/project/blaze) (📥 8.1K / month): ``` pip install blaze ``` @@ -5415,594 +5423,586 @@ _通用数据容器和结构以及pandas的实用程序和扩展。_ conda install -c conda-forge blaze ```
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Modin (🥈25 · ⭐ 6.6K) - Modin：通过更改一行来加快Pandas工作流程。❗Unlicensed +
Vaex (🥉26 · ⭐ 7.3K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and.. MIT -- [GitHub](https://github.com/modin-project/modin) (👨‍💻 85 · 🔀 460 · 📥 200K · 📦 520 · 📋 2.2K - 28% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/vaexio/vaex) (👨‍💻 70 · 🔀 550 · 📥 240 · 📦 310 · 📋 1.1K - 31% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/modin-project/modin + git clone https://github.com/vaexio/vaex ``` -- [PyPi](https://pypi.org/project/modin): +- [PyPi](https://pypi.org/project/vaex) (📥 44K / month): ``` - pip install modin + pip install vaex + ``` +- [Conda](https://anaconda.org/conda-forge/vaex) (📥 140K · ⏱️ 27.07.2022): + ``` + conda install -c conda-forge vaex ```
-
bcolz (🥉23 · ⭐ 940 · 💀) - 可以压缩的列式数据容器。❗Unlicensed +
zarr (🥉26 · ⭐ 970) - An implementation of chunked, compressed, N-dimensional arrays for Python. MIT -- [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 120 · 📦 1.7K · 📋 240 - 50% open · ⏱️ 10.09.2020): +- [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 65 · 🔀 160 · 📦 1.4K · 📋 500 - 38% open · ⏱️ 15.08.2022): ``` - git clone https://github.com/Blosc/bcolz + git clone https://github.com/zarr-developers/zarr-python ``` -- [PyPi](https://pypi.org/project/bcolz) (📥 14K / month): +- [PyPi](https://pypi.org/project/zarr) (📥 120K / month): ``` - pip install bcolz + pip install zarr ``` -- [Conda](https://anaconda.org/conda-forge/bcolz) (📥 280K · ⏱️ 05.11.2019): +- [Conda](https://anaconda.org/conda-forge/zarr) (📥 1.6M · ⏱️ 23.06.2022): ``` - conda install -c conda-forge bcolz + conda install -c conda-forge zarr ```
-
Vaex (🥉22 · ⭐ 6.8K) - 用于Python，ML的核外混合Apache Arrow / NumPy DataFrame可视化等实现。MIT +
numexpr (🥉25 · ⭐ 1.8K) - Fast numerical array expression evaluator for Python, NumPy, PyTables,.. MIT -- [GitHub](https://github.com/vaexio/vaex) (👨‍💻 62 · 🔀 520 · 📥 220 · 📋 890 - 31% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pydata/numexpr) (👨‍💻 63 · 🔀 180 · 📥 62 · 📋 330 - 18% open · ⏱️ 19.07.2022): ``` - git clone https://github.com/vaexio/vaex + git clone https://github.com/pydata/numexpr ``` -- [PyPi](https://pypi.org/project/vaex) (📥 22K / month): +- [PyPi](https://pypi.org/project/numexpr) (📥 2.6M / month): ``` - pip install vaex + pip install numexpr ``` -- [Conda](https://anaconda.org/conda-forge/vaex) (📥 120K · ⏱️ 30.11.2021): +- [Conda](https://anaconda.org/conda-forge/numexpr) (📥 4.7M · ⏱️ 17.07.2022): ``` - conda install -c conda-forge vaex + conda install -c conda-forge numexpr ```
-
TinyDB (🥉22 · ⭐ 4.7K) - TinyDB：轻型面向文档的数据库。MIT +
PyTables (🥉25 · ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 -- [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 70 · 🔀 410 · 📋 270 - 2% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 110 · 🔀 210 · 📥 170 · 📋 650 - 22% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/msiemens/tinydb + git clone https://github.com/PyTables/PyTables ``` -- [PyPi](https://pypi.org/project/tinydb): +- [PyPi](https://pypi.org/project/tables) (📥 1M / month): ``` - pip install tinydb + pip install tables ``` -- [Conda](https://anaconda.org/conda-forge/tinydb) (📥 150K · ⏱️ 23.09.2021): +- [Conda](https://anaconda.org/conda-forge/pytables) (📥 4.6M · ⏱️ 13.08.2022): ``` - conda install -c conda-forge tinydb + conda install -c conda-forge pytables ```
-
Arctic (🥉22 · ⭐ 2.5K) - Arctic是用于数字数据的高性能数据存储。❗️LGPL-2.1 +
Arctic (🥉24 · ⭐ 2.8K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 -- [GitHub](https://github.com/man-group/arctic) (👨‍💻 72 · 🔀 490 · 📥 180 · 📦 140 · 📋 520 - 15% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/man-group/arctic) (👨‍💻 76 · 🔀 530 · 📥 190 · 📦 180 · 📋 530 - 14% open · ⏱️ 02.03.2022): ``` git clone https://github.com/man-group/arctic ``` -- [PyPi](https://pypi.org/project/arctic): +- [PyPi](https://pypi.org/project/arctic) (📥 6.4K / month): ``` pip install arctic ``` -- [Conda](https://anaconda.org/conda-forge/arctic) (📥 17K · ⏱️ 16.12.2019): +- [Conda](https://anaconda.org/conda-forge/arctic) (📥 21K · ⏱️ 11.05.2022): ``` conda install -c conda-forge arctic ```
-
swifter (🥉22 · ⭐ 1.8K) - 一个可以对pandas Dataframe或者series做高效function映射的工具库。MIT +
Pandaral·lel (🥉24 · ⭐ 2.4K) - A simple and efficient tool to parallelize Pandas.. BSD-3 -- [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 14 · 🔀 84 · 📦 440 · 📋 110 - 21% open · ⏱️ 25.06.2021): +- [GitHub](https://github.com/nalepae/pandarallel) (👨‍💻 20 · 🔀 150 · 📋 170 - 46% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/jmcarpenter2/swifter - ``` -- [PyPi](https://pypi.org/project/swifter): - ``` - pip install swifter + git clone https://github.com/nalepae/pandarallel ``` -- [Conda](https://anaconda.org/conda-forge/swifter) (📥 130K · ⏱️ 26.06.2021): +- [PyPi](https://pypi.org/project/pandarallel) (📥 520K / month): ``` - conda install -c conda-forge swifter + pip install pandarallel ```
-
numexpr (🥉22 · ⭐ 1.7K) - 适用于Python，NumPy，PyTables等的快速数值数组表达式评估器。MIT +
swifter (🥉24 · ⭐ 2.1K) - A package which efficiently applies any function to a pandas.. MIT -- [GitHub](https://github.com/pydata/numexpr) (👨‍💻 59 · 🔀 160 · 📋 310 - 17% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 17 · 🔀 97 · 📦 660 · 📋 120 - 7% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/pydata/numexpr + git clone https://github.com/jmcarpenter2/swifter ``` -- [PyPi](https://pypi.org/project/numexpr): +- [PyPi](https://pypi.org/project/swifter) (📥 270K / month): ``` - pip install numexpr + pip install swifter ``` -- [Conda](https://anaconda.org/conda-forge/numexpr) (📥 3.4M · ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/swifter) (📥 150K · ⏱️ 17.08.2022): ``` - conda install -c conda-forge numexpr + conda install -c conda-forge swifter ```
-
datasketch (🥉22 · ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog等实现。MIT +
pandasql (🥉24 · ⭐ 1.1K · 💀) - sqldf for pandas. MIT -- [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 20 · 🔀 230 · 📥 18 · 📦 330 · 📋 120 - 21% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 1.5K · 📋 70 - 65% open · ⏱️ 01.02.2017): ``` - git clone https://github.com/ekzhu/datasketch + git clone https://github.com/yhat/pandasql ``` -- [PyPi](https://pypi.org/project/datasketch): +- [PyPi](https://pypi.org/project/pandasql) (📥 1.6M / month): ``` - pip install datasketch + pip install pandasql ```
-
PyTables (🥉22 · ⭐ 1.1K) - 一个Python包，用于管理大量数据。BSD-3 +
bcolz (🥉24 · ⭐ 940 · 💀) - A columnar data container that can be compressed. ❗Unlicensed -- [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 100 · 🔀 200 · 📥 160 · 📋 630 - 26% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 130 · 📦 1.8K · 📋 240 - 50% open · ⏱️ 10.09.2020): ``` - git clone https://github.com/PyTables/PyTables + git clone https://github.com/Blosc/bcolz ``` -- [PyPi](https://pypi.org/project/tables): +- [PyPi](https://pypi.org/project/bcolz) (📥 14K / month): ``` - pip install tables + pip install bcolz ``` -- [Conda](https://anaconda.org/conda-forge/pytables) (📥 3.6M · ⏱️ 29.11.2021): +- [Conda](https://anaconda.org/conda-forge/bcolz) (📥 310K · ⏱️ 20.06.2022): ``` - conda install -c conda-forge pytables + conda install -c conda-forge bcolz ```
-
pandasql (🥉22 · ⭐ 1.1K · 💀) - pandas的sqldf。MIT +
TinyDB (🥉23 · ⭐ 5.3K) - TinyDB is a lightweight document oriented database optimized for your.. MIT -- [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 1K · 📋 65 - 64% open · ⏱️ 01.02.2017): +- [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 78 · 🔀 450 · 📋 280 - 3% open · ⏱️ 23.07.2022): ``` - git clone https://github.com/yhat/pandasql + git clone https://github.com/msiemens/tinydb ``` -- [PyPi](https://pypi.org/project/pandasql) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/tinydb) (📥 390K / month): ``` - pip install pandasql + pip install tinydb + ``` +- [Conda](https://anaconda.org/conda-forge/tinydb) (📥 200K · ⏱️ 19.02.2022): + ``` + conda install -c conda-forge tinydb ```
-
StaticFrame (🥉22 · ⭐ 260) - 类似Pandas的DataFrame的不可变且仅增长的高效数据结构实现。MIT +
StaticFrame (🥉22 · ⭐ 310) - Immutable and grow-only Pandas-like DataFrames with a more explicit.. MIT -- [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 16 · 🔀 23 · 📦 10 · 📋 360 - 10% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 20 · 🔀 26 · 📦 11 · 📋 450 - 9% open · ⏱️ 23.08.2022): ``` git clone https://github.com/InvestmentSystems/static-frame ``` -- [PyPi](https://pypi.org/project/static-frame): +- [PyPi](https://pypi.org/project/static-frame) (📥 1.6K / month): ``` pip install static-frame ``` -- [Conda](https://anaconda.org/conda-forge/static-frame) (📥 130K · ⏱️ 01.12.2021): +- [Conda](https://anaconda.org/conda-forge/static-frame) (📥 180K · ⏱️ 14.08.2022): ``` conda install -c conda-forge static-frame ```
-
Pandaral·lel (🥉20 · ⭐ 1.9K) - A simple and efficient tool to parallelize Pandas.. BSD-3 +
datatable (🥉20 · ⭐ 1.6K) - A Python package for manipulating 2-dimensional tabular data.. MPL-2.0 -- [GitHub](https://github.com/nalepae/pandarallel) (👨‍💻 18 · 🔀 120 · 📦 360 · 📋 140 - 54% open · ⏱️ 17.10.2021): +- [GitHub](https://github.com/h2oai/datatable) (👨‍💻 33 · 🔀 140 · 📥 1.7K · 📋 1.4K - 10% open · ⏱️ 12.08.2022): ``` - git clone https://github.com/nalepae/pandarallel + git clone https://github.com/h2oai/datatable ``` -- [PyPi](https://pypi.org/project/pandarallel): +- [PyPi](https://pypi.org/project/datatable) (📥 67K / month): ``` - pip install pandarallel + pip install datatable ```
-
fletcher (🥉19 · ⭐ 220 · 💤) - 由Apache Arrow支持的Pandas ExtensionDType/Array。MIT +
pickleDB (🥉20 · ⭐ 700 · 💀) - pickleDB is an open source key-value store using Python's json.. BSD-3 -- [GitHub](https://github.com/xhochy/fletcher) (👨‍💻 24 · 🔀 34 · 📥 13 · 📦 3 · 📋 73 - 45% open · ⏱️ 18.02.2021): +- [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 110 · 📦 940 · 📋 57 - 28% open · ⏱️ 15.11.2019): ``` - git clone https://github.com/xhochy/fletcher - ``` -- [PyPi](https://pypi.org/project/fletcher): - ``` - pip install fletcher + git clone https://github.com/patx/pickledb ``` -- [Conda](https://anaconda.org/conda-forge/fletcher) (📥 35K · ⏱️ 04.11.2021): +- [PyPi](https://pypi.org/project/pickledb) (📥 38K / month): ``` - conda install -c conda-forge fletcher + pip install pickledb ```
-
datatable (🥉17 · ⭐ 1.4K) - 一个用于处理二维表格数据的Python包。MPL-2.0 +
fletcher (🥉19 · ⭐ 220 · 💀) - Pandas ExtensionDType/Array backed by Apache Arrow. MIT -- [GitHub](https://github.com/h2oai/datatable) (👨‍💻 32 · 🔀 120 · 📥 1.2K · 📋 1.4K - 9% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/xhochy/fletcher) (👨‍💻 24 · 🔀 33 · 📥 13 · 📦 4 · 📋 74 - 45% open · ⏱️ 18.02.2021): ``` - git clone https://github.com/h2oai/datatable - ``` -- [PyPi](https://pypi.org/project/datatable): - ``` - pip install datatable + git clone https://github.com/xhochy/fletcher ``` -
-
Bounter (🥉16 · ⭐ 930 · 💤) - 使用有限内存的高效计数器。MIT - -- [GitHub](https://github.com/RaRe-Technologies/bounter) (👨‍💻 8 · 🔀 45 · 📦 25 · 📋 23 - 60% open · ⏱️ 24.05.2021): - +- [PyPi](https://pypi.org/project/fletcher) (📥 620 / month): ``` - git clone https://github.com/RaRe-Technologies/bounter + pip install fletcher ``` -- [PyPi](https://pypi.org/project/bounter): +- [Conda](https://anaconda.org/conda-forge/fletcher) (📥 46K · ⏱️ 04.11.2021): ``` - pip install bounter + conda install -c conda-forge fletcher ```
-
pickleDB (🥉16 · ⭐ 620 · 💀) - pickleDB是使用Python的json的开源键值存储。BSD-3 +
Bounter (🥉18 · ⭐ 940 · 💀) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT -- [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 100 · 📦 790 · 📋 54 - 27% open · ⏱️ 15.11.2019): +- [GitHub](https://github.com/RaRe-Technologies/bounter) (👨‍💻 8 · 🔀 44 · 📦 26 · 📋 25 - 64% open · ⏱️ 24.05.2021): ``` - git clone https://github.com/patx/pickledb + git clone https://github.com/RaRe-Technologies/bounter ``` -- [PyPi](https://pypi.org/project/pickledb): +- [PyPi](https://pypi.org/project/bounter) (📥 170 / month): ``` - pip install pickledb + pip install bounter ```
-
Pandas Summary (🥉13 · ⭐ 370) - pandas Dataframe的describe函数功能扩展。Apache-2 +
Pandas Summary (🥉16 · ⭐ 430) - An extension to pandas dataframes describe function. Apache-2 -- [GitHub](https://github.com/polyaxon/datatile) (👨‍💻 7 · 🔀 37 · 📦 3 · 📋 13 - 53% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/polyaxon/datatile) (👨‍💻 8 · 🔀 39 · 📋 13 - 46% open · ⏱️ 14.08.2022): ``` git clone https://github.com/mouradmourafiq/pandas-summary ``` -- [PyPi](https://pypi.org/project/pandas-summary): +- [PyPi](https://pypi.org/project/pandas-summary) (📥 46K / month): ``` pip install pandas-summary ```
-
PandaPy (🥉11 · ⭐ 490) - PandaPy：具有NumPy的速度，性能高于pandas的表格数据实现。❗Unlicensed +
PandaPy (🥉10 · ⭐ 510 · 💤) - PandaPy has the speed of NumPy and the usability of.. ❗Unlicensed -- [GitHub](https://github.com/firmai/pandapy) (👨‍💻 3 · 🔀 56 · 📦 1 · 📋 2 - 50% open · ⏱️ 20.10.2021): +- [GitHub](https://github.com/firmai/pandapy) (👨‍💻 3 · 🔀 58 · 📦 2 · 📋 2 - 50% open · ⏱️ 20.10.2021): ``` git clone https://github.com/firmai/pandapy ``` -- [PyPi](https://pypi.org/project/pandapy) (📥 67 / month): +- [PyPi](https://pypi.org/project/pandapy) (📥 71 / month): ``` pip install pandapy ```

-## 数据读写与提取 +## Data Loading & Extraction -Back to top +Back to top -_用于从各种数据源和格式加载，收集和提取数据的库。_ +_Libraries for loading, collecting, and extracting data from a variety of data sources and formats._ -
Faker (🥇37 · ⭐ 13K) - Faker是一个Python软件包，可为您生成伪造数据。MIT +
Faker (🥇37 · ⭐ 15K) - Faker is a Python package that generates fake data for you. MIT -- [GitHub](https://github.com/joke2k/faker) (👨‍💻 430 · 🔀 1.5K · 📦 45K · 📋 530 - 24% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/joke2k/faker) (👨‍💻 470 · 🔀 1.6K · 📦 67K · 📋 580 - 2% open · ⏱️ 17.08.2022): ``` git clone https://github.com/joke2k/faker ``` -- [PyPi](https://pypi.org/project/Faker) (📥 5.3M / month): +- [PyPi](https://pypi.org/project/Faker) (📥 6.6M / month): ``` pip install Faker ``` -- [Conda](https://anaconda.org/conda-forge/faker) (📥 530K · ⏱️ 07.12.2021): +- [Conda](https://anaconda.org/conda-forge/faker) (📥 620K · ⏱️ 18.08.2022): ``` conda install -c conda-forge faker ```
-
Datasets (🥇34 · ⭐ 12K) - 具有ML模型的最大的即用型NLP数据集合。Apache-2 +
Datasets (🥇32 · ⭐ 14K) - The largest hub of ready-to-use NLP datasets for ML models with.. Apache-2 -- [GitHub](https://github.com/huggingface/datasets) (👨‍💻 360 · 🔀 1.3K · 📦 2.4K · 📋 1.2K - 34% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/huggingface/datasets) (👨‍💻 440 · 🔀 1.8K · 📦 6K · 📋 1.7K - 26% open · ⏱️ 25.08.2022): ``` git clone https://github.com/huggingface/datasets ``` -- [PyPi](https://pypi.org/project/datasets) (📥 540K / month): +- [PyPi](https://pypi.org/project/datasets) (📥 1.2M / month): ``` pip install datasets ```
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xmltodict (🥇31 · ⭐ 4.6K · 💀) - 像处理JSON一样处理XML。MIT +
Tablib (🥇32 · ⭐ 4.2K) - Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c. MIT -- [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 41 · 🔀 420 · 📦 34K · 📋 200 - 32% open · ⏱️ 26.04.2020): +- [GitHub](https://github.com/jazzband/tablib) (👨‍💻 120 · 🔀 540 · 📦 15K · 📋 240 - 12% open · ⏱️ 11.07.2022): ``` - git clone https://github.com/martinblech/xmltodict + git clone https://github.com/jazzband/tablib ``` -- [PyPi](https://pypi.org/project/xmltodict) (📥 15M / month): +- [PyPi](https://pypi.org/project/tablib) (📥 1.2M / month): ``` - pip install xmltodict + pip install tablib ``` -- [Conda](https://anaconda.org/conda-forge/xmltodict) (📥 1.3M · ⏱️ 11.02.2019): +- [Conda](https://anaconda.org/conda-forge/tablib) (📥 75K · ⏱️ 09.04.2022): ``` - conda install -c conda-forge xmltodict + conda install -c conda-forge tablib ```
-
Tablib (🥈29 · ⭐ 4.1K) - 用于XLS，CSV，JSON，YAML和＆c中表格数据集的Python模块。MIT +
xmltodict (🥈31 · ⭐ 4.9K) - Python module that makes working with XML feel like you are.. MIT -- [GitHub](https://github.com/jazzband/tablib) (👨‍💻 120 · 🔀 550 · 📦 13K · 📋 240 - 11% open · ⏱️ 04.11.2021): +- [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 49 · 🔀 430 · 📦 42K · 📋 220 - 27% open · ⏱️ 08.05.2022): ``` - git clone https://github.com/jazzband/tablib + git clone https://github.com/martinblech/xmltodict ``` -- [PyPi](https://pypi.org/project/tablib): +- [PyPi](https://pypi.org/project/xmltodict) (📥 18M / month): ``` - pip install tablib + pip install xmltodict ``` -- [Conda](https://anaconda.org/conda-forge/tablib) (📥 69K · ⏱️ 26.10.2021): +- [Conda](https://anaconda.org/conda-forge/xmltodict) (📥 1.9M · ⏱️ 08.05.2022): ``` - conda install -c conda-forge tablib + conda install -c conda-forge xmltodict ```
-
xlrd (🥈29 · ⭐ 2K) - xlrd是python语言中用于读取excel表格内容的库。❗Unlicensed +
python-magic (🥈29 · ⭐ 2.2K) - A python wrapper for libmagic. ❗Unlicensed -- [GitHub](https://github.com/python-excel/xlrd) (👨‍💻 51 · 🔀 410 · 📦 86K · ⏱️ 21.08.2021): +- [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 55 · 🔀 240 · 📦 31K · 📋 180 - 15% open · ⏱️ 20.06.2022): ``` - git clone https://github.com/python-excel/xlrd + git clone https://github.com/ahupp/python-magic ``` -- [PyPi](https://pypi.org/project/xlrd) (📥 12M / month): +- [PyPi](https://pypi.org/project/python-magic) (📥 5.9M / month): ``` - pip install xlrd + pip install python-magic ``` -- [Conda](https://anaconda.org/conda-forge/xlrd) (📥 2M · ⏱️ 09.01.2021): +- [Conda](https://anaconda.org/conda-forge/python-magic) (📥 160K · ⏱️ 10.06.2022): ``` - conda install -c conda-forge xlrd + conda install -c conda-forge python-magic ```
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TensorFlow Datasets (🥈28 · ⭐ 3.1K) - TFDS是一个高级数据集合。Apache-2 +
xlrd (🥈29 · ⭐ 2K · 💤) - Please use openpyxl where you can... ❗Unlicensed -- [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 240 · 🔀 1.1K · 📋 910 - 33% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/python-excel/xlrd) (👨‍💻 51 · 🔀 420 · 📦 100K · ⏱️ 21.08.2021): ``` - git clone https://github.com/tensorflow/datasets + git clone https://github.com/python-excel/xlrd ``` -- [PyPi](https://pypi.org/project/tensorflow-datasets) (📥 1.9M / month): +- [PyPi](https://pypi.org/project/xlrd) (📥 18M / month): ``` - pip install tensorflow-datasets + pip install xlrd + ``` +- [Conda](https://anaconda.org/conda-forge/xlrd) (📥 2.6M · ⏱️ 09.01.2021): + ``` + conda install -c conda-forge xlrd ```
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snorkel (🥈27 · ⭐ 5K) - 在弱监督环境下快速生成训练数据的系统。Apache-2 +
csvkit (🥈28 · ⭐ 5.1K) - A suite of utilities for converting to and working with CSV, the king of.. MIT -- [GitHub](https://github.com/snorkel-team/snorkel) (👨‍💻 74 · 🔀 780 · 📥 900 · 📦 140 · 📋 960 - 1% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 560 · 📦 1.1K · 📋 860 - 8% open · ⏱️ 11.04.2022): ``` - git clone https://github.com/snorkel-team/snorkel + git clone https://github.com/wireservice/csvkit ``` -- [PyPi](https://pypi.org/project/snorkel) (📥 58K / month): +- [PyPi](https://pypi.org/project/csvkit) (📥 160K / month): ``` - pip install snorkel + pip install csvkit ``` -- [Conda](https://anaconda.org/conda-forge/snorkel) (📥 24K · ⏱️ 23.11.2021): +- [Conda](https://anaconda.org/conda-forge/csvkit) (📥 67K · ⏱️ 20.03.2022): ``` - conda install -c conda-forge snorkel + conda install -c conda-forge csvkit ```
-
csvkit (🥈27 · ⭐ 4.8K) - 一套实用工具，可转换为CSV并操作。MIT +
TensorFlow Datasets (🥈28 · ⭐ 3.4K) - TFDS is a collection of datasets ready to use with.. Apache-2 -- [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 540 · 📦 970 · 📋 830 - 7% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 260 · 🔀 1.3K · 📋 980 - 36% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/wireservice/csvkit - ``` -- [PyPi](https://pypi.org/project/csvkit) (📥 54K / month): - ``` - pip install csvkit + git clone https://github.com/tensorflow/datasets ``` -- [Conda](https://anaconda.org/conda-forge/csvkit) (📥 58K · ⏱️ 13.07.2021): +- [PyPi](https://pypi.org/project/tensorflow-datasets) (📥 1.2M / month): ``` - conda install -c conda-forge csvkit + pip install tensorflow-datasets ```
-
PDFMiner (🥈26 · ⭐ 4.7K · 💀) - Python PDF解析器。MIT +
PDFMiner (🥈26 · ⭐ 4.9K · 💀) - Python PDF Parser (Not actively maintained). Check out pdfminer.six. MIT -- [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 960 · 📦 2.7K · 📋 230 - 82% open · ⏱️ 18.01.2020): +- [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 980 · 📦 3.2K · 📋 240 - 82% open · ⏱️ 18.01.2020): ``` git clone https://github.com/euske/pdfminer ``` -- [PyPi](https://pypi.org/project/pdfminer) (📥 150K / month): +- [PyPi](https://pypi.org/project/pdfminer) (📥 120K / month): ``` pip install pdfminer ``` -- [Conda](https://anaconda.org/conda-forge/pdfminer) (📥 20K · ⏱️ 15.02.2021): +- [Conda](https://anaconda.org/conda-forge/pdfminer) (📥 24K · ⏱️ 15.02.2021): ``` conda install -c conda-forge pdfminer ```
-
smart-open (🥈26 · ⭐ 2.3K) - 用于大文件（S3，HDFS，gzip，bz2 ...）流传输的实用程序。MIT +
smart-open (🥈26 · ⭐ 2.6K) - Utils for streaming large files (S3, HDFS, gzip, bz2...). MIT -- [GitHub](https://github.com/RaRe-Technologies/smart_open) (👨‍💻 89 · 🔀 290 · 📋 330 - 18% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/RaRe-Technologies/smart_open) (👨‍💻 96 · 🔀 310 · 📋 360 - 16% open · ⏱️ 21.08.2022): ``` git clone https://github.com/RaRe-Technologies/smart_open ``` -- [PyPi](https://pypi.org/project/smart-open) (📥 16M / month): +- [PyPi](https://pypi.org/project/smart-open) (📥 11M / month): ``` pip install smart-open ```
-
python-magic (🥉25 · ⭐ 2K) - 用于libmagic的python包装器。❗Unlicensed +
snorkel (🥉25 · ⭐ 5.2K) - A system for quickly generating training data with weak supervision. Apache-2 -- [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 53 · 🔀 220 · 📦 21K · 📋 160 - 14% open · ⏱️ 23.10.2021): +- [GitHub](https://github.com/snorkel-team/snorkel) (👨‍💻 78 · 🔀 820 · 📥 980 · 📦 190 · 📋 970 - 1% open · ⏱️ 29.07.2022): ``` - git clone https://github.com/ahupp/python-magic + git clone https://github.com/snorkel-team/snorkel ``` -- [PyPi](https://pypi.org/project/python-magic): +- [PyPi](https://pypi.org/project/snorkel) (📥 65K / month): ``` - pip install python-magic + pip install snorkel ``` -- [Conda](https://anaconda.org/conda-forge/python-magic) (📥 110K · ⏱️ 05.11.2021): +- [Conda](https://anaconda.org/conda-forge/snorkel) (📥 30K · ⏱️ 29.07.2022): ``` - conda install -c conda-forge python-magic + conda install -c conda-forge snorkel ```
-
textract (🥉24 · ⭐ 3.2K) - 从任何文档中提取文本。MIT +
Intake (🥉24 · ⭐ 800) - Intake is a lightweight package for finding, investigating, loading and.. BSD-2 -- [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 39 · 🔀 440 · 📋 200 - 37% open · ⏱️ 21.08.2021): +- [GitHub](https://github.com/intake/intake) (👨‍💻 78 · 🔀 120 · 📦 480 · 📋 310 - 27% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/deanmalmgren/textract + git clone https://github.com/intake/intake ``` -- [PyPi](https://pypi.org/project/textract) (📥 74K / month): +- [PyPi](https://pypi.org/project/intake) (📥 21K / month): ``` - pip install textract + pip install intake ``` -- [Conda](https://anaconda.org/conda-forge/textract) (📥 13K · ⏱️ 22.08.2021): +- [Conda](https://anaconda.org/conda-forge/intake) (📥 220K · ⏱️ 10.01.2022): ``` - conda install -c conda-forge textract + conda install -c conda-forge intake ```
-
Intake (🥉24 · ⭐ 660) - Intake是一个轻量级的程序包，用于查找，调查，加载等。BSD-2 +
textract (🥉23 · ⭐ 3.3K) - extract text from any document. no muss. no fuss. MIT -- [GitHub](https://github.com/intake/intake) (👨‍💻 67 · 🔀 110 · 📦 320 · 📋 280 - 25% open · ⏱️ 01.12.2021): +- [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 40 · 🔀 470 · 📋 210 - 39% open · ⏱️ 10.03.2022): ``` - git clone https://github.com/intake/intake + git clone https://github.com/deanmalmgren/textract ``` -- [PyPi](https://pypi.org/project/intake) (📥 12K / month): +- [PyPi](https://pypi.org/project/textract) (📥 120K / month): ``` - pip install intake + pip install textract ``` -- [Conda](https://anaconda.org/conda-forge/intake) (📥 120K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/textract) (📥 16K · ⏱️ 10.03.2022): ``` - conda install -c conda-forge intake + conda install -c conda-forge textract ```
-
SDV (🥉23 · ⭐ 600) - 用于表格，关系和时间序列数据的综合数据生成。MIT +
SDV (🥉23 · ⭐ 980) - Synthetic Data Generation for tabular, relational and time series data. ❗Unlicensed -- [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 39 · 🔀 100 · 📦 41 · 📋 410 - 33% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 41 · 🔀 160 · 📦 81 · 📋 580 - 20% open · ⏱️ 19.08.2022): ``` git clone https://github.com/sdv-dev/SDV ``` -- [PyPi](https://pypi.org/project/sdv) (📥 23K / month): +- [PyPi](https://pypi.org/project/sdv) (📥 33K / month): ``` pip install sdv ```
-
tabulator-py (🥉22 · ⭐ 220 · 💤) - 用于读取和写入图像数据的Python库。MIT +
tabulator-py (🥉22 · ⭐ 230 · 💀) - Python library for reading and writing tabular data via streams. MIT -- [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 670 · ⏱️ 22.03.2021): +- [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 830 · ⏱️ 22.03.2021): ``` git clone https://github.com/frictionlessdata/tabulator-py ``` -- [PyPi](https://pypi.org/project/tabulator) (📥 370K / month): +- [PyPi](https://pypi.org/project/tabulator) (📥 210K / month): ``` pip install tabulator ``` -- [Conda](https://anaconda.org/conda-forge/tabulator-py) (📥 46K · ⏱️ 24.07.2018): +- [Conda](https://anaconda.org/conda-forge/tabulator-py) (📥 48K · ⏱️ 24.07.2018): ``` conda install -c conda-forge tabulator-py ```
-
messytables (🥉21 · ⭐ 380 · 💀) - 解析混乱的表格数据的工具。❗Unlicensed +
pyexcel-xlsx (🥉22 · ⭐ 110 · 💀) - A wrapper library to read, manipulate and write data.. ❗Unlicensed -- [GitHub](https://github.com/okfn/messytables) (👨‍💻 44 · 🔀 100 · 📦 220 · 📋 85 - 35% open · ⏱️ 13.11.2019): +- [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 23 · 📥 51 · 📦 1.7K · 📋 34 - 26% open · ⏱️ 28.11.2020): ``` - git clone https://github.com/okfn/messytables + git clone https://github.com/pyexcel/pyexcel-xlsx ``` -- [PyPi](https://pypi.org/project/messytables) (📥 9.2K / month): +- [PyPi](https://pypi.org/project/pyexcel-xlsx) (📥 88K / month): ``` - pip install messytables + pip install pyexcel-xlsx + ``` +- [Conda](https://anaconda.org/conda-forge/pyexcel-xlsx) (📥 21K · ⏱️ 10.10.2020): + ``` + conda install -c conda-forge pyexcel-xlsx ```
-
pandas-datareader (🥉20 · ⭐ 2.2K) - 从各种各样的网络来源中提取数据。❗Unlicensed +
messytables (🥉21 · ⭐ 380 · 💀) - Tools for parsing messy tabular data. This is now.. ❗Unlicensed -- [GitHub](https://github.com/pydata/pandas-datareader) (👨‍💻 83 · 🔀 550 · 📋 480 - 19% open · ⏱️ 07.08.2021): +- [GitHub](https://github.com/okfn/messytables) (👨‍💻 44 · 🔀 100 · 📦 250 · 📋 85 - 35% open · ⏱️ 13.11.2019): ``` - git clone https://github.com/pydata/pandas-datareader - ``` -- [PyPi](https://pypi.org/project/pandas-datareader) (📥 240K / month): - ``` - pip install pandas-datareader + git clone https://github.com/okfn/messytables ``` -- [Conda](https://anaconda.org/conda-forge/pandas-datareader) (📥 160K · ⏱️ 14.07.2021): +- [PyPi](https://pypi.org/project/messytables) (📥 10K / month): ``` - conda install -c conda-forge pandas-datareader + pip install messytables ```
-
pyexcel-xlsx (🥉20 · ⭐ 95 · 💀) - 一个包装器库，用于在xlsx和xlsm等文件格式中读取，操作和写入数据。❗Unlicensed +
rows (🥉20 · ⭐ 810) - A common, beautiful interface to tabular data, no matter the format. ❗️LGPL-3.0 -- [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 17 · 📥 51 · 📦 1.4K · 📋 33 - 39% open · ⏱️ 28.11.2020): +- [GitHub](https://github.com/turicas/rows) (👨‍💻 31 · 🔀 140 · 📥 38 · 📦 140 · 📋 290 - 49% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/pyexcel/pyexcel-xlsx - ``` -- [PyPi](https://pypi.org/project/pyexcel-xlsx) (📥 110K / month): - ``` - pip install pyexcel-xlsx + git clone https://github.com/turicas/rows ``` -- [Conda](https://anaconda.org/conda-forge/pyexcel-xlsx) (📥 19K · ⏱️ 10.10.2020): +- [PyPi](https://pypi.org/project/rows) (📥 880 / month): ``` - conda install -c conda-forge pyexcel-xlsx + pip install rows ```
-
Camelot (🥉19 · ⭐ 3.1K · 💀) - Camelot：简单的PDF表提取。❗Unlicensed +
Camelot (🥉19 · ⭐ 3.3K · 💀) - Camelot: PDF Table Extraction for Humans. ❗Unlicensed -- [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 330 · 📋 350 - 21% open · ⏱️ 15.10.2019): +- [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 330 · 📋 360 - 23% open · ⏱️ 15.10.2019): ``` git clone https://github.com/atlanhq/camelot ``` -- [PyPi](https://pypi.org/project/camelot-py) (📥 43K / month): +- [PyPi](https://pypi.org/project/camelot-py) (📥 79K / month): ``` pip install camelot-py ```
-
datatest (🥉19 · ⭐ 250) - 用于测试驱动的数据整理和数据验证的工具。❗Unlicensed +
pandas-datareader (🥉19 · ⭐ 2.4K) - Extract data from a wide range of Internet sources.. ❗Unlicensed -- [GitHub](https://github.com/shawnbrown/datatest) (👨‍💻 7 · 🔀 12 · 📦 59 · 📋 52 - 19% open · ⏱️ 05.12.2021): +- [GitHub](https://github.com/pydata/pandas-datareader) (👨‍💻 85 · 🔀 590 · 📋 500 - 20% open · ⏱️ 16.03.2022): ``` - git clone https://github.com/shawnbrown/datatest + git clone https://github.com/pydata/pandas-datareader ``` -- [PyPi](https://pypi.org/project/datatest) (📥 5.6K / month): +- [PyPi](https://pypi.org/project/pandas-datareader) (📥 320K / month): ``` - pip install datatest + pip install pandas-datareader + ``` +- [Conda](https://anaconda.org/conda-forge/pandas-datareader) (📥 190K · ⏱️ 14.07.2021): + ``` + conda install -c conda-forge pandas-datareader ```
-
Singer (🥉18 · ⭐ 910 · 💤) - 在数据库，Web API，文件，队列等之间移动数据的标准。❗️AGPL-3.0 +
datatest (🥉19 · ⭐ 260 · 💤) - Tools for test driven data-wrangling and data validation. ❗Unlicensed -- [GitHub](https://github.com/singer-io/getting-started) (👨‍💻 26 · 🔀 120 · 📋 37 - 51% open · ⏱️ 29.04.2021): +- [GitHub](https://github.com/shawnbrown/datatest) (👨‍💻 7 · 🔀 13 · 📦 74 · 📋 55 - 21% open · ⏱️ 05.12.2021): ``` - git clone https://github.com/singer-io/getting-started + git clone https://github.com/shawnbrown/datatest ``` -- [PyPi](https://pypi.org/project/singer-python) (📥 130K / month): +- [PyPi](https://pypi.org/project/datatest) (📥 8.3K / month): ``` - pip install singer-python + pip install datatest ```
-
rows (🥉18 · ⭐ 780) - 通用美观的表格数据界面。❗️LGPL-3.0 +
Singer (🥉17 · ⭐ 1K · 💀) - Standard for moving data between databases, web APIs, files,.. ❗️AGPL-3.0 -- [GitHub](https://github.com/turicas/rows) (👨‍💻 30 · 🔀 130 · 📥 37 · 📦 130 · 📋 290 - 48% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/singer-io/getting-started) (👨‍💻 26 · 🔀 140 · 📋 38 - 52% open · ⏱️ 29.04.2021): ``` - git clone https://github.com/turicas/rows + git clone https://github.com/singer-io/getting-started ``` -- [PyPi](https://pypi.org/project/rows): +- [PyPi](https://pypi.org/project/singer-python) (📥 270K / month): ``` - pip install rows + pip install singer-python ```
-
openpyxl (🥉15 · ⭐ 31) - 一个用于读取/写入Excel 2010 xlsx/xlsm文件的Python库。MIT +
openpyxl (🥉16 · ⭐ 45) - A Python library to read/write Excel 2010 xlsx/xlsm files. MIT -- [PyPi](https://pypi.org/project/openpyxl) (📥 20M / month): +- [PyPi](https://pypi.org/project/openpyxl) (📥 35M / month): ``` pip install openpyxl ``` -- [GitLab](https://foss.heptapod.net/openpyxl/openpyxl) (🔀 0 · 📋 1.8K - 12% open · ⏱️ 05.10.2021): +- [GitLab](https://foss.heptapod.net/openpyxl/openpyxl) (🔀 0 · 📋 1.9K - 12% open · ⏱️ 07.07.2022): ``` git clone https://foss.heptapod.net/openpyxl/openpyxl ``` -- [Conda](https://anaconda.org/anaconda/openpyxl) (📥 63K · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/anaconda/openpyxl) (📥 98K · ⏱️ 07.07.2022): ``` conda install -c anaconda openpyxl ``` @@ -6013,473 +6013,473 @@ _用于从各种数据源和格式加载，收集和提取数据的库。_

-## 网页抓取和爬虫 +## Web Scraping & Crawling -Back to top +Back to top -_用于Web抓取、爬虫，下载和挖掘的库以及库。_ +_Libraries for web scraping, crawling, downloading, and mining as well as libraries._ -🔗 Python Web Scraping ( ⭐ 1.4K) - Collection of web-scraping and crawling libraries. +🔗 Python Web Scraping ( ⭐ 1.6K) - Collection of web-scraping and crawling libraries.
-## 数据管道和流处理 +## Data Pipelines & Streaming -Back to top +Back to top -_用于数据批处理和流处理，工作流自动化，作业调度和其他数据管道任务的库。_ +_Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks._ -
Celery (🥇37 · ⭐ 18K) - 基于分布式消息传递的异步任务队列/作业队列。❗Unlicensed +
Celery (🥇36 · ⭐ 20K) - Asynchronous task queue/job queue based on distributed message.. ❗Unlicensed -- [GitHub](https://github.com/celery/celery) (👨‍💻 1.2K · 🔀 4K · 📦 62K · 📋 4.6K - 9% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/celery/celery) (👨‍💻 1.2K · 🔀 4.2K · 📦 75K · 📋 4.7K - 10% open · ⏱️ 25.08.2022): ``` git clone https://github.com/celery/celery ``` -- [PyPi](https://pypi.org/project/celery) (📥 4.9M / month): +- [PyPi](https://pypi.org/project/celery) (📥 5.9M / month): ``` pip install celery ``` -- [Conda](https://anaconda.org/conda-forge/celery) (📥 760K · ⏱️ 29.06.2021): +- [Conda](https://anaconda.org/conda-forge/celery) (📥 930K · ⏱️ 29.05.2022): ``` conda install -c conda-forge celery ```
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joblib (🥇34 · ⭐ 2.6K) - 使用Python函数进行计算。BSD-3 +
luigi (🥇34 · ⭐ 16K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 -- [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 300 · 📦 150K · 📋 660 - 43% open · ⏱️ 08.11.2021): +- [GitHub](https://github.com/spotify/luigi) (👨‍💻 590 · 🔀 2.3K · 📦 1.8K · 📋 940 - 7% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/joblib/joblib + git clone https://github.com/spotify/luigi ``` -- [PyPi](https://pypi.org/project/joblib) (📥 27M / month): +- [PyPi](https://pypi.org/project/luigi) (📥 670K / month): ``` - pip install joblib + pip install luigi ``` -- [Conda](https://anaconda.org/conda-forge/joblib) (📥 6.5M · ⏱️ 07.10.2021): +- [Conda](https://anaconda.org/anaconda/luigi) (📥 11K · ⏱️ 02.05.2022): ``` - conda install -c conda-forge joblib + conda install -c anaconda luigi ```
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Dagster (🥇31 · ⭐ 4.1K) - 用于机器学习，分析和ETL的数据协调器。Apache-2 +
joblib (🥇33 · ⭐ 2.9K) - Computing with Python functions. BSD-3 -- [GitHub](https://github.com/dagster-io/dagster) (👨‍💻 180 · 🔀 480 · 📦 270 · 📋 3.5K - 22% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 330 · 📦 210K · 📋 710 - 43% open · ⏱️ 20.05.2022): ``` - git clone https://github.com/dagster-io/dagster + git clone https://github.com/joblib/joblib ``` -- [PyPi](https://pypi.org/project/dagster) (📥 190K / month): +- [PyPi](https://pypi.org/project/joblib) (📥 23M / month): ``` - pip install dagster + pip install joblib ``` -- [Conda](https://anaconda.org/conda-forge/dagster) (📥 420K · ⏱️ 10.12.2021): +- [Conda](https://anaconda.org/conda-forge/joblib) (📥 11M · ⏱️ 07.10.2021): ``` - conda install -c conda-forge dagster + conda install -c conda-forge joblib ```
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Airflow (🥇29 · ⭐ 24K) - 代码实现的创建，安排和监视工作流的平台。Apache-2 +
rq (🥇32 · ⭐ 8.5K) - Simple job queues for Python. ❗Unlicensed -- [GitHub](https://github.com/apache/airflow) (👨‍💻 2.2K · 🔀 9.4K · 📥 220K · 📋 4.6K - 17% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/rq/rq) (👨‍💻 270 · 🔀 1.3K · 📦 11K · 📋 980 - 19% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/apache/airflow - ``` -- [PyPi](https://pypi.org/project/apache-airflow) (📥 4.3M / month): - ``` - pip install apache-airflow + git clone https://github.com/rq/rq ``` -- [Conda](https://anaconda.org/conda-forge/airflow) (📥 510K · ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/rq) (📥 680K / month): ``` - conda install -c conda-forge airflow + pip install rq ``` -- [Docker Hub](https://hub.docker.com/r/apache/airflow) (📥 55M · ⭐ 310 · ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/conda-forge/rq) (📥 76K · ⏱️ 30.06.2021): ``` - docker pull apache/airflow + conda install -c conda-forge rq ```
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Prefect (🥇29 · ⭐ 7.9K) - 自动化数据的最简单方法。Apache-2 +
Dagster (🥇32 · ⭐ 5.3K) - A data orchestrator for machine learning, analytics, and ETL. Apache-2 -- [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 280 · 🔀 730 · 📦 530 · 📋 2K - 18% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/dagster-io/dagster) (👨‍💻 230 · 🔀 650 · 📦 500 · 📋 4.4K - 23% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/PrefectHQ/prefect + git clone https://github.com/dagster-io/dagster ``` -- [PyPi](https://pypi.org/project/prefect): +- [PyPi](https://pypi.org/project/dagster) (📥 480K / month): ``` - pip install prefect + pip install dagster ``` -- [Conda](https://anaconda.org/conda-forge/prefect) (📥 230K · ⏱️ 01.12.2021): +- [Conda](https://anaconda.org/conda-forge/dagster) (📥 610K · ⏱️ 12.08.2022): ``` - conda install -c conda-forge prefect + conda install -c conda-forge dagster ```
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Beam (🥇29 · ⭐ 5.1K) - 统一的编程模型，用于定义和执行数据处理。❗Unlicensed +
Beam (🥈31 · ⭐ 5.8K) - Unified programming model to define and execute data processing.. Apache-2 -- [GitHub](https://github.com/apache/beam) (👨‍💻 1.2K · 🔀 3.2K · ⏱️ 16.12.2021): +- [GitHub](https://github.com/apache/beam) (👨‍💻 1.3K · 🔀 3.5K · 📋 4.4K - 89% open · ⏱️ 25.08.2022): ``` git clone https://github.com/apache/beam ``` -- [PyPi](https://pypi.org/project/apache-beam) (📥 3.8M / month): +- [PyPi](https://pypi.org/project/apache-beam) (📥 6.6M / month): ``` pip install apache-beam ```
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luigi (🥈28 · ⭐ 15K) - Luigi是一个Python模块，可帮助您构建复杂的批处理管道。Apache-2 +
dbt (🥈30 · ⭐ 5.4K) - dbt (data build tool) enables data analysts and engineers to transform.. Apache-2 -- [GitHub](https://github.com/spotify/luigi) (👨‍💻 570 · 🔀 2.2K · 📦 1.6K · 📋 920 - 7% open · ⏱️ 27.11.2021): +- [GitHub](https://github.com/dbt-labs/dbt-core) (👨‍💻 230 · 🔀 960 · 📥 520 · 📦 660 · 📋 3K - 10% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/spotify/luigi + git clone https://github.com/fishtown-analytics/dbt ``` -- [PyPi](https://pypi.org/project/luigi): +- [PyPi](https://pypi.org/project/dbt) (📥 170K / month): ``` - pip install luigi + pip install dbt ``` -- [Conda](https://anaconda.org/anaconda/luigi) (📥 8.5K · ⏱️ 17.04.2021): +- [Conda](https://anaconda.org/conda-forge/dbt) (📥 210K · ⏱️ 09.12.2021): ``` - conda install -c anaconda luigi + conda install -c conda-forge dbt ```
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rq (🥈28 · ⭐ 8.1K) - 适用于Python的简单作业队列。❗Unlicensed +
Airflow (🥈29 · ⭐ 28K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 -- [GitHub](https://github.com/rq/rq) (👨‍💻 250 · 🔀 1.2K · 📦 9.2K · 📋 930 - 16% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/apache/airflow) (👨‍💻 2.5K · 🔀 11K · 📥 340K · 📋 6K - 11% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/rq/rq - ``` -- [PyPi](https://pypi.org/project/rq): - ``` - pip install rq - ``` -- [Conda](https://anaconda.org/conda-forge/rq) (📥 66K · ⏱️ 30.06.2021): - ``` - conda install -c conda-forge rq + git clone https://github.com/apache/airflow ``` -
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dbt (🥈28 · ⭐ 3.9K) - dbt（数据构建工具）方便数据分析人员和工程师快速使用。Apache-2 - -- [GitHub](https://github.com/dbt-labs/dbt-core) (👨‍💻 190 · 🔀 700 · 📥 21 · 📦 230 · 📋 2.4K - 11% open · ⏱️ 14.12.2021): - +- [PyPi](https://pypi.org/project/apache-airflow) (📥 8.9M / month): ``` - git clone https://github.com/fishtown-analytics/dbt + pip install apache-airflow ``` -- [PyPi](https://pypi.org/project/dbt): +- [Conda](https://anaconda.org/conda-forge/airflow) (📥 700K · ⏱️ 25.08.2022): ``` - pip install dbt + conda install -c conda-forge airflow ``` -- [Conda](https://anaconda.org/conda-forge/dbt) (📥 190K · ⏱️ 09.12.2021): +- [Docker Hub](https://hub.docker.com/r/apache/airflow) (📥 82M · ⭐ 380 · ⏱️ 23.08.2022): ``` - conda install -c conda-forge dbt + docker pull apache/airflow ```
-
mrjob (🥈27 · ⭐ 2.6K · 💀) - 在Hadoop或Amazon Web Services上运行MapReduce作业。Apache-2 +
mrjob (🥈29 · ⭐ 2.6K · 💀) - Run MapReduce jobs on Hadoop or Amazon Web Services. Apache-2 -- [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 570 · 📦 900 · 📋 1.3K - 15% open · ⏱️ 16.11.2020): +- [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 580 · 📦 1.1K · 📋 1.3K - 15% open · ⏱️ 16.11.2020): ``` git clone https://github.com/Yelp/mrjob ``` -- [PyPi](https://pypi.org/project/mrjob): +- [PyPi](https://pypi.org/project/mrjob) (📥 76K / month): ``` pip install mrjob ``` -- [Conda](https://anaconda.org/conda-forge/mrjob) (📥 420K · ⏱️ 24.12.2020): +- [Conda](https://anaconda.org/conda-forge/mrjob) (📥 490K · ⏱️ 06.02.2022): ``` conda install -c conda-forge mrjob ```
-
petl (🥈27 · ⭐ 950) - Python提取转换并加载数据表。MIT +
Prefect (🥈28 · ⭐ 9.9K) - The easiest way to automate your data. Apache-2 -- [GitHub](https://github.com/petl-developers/petl) (👨‍💻 51 · 🔀 160 · 📦 580 · 📋 420 - 17% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 60 · 🔀 950 · 📦 1.1K · 📋 2.6K - 25% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/petl-developers/petl + git clone https://github.com/PrefectHQ/prefect ``` -- [PyPi](https://pypi.org/project/petl) (📥 46K / month): +- [PyPi](https://pypi.org/project/prefect) (📥 400K / month): ``` - pip install petl + pip install prefect ``` -- [Conda](https://anaconda.org/conda-forge/petl) (📥 54K · ⏱️ 05.04.2021): +- [Conda](https://anaconda.org/conda-forge/prefect) (📥 310K · ⏱️ 23.08.2022): ``` - conda install -c conda-forge petl + conda install -c conda-forge prefect ```
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faust (🥈26 · ⭐ 5.9K · 💀) - Python流处理。❗Unlicensed +
Kedro (🥈28 · ⭐ 7.5K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 -- [GitHub](https://github.com/robinhood/faust) (👨‍💻 93 · 🔀 490 · 📦 900 · 📋 460 - 48% open · ⏱️ 09.10.2020): +- [GitHub](https://github.com/kedro-org/kedro) (👨‍💻 160 · 🔀 680 · 📦 1K · 📋 870 - 17% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/robinhood/faust + git clone https://github.com/quantumblacklabs/kedro ``` -- [PyPi](https://pypi.org/project/faust) (📥 420K / month): +- [PyPi](https://pypi.org/project/kedro) (📥 420K / month): ``` - pip install faust + pip install kedro ```
-
Kedro (🥈26 · ⭐ 4.8K) - 用于创建可重现，可维护和模块化的Python框架。Apache-2 +
petl (🥈28 · ⭐ 1K) - Python Extract Transform and Load Tables of Data. MIT -- [GitHub](https://github.com/quantumblacklabs/kedro) (👨‍💻 130 · 🔀 530 · 📦 640 · 📋 590 - 7% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/petl-developers/petl) (👨‍💻 55 · 🔀 170 · 📦 790 · 📋 440 - 16% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/quantumblacklabs/kedro + git clone https://github.com/petl-developers/petl ``` -- [PyPi](https://pypi.org/project/kedro) (📥 230K / month): +- [PyPi](https://pypi.org/project/petl) (📥 280K / month): ``` - pip install kedro + pip install petl + ``` +- [Conda](https://anaconda.org/conda-forge/petl) (📥 120K · ⏱️ 22.08.2022): + ``` + conda install -c conda-forge petl ```
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Hub (🥈26 · ⭐ 4K) - TensorFlow/PyTorch最快的非结构化数据集管理。MPL-2.0 +
PyFunctional (🥈26 · ⭐ 2.1K) - Python library for creating data pipelines with chain functional.. MIT -- [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 88 · 🔀 320 · 📦 140 · 📋 310 - 14% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 26 · 🔀 110 · 📦 460 · 📋 130 - 5% open · ⏱️ 05.08.2022): ``` - git clone https://github.com/activeloopai/Hub + git clone https://github.com/EntilZha/PyFunctional ``` -- [PyPi](https://pypi.org/project/hub) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/pyfunctional) (📥 230K / month): ``` - pip install hub + pip install pyfunctional ```
-
Great Expectations (🥈24 · ⭐ 5.8K) - 通过数据测试，文档编制和性能分析，帮助数据团队加速流水线效率。Apache-2 +
Great Expectations (🥈25 · ⭐ 7.1K) - Always know what to expect from your data. Apache-2 -- [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 250 · 🔀 780 · 📋 1.1K - 11% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 320 · 🔀 1K · 📋 1.4K - 12% open · ⏱️ 26.08.2022): ``` git clone https://github.com/great-expectations/great_expectations ``` -- [PyPi](https://pypi.org/project/great_expectations) (📥 2.6M / month): +- [PyPi](https://pypi.org/project/great_expectations) (📥 5.3M / month): ``` pip install great_expectations ```
-
TaskTiger (🥉22 · ⭐ 1.1K) - 使用Redis的Python任务队列。MIT +
faust (🥈25 · ⭐ 6.3K · 💀) - Python Stream Processing. ❗Unlicensed -- [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 24 · 🔀 59 · 📦 21 · 📋 57 - 38% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/robinhood/faust) (👨‍💻 94 · 🔀 530 · 📦 1.1K · 📋 460 - 48% open · ⏱️ 09.10.2020): ``` - git clone https://github.com/closeio/tasktiger + git clone https://github.com/robinhood/faust ``` -- [PyPi](https://pypi.org/project/tasktiger) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/faust) (📥 32K / month): ``` - pip install tasktiger + pip install faust ```
-
PyFunctional (🥉21 · ⭐ 1.9K) - 用于创建具有链功能的数据管道的Python库。MIT +
TFX (🥈25 · ⭐ 1.8K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 -- [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 25 · 🔀 100 · 📦 370 · 📋 120 - 4% open · ⏱️ 05.11.2021): +- [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 150 · 🔀 580 · 📋 780 - 26% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/EntilZha/PyFunctional + git clone https://github.com/tensorflow/tfx ``` -- [PyPi](https://pypi.org/project/pyfunctional): +- [PyPi](https://pypi.org/project/tfx) (📥 370K / month): ``` - pip install pyfunctional + pip install tfx ```
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bonobo (🥉21 · ⭐ 1.5K · 💤) - 提取适用于Python 3.5+的Transform Load。Apache-2 +
ploomber (🥉24 · ⭐ 2.6K) - Lean Data Science workflows: develop and test locally. Deploy to.. Apache-2 -- [GitHub](https://github.com/python-bonobo/bonobo) (👨‍💻 37 · 🔀 120 · 📦 130 · 📋 180 - 38% open · ⏱️ 10.03.2021): +- [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 59 · 🔀 180 · 📦 51 · 📋 790 - 25% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/python-bonobo/bonobo + git clone https://github.com/ploomber/ploomber ``` -- [PyPi](https://pypi.org/project/bonobo) (📥 4.3K / month): +- [PyPi](https://pypi.org/project/ploomber) (📥 15K / month): ``` - pip install bonobo + pip install ploomber ```
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streamparse (🥉21 · ⭐ 1.4K · 💤) - 在Apache Storm拓扑中运行Python。 Pythonic API，CLI 等。❗Unlicensed +
streamparse (🥉24 · ⭐ 1.5K) - Run Python in Apache Storm topologies. Pythonic API, CLI.. Apache-2 -- [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 41 · 🔀 210 · 📦 52 · 📋 320 - 19% open · ⏱️ 18.12.2020): +- [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 43 · 🔀 210 · 📦 55 · 📋 330 - 19% open · ⏱️ 18.07.2022): ``` git clone https://github.com/Parsely/streamparse ``` -- [PyPi](https://pypi.org/project/streamparse) (📥 5.6K / month): +- [PyPi](https://pypi.org/project/streamparse) (📥 2.2K / month): ``` pip install streamparse ```
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pysparkling (🥉21 · ⭐ 240 · 💤) - Apache Spark的RDD和DStream的纯Python实现。❗Unlicensed +
Hub (🥉23 · ⭐ 4.8K) - Fastest unstructured dataset management for TensorFlow/PyTorch... MPL-2.0 -- [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 41 · 📦 81 · 📋 27 - 22% open · ⏱️ 22.02.2021): +- [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 99 · 🔀 390 · 📋 380 - 11% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/svenkreiss/pysparkling + git clone https://github.com/activeloopai/Hub ``` -- [PyPi](https://pypi.org/project/pysparkling) (📥 20K / month): +- [PyPi](https://pypi.org/project/hub) (📥 3.7K / month): ``` - pip install pysparkling + pip install hub ```
-
dpark (🥉20 · ⭐ 2.7K · 💤) - dpark是Python中与MapReduce相似的框架。BSD-3 +
bonobo (🥉21 · ⭐ 1.5K · 💀) - Extract Transform Load for Python 3.5+. Apache-2 -- [GitHub](https://github.com/douban/dpark) (👨‍💻 35 · 🔀 540 · 📦 4 · ⏱️ 25.12.2020): +- [GitHub](https://github.com/python-bonobo/bonobo) (👨‍💻 37 · 🔀 130 · 📦 140 · 📋 180 - 39% open · ⏱️ 10.03.2021): ``` - git clone https://github.com/douban/dpark + git clone https://github.com/python-bonobo/bonobo ``` -- [PyPi](https://pypi.org/project/dpark) (📥 82 / month): +- [PyPi](https://pypi.org/project/bonobo) (📥 7.3K / month): ``` - pip install dpark + pip install bonobo ```
-
TFX (🥉20 · ⭐ 1.7K) - TFX是用于部署机器学习生产流水线的端到端平台。Apache-2 +
TaskTiger (🥉21 · ⭐ 1.2K) - Python task queue using Redis. MIT -- [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 120 · 🔀 510 · 📋 710 - 32% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 24 · 🔀 64 · 📦 23 · 📋 58 - 37% open · ⏱️ 25.04.2022): ``` - git clone https://github.com/tensorflow/tfx + git clone https://github.com/closeio/tasktiger ``` -- [PyPi](https://pypi.org/project/tfx): +- [PyPi](https://pypi.org/project/tasktiger) (📥 1.5K / month): ``` - pip install tfx + pip install tasktiger ```
-
mrq (🥉20 · ⭐ 860 · 💤) - Mr. Queue - 使用Redis和gevent的Python中的分布式worker任务队列。MIT +
pdpipe (🥉21 · ⭐ 680) - Easy pipelines for pandas DataFrames. MIT -- [GitHub](https://github.com/pricingassistant/mrq) (👨‍💻 37 · 🔀 110 · 📦 27 · 📋 170 - 30% open · ⏱️ 13.12.2020): +- [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 10 · 🔀 42 · 📦 41 · 📋 51 - 31% open · ⏱️ 09.08.2022): ``` - git clone https://github.com/pricingassistant/mrq + git clone https://github.com/pdpipe/pdpipe ``` -- [PyPi](https://pypi.org/project/mrq) (📥 260 / month): +- [PyPi](https://pypi.org/project/pdpipe) (📥 1.7K / month): ``` - pip install mrq + pip install pdpipe ```
-
ploomber (🥉20 · ⭐ 790) - 精益数据科学工作流程。Apache-2 +
dpark (🥉20 · ⭐ 2.7K · 💀) - Python clone of Spark, a MapReduce alike framework in Python. BSD-3 -- [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 23 · 🔀 64 · 📦 22 · 📋 400 - 19% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/douban/dpark) (👨‍💻 35 · 🔀 540 · 📦 5 · 📋 61 - 1% open · ⏱️ 25.12.2020): ``` - git clone https://github.com/ploomber/ploomber + git clone https://github.com/douban/dpark ``` -- [PyPi](https://pypi.org/project/ploomber) (📥 2.7K / month): +- [PyPi](https://pypi.org/project/dpark) (📥 32 / month): ``` - pip install ploomber + pip install dpark ```
-
zenml (🥉18 · ⭐ 1.5K) - ZenML：MLOps框架。Apache-2 +
zenml (🥉20 · ⭐ 2.3K) - ZenML : MLOps framework to create reproducible ML pipelines for.. Apache-2 -- [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 21 · 🔀 83 · 📋 49 - 8% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 46 · 🔀 190 · 📋 110 - 22% open · ⏱️ 25.08.2022): ``` git clone https://github.com/maiot-io/zenml ``` -- [PyPi](https://pypi.org/project/zenml) (📥 460 / month): +- [PyPi](https://pypi.org/project/zenml) (📥 2.5K / month): ``` pip install zenml ```
-
Optimus (🥉18 · ⭐ 1.1K) - 基于pandas、dask等的敏捷数据预处理工作流程。Apache-2 +
Pypeline (🥉20 · ⭐ 1.4K) - Concurrent data pipelines in Python . MIT -- [GitHub](https://github.com/hi-primus/optimus) (👨‍💻 23 · 🔀 200 · 📋 220 - 13% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 13 · 🔀 80 · 📋 59 - 25% open · ⏱️ 23.06.2022): ``` - git clone https://github.com/ironmussa/Optimus + git clone https://github.com/cgarciae/pypeln ``` -- [PyPi](https://pypi.org/project/optimuspyspark) (📥 7.4K / month): +- [PyPi](https://pypi.org/project/pypeln) (📥 8.3K / month): ``` - pip install optimuspyspark + pip install pypeln ```
-
spark-deep-learning (🥉17 · ⭐ 1.9K) - 适用于Apache Spark的深度学习管道。Apache-2 +
pysparkling (🥉20 · ⭐ 250 · 💀) - A pure Python implementation of Apache Spark's RDD and.. ❗Unlicensed -- [GitHub](https://github.com/databricks/spark-deep-learning) (👨‍💻 16 · 🔀 460 · 📦 19 · 📋 100 - 73% open · ⏱️ 19.08.2021): +- [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 42 · 📦 120 · 📋 27 - 22% open · ⏱️ 22.02.2021): ``` - git clone https://github.com/databricks/spark-deep-learning + git clone https://github.com/svenkreiss/pysparkling + ``` +- [PyPi](https://pypi.org/project/pysparkling) (📥 13K / month): + ``` + pip install pysparkling ```
-
BatchFlow (🥉17 · ⭐ 170) - BatchFlow可帮助您方便地使用随机或顺序调度数据进行机器学习任务。Apache-2 +
Optimus (🥉19 · ⭐ 1.2K) - Agile Data Preparation Workflows madeeasy with pandas, dask,.. Apache-2 -- [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 30 · 🔀 37 · 📋 100 - 33% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/hi-primus/optimus) (👨‍💻 23 · 🔀 210 · 📋 230 - 14% open · ⏱️ 21.06.2022): ``` - git clone https://github.com/analysiscenter/batchflow + git clone https://github.com/ironmussa/Optimus ``` -- [PyPi](https://pypi.org/project/batchflow): +- [PyPi](https://pypi.org/project/optimuspyspark) (📥 52K / month): ``` - pip install batchflow + pip install optimuspyspark ```
-
Mara Pipelines (🥉16 · ⭐ 1.8K) - 一个轻量级的ETL框架。MIT +
mrq (🥉19 · ⭐ 870 · 💀) - Mr. Queue - A distributed worker task queue in Python using Redis & gevent. MIT -- [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 16 · 🔀 85 · 📦 8 · 📋 18 - 33% open · ⏱️ 18.09.2021): +- [GitHub](https://github.com/pricingassistant/mrq) (👨‍💻 40 · 🔀 110 · 📦 29 · 📋 170 - 30% open · ⏱️ 13.12.2020): ``` - git clone https://github.com/mara/mara-pipelines + git clone https://github.com/pricingassistant/mrq ``` -- [PyPi](https://pypi.org/project/mara-pipelines): +- [PyPi](https://pypi.org/project/mrq) (📥 130 / month): ``` - pip install mara-pipelines + pip install mrq ```
-
riko (🥉16 · ⭐ 1.6K · 💀) - 一个模仿Yahoo!的Python流处理引擎。MIT +
BatchFlow (🥉19 · ⭐ 180) - BatchFlow helps you conveniently work with random or sequential.. Apache-2 -- [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 67 · 📋 29 - 72% open · ⏱️ 14.08.2020): +- [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 32 · 🔀 40 · 📦 2 · 📋 100 - 28% open · ⏱️ 03.08.2022): ``` - git clone https://github.com/nerevu/riko + git clone https://github.com/analysiscenter/batchflow ``` -- [PyPi](https://pypi.org/project/riko) (📥 270 / month): +- [PyPi](https://pypi.org/project/batchflow) (📥 140 / month): ``` - pip install riko + pip install batchflow ```
-
pdpipe (🥉16 · ⭐ 630) - pandas DataFrames的简单管道。❗Unlicensed +
spark-deep-learning (🥉17 · ⭐ 1.9K) - Deep Learning Pipelines for Apache Spark. Apache-2 -- [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 9 · 🔀 29 · 📦 38 · 📋 38 - 39% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/databricks/spark-deep-learning) (👨‍💻 17 · 🔀 460 · 📦 24 · 📋 100 - 74% open · ⏱️ 21.03.2022): ``` - git clone https://github.com/pdpipe/pdpipe + git clone https://github.com/databricks/spark-deep-learning ``` -- [PyPi](https://pypi.org/project/pdpipe): +
+
Mara Pipelines (🥉17 · ⭐ 1.9K) - A lightweight opinionated ETL framework, halfway between plain.. MIT + +- [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 17 · 🔀 89 · 📋 30 - 53% open · ⏱️ 18.07.2022): + ``` - pip install pdpipe + git clone https://github.com/mara/mara-pipelines + ``` +- [PyPi](https://pypi.org/project/mara-pipelines) (📥 360 / month): + ``` + pip install mara-pipelines ```
-
Pypeline (🥉15 · ⭐ 1.3K · 💤) - Python中的并发数据管道。MIT +
riko (🥉15 · ⭐ 1.6K · 💤) - A Python stream processing engine modeled after Yahoo! Pipes. MIT -- [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 10 · 🔀 73 · 📋 52 - 26% open · ⏱️ 13.04.2021): +- [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 68 · 📋 29 - 72% open · ⏱️ 28.12.2021): ``` - git clone https://github.com/cgarciae/pypeln + git clone https://github.com/nerevu/riko ``` -- [PyPi](https://pypi.org/project/pypeln): +- [PyPi](https://pypi.org/project/riko) (📥 30 / month): ``` - pip install pypeln + pip install riko ```
-
Databolt Flow (🥉15 · ⭐ 940) - Python库，用于构建高效的数据科学工作流程。MIT +
Databolt Flow (🥉15 · ⭐ 940 · 💤) - Python library for building highly effective data science.. MIT -- [GitHub](https://github.com/d6t/d6tflow) (👨‍💻 12 · 🔀 68 · 📦 17 · 📋 22 - 40% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/d6t/d6tflow) (👨‍💻 12 · 🔀 71 · 📦 20 · 📋 23 - 43% open · ⏱️ 28.09.2021): ``` git clone https://github.com/d6t/d6tflow ``` -- [PyPi](https://pypi.org/project/d6tflow): +- [PyPi](https://pypi.org/project/d6tflow) (📥 120 / month): ``` pip install d6tflow ```
-
flupy (🥉14 · ⭐ 170) - python中的流利数据管道。❗Unlicensed +
flupy (🥉14 · ⭐ 170) - Fluent data pipelines for python and your shell. ❗Unlicensed -- [GitHub](https://github.com/olirice/flupy) (👨‍💻 6 · 🔀 12 · ⏱️ 05.11.2021): +- [GitHub](https://github.com/olirice/flupy) (👨‍💻 6 · 🔀 12 · ⏱️ 17.02.2022): ``` git clone https://github.com/olirice/flupy ``` -- [PyPi](https://pypi.org/project/flupy) (📥 36K / month): +- [PyPi](https://pypi.org/project/flupy) (📥 73K / month): ``` pip install flupy ```
-
bodywork-core (🥉12 · ⭐ 310) - MLOps工具，用于将机器学习项目部署到Kubernetes。❗️AGPL-3.0 +
bodywork-core (🥉13 · ⭐ 400) - MLOps tool for deploying machine learning projects to.. ❗️AGPL-3.0 -- [GitHub](https://github.com/bodywork-ml/bodywork-core) (👨‍💻 4 · 🔀 14 · 📦 9 · 📋 55 - 21% open · ⏱️ 05.07.2021): +- [GitHub](https://github.com/bodywork-ml/bodywork-core) (👨‍💻 4 · 🔀 18 · 📦 10 · 📋 77 - 25% open · ⏱️ 04.07.2022): ``` git clone https://github.com/bodywork-ml/bodywork-core @@ -6489,106 +6489,134 @@ _用于数据批处理和流处理，工作流自动化，作业调度和其他 pip install bodywork-core ```
-
Botflow (🥉11 · ⭐ 1.2K · 💀) - 适用于数据管道工作的Python快速数据流编程框架。❗Unlicensed +
Botflow (🥉12 · ⭐ 1.2K · 💀) - Python Fast Dataflow programming framework for Data pipeline.. ❗Unlicensed -- [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 100 · 📦 1 · 📋 4 - 50% open · ⏱️ 23.05.2019): +- [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 100 · 📦 1 · 📋 5 - 60% open · ⏱️ 23.05.2019): ``` git clone https://github.com/kkyon/botflow ``` -- [PyPi](https://pypi.org/project/botflow): +- [PyPi](https://pypi.org/project/botflow) (📥 23 / month): ``` pip install botflow ```

-## 分布式机器学习 +## Distributed Machine Learning -Back to top +Back to top -_提供在大型计算基础架构中分布和并行化机器学习任务的功能的库。_ +_Libraries that provide capabilities to distribute and parallelize machine learning tasks across large-scale compute infrastructure._ -
dask (🥇32 · ⭐ 9.3K) - 具有任务调度的并行计算。BSD-3 +
Ray (🥇35 · ⭐ 22K) - An open source framework that provides a simple, universal API for.. Apache-2 + +- [GitHub](https://github.com/ray-project/ray) (👨‍💻 740 · 🔀 3.7K · 📦 5.7K · 📋 11K - 21% open · ⏱️ 26.08.2022): + + ``` + git clone https://github.com/ray-project/ray + ``` +- [PyPi](https://pypi.org/project/ray) (📥 1.8M / month): + ``` + pip install ray + ``` +
+
dask (🥇32 · ⭐ 10K) - Parallel computing with task scheduling. BSD-3 -- [GitHub](https://github.com/dask/dask) (👨‍💻 490 · 🔀 1.4K · 📦 32K · 📋 4K - 16% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/dask/dask) (👨‍💻 550 · 🔀 1.5K · 📦 39K · 📋 4.4K - 15% open · ⏱️ 25.08.2022): ``` git clone https://github.com/dask/dask ``` -- [PyPi](https://pypi.org/project/dask) (📥 5.7M / month): +- [PyPi](https://pypi.org/project/dask) (📥 7.1M / month): ``` pip install dask ``` -- [Conda](https://anaconda.org/conda-forge/dask) (📥 4.7M · ⏱️ 11.12.2021): +- [Conda](https://anaconda.org/conda-forge/dask) (📥 6.4M · ⏱️ 19.08.2022): ``` conda install -c conda-forge dask ```
-
Ray (🥇28 · ⭐ 19K) - 一个开源代码框架，提供了用于构建分布式应用程序的简单通用API。Apache-2 +
horovod (🥇30 · ⭐ 13K) - Distributed training framework for TensorFlow, Keras, PyTorch,.. ❗Unlicensed -- [GitHub](https://github.com/ray-project/ray) (👨‍💻 600 · 🔀 3K · 📦 3.5K · 📋 8.6K - 21% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/horovod/horovod) (👨‍💻 160 · 🔀 2K · 📦 650 · 📋 2.1K - 15% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/ray-project/ray + git clone https://github.com/horovod/horovod ``` -- [PyPi](https://pypi.org/project/ray): +- [PyPi](https://pypi.org/project/horovod) (📥 73K / month): ``` - pip install ray + pip install horovod ```
-
dask.distributed (🥇28 · ⭐ 1.3K) - Dask的分布式任务调度规划程序。❗Unlicensed +
dask.distributed (🥇30 · ⭐ 1.4K) - A distributed task scheduler for Dask. BSD-3 -- [GitHub](https://github.com/dask/distributed) (👨‍💻 260 · 🔀 560 · 📦 21K · 📋 2.4K - 29% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/dask/distributed) (👨‍💻 280 · 🔀 620 · 📦 25K · 📋 2.9K - 33% open · ⏱️ 26.08.2022): ``` git clone https://github.com/dask/distributed ``` -- [PyPi](https://pypi.org/project/distributed) (📥 7M / month): +- [PyPi](https://pypi.org/project/distributed) (📥 4.9M / month): + ``` + pip install distributed + ``` +- [Conda](https://anaconda.org/conda-forge/distributed) (📥 7.8M · ⏱️ 19.08.2022): + ``` + conda install -c conda-forge distributed + ``` +
+
DeepSpeed (🥈28 · ⭐ 7.7K) - DeepSpeed is a deep learning optimization library that makes.. MIT + +- [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 130 · 🔀 830 · 📦 340 · 📋 980 - 48% open · ⏱️ 25.08.2022): + + ``` + git clone https://github.com/microsoft/DeepSpeed + ``` +- [PyPi](https://pypi.org/project/deepspeed) (📥 220K / month): ``` - pip install distributed + pip install deepspeed ``` -- [Conda](https://anaconda.org/conda-forge/distributed) (📥 5.9M · ⏱️ 11.12.2021): +- [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (📥 14K · ⭐ 3 · ⏱️ 06.06.2022): ``` - conda install -c conda-forge distributed + docker pull deepspeed/deepspeed ```
-
DEAP (🥈27 · ⭐ 4.5K) - Python中的分布式进化算法。❗️LGPL-3.0 +
DEAP (🥈27 · ⭐ 4.8K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 -- [GitHub](https://github.com/DEAP/deap) (👨‍💻 76 · 🔀 920 · 📦 2.3K · 📋 430 - 42% open · ⏱️ 21.11.2021): +- [GitHub](https://github.com/DEAP/deap) (👨‍💻 79 · 🔀 980 · 📦 2.8K · 📋 470 - 43% open · ⏱️ 08.08.2022): ``` git clone https://github.com/deap/deap ``` -- [PyPi](https://pypi.org/project/deap) (📥 190K / month): +- [PyPi](https://pypi.org/project/deap) (📥 160K / month): ``` pip install deap ``` -- [Conda](https://anaconda.org/conda-forge/deap) (📥 160K · ⏱️ 07.11.2021): +- [Conda](https://anaconda.org/conda-forge/deap) (📥 200K · ⏱️ 08.08.2022): ``` conda install -c conda-forge deap ```
-
Mesh (🥈27 · ⭐ 1.2K) - Mesh TensorFlow：简化模型并行化。Apache-2 +
petastorm (🥈27 · ⭐ 1.5K) - Petastorm library enables single machine or distributed training.. Apache-2 -- [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 44 · 🔀 200 · 📦 610 · 📋 75 - 81% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/uber/petastorm) (👨‍💻 45 · 🔀 250 · 📥 340 · 📦 74 · 📋 280 - 49% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/tensorflow/mesh + git clone https://github.com/uber/petastorm ``` -- [PyPi](https://pypi.org/project/mesh-tensorflow) (📥 400K / month): +- [PyPi](https://pypi.org/project/petastorm) (📥 63K / month): ``` - pip install mesh-tensorflow + pip install petastorm ```
-
BigDL (🥈26 · ⭐ 3.8K) - BigDL：适用于Apache Spark的分布式深度学习框架。Apache-2 +
BigDL (🥈26 · ⭐ 4K) - BigDL: Distributed Deep Learning Framework for Apache Spark. Apache-2 -- [GitHub](https://github.com/intel-analytics/BigDL) (👨‍💻 130 · 🔀 890 · 📦 31 · 📋 1K - 25% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/intel-analytics/BigDL) (👨‍💻 170 · 🔀 970 · 📦 38 · 📋 1.4K - 30% open · ⏱️ 26.08.2022): ``` git clone https://github.com/intel-analytics/BigDL ``` -- [PyPi](https://pypi.org/project/bigdl) (📥 16K / month): +- [PyPi](https://pypi.org/project/bigdl) (📥 4K / month): ``` pip install bigdl ``` @@ -6601,827 +6629,799 @@ _提供在大型计算基础架构中分布和并行化机器学习任务的功 ```
-
analytics-zoo (🥈25 · ⭐ 2.4K) - Apache上的分布式Tensorflow，Keras和PyTorch。Apache-2 - -- [GitHub](https://github.com/intel-analytics/analytics-zoo) (👨‍💻 100 · 🔀 690 · 📦 3 · 📋 1.3K - 33% open · ⏱️ 15.12.2021): - - ``` - git clone https://github.com/intel-analytics/analytics-zoo - ``` -- [PyPi](https://pypi.org/project/analytics-zoo) (📥 13K / month): - ``` - pip install analytics-zoo - ``` -
-
horovod (🥈24 · ⭐ 12K) - 基于TensorFlow，Keras，PyTorch，MXNet等的分布式训练框架。❗Unlicensed +
FairScale (🥈26 · ⭐ 1.8K) - PyTorch extensions for high performance and large scale training. BSD-3 -- [GitHub](https://github.com/horovod/horovod) (👨‍💻 140 · 🔀 1.9K · 📦 480 · 📋 1.9K - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 63 · 🔀 180 · 📦 490 · 📋 320 - 21% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/horovod/horovod + git clone https://github.com/facebookresearch/fairscale ``` -- [PyPi](https://pypi.org/project/horovod): +- [PyPi](https://pypi.org/project/fairscale) (📥 230K / month): ``` - pip install horovod + pip install fairscale ```
-
DeepSpeed (🥈24 · ⭐ 6K) - DeepSpeed是一个深度学习优化库。MIT +
Elephas (🥈26 · ⭐ 1.5K) - Distributed Deep learning with Keras & Spark. MIT keras -- [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 86 · 🔀 640 · 📦 130 · 📋 720 - 47% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/maxpumperla/elephas) (👨‍💻 27 · 🔀 290 · 📦 56 · 📋 160 - 12% open · ⏱️ 30.03.2022): ``` - git clone https://github.com/microsoft/DeepSpeed - ``` -- [PyPi](https://pypi.org/project/deepspeed): - ``` - pip install deepspeed + git clone https://github.com/maxpumperla/elephas ``` -- [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (📥 12K · ⭐ 3 · ⏱️ 05.05.2021): +- [PyPi](https://pypi.org/project/elephas) (📥 120K / month): ``` - docker pull deepspeed/deepspeed + pip install elephas ```
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MMLSpark (🥈23 · ⭐ 2.9K) - 适用于Apache Spark的Microsoft机器学习。MIT +
Mesh (🥈26 · ⭐ 1.3K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 -- [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 78 · 🔀 590 · 📋 480 - 40% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 48 · 🔀 220 · 📦 710 · 📋 78 - 82% open · ⏱️ 10.06.2022): ``` - git clone https://github.com/Azure/mmlspark + git clone https://github.com/tensorflow/mesh ``` -- [PyPi](https://pypi.org/project/mmlspark) (📥 53K / month): +- [PyPi](https://pypi.org/project/mesh-tensorflow) (📥 21K / month): ``` - pip install mmlspark + pip install mesh-tensorflow ```
-
dask-ml (🥈23 · ⭐ 770) - 使用Dask进行可扩展的机器学习。BSD-3 +
dask-ml (🥉25 · ⭐ 820) - Scalable Machine Learning with Dask. BSD-3 -- [GitHub](https://github.com/dask/dask-ml) (👨‍💻 69 · 🔀 210 · 📦 530 · 📋 420 - 44% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/dask/dask-ml) (👨‍💻 76 · 🔀 230 · 📦 660 · 📋 440 - 45% open · ⏱️ 19.06.2022): ``` git clone https://github.com/dask/dask-ml ``` -- [PyPi](https://pypi.org/project/dask-ml): +- [PyPi](https://pypi.org/project/dask-ml) (📥 70K / month): ``` pip install dask-ml ``` -- [Conda](https://anaconda.org/conda-forge/dask-ml) (📥 260K · ⏱️ 30.11.2021): +- [Conda](https://anaconda.org/conda-forge/dask-ml) (📥 400K · ⏱️ 27.05.2022): ``` conda install -c conda-forge dask-ml ```
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Elephas (🥉22 · ⭐ 1.5K) - 使用Keras和Spark进行分布式深度学习。MIT keras +
TensorFlowOnSpark (🥉23 · ⭐ 3.8K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 -- [GitHub](https://github.com/maxpumperla/elephas) (👨‍💻 27 · 🔀 290 · 📦 51 · 📋 150 - 10% open · ⏱️ 17.08.2021): +- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 34 · 🔀 920 · 📋 360 - 2% open · ⏱️ 21.04.2022): ``` - git clone https://github.com/maxpumperla/elephas + git clone https://github.com/yahoo/TensorFlowOnSpark ``` -- [PyPi](https://pypi.org/project/elephas): +- [PyPi](https://pypi.org/project/tensorflowonspark) (📥 270K / month): ``` - pip install elephas + pip install tensorflowonspark ```
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petastorm (🥉22 · ⭐ 1.3K) - Petastorm库单机或分布式训练。Apache-2 +
analytics-zoo (🥉23 · ⭐ 2.5K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 -- [GitHub](https://github.com/uber/petastorm) (👨‍💻 43 · 🔀 220 · 📥 310 · 📦 53 · 📋 260 - 49% open · ⏱️ 27.10.2021): +- [GitHub](https://github.com/intel-analytics/analytics-zoo) (👨‍💻 100 · 🔀 700 · 📦 3 · 📋 1.3K - 32% open · ⏱️ 01.06.2022): ``` - git clone https://github.com/uber/petastorm + git clone https://github.com/intel-analytics/analytics-zoo ``` -- [PyPi](https://pypi.org/project/petastorm): +- [PyPi](https://pypi.org/project/analytics-zoo) (📥 2.2K / month): ``` - pip install petastorm + pip install analytics-zoo ```
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ipyparallel (🥉21 · ⭐ 2.1K) - Python中的交互式并行计算。❗Unlicensed +
Hivemind (🥉23 · ⭐ 1.1K) - Decentralized deep learning in PyTorch. Built to train models on.. MIT -- [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 100 · 🔀 810 · 📦 1.8K · 📋 310 - 15% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/learning-at-home/hivemind) (👨‍💻 23 · 🔀 67 · 📦 10 · 📋 120 - 28% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/ipython/ipyparallel - ``` -- [PyPi](https://pypi.org/project/ipyparallel): - ``` - pip install ipyparallel + git clone https://github.com/learning-at-home/hivemind ``` -- [Conda](https://anaconda.org/conda-forge/ipyparallel) (📥 540K · ⏱️ 02.12.2021): +- [PyPi](https://pypi.org/project/hivemind) (📥 5.2K / month): ``` - conda install -c conda-forge ipyparallel + pip install hivemind ```
-
mpi4py (🥉21 · ⭐ 480) - MPI的Python接口。BSD-2 +
mpi4py (🥉22 · ⭐ 570) - Python bindings for MPI. BSD-2 -- [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 20 · 🔀 74 · 📥 2.7K · 📋 54 - 24% open · ⏱️ 25.11.2021): +- [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 21 · 🔀 78 · 📥 6.2K · 📋 84 - 11% open · ⏱️ 21.08.2022): ``` git clone https://github.com/mpi4py/mpi4py ``` -- [PyPi](https://pypi.org/project/mpi4py): +- [PyPi](https://pypi.org/project/mpi4py) (📥 290K / month): ``` pip install mpi4py ``` -- [Conda](https://anaconda.org/conda-forge/mpi4py) (📥 860K · ⏱️ 25.11.2021): +- [Conda](https://anaconda.org/conda-forge/mpi4py) (📥 1.3M · ⏱️ 12.08.2022): ``` conda install -c conda-forge mpi4py ```
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Apache Singa (🥉19 · ⭐ 2.4K) - 分布式深度学习平台。Apache-2 +
MMLSpark (🥉20 · ⭐ 3.5K) - Microsoft Machine Learning for Apache Spark. MIT -- [GitHub](https://github.com/apache/singa) (👨‍💻 76 · 🔀 720 · 📦 1 · 📋 67 - 26% open · ⏱️ 10.08.2021): +- [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 97 · 🔀 670 · 📋 570 - 39% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/apache/singa - ``` -- [Conda](https://anaconda.org/nusdbsystem/singa) (📥 390 · ⏱️ 09.08.2021): - ``` - conda install -c nusdbsystem singa + git clone https://github.com/Azure/mmlspark ``` -- [Docker Hub](https://hub.docker.com/r/apache/singa) (📥 210 · ⭐ 4 · ⏱️ 04.06.2019): +- [PyPi](https://pypi.org/project/mmlspark) (📥 4 / month): ``` - docker pull apache/singa + pip install mmlspark ```
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FairScale (🥉19 · ⭐ 1.5K) - PyTorch扩展用于高性能和大规模训练。BSD-3 +
Apache Singa (🥉19 · ⭐ 2.7K) - a distributed deep learning platform. Apache-2 -- [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 51 · 🔀 140 · 📦 120 · 📋 250 - 21% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/apache/singa) (👨‍💻 79 · 🔀 780 · 📦 1 · 📋 79 - 21% open · ⏱️ 01.06.2022): ``` - git clone https://github.com/facebookresearch/fairscale + git clone https://github.com/apache/singa ``` -- [PyPi](https://pypi.org/project/fairscale): +- [Conda](https://anaconda.org/nusdbsystem/singa) (📥 510 · ⏱️ 09.08.2021): ``` - pip install fairscale + conda install -c nusdbsystem singa + ``` +- [Docker Hub](https://hub.docker.com/r/apache/singa) (📥 690 · ⭐ 4 · ⏱️ 31.05.2022): + ``` + docker pull apache/singa ```
-
TensorFrames (🥉19 · ⭐ 760 · 💀) - 用于DataFrames的Tensorflow包装器。Apache-2 +
TensorFrames (🥉19 · ⭐ 760 · 💀) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 -- [GitHub](https://github.com/databricks/tensorframes) (👨‍💻 16 · 🔀 160 · 📋 91 - 52% open · ⏱️ 15.11.2019): +- [GitHub](https://github.com/databricks/tensorframes) (👨‍💻 16 · 🔀 160 · 📋 92 - 53% open · ⏱️ 15.11.2019): ``` git clone https://github.com/databricks/tensorframes ``` -- [PyPi](https://pypi.org/project/tensorframes) (📥 21K / month): +- [PyPi](https://pypi.org/project/tensorframes) (📥 40K / month): ``` pip install tensorframes ```
-
somoclu (🥉19 · ⭐ 230) - 大规模并行的自组织图：加速训练。MIT +
ipyparallel (🥉18 · ⭐ 2.3K) - Interactive Parallel Computing in Python. ❗Unlicensed -- [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 61 · 📥 1.5K · 📋 130 - 18% open · ⏱️ 31.10.2021): +- [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 110 · 🔀 870 · 📋 330 - 15% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/peterwittek/somoclu + git clone https://github.com/ipython/ipyparallel ``` -- [PyPi](https://pypi.org/project/somoclu) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/ipyparallel) (📥 120K / month): ``` - pip install somoclu + pip install ipyparallel ``` -- [Conda](https://anaconda.org/conda-forge/somoclu) (📥 57K · ⏱️ 15.11.2021): +- [Conda](https://anaconda.org/conda-forge/ipyparallel) (📥 670K · ⏱️ 21.06.2022): ``` - conda install -c conda-forge somoclu + conda install -c conda-forge ipyparallel ```
-
TensorFlowOnSpark (🥉18 · ⭐ 3.7K) - TensorFlowOnSpark将TensorFlow程序引入Spark。Apache-2 +
Submit it (🥉18 · ⭐ 680) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT -- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 33 · 🔀 920 · 📋 360 - 1% open · ⏱️ 15.10.2021): +- [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 23 · 🔀 74 · 📋 71 - 32% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/yahoo/TensorFlowOnSpark - ``` -- [PyPi](https://pypi.org/project/tensorflowonspark): - ``` - pip install tensorflowonspark + git clone https://github.com/facebookincubator/submitit ``` -
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Hivemind (🥉17 · ⭐ 880) - PyTorch中的分布式深度学习。专为训练模型而设计。MIT - -- [GitHub](https://github.com/learning-at-home/hivemind) (👨‍💻 19 · 🔀 57 · 📦 4 · 📋 110 - 34% open · ⏱️ 16.12.2021): - +- [PyPi](https://pypi.org/project/submitit) (📥 37K / month): ``` - git clone https://github.com/learning-at-home/hivemind + pip install submitit ``` -- [PyPi](https://pypi.org/project/hivemind): +- [Conda](https://anaconda.org/conda-forge/submitit) (📥 8.1K · ⏱️ 10.02.2021): ``` - pip install hivemind + conda install -c conda-forge submitit ```
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BytePS (🥉16 · ⭐ 3K) - 分布式DNN训练的高性能通用框架。Apache-2 +
sk-dist (🥉18 · ⭐ 280 · 💀) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 -- [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 420 · 📋 250 - 37% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Ibotta/sk-dist) (👨‍💻 7 · 🔀 49 · 📦 10 · 📋 17 - 41% open · ⏱️ 07.07.2021): ``` - git clone https://github.com/bytedance/byteps - ``` -- [PyPi](https://pypi.org/project/byteps): - ``` - pip install byteps + git clone https://github.com/Ibotta/sk-dist ``` -- [Docker Hub](https://hub.docker.com/r/bytepsimage/tensorflow) (📥 1.2K · ⏱️ 03.03.2020): +- [PyPi](https://pypi.org/project/sk-dist) (📥 170K / month): ``` - docker pull bytepsimage/tensorflow + pip install sk-dist ```
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Fiber (🥉16 · ⭐ 950 · 💤) - 简化了AI的分布式计算。Apache-2 +
somoclu (🥉17 · ⭐ 240 · 💤) - Massively parallel self-organizing maps: accelerate training on.. MIT -- [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 100 · 📦 30 · 📋 24 - 66% open · ⏱️ 15.03.2021): +- [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 62 · 📥 1.6K · 📋 130 - 18% open · ⏱️ 31.10.2021): ``` - git clone https://github.com/uber/fiber + git clone https://github.com/peterwittek/somoclu ``` -- [PyPi](https://pypi.org/project/fiber) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/somoclu) (📥 980 / month): ``` - pip install fiber + pip install somoclu + ``` +- [Conda](https://anaconda.org/conda-forge/somoclu) (📥 64K · ⏱️ 15.11.2021): + ``` + conda install -c conda-forge somoclu ```
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Submit it (🥉15 · ⭐ 510) - 用于将作业提交到Slurm的Python工具箱。MIT +
BytePS (🥉16 · ⭐ 3.3K) - A high performance and generic framework for distributed DNN training. Apache-2 -- [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 17 · 🔀 48 · 📋 53 - 41% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 450 · 📋 260 - 38% open · ⏱️ 10.02.2022): ``` - git clone https://github.com/facebookincubator/submitit + git clone https://github.com/bytedance/byteps ``` -- [PyPi](https://pypi.org/project/submitit): +- [PyPi](https://pypi.org/project/byteps) (📥 19 / month): ``` - pip install submitit + pip install byteps ``` -- [Conda](https://anaconda.org/conda-forge/submitit) (📥 5.1K · ⏱️ 10.02.2021): +- [Docker Hub](https://hub.docker.com/r/bytepsimage/tensorflow) (📥 1.3K · ⏱️ 03.03.2020): ``` - conda install -c conda-forge submitit + docker pull bytepsimage/tensorflow ```
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sk-dist (🥉12 · ⭐ 270) - PySpark中的分布式scikit学习元估计器。Apache-2 +
Fiber (🥉16 · ⭐ 980 · 💀) - Distributed Computing for AI Made Simple. Apache-2 -- [GitHub](https://github.com/Ibotta/sk-dist) (👨‍💻 7 · 🔀 46 · 📦 8 · 📋 17 - 41% open · ⏱️ 07.07.2021): +- [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 110 · 📦 43 · 📋 25 - 68% open · ⏱️ 15.03.2021): ``` - git clone https://github.com/Ibotta/sk-dist + git clone https://github.com/uber/fiber ``` -- [PyPi](https://pypi.org/project/sk-dist): +- [PyPi](https://pypi.org/project/fiber) (📥 60 / month): ``` - pip install sk-dist + pip install fiber ```
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LazyCluster (🥉10 · ⭐ 43) - 分布式机器学习框架。Apache-2 +
LazyCluster (🥉13 · ⭐ 43 · 💤) - Distributed machine learning made simple. Apache-2 -- [GitHub](https://github.com/ml-tooling/lazycluster) (👨‍💻 2 · 🔀 8 · 📦 7 · ⏱️ 19.08.2021): +- [GitHub](https://github.com/ml-tooling/lazycluster) (👨‍💻 2 · 🔀 9 · 📦 17 · ⏱️ 19.08.2021): ``` git clone https://github.com/ml-tooling/lazycluster ``` -- [PyPi](https://pypi.org/project/lazycluster): +- [PyPi](https://pypi.org/project/lazycluster) (📥 42 / month): ``` pip install lazycluster ```

-## 超参数优化和AutoML +## Hyperparameter Optimization & AutoML -Back to top +Back to top -_用于超参数优化，自动机器学习和神经体系结构搜索的库。_ +_Libraries for hyperparameter optimization, automl and neural architecture search._ -
Optuna (🥇33 · ⭐ 5.7K) - 超参数优化框架。MIT +
Optuna (🥇34 · ⭐ 6.8K) - A hyperparameter optimization framework. MIT -- [GitHub](https://github.com/optuna/optuna) (👨‍💻 170 · 🔀 620 · 📦 2.3K · 📋 1K - 11% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/optuna/optuna) (👨‍💻 200 · 🔀 730 · 📦 4K · 📋 1.2K - 7% open · ⏱️ 26.08.2022): ``` git clone https://github.com/optuna/optuna ``` -- [PyPi](https://pypi.org/project/optuna) (📥 820K / month): +- [PyPi](https://pypi.org/project/optuna) (📥 1.5M / month): ``` pip install optuna ``` -- [Conda](https://anaconda.org/conda-forge/optuna) (📥 48K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/optuna) (📥 320K · ⏱️ 06.07.2022): ``` conda install -c conda-forge optuna ```
-
scikit-optimize (🥇31 · ⭐ 2.3K) - SMBO模型优化实现。BSD-3 +
NNI (🥇30 · ⭐ 12K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT -- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 75 · 🔀 410 · 📦 2.2K · 📋 580 - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/microsoft/nni) (👨‍💻 180 · 🔀 1.6K · 📦 260 · 📋 1.7K - 17% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/scikit-optimize/scikit-optimize - ``` -- [PyPi](https://pypi.org/project/scikit-optimize) (📥 500K / month): - ``` - pip install scikit-optimize + git clone https://github.com/microsoft/nni ``` -- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (📥 520K · ⏱️ 15.12.2021): +- [PyPi](https://pypi.org/project/nni) (📥 10K / month): ``` - conda install -c conda-forge scikit-optimize + pip install nni ```
-
Keras Tuner (🥇30 · ⭐ 2.4K · 📈) - 简单易用的超参数调整。Apache-2 +
AutoKeras (🥇30 · ⭐ 8.6K) - AutoML library for deep learning. Apache-2 -- [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 41 · 🔀 310 · 📦 1K · 📋 360 - 45% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 140 · 🔀 1.3K · 📥 7.4K · 📦 350 · 📋 840 - 11% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/keras-team/keras-tuner + git clone https://github.com/keras-team/autokeras ``` -- [PyPi](https://pypi.org/project/keras-tuner) (📥 970K / month): +- [PyPi](https://pypi.org/project/autokeras) (📥 17K / month): ``` - pip install keras-tuner + pip install autokeras ```
-
Bayesian Optimization (🥇29 · ⭐ 5.6K · 💤) - 全局优化的Python实现。MIT +
Keras Tuner (🥇30 · ⭐ 2.6K) - Hyperparameter tuning for humans. Apache-2 -- [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 27 · 🔀 1.2K · 📥 70 · 📦 990 · 📋 220 - 20% open · ⏱️ 19.12.2020): +- [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 50 · 🔀 330 · 📦 1.6K · 📋 400 - 43% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/fmfn/BayesianOptimization + git clone https://github.com/keras-team/keras-tuner ``` -- [PyPi](https://pypi.org/project/bayesian-optimization) (📥 190K / month): +- [PyPi](https://pypi.org/project/keras-tuner) (📥 610K / month): ``` - pip install bayesian-optimization + pip install keras-tuner ```
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Hyperopt (🥇28 · ⭐ 6K) - Python中的分布式异步超参数优化。❗Unlicensed +
scikit-optimize (🥇30 · ⭐ 2.4K · 💤) - Sequential model-based optimization with a.. BSD-3 -- [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 93 · 🔀 810 · 📦 5.4K · 📋 590 - 60% open · ⏱️ 29.11.2021): +- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 76 · 🔀 420 · 📦 3K · 📋 600 - 35% open · ⏱️ 12.10.2021): ``` - git clone https://github.com/hyperopt/hyperopt + git clone https://github.com/scikit-optimize/scikit-optimize ``` -- [PyPi](https://pypi.org/project/hyperopt) (📥 1.9M / month): +- [PyPi](https://pypi.org/project/scikit-optimize) (📥 790K / month): ``` - pip install hyperopt + pip install scikit-optimize ``` -- [Conda](https://anaconda.org/conda-forge/hyperopt) (📥 310K · ⏱️ 14.10.2020): +- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (📥 570K · ⏱️ 15.12.2021): ``` - conda install -c conda-forge hyperopt + conda install -c conda-forge scikit-optimize ```
-
featuretools (🥇28 · ⭐ 5.9K) - 一个用于自动化特征工程的开源python库。BSD-3 +
TPOT (🥈29 · ⭐ 8.7K) - A Python Automated Machine Learning tool that optimizes machine.. ❗️LGPL-3.0 -- [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 57 · 🔀 750 · 📦 890 · 📋 700 - 21% open · ⏱️ 12.12.2021): +- [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.5K · 📦 1.6K · 📋 860 - 29% open · ⏱️ 29.07.2022): ``` - git clone https://github.com/alteryx/featuretools + git clone https://github.com/EpistasisLab/tpot ``` -- [PyPi](https://pypi.org/project/featuretools) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/tpot) (📥 41K / month): ``` - pip install featuretools + pip install tpot ``` -- [Conda](https://anaconda.org/conda-forge/featuretools) (📥 74K · ⏱️ 03.12.2021): +- [Conda](https://anaconda.org/conda-forge/tpot) (📥 170K · ⏱️ 05.03.2021): ``` - conda install -c conda-forge featuretools + conda install -c conda-forge tpot ```
-
TPOT (🥈27 · ⭐ 8.4K · 💤) - Python自动化机器学习工具。❗️LGPL-3.0 +
auto-sklearn (🥈29 · ⭐ 6.5K) - Automated Machine Learning with scikit-learn. BSD-3 -- [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.4K · 📦 1.2K · 📋 830 - 27% open · ⏱️ 06.01.2021): +- [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 86 · 🔀 1.2K · 📥 37 · 📦 310 · 📋 920 - 12% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/EpistasisLab/tpot + git clone https://github.com/automl/auto-sklearn ``` -- [PyPi](https://pypi.org/project/tpot): +- [PyPi](https://pypi.org/project/auto-sklearn) (📥 40K / month): ``` - pip install tpot + pip install auto-sklearn + ``` +
+
Bayesian Optimization (🥈29 · ⭐ 6.2K) - A Python implementation of global optimization with.. MIT + +- [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 35 · 🔀 1.3K · 📥 96 · 📦 1.3K · 📋 260 - 7% open · ⏱️ 17.08.2022): + + ``` + git clone https://github.com/fmfn/BayesianOptimization ``` -- [Conda](https://anaconda.org/conda-forge/tpot) (📥 140K · ⏱️ 05.03.2021): +- [PyPi](https://pypi.org/project/bayesian-optimization) (📥 200K / month): ``` - conda install -c conda-forge tpot + pip install bayesian-optimization ```
-
AutoKeras (🥈26 · ⭐ 8.3K) - 用于深度学习的AutoML库。Apache-2 +
Hyperopt (🥈28 · ⭐ 6.4K · 💤) - Distributed Asynchronous Hyperparameter Optimization in.. ❗Unlicensed -- [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 130 · 🔀 1.3K · 📥 1.7K · 📦 260 · 📋 790 - 7% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 93 · 🔀 860 · 📦 7.4K · 📋 610 - 61% open · ⏱️ 29.11.2021): ``` - git clone https://github.com/keras-team/autokeras + git clone https://github.com/hyperopt/hyperopt ``` -- [PyPi](https://pypi.org/project/autokeras): +- [PyPi](https://pypi.org/project/hyperopt) (📥 1.8M / month): ``` - pip install autokeras + pip install hyperopt + ``` +- [Conda](https://anaconda.org/conda-forge/hyperopt) (📥 500K · ⏱️ 30.04.2022): + ``` + conda install -c conda-forge hyperopt ```
-
AutoGluon (🥈26 · ⭐ 3.9K) - AutoGluon：用于文本，图像和表格数据的AutoML。Apache-2 +
AutoGluon (🥈26 · ⭐ 4.7K) - AutoGluon: AutoML for Text, Image, and Tabular Data. Apache-2 -- [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 62 · 🔀 500 · 📦 86 · 📋 560 - 22% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 85 · 🔀 620 · 📦 160 · 📋 740 - 21% open · ⏱️ 25.08.2022): ``` git clone https://github.com/awslabs/autogluon ``` -- [PyPi](https://pypi.org/project/autogluon) (📥 19K / month): +- [PyPi](https://pypi.org/project/autogluon) (📥 40K / month): ``` pip install autogluon ```
-
BoTorch (🥈26 · ⭐ 2.1K) - PyTorch中的贝叶斯优化。MIT +
BoTorch (🥈26 · ⭐ 2.3K) - Bayesian optimization in PyTorch. MIT -- [GitHub](https://github.com/pytorch/botorch) (👨‍💻 64 · 🔀 230 · 📦 190 · 📋 230 - 21% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/pytorch/botorch) (👨‍💻 80 · 🔀 260 · 📦 300 · 📋 290 - 15% open · ⏱️ 25.08.2022): ``` git clone https://github.com/pytorch/botorch ``` -- [PyPi](https://pypi.org/project/botorch) (📥 130K / month): +- [PyPi](https://pypi.org/project/botorch) (📥 210K / month): ``` pip install botorch ```
-
Ax (🥈26 · ⭐ 1.7K) - 自适应实验平台。MIT +
Ax (🥈26 · ⭐ 1.9K) - Adaptive Experimentation Platform. MIT -- [GitHub](https://github.com/facebook/Ax) (👨‍💻 110 · 🔀 170 · 📦 220 · 📋 320 - 6% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/facebook/Ax) (👨‍💻 120 · 🔀 210 · 📦 310 · 📋 430 - 8% open · ⏱️ 25.08.2022): ``` git clone https://github.com/facebook/Ax ``` -- [PyPi](https://pypi.org/project/ax-platform) (📥 100K / month): +- [PyPi](https://pypi.org/project/ax-platform) (📥 160K / month): ``` pip install ax-platform ```
-
NNI (🥈25 · ⭐ 11K) - 一个开源AutoML工具箱，用于自动化机器学习生命周期。MIT - -- [GitHub](https://github.com/microsoft/nni) (👨‍💻 150 · 🔀 1.5K · 📦 160 · 📋 1.4K - 15% open · ⏱️ 15.12.2021): - - ``` - git clone https://github.com/microsoft/nni - ``` -- [PyPi](https://pypi.org/project/nni): - ``` - pip install nni - ``` -
-
auto-sklearn (🥈24 · ⭐ 5.9K) - 使用scikit-learn的自动化机器学习。BSD-3 +
Hyperas (🥈24 · ⭐ 2.1K · 💤) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT -- [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 77 · 🔀 1.1K · 📦 240 · 📋 810 - 11% open · ⏱️ 09.11.2021): +- [GitHub](https://github.com/maxpumperla/hyperas) (👨‍💻 21 · 🔀 300 · 📦 250 · 📋 250 - 37% open · ⏱️ 19.11.2021): ``` - git clone https://github.com/automl/auto-sklearn + git clone https://github.com/maxpumperla/hyperas ``` -- [PyPi](https://pypi.org/project/auto-sklearn): +- [PyPi](https://pypi.org/project/hyperas) (📥 18K / month): ``` - pip install auto-sklearn + pip install hyperas ```
-
Hyperas (🥈24 · ⭐ 2.1K) - Keras + Hyperopt：一个非常简单的包装，方便使用。MIT +
mljar-supervised (🥈24 · ⭐ 2K) - Automated Machine Learning Pipeline with Feature Engineering.. MIT -- [GitHub](https://github.com/maxpumperla/hyperas) (👨‍💻 21 · 🔀 300 · 📦 220 · 📋 250 - 36% open · ⏱️ 19.11.2021): +- [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 19 · 🔀 280 · 📦 50 · 📋 490 - 19% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/maxpumperla/hyperas + git clone https://github.com/mljar/mljar-supervised ``` -- [PyPi](https://pypi.org/project/hyperas) (📥 12K / month): +- [PyPi](https://pypi.org/project/mljar-supervised) (📥 7.4K / month): ``` - pip install hyperas + pip install mljar-supervised ```
-
nevergrad (🥈23 · ⭐ 3.2K) - 用于执行无梯度优化(gradient-free optimization)的Python工具箱。MIT +
nevergrad (🥈23 · ⭐ 3.3K) - A Python toolbox for performing gradient-free optimization. MIT -- [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 46 · 🔀 300 · 📦 270 · 📋 210 - 27% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 50 · 🔀 310 · 📦 370 · 📋 220 - 30% open · ⏱️ 10.08.2022): ``` git clone https://github.com/facebookresearch/nevergrad ``` -- [PyPi](https://pypi.org/project/nevergrad) (📥 32K / month): +- [PyPi](https://pypi.org/project/nevergrad) (📥 33K / month): ``` pip install nevergrad ``` -- [Conda](https://anaconda.org/conda-forge/nevergrad) (📥 20K · ⏱️ 14.06.2021): +- [Conda](https://anaconda.org/conda-forge/nevergrad) (📥 31K · ⏱️ 14.06.2021): ``` conda install -c conda-forge nevergrad ```
-
GPyOpt (🥈23 · ⭐ 780 · 💀) - 使用GPy进行高斯过程优化。BSD-3 +
GPyOpt (🥈23 · ⭐ 830 · 💀) - Gaussian Process Optimization using GPy. BSD-3 -- [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 240 · 📦 230 · 📋 280 - 34% open · ⏱️ 05.11.2020): +- [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 250 · 📦 310 · 📋 290 - 35% open · ⏱️ 05.11.2020): ``` git clone https://github.com/SheffieldML/GPyOpt ``` -- [PyPi](https://pypi.org/project/gpyopt) (📥 18K / month): +- [PyPi](https://pypi.org/project/gpyopt) (📥 12K / month): ``` pip install gpyopt ```
-
SMAC3 (🥈21 · ⭐ 640) - Sequential Model-based算法的配置。❗Unlicensed +
featuretools (🥈22 · ⭐ 6.3K) - An open source python library for automated feature engineering. BSD-3 -- [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 160 · 📋 350 - 18% open · ⏱️ 05.11.2021): +- [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 67 · 🔀 800 · 📋 850 - 18% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/automl/SMAC3 + git clone https://github.com/alteryx/featuretools ``` -- [PyPi](https://pypi.org/project/smac) (📥 30K / month): +- [PyPi](https://pypi.org/project/featuretools) (📥 160K / month): ``` - pip install smac + pip install featuretools + ``` +- [Conda](https://anaconda.org/conda-forge/featuretools) (📥 100K · ⏱️ 18.08.2022): + ``` + conda install -c conda-forge featuretools ```
-
mljar-supervised (🥈20 · ⭐ 1.7K) - 使用scikit-learn的自动化机器学习。MIT +
AdaNet (🥈22 · ⭐ 3.4K · 💤) - Fast and flexible AutoML with learning guarantees. Apache-2 -- [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 14 · 🔀 240 · 📦 33 · 📋 450 - 16% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 44 · 📋 110 - 56% open · ⏱️ 30.08.2021): ``` - git clone https://github.com/mljar/mljar-supervised + git clone https://github.com/tensorflow/adanet ``` -- [PyPi](https://pypi.org/project/mljar-supervised): +- [PyPi](https://pypi.org/project/adanet) (📥 490 / month): ``` - pip install mljar-supervised + pip install adanet ```
-
auto_ml (🥈20 · ⭐ 1.6K · 💀) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT +
Talos (🥈22 · ⭐ 1.5K) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT -- [GitHub](https://github.com/ClimbsRocks/auto_ml) (👨‍💻 13 · 🔀 300 · 📥 38 · 📋 390 - 45% open · ⏱️ 25.03.2018): +- [GitHub](https://github.com/autonomio/talos) (👨‍💻 22 · 🔀 260 · 📦 150 · 📋 400 - 6% open · ⏱️ 23.04.2022): ``` - git clone https://github.com/ClimbsRocks/auto_ml + git clone https://github.com/autonomio/talos ``` -- [PyPi](https://pypi.org/project/auto_ml) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/talos) (📥 750 / month): ``` - pip install auto_ml + pip install talos ```
-
Talos (🥈20 · ⭐ 1.5K · 💤) - TensorFlow，Keras和PyTorch的超参数优化。MIT +
Orion (🥈22 · ⭐ 240) - Asynchronous Distributed Hyperparameter Optimization. ❗Unlicensed -- [GitHub](https://github.com/autonomio/talos) (👨‍💻 19 · 🔀 250 · 📦 130 · 📋 390 - 8% open · ⏱️ 27.05.2021): +- [GitHub](https://github.com/Epistimio/orion) (👨‍💻 27 · 🔀 43 · 📦 73 · 📋 350 - 52% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/autonomio/talos + git clone https://github.com/Epistimio/orion ``` -- [PyPi](https://pypi.org/project/talos) (📥 810 / month): +- [PyPi](https://pypi.org/project/orion) (📥 4.4K / month): ``` - pip install talos + pip install orion ```
-
MLBox (🥈20 · ⭐ 1.3K · 💀) - MLBox是功能强大的自动机器学习python库。❗Unlicensed +
MLBox (🥉21 · ⭐ 1.3K · 💀) - MLBox is a powerful Automated Machine Learning python library. ❗Unlicensed -- [GitHub](https://github.com/AxeldeRomblay/MLBox) (👨‍💻 9 · 🔀 260 · 📦 28 · 📋 90 - 17% open · ⏱️ 25.08.2020): +- [GitHub](https://github.com/AxeldeRomblay/MLBox) (👨‍💻 9 · 🔀 270 · 📦 28 · 📋 92 - 19% open · ⏱️ 25.08.2020): ``` git clone https://github.com/AxeldeRomblay/MLBox ``` -- [PyPi](https://pypi.org/project/mlbox) (📥 2.8K / month): +- [PyPi](https://pypi.org/project/mlbox) (📥 2.9K / month): ``` pip install mlbox ```
-
lazypredict (🥈20 · ⭐ 270) - Lazy Predict帮助您无需大量代码即可构建许多基本模型。MIT +
Neuraxle (🥉21 · ⭐ 540) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 -- [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 16 · 🔀 36 · 📦 210 · 📋 59 - 49% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/Neuraxio/Neuraxle) (👨‍💻 7 · 🔀 52 · 📦 34 · 📋 320 - 19% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/shankarpandala/lazypredict + git clone https://github.com/Neuraxio/Neuraxle ``` -- [PyPi](https://pypi.org/project/lazypredict) (📥 7.9K / month): +- [PyPi](https://pypi.org/project/neuraxle) (📥 490 / month): ``` - pip install lazypredict + pip install neuraxle ```
-
AdaNet (🥉19 · ⭐ 3.3K) - 具有学习保证的快速灵活的AutoML。Apache-2 +
optunity (🥉21 · ⭐ 390 · 💀) - optimization routines for hyperparameter tuning. BSD-3 -- [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 41 · 📋 110 - 58% open · ⏱️ 30.08.2021): +- [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 75 · 📥 67 · 📦 81 · 📋 97 - 50% open · ⏱️ 11.05.2020): ``` - git clone https://github.com/tensorflow/adanet + git clone https://github.com/claesenm/optunity ``` -- [PyPi](https://pypi.org/project/adanet): +- [PyPi](https://pypi.org/project/optunity) (📥 11K / month): ``` - pip install adanet + pip install optunity ```
-
sklearn-deap (🥉19 · ⭐ 670) - 使用进化算法而非gridsearch的超参数优化。MIT +
HpBandSter (🥉20 · ⭐ 540) - a distributed Hyperband implementation on Steroids. BSD-3 -- [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 110 · 📦 30 · 📋 50 - 32% open · ⏱️ 30.07.2021): +- [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 110 · 📦 240 · 📋 89 - 60% open · ⏱️ 22.04.2022): ``` - git clone https://github.com/rsteca/sklearn-deap + git clone https://github.com/automl/HpBandSter ``` -- [PyPi](https://pypi.org/project/sklearn-deap) (📥 1K / month): +- [PyPi](https://pypi.org/project/hpbandster) (📥 22K / month): ``` - pip install sklearn-deap + pip install hpbandster ```
-
HpBandSter (🥉19 · ⭐ 500 · 💀) - 分布式自动化机器学习库。BSD-3 +
auto_ml (🥉19 · ⭐ 1.6K · 💀) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT -- [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 110 · 📦 190 · 📋 86 - 59% open · ⏱️ 26.03.2019): +- [GitHub](https://github.com/ClimbsRocks/auto_ml) (👨‍💻 13 · 🔀 300 · 📥 42 · 📋 400 - 45% open · ⏱️ 25.03.2018): ``` - git clone https://github.com/automl/HpBandSter + git clone https://github.com/ClimbsRocks/auto_ml ``` -- [PyPi](https://pypi.org/project/hpbandster) (📥 25K / month): +- [PyPi](https://pypi.org/project/auto_ml) (📥 840 / month): ``` - pip install hpbandster + pip install auto_ml ```
-
Neuraxle (🥉19 · ⭐ 490) - 类似于Sklearn的超参数调整和AutoML输入框架。Apache-2 +
lazypredict (🥉19 · ⭐ 380) - Lazy Predict help build a lot of basic models without much code.. MIT -- [GitHub](https://github.com/Neuraxio/Neuraxle) (👨‍💻 7 · 🔀 52 · 📦 24 · 📋 310 - 41% open · ⏱️ 01.11.2021): +- [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 17 · 🔀 67 · 📦 320 · 📋 66 - 48% open · ⏱️ 25.05.2022): ``` - git clone https://github.com/Neuraxio/Neuraxle + git clone https://github.com/shankarpandala/lazypredict ``` -- [PyPi](https://pypi.org/project/neuraxle): +- [PyPi](https://pypi.org/project/lazypredict) (📥 5.1K / month): ``` - pip install neuraxle + pip install lazypredict ```
-
Test Tube (🥉18 · ⭐ 700 · 💀) - 可轻松记录实验并进行并行化的Python库。MIT +
Sherpa (🥉19 · ⭐ 310 · 💀) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 -- [GitHub](https://github.com/williamFalcon/test-tube) (👨‍💻 16 · 🔀 64 · 📥 10 · 📋 44 - 52% open · ⏱️ 17.03.2020): +- [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 48 · 📦 23 · 📋 57 - 28% open · ⏱️ 18.10.2020): ``` - git clone https://github.com/williamFalcon/test-tube + git clone https://github.com/sherpa-ai/sherpa ``` -- [PyPi](https://pypi.org/project/test_tube) (📥 13K / month): +- [PyPi](https://pypi.org/project/parameter-sherpa) (📥 1.1K / month): ``` - pip install test_tube + pip install parameter-sherpa ```
-
AlphaPy (🥉18 · ⭐ 680) - 使用scikit-learn的自动化机器学习。Apache-2 +
SMAC3 (🥉18 · ⭐ 730) - Sequential Model-based Algorithm Configuration. ❗Unlicensed -- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 140 · 📦 3 · 📋 40 - 27% open · ⏱️ 23.10.2021): +- [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 170 · 📋 400 - 18% open · ⏱️ 14.07.2022): ``` - git clone https://github.com/ScottfreeLLC/AlphaPy + git clone https://github.com/automl/SMAC3 ``` -- [PyPi](https://pypi.org/project/alphapy) (📥 180 / month): +- [PyPi](https://pypi.org/project/smac) (📥 50K / month): ``` - pip install alphapy + pip install smac ```
-
Dragonfly (🥉17 · ⭐ 610 · 💀) - 一个用于自动化特征工程的开源python库。MIT +
Test Tube (🥉18 · ⭐ 720 · 💀) - Python library to easily log experiments and parallelize.. MIT -- [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 12 · 🔀 200 · 📋 49 - 63% open · ⏱️ 03.07.2020): +- [GitHub](https://github.com/williamFalcon/test-tube) (👨‍💻 16 · 🔀 67 · 📥 12 · 📋 44 - 52% open · ⏱️ 17.03.2020): ``` - git clone https://github.com/dragonfly/dragonfly + git clone https://github.com/williamFalcon/test-tube ``` -- [PyPi](https://pypi.org/project/dragonfly-opt) (📥 34K / month): +- [PyPi](https://pypi.org/project/test_tube) (📥 51K / month): ``` - pip install dragonfly-opt + pip install test_tube ```
-
optunity (🥉17 · ⭐ 380 · 💀) - 超参数优化的优化例程。BSD-3 +
sklearn-deap (🥉18 · ⭐ 700 · 💀) - Use evolutionary algorithms instead of gridsearch in.. MIT -- [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 73 · 📥 67 · 📦 68 · 📋 95 - 49% open · ⏱️ 11.05.2020): +- [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 120 · 📦 35 · 📋 50 - 32% open · ⏱️ 30.07.2021): ``` - git clone https://github.com/claesenm/optunity + git clone https://github.com/rsteca/sklearn-deap ``` -- [PyPi](https://pypi.org/project/optunity): +- [PyPi](https://pypi.org/project/sklearn-deap) (📥 670 / month): ``` - pip install optunity + pip install sklearn-deap ```
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Auto ViML (🥉17 · ⭐ 310) - 用单行代码自动构建多个ML模型。Apache-2 +
Dragonfly (🥉18 · ⭐ 670) - An open source python library for scalable Bayesian optimisation. MIT -- [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 69 · 📦 15 · 📋 18 - 22% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 13 · 🔀 210 · 📋 56 - 64% open · ⏱️ 14.07.2022): ``` - git clone https://github.com/AutoViML/Auto_ViML + git clone https://github.com/dragonfly/dragonfly ``` -- [PyPi](https://pypi.org/project/autoviml) (📥 930 / month): +- [PyPi](https://pypi.org/project/dragonfly-opt) (📥 35K / month): ``` - pip install autoviml + pip install dragonfly-opt ```
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Sherpa (🥉17 · ⭐ 310 · 💀) - 超参数优化库。❗Unlicensed +
AlphaPy (🥉17 · ⭐ 800) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 -- [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 48 · 📦 17 · 📋 56 - 26% open · ⏱️ 18.10.2020): +- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 160 · 📦 3 · 📋 41 - 29% open · ⏱️ 23.04.2022): ``` - git clone https://github.com/sherpa-ai/sherpa + git clone https://github.com/ScottfreeLLC/AlphaPy ``` -- [PyPi](https://pypi.org/project/parameter-sherpa) (📥 420 / month): +- [PyPi](https://pypi.org/project/alphapy) (📥 59 / month): ``` - pip install parameter-sherpa + pip install alphapy ```
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Orion (🥉17 · ⭐ 210) - 异步分布式超参数优化。❗Unlicensed +
Auto Tune Models (🥉17 · ⭐ 520 · 💀) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT -- [GitHub](https://github.com/Epistimio/orion) (👨‍💻 24 · 🔀 41 · 📦 47 · 📋 200 - 29% open · ⏱️ 01.12.2021): +- [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 12 · 📋 89 - 20% open · ⏱️ 21.02.2020): ``` - git clone https://github.com/Epistimio/orion + git clone https://github.com/HDI-Project/ATM ``` -- [PyPi](https://pypi.org/project/orion): +- [PyPi](https://pypi.org/project/atm) (📥 67 / month): ``` - pip install orion + pip install atm ```
-
Auto Tune Models (🥉16 · ⭐ 510 · 💀) - 自动调整模型。MIT +
Auto ViML (🥉17 · ⭐ 360) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 -- [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 8 · 📋 88 - 19% open · ⏱️ 21.02.2020): +- [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 81 · 📦 17 · 📋 21 - 19% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/HDI-Project/ATM + git clone https://github.com/AutoViML/Auto_ViML ``` -- [PyPi](https://pypi.org/project/atm) (📥 97 / month): +- [PyPi](https://pypi.org/project/autoviml) (📥 460 / month): ``` - pip install atm + pip install autoviml ```
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featurewiz (🥉16 · ⭐ 99) - 自动化特征工程并进行特征选择的工具库。Apache-2 +
Parfit (🥉17 · ⭐ 200 · 💀) - A package for parallelizing the fit and flexibly scoring of.. MIT -- [GitHub](https://github.com/AutoViML/featurewiz) (👨‍💻 3 · 🔀 27 · 📦 3 · 📋 7 - 71% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 4 · 🔀 25 · 📦 16 · 📋 11 - 54% open · ⏱️ 04.04.2020): ``` - git clone https://github.com/AutoViML/featurewiz + git clone https://github.com/jmcarpenter2/parfit ``` -- [PyPi](https://pypi.org/project/featurewiz) (📥 120K / month): +- [PyPi](https://pypi.org/project/parfit) (📥 9.7K / month): ``` - pip install featurewiz + pip install parfit ```
-
automl-gs (🥉15 · ⭐ 1.8K · 💀) - 提供输入CSV和目标字段以进行预测，自动生成可运行代码。MIT +
automl-gs (🥉16 · ⭐ 1.8K · 💀) - Provide an input CSV and a target field to predict, generate a.. MIT -- [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 27 · 📋 30 - 80% open · ⏱️ 05.04.2019): +- [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 32 · 📋 30 - 80% open · ⏱️ 05.04.2019): ``` git clone https://github.com/minimaxir/automl-gs ``` -- [PyPi](https://pypi.org/project/automl_gs) (📥 19 / month): +- [PyPi](https://pypi.org/project/automl_gs) (📥 22 / month): ``` pip install automl_gs ```
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Advisor (🥉15 · ⭐ 1.4K · 💀) - Google Vizier的超参数开源实现。Apache-2 +
featurewiz (🥉16 · ⭐ 270) - Use advanced feature engineering strategies and select the.. Apache-2 -- [GitHub](https://github.com/tobegit3hub/advisor) (👨‍💻 11 · 🔀 260 · 📋 32 - 59% open · ⏱️ 11.11.2019): +- [GitHub](https://github.com/AutoViML/featurewiz) (👨‍💻 4 · 🔀 57 · 📦 14 · ⏱️ 21.08.2022): ``` - git clone https://github.com/tobegit3hub/advisor - ``` -- [PyPi](https://pypi.org/project/advisor) (📥 62 / month): - ``` - pip install advisor + git clone https://github.com/AutoViML/featurewiz ``` -- [Docker Hub](https://hub.docker.com/r/tobegit3hub/advisor) (📥 1.6K · ⏱️ 11.11.2019): +- [PyPi](https://pypi.org/project/featurewiz) (📥 6.5K / month): ``` - docker pull tobegit3hub/advisor + pip install featurewiz ```
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Xcessiv (🥉15 · ⭐ 1.3K · 💀) - 基于Web的应用程序，高效、可扩展且自动化。Apache-2 +
Advisor (🥉15 · ⭐ 1.5K · 💀) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 -- [GitHub](https://github.com/reiinakano/xcessiv) (👨‍💻 6 · 🔀 110 · 📦 1 · 📋 34 - 61% open · ⏱️ 21.08.2017): +- [GitHub](https://github.com/tobegit3hub/advisor) (👨‍💻 11 · 🔀 260 · 📋 32 - 59% open · ⏱️ 11.11.2019): ``` - git clone https://github.com/reiinakano/xcessiv + git clone https://github.com/tobegit3hub/advisor + ``` +- [PyPi](https://pypi.org/project/advisor) (📥 34 / month): + ``` + pip install advisor ``` -- [PyPi](https://pypi.org/project/xcessiv): +- [Docker Hub](https://hub.docker.com/r/tobegit3hub/advisor) (📥 1.7K · ⏱️ 11.11.2019): ``` - pip install xcessiv + docker pull tobegit3hub/advisor ```
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Parfit (🥉15 · ⭐ 200 · 💀) - 并行化拟合与评估工具库。MIT +
Xcessiv (🥉15 · ⭐ 1.3K · 💀) - A web-based application for quick, scalable, and automated.. Apache-2 -- [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 2 · 🔀 25 · 📦 9 · 📋 11 - 54% open · ⏱️ 04.04.2020): +- [GitHub](https://github.com/reiinakano/xcessiv) (👨‍💻 6 · 🔀 110 · 📦 1 · 📋 34 - 61% open · ⏱️ 21.08.2017): ``` - git clone https://github.com/jmcarpenter2/parfit + git clone https://github.com/reiinakano/xcessiv ``` -- [PyPi](https://pypi.org/project/parfit) (📥 16K / month): +- [PyPi](https://pypi.org/project/xcessiv) (📥 10 / month): ``` - pip install parfit + pip install xcessiv ```
-
HyperparameterHunter (🥉14 · ⭐ 680 · 💤) - 轻松进行超参数优化和自动结果评估。MIT +
HyperparameterHunter (🥉15 · ⭐ 690 · 💀) - Easy hyperparameter optimization and automatic result.. MIT -- [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (👨‍💻 4 · 🔀 87 · 📥 330 · 📋 120 - 27% open · ⏱️ 20.01.2021): +- [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (👨‍💻 4 · 🔀 88 · 📥 330 · 📋 120 - 27% open · ⏱️ 20.01.2021): ``` git clone https://github.com/HunterMcGushion/hyperparameter_hunter ``` -- [PyPi](https://pypi.org/project/hyperparameter-hunter): +- [PyPi](https://pypi.org/project/hyperparameter-hunter) (📥 61 / month): ``` pip install hyperparameter-hunter ```
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ENAS (🥉13 · ⭐ 2.5K · 💀) - Efficient Neural Architecture Search的Pytorch实现。Apache-2 +
ENAS (🥉13 · ⭐ 2.6K · 💀) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 -- [GitHub](https://github.com/carpedm20/ENAS-pytorch) (👨‍💻 6 · 🔀 460 · 📋 44 - 84% open · ⏱️ 16.06.2020): +- [GitHub](https://github.com/carpedm20/ENAS-pytorch) (👨‍💻 6 · 🔀 470 · 📋 44 - 84% open · ⏱️ 16.06.2020): ``` git clone https://github.com/carpedm20/ENAS-pytorch ```
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Auptimizer (🥉13 · ⭐ 180 · 💤) - 自动ML模型优化工具。❗️GPL-3.0 +
Auptimizer (🥉13 · ⭐ 190 · 💀) - An automatic ML model optimization tool. ❗️GPL-3.0 -- [GitHub](https://github.com/LGE-ARC-AdvancedAI/auptimizer) (👨‍💻 11 · 🔀 21 · ⏱️ 03.03.2021): +- [GitHub](https://github.com/LGE-ARC-AdvancedAI/auptimizer) (👨‍💻 11 · 🔀 22 · 📋 6 - 16% open · ⏱️ 03.03.2021): ``` git clone https://github.com/LGE-ARC-AdvancedAI/auptimizer ``` -- [PyPi](https://pypi.org/project/auptimizer) (📥 33 / month): +- [PyPi](https://pypi.org/project/auptimizer) (📥 25 / month): ``` pip install auptimizer ```
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Hypermax (🥉12 · ⭐ 97 · 💀) - 更好更快的超参数优化。BSD-3 +
Hypermax (🥉12 · ⭐ 100 · 💀) - Better, faster hyper-parameter optimization. BSD-3 - [GitHub](https://github.com/electricbrainio/hypermax) (👨‍💻 9 · 🔀 13 · 📦 4 · 📋 5 - 60% open · ⏱️ 02.08.2020): ``` git clone https://github.com/electricbrainio/hypermax ``` -- [PyPi](https://pypi.org/project/hypermax) (📥 31 / month): +- [PyPi](https://pypi.org/project/hypermax) (📥 30 / month): ``` pip install hypermax ```
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Devol (🥉11 · ⭐ 940 · 💀) - 使用Keras进行遗传神经体系结构搜索。MIT +
Devol (🥉11 · ⭐ 940 · 💀) - Genetic neural architecture search with Keras. MIT - [GitHub](https://github.com/joeddav/devol) (👨‍💻 18 · 🔀 110 · 📋 27 - 25% open · ⏱️ 05.07.2020): @@ -7429,1871 +7429,1871 @@ _用于超参数优化，自动机器学习和神经体系结构搜索的库。_ git clone https://github.com/joeddav/devol ```
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Hypertunity (🥉11 · ⭐ 120 · 💀) - 黑盒超参数优化的工具集。Apache-2 +
Hypertunity (🥉10 · ⭐ 120 · 💀) - A toolset for black-box hyperparameter optimisation. Apache-2 - [GitHub](https://github.com/gdikov/hypertunity) (👨‍💻 2 · 🔀 9 · 📦 2 · ⏱️ 26.01.2020): ``` git clone https://github.com/gdikov/hypertunity ``` -- [PyPi](https://pypi.org/project/hypertunity) (📥 25 / month): +- [PyPi](https://pypi.org/project/hypertunity) (📥 18 / month): ``` pip install hypertunity ```

-## 强化学习 +## Reinforcement Learning -Back to top +Back to top -_用于构建和评估强化学习和基于agent的系统的库。_ +_Libraries for building and evaluating reinforcement learning & agent-based systems._ -
OpenAI Gym (🥇36 · ⭐ 26K) - 开发和比较强化学习的工具包。MIT +
OpenAI Gym (🥇36 · ⭐ 28K) - A toolkit for developing and comparing reinforcement learning.. MIT -- [GitHub](https://github.com/openai/gym) (👨‍💻 330 · 🔀 7K · 📦 25K · 📋 1.4K - 6% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/openai/gym) (👨‍💻 380 · 🔀 7.5K · 📦 32K · 📋 1.6K - 0% open · ⏱️ 24.08.2022): ``` git clone https://github.com/openai/gym ``` -- [PyPi](https://pypi.org/project/gym) (📥 930K / month): +- [PyPi](https://pypi.org/project/gym) (📥 620K / month): ``` pip install gym ```
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ViZDoom (🥇23 · ⭐ 1.3K) - 人工智能强化学习工具库。❗Unlicensed +
TF-Agents (🥇27 · ⭐ 2.3K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 -- [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 45 · 🔀 300 · 📥 11K · 📦 120 · 📋 420 - 19% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/tensorflow/agents) (👨‍💻 120 · 🔀 620 · 📦 880 · 📋 560 - 22% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/mwydmuch/ViZDoom + git clone https://github.com/tensorflow/agents ``` -- [PyPi](https://pypi.org/project/vizdoom): +- [PyPi](https://pypi.org/project/tf-agents) (📥 150K / month): ``` - pip install vizdoom + pip install tf-agents ```
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baselines (🥈22 · ⭐ 12K · 💀) - OpenAI基线：强化学习的高质量实现。MIT +
keras-rl (🥈25 · ⭐ 5.3K · 💀) - Deep Reinforcement Learning for Keras. MIT -- [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.3K · 📦 360 · 📋 820 - 47% open · ⏱️ 31.01.2020): +- [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 610 · 📋 230 - 2% open · ⏱️ 11.11.2019): ``` - git clone https://github.com/openai/baselines + git clone https://github.com/keras-rl/keras-rl ``` -- [PyPi](https://pypi.org/project/baselines): +- [PyPi](https://pypi.org/project/keras-rl) (📥 1.3K / month): ``` - pip install baselines + pip install keras-rl ```
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keras-rl (🥈22 · ⭐ 5.2K · 💀) - Keras的深度强化学习。MIT +
baselines (🥈24 · ⭐ 13K · 💀) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT -- [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 540 · 📋 230 - 4% open · ⏱️ 11.11.2019): +- [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.5K · 📦 410 · 📋 830 - 47% open · ⏱️ 31.01.2020): ``` - git clone https://github.com/keras-rl/keras-rl + git clone https://github.com/openai/baselines ``` -- [PyPi](https://pypi.org/project/keras-rl): +- [PyPi](https://pypi.org/project/baselines) (📥 940 / month): ``` - pip install keras-rl + pip install baselines ```
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Acme (🥈22 · ⭐ 2.4K) - 强化学习组件和代理库。Apache-2 +
Acme (🥈24 · ⭐ 2.7K) - A library of reinforcement learning components and agents. Apache-2 -- [GitHub](https://github.com/deepmind/acme) (👨‍💻 53 · 🔀 290 · 📦 47 · 📋 140 - 27% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/deepmind/acme) (👨‍💻 75 · 🔀 340 · 📦 99 · 📋 210 - 14% open · ⏱️ 25.08.2022): ``` git clone https://github.com/deepmind/acme ``` -- [PyPi](https://pypi.org/project/dm-acme): +- [PyPi](https://pypi.org/project/dm-acme) (📥 5K / month): ``` pip install dm-acme ```
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TF-Agents (🥈21 · ⭐ 2.1K) - TF-Agents：可靠，可扩展且易于使用的TensorFlow的强化学习库。Apache-2 +
garage (🥈23 · ⭐ 1.5K) - A toolkit for reproducible reinforcement learning research. MIT -- [GitHub](https://github.com/tensorflow/agents) (👨‍💻 110 · 🔀 560 · 📦 650 · 📋 510 - 19% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 78 · 🔀 260 · 📦 51 · 📋 1K - 19% open · ⏱️ 20.05.2022): ``` - git clone https://github.com/tensorflow/agents + git clone https://github.com/rlworkgroup/garage ``` -- [PyPi](https://pypi.org/project/tf-agents): +- [PyPi](https://pypi.org/project/garage) (📥 460 / month): ``` - pip install tf-agents + pip install garage ```
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PFRL (🥈21 · ⭐ 750) - PFRL：基于PyTorch的深度强化学习库。MIT +
ViZDoom (🥈23 · ⭐ 1.4K) - Doom-based AI Research Platform for Reinforcement Learning from.. ❗Unlicensed -- [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 15 · 🔀 98 · 📦 27 · 📋 56 - 41% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 49 · 🔀 330 · 📥 12K · 📦 150 · 📋 440 - 19% open · ⏱️ 26.06.2022): ``` - git clone https://github.com/pfnet/pfrl + git clone https://github.com/mwydmuch/ViZDoom ``` -- [PyPi](https://pypi.org/project/pfrl) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/vizdoom) (📥 630 / month): ``` - pip install pfrl + pip install vizdoom ```
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TensorForce (🥈20 · ⭐ 3.1K) - Tensorforce：一个基于TensorFlow的强化学习库。Apache-2 +
Dopamine (🥈22 · ⭐ 9.9K) - Dopamine is a research framework for fast prototyping of.. Apache-2 -- [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 81 · 🔀 490 · 📋 620 - 0% open · ⏱️ 10.11.2021): +- [GitHub](https://github.com/google/dopamine) (👨‍💻 15 · 🔀 1.3K · 📋 150 - 43% open · ⏱️ 13.06.2022): ``` - git clone https://github.com/tensorforce/tensorforce + git clone https://github.com/google/dopamine ``` -- [PyPi](https://pypi.org/project/tensorforce): +- [PyPi](https://pypi.org/project/dopamine-rl) (📥 49K / month): ``` - pip install tensorforce + pip install dopamine-rl ```
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garage (🥈20 · ⭐ 1.4K) - 用于可重复的强化学习研究的工具包。MIT +
TensorForce (🥈22 · ⭐ 3.2K) - Tensorforce: a TensorFlow library for applied.. Apache-2 -- [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 78 · 🔀 240 · 📦 23 · 📋 990 - 19% open · ⏱️ 20.10.2021): +- [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 82 · 🔀 510 · 📋 650 - 3% open · ⏱️ 10.02.2022): ``` - git clone https://github.com/rlworkgroup/garage + git clone https://github.com/tensorforce/tensorforce ``` -- [PyPi](https://pypi.org/project/garage): +- [PyPi](https://pypi.org/project/tensorforce) (📥 1.2K / month): ``` - pip install garage + pip install tensorforce ```
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ChainerRL (🥈20 · ⭐ 1K · 💤) - ChainerRL是建立在Chainer之上的深度强化学习库。MIT +
ChainerRL (🥈22 · ⭐ 1.1K · 💀) - ChainerRL is a deep reinforcement learning library built on top of.. MIT -- [GitHub](https://github.com/chainer/chainerrl) (👨‍💻 29 · 🔀 210 · 📦 110 · 📋 200 - 25% open · ⏱️ 17.04.2021): +- [GitHub](https://github.com/chainer/chainerrl) (👨‍💻 29 · 🔀 220 · 📦 130 · 📋 200 - 25% open · ⏱️ 17.04.2021): ``` git clone https://github.com/chainer/chainerrl ``` -- [PyPi](https://pypi.org/project/chainerrl): +- [PyPi](https://pypi.org/project/chainerrl) (📥 520 / month): ``` pip install chainerrl ```
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Dopamine (🥉18 · ⭐ 9.7K) - Dopamine是一个用于快速对强化学习进行原型制作的研究框架。Apache-2 +
RLax (🥈22 · ⭐ 890) - A library of reinforcement learning building blocks in JAX. Apache-2 jax -- [GitHub](https://github.com/google/dopamine) (👨‍💻 14 · 🔀 1.3K · 📋 140 - 42% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/deepmind/rlax) (👨‍💻 19 · 🔀 66 · 📦 75 · 📋 19 - 21% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/google/dopamine + git clone https://github.com/deepmind/rlax ``` -- [PyPi](https://pypi.org/project/dopamine-rl): +- [PyPi](https://pypi.org/project/rlax) (📥 5.3K / month): ``` - pip install dopamine-rl + pip install rlax ```
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TensorLayer (🥉18 · ⭐ 6.8K) - 深度学习和强化学习库。❗Unlicensed +
TensorLayer (🥉21 · ⭐ 7.1K) - Deep Learning and Reinforcement Learning Library for.. ❗Unlicensed -- [GitHub](https://github.com/tensorlayer/TensorLayer) (👨‍💻 130 · 🔀 1.5K · 📥 1.3K · 📋 460 - 3% open · ⏱️ 29.10.2021): +- [GitHub](https://github.com/tensorlayer/TensorLayer) (👨‍💻 130 · 🔀 1.6K · 📥 1.4K · 📋 460 - 4% open · ⏱️ 23.04.2022): ``` git clone https://github.com/tensorlayer/tensorlayer ``` -- [PyPi](https://pypi.org/project/tensorlayer): +- [PyPi](https://pypi.org/project/tensorlayer) (📥 1.5K / month): ``` pip install tensorlayer ```
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PARL (🥉18 · ⭐ 2.3K) - 强化学习高性能分布式训练框架。Apache-2 +
Stable Baselines (🥉20 · ⭐ 3.6K · 💤) - A fork of OpenAI Baselines, implementations of.. MIT -- [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 28 · 🔀 590 · 📦 84 · 📋 280 - 21% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 690 · 📋 920 - 11% open · ⏱️ 25.08.2021): ``` - git clone https://github.com/PaddlePaddle/PARL + git clone https://github.com/hill-a/stable-baselines ``` -- [PyPi](https://pypi.org/project/parl): +- [PyPi](https://pypi.org/project/stable-baselines) (📥 7.9K / month): ``` - pip install parl + pip install stable-baselines ```
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Stable Baselines (🥉17 · ⭐ 3.4K) - OpenAI Baselines的一个分支，强化学习的实现。MIT +
PARL (🥉20 · ⭐ 2.7K) - A high-performance distributed training framework for Reinforcement.. Apache-2 -- [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 650 · 📋 900 - 11% open · ⏱️ 25.08.2021): +- [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 31 · 🔀 730 · 📦 94 · 📋 410 - 15% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/hill-a/stable-baselines + git clone https://github.com/PaddlePaddle/PARL ``` -- [PyPi](https://pypi.org/project/stable-baselines): +- [PyPi](https://pypi.org/project/parl) (📥 500 / month): ``` - pip install stable-baselines + pip install parl ```
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ReAgent (🥉17 · ⭐ 3.1K) - 推理系统平台。BSD-3 +
PFRL (🥉20 · ⭐ 890) - PFRL: a PyTorch-based deep reinforcement learning library. MIT -- [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 120 · 🔀 420 · 📋 97 - 22% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 16 · 🔀 120 · 📦 54 · 📋 63 - 38% open · ⏱️ 14.03.2022): ``` - git clone https://github.com/facebookresearch/ReAgent + git clone https://github.com/pfnet/pfrl + ``` +- [PyPi](https://pypi.org/project/pfrl) (📥 410 / month): + ``` + pip install pfrl ```
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Coach (🥉17 · ⭐ 2.1K) - 英特尔AI实验室的强化学习训练器。Apache-2 +
TRFL (🥉19 · ⭐ 3.1K · 💤) - TensorFlow Reinforcement Learning. Apache-2 -- [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 410 · 📋 260 - 29% open · ⏱️ 28.06.2021): +- [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 380 · 📦 89 · 📋 20 - 20% open · ⏱️ 16.08.2021): ``` - git clone https://github.com/IntelLabs/coach + git clone https://github.com/deepmind/trfl ``` -- [PyPi](https://pypi.org/project/rl_coach): +- [PyPi](https://pypi.org/project/trfl) (📥 4.2K / month): ``` - pip install rl_coach + pip install trfl ```
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RLax (🥉17 · ⭐ 720) - 强化学习组件和代理库。Apache-2 jax +
Coach (🥉18 · ⭐ 2.2K · 💀) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 -- [GitHub](https://github.com/deepmind/rlax) (👨‍💻 16 · 🔀 56 · 📦 32 · 📋 12 - 25% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 430 · 📋 260 - 30% open · ⏱️ 28.06.2021): ``` - git clone https://github.com/deepmind/rlax + git clone https://github.com/IntelLabs/coach ``` -- [PyPi](https://pypi.org/project/rlax): +- [PyPi](https://pypi.org/project/rl_coach) (📥 120 / month): ``` - pip install rlax + pip install rl_coach ```
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DeepMind Lab (🥉16 · ⭐ 6.6K) - 可定制的3D平台，用于agent-based AI研究。❗️GPL-2.0 +
ReAgent (🥉17 · ⭐ 3.2K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 -- [GitHub](https://github.com/deepmind/lab) (👨‍💻 7 · 🔀 1.3K · 📋 210 - 23% open · ⏱️ 21.07.2021): +- [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 140 · 🔀 460 · 📋 100 - 25% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/deepmind/lab + git clone https://github.com/facebookresearch/ReAgent ```
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TRFL (🥉16 · ⭐ 3.1K) - TensorFlow强化学习。Apache-2 +
DeepMind Lab (🥉15 · ⭐ 6.7K) - A customisable 3D platform for agent-based AI research. ❗Unlicensed -- [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 370 · 📦 68 · 📋 20 - 20% open · ⏱️ 16.08.2021): +- [GitHub](https://github.com/deepmind/lab) (👨‍💻 8 · 🔀 1.3K · 📋 220 - 25% open · ⏱️ 09.06.2022): ``` - git clone https://github.com/deepmind/trfl - ``` -- [PyPi](https://pypi.org/project/trfl): - ``` - pip install trfl + git clone https://github.com/deepmind/lab ```

-## 推荐系统 +## Recommender Systems -Back to top +Back to top -_用于建立和评估推荐系统的库。_ +_Libraries for building and evaluating recommendation systems._ -
TF Recommenders (🥇25 · ⭐ 1.1K) - TensorFlow Recommenders是一个用于构建推荐系统的工具库。Apache-2 +
lightfm (🥇26 · ⭐ 4.1K) - A Python implementation of LightFM, a hybrid recommendation algorithm. Apache-2 -- [GitHub](https://github.com/tensorflow/recommenders) (👨‍💻 29 · 🔀 150 · 📦 61 · 📋 200 - 53% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 630 · 📦 790 · 📋 460 - 24% open · ⏱️ 19.07.2022): ``` - git clone https://github.com/tensorflow/recommenders + git clone https://github.com/lyst/lightfm ``` -- [PyPi](https://pypi.org/project/tensorflow-recommenders) (📥 250K / month): +- [PyPi](https://pypi.org/project/lightfm) (📥 360K / month): ``` - pip install tensorflow-recommenders + pip install lightfm + ``` +- [Conda](https://anaconda.org/conda-forge/lightfm) (📥 130K · ⏱️ 09.03.2022): + ``` + conda install -c conda-forge lightfm ```
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lightfm (🥇24 · ⭐ 3.9K · 💤) - 全局优化的Python实现。Apache-2 +
implicit (🥇26 · ⭐ 2.9K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT -- [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 610 · 📦 610 · 📋 430 - 20% open · ⏱️ 07.02.2021): +- [GitHub](https://github.com/benfred/implicit) (👨‍💻 32 · 🔀 530 · 📥 95 · 📦 650 · 📋 420 - 16% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/lyst/lightfm + git clone https://github.com/benfred/implicit ``` -- [PyPi](https://pypi.org/project/lightfm): +- [PyPi](https://pypi.org/project/implicit) (📥 160K / month): ``` - pip install lightfm + pip install implicit ``` -- [Conda](https://anaconda.org/conda-forge/lightfm) (📥 110K · ⏱️ 07.02.2021): +- [Conda](https://anaconda.org/conda-forge/implicit) (📥 390K · ⏱️ 29.01.2022): ``` - conda install -c conda-forge lightfm + conda install -c conda-forge implicit ```
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implicit (🥇24 · ⭐ 2.6K) - 隐式反馈数据集的快速Python协同过滤。MIT +
TF Recommenders (🥇26 · ⭐ 1.4K) - TensorFlow Recommenders is a library for building.. Apache-2 -- [GitHub](https://github.com/benfred/implicit) (👨‍💻 30 · 🔀 500 · 📦 520 · 📋 370 - 22% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/tensorflow/recommenders) (👨‍💻 37 · 🔀 200 · 📦 140 · 📋 280 - 49% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/benfred/implicit + git clone https://github.com/tensorflow/recommenders ``` -- [PyPi](https://pypi.org/project/implicit) (📥 120K / month): +- [PyPi](https://pypi.org/project/tensorflow-recommenders) (📥 560K / month): ``` - pip install implicit + pip install tensorflow-recommenders + ``` +
+
TF Ranking (🥈23 · ⭐ 2.5K) - Learning to Rank in TensorFlow. Apache-2 + +- [GitHub](https://github.com/tensorflow/ranking) (👨‍💻 28 · 🔀 430 · 📋 290 - 19% open · ⏱️ 26.04.2022): + + ``` + git clone https://github.com/tensorflow/ranking ``` -- [Conda](https://anaconda.org/conda-forge/implicit) (📥 320K · ⏱️ 29.08.2021): +- [PyPi](https://pypi.org/project/tensorflow_ranking) (📥 110K / month): ``` - conda install -c conda-forge implicit + pip install tensorflow_ranking ```
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Cornac (🥇24 · ⭐ 490) - 多模态推荐系统的比较框架。Apache-2 +
Cornac (🥈23 · ⭐ 630) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 -- [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 13 · 🔀 81 · 📦 68 · 📋 74 - 1% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 15 · 🔀 100 · 📦 120 · 📋 100 - 8% open · ⏱️ 22.07.2022): ``` git clone https://github.com/PreferredAI/cornac ``` -- [PyPi](https://pypi.org/project/cornac) (📥 7.2K / month): +- [PyPi](https://pypi.org/project/cornac) (📥 40K / month): ``` pip install cornac ``` -- [Conda](https://anaconda.org/conda-forge/cornac) (📥 190K · ⏱️ 15.11.2021): +- [Conda](https://anaconda.org/conda-forge/cornac) (📥 240K · ⏱️ 19.02.2022): ``` conda install -c conda-forge cornac ```
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scikit-surprise (🥈22 · ⭐ 5.1K · 💀) - 用于构建和分析推荐算法的Python scikit工具库。BSD-3 +
scikit-surprise (🥉22 · ⭐ 5.5K) - A Python scikit for building and analyzing recommender.. BSD-3 -- [GitHub](https://github.com/NicolasHug/Surprise) (👨‍💻 38 · 🔀 890 · 📋 330 - 12% open · ⏱️ 05.08.2020): +- [GitHub](https://github.com/NicolasHug/Surprise) (👨‍💻 43 · 🔀 920 · 📋 350 - 15% open · ⏱️ 21.08.2022): ``` git clone https://github.com/NicolasHug/Surprise ``` -- [PyPi](https://pypi.org/project/scikit-surprise) (📥 72K / month): +- [PyPi](https://pypi.org/project/scikit-surprise) (📥 120K / month): ``` pip install scikit-surprise ``` -- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (📥 200K · ⏱️ 18.11.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (📥 250K · ⏱️ 18.11.2021): ``` conda install -c conda-forge scikit-surprise ```
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RecBole (🥉21 · ⭐ 1.5K) - 统一，全面，高效的推荐库。MIT +
RecBole (🥉22 · ⭐ 2K) - A unified, comprehensive and efficient recommendation library. MIT -- [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 41 · 🔀 250 · 📋 260 - 16% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 47 · 🔀 380 · 📋 460 - 13% open · ⏱️ 26.08.2022): ``` git clone https://github.com/RUCAIBox/RecBole ``` -- [PyPi](https://pypi.org/project/recbole): +- [PyPi](https://pypi.org/project/recbole) (📥 6.7K / month): ``` pip install recbole ``` -- [Conda](https://anaconda.org/aibox/recbole) (📥 910 · ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/aibox/recbole) (📥 1.9K · ⏱️ 25.02.2022): ``` conda install -c aibox recbole ```
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Recommenders (🥉19 · ⭐ 12K) - 推荐系统最佳实践。MIT +
Recommenders (🥉21 · ⭐ 14K) - Best Practices on Recommendation Systems. MIT -- [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 100 · 🔀 2K · 📥 85 · 📦 5 · 📋 630 - 23% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 120 · 🔀 2.4K · 📥 230 · 📦 33 · 📋 710 - 20% open · ⏱️ 20.07.2022): ``` git clone https://github.com/microsoft/recommenders ```
-
TF Ranking (🥉19 · ⭐ 2.4K) - 在TensorFlow中学习推荐排序。Apache-2 - -- [GitHub](https://github.com/tensorflow/ranking) (👨‍💻 25 · 🔀 410 · 📋 280 - 16% open · ⏱️ 22.11.2021): - - ``` - git clone https://github.com/tensorflow/ranking - ``` -- [PyPi](https://pypi.org/project/tensorflow_ranking): - ``` - pip install tensorflow_ranking - ``` -
-
Case Recommender (🥉19 · ⭐ 370) - Case Recommender：灵活且可扩展的Python推荐系统工具库。MIT +
fastFM (🥉19 · ⭐ 1K · 💀) - fastFM: A Library for Factorization Machines. ❗Unlicensed -- [GitHub](https://github.com/caserec/CaseRecommender) (👨‍💻 11 · 🔀 77 · 📦 9 · 📋 24 - 16% open · ⏱️ 25.11.2021): +- [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 200 · 📥 450 · 📦 97 · 📋 110 - 43% open · ⏱️ 24.03.2021): ``` - git clone https://github.com/caserec/CaseRecommender + git clone https://github.com/ibayer/fastFM ``` -- [PyPi](https://pypi.org/project/caserecommender) (📥 820 / month): +- [PyPi](https://pypi.org/project/fastfm) (📥 370 / month): ``` - pip install caserecommender + pip install fastfm ```
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tensorrec (🥉18 · ⭐ 1.2K · 💀) - TensorFlow推荐算法和框架。Apache-2 +
recmetrics (🥉19 · ⭐ 420) - A library of metrics for evaluating recommender systems. MIT -- [GitHub](https://github.com/jfkirk/tensorrec) (👨‍💻 9 · 🔀 220 · 📦 26 · 📋 120 - 28% open · ⏱️ 04.02.2020): +- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 16 · 🔀 85 · 📦 29 · 📋 20 - 40% open · ⏱️ 17.04.2022): ``` - git clone https://github.com/jfkirk/tensorrec + git clone https://github.com/statisticianinstilettos/recmetrics ``` -- [PyPi](https://pypi.org/project/tensorrec) (📥 310 / month): +- [PyPi](https://pypi.org/project/recmetrics) (📥 3.3K / month): ``` - pip install tensorrec + pip install recmetrics ```
-
recmetrics (🥉18 · ⭐ 330) - 用于评估推荐系统的度量标准库。MIT +
Spotlight (🥉18 · ⭐ 2.8K · 💀) - Deep recommender models using PyTorch. MIT -- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 13 · 🔀 74 · 📦 20 · 📋 16 - 37% open · ⏱️ 27.10.2021): +- [GitHub](https://github.com/maciejkula/spotlight) (👨‍💻 11 · 🔀 400 · 📋 110 - 56% open · ⏱️ 09.02.2020): ``` - git clone https://github.com/statisticianinstilettos/recmetrics + git clone https://github.com/maciejkula/spotlight ``` -- [PyPi](https://pypi.org/project/recmetrics) (📥 1.1K / month): +- [Conda](https://anaconda.org/maciejkula/spotlight) (📥 7.6K · ⏱️ 27.05.2018): ``` - pip install recmetrics + conda install -c maciejkula spotlight ```
-
Spotlight (🥉17 · ⭐ 2.6K · 💀) - 使用PyTorch的深度推荐系统模型实现。MIT +
tensorrec (🥉18 · ⭐ 1.2K · 💀) - A TensorFlow recommendation algorithm and framework in.. Apache-2 -- [GitHub](https://github.com/maciejkula/spotlight) (👨‍💻 11 · 🔀 390 · 📋 110 - 55% open · ⏱️ 09.02.2020): +- [GitHub](https://github.com/jfkirk/tensorrec) (👨‍💻 9 · 🔀 220 · 📦 27 · 📋 130 - 28% open · ⏱️ 04.02.2020): ``` - git clone https://github.com/maciejkula/spotlight + git clone https://github.com/jfkirk/tensorrec ``` -- [Conda](https://anaconda.org/maciejkula/spotlight) (📥 6.5K · ⏱️ 27.05.2018): +- [PyPi](https://pypi.org/project/tensorrec) (📥 470 / month): ``` - conda install -c maciejkula spotlight + pip install tensorrec ```
-
fastFM (🥉17 · ⭐ 960 · 💤) - fastFM：用于分解机的工具库。❗Unlicensed +
Case Recommender (🥉17 · ⭐ 420 · 💤) - Case Recommender: A Flexible and Extensible Python.. MIT -- [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 190 · 📥 420 · 📦 91 · 📋 110 - 43% open · ⏱️ 24.03.2021): +- [GitHub](https://github.com/caserec/CaseRecommender) (👨‍💻 11 · 🔀 79 · 📦 10 · 📋 25 - 20% open · ⏱️ 25.11.2021): ``` - git clone https://github.com/ibayer/fastFM + git clone https://github.com/caserec/CaseRecommender ``` -- [PyPi](https://pypi.org/project/fastfm): +- [PyPi](https://pypi.org/project/caserecommender) (📥 130 / month): ``` - pip install fastfm + pip install caserecommender ```

-## 隐私机器学习 +## Privacy Machine Learning -Back to top +Back to top -_使用联合学习和差异隐私之类的方法进行加密和保留隐私的机器学习的库。_ +_Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy._ -
PySyft (🥇26 · ⭐ 7.8K) - 基于内部数据自动化回答问题的工具库。Apache-2 +
PySyft (🥇26 · ⭐ 8.3K) - A library for answering questions using data you cannot see. Apache-2 -- [GitHub](https://github.com/OpenMined/PySyft) (👨‍💻 430 · 🔀 1.7K · 📋 3K - 9% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/OpenMined/PySyft) (👨‍💻 450 · 🔀 1.8K · 📋 3.1K - 1% open · ⏱️ 25.08.2022): ``` git clone https://github.com/OpenMined/PySyft ``` -- [PyPi](https://pypi.org/project/syft) (📥 4.7K / month): +- [PyPi](https://pypi.org/project/syft) (📥 4K / month): ``` pip install syft ```
-
TensorFlow Privacy (🥈23 · ⭐ 1.5K) - 用于训练机器学习模型的库。Apache-2 +
Opacus (🥈24 · ⭐ 1.2K) - Training PyTorch models with differential privacy. Apache-2 -- [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 43 · 🔀 330 · 📥 59 · 📋 140 - 39% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/pytorch/opacus) (👨‍💻 55 · 🔀 220 · 📥 51 · 📦 130 · 📋 200 - 21% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/tensorflow/privacy + git clone https://github.com/pytorch/opacus ``` -- [PyPi](https://pypi.org/project/tensorflow-privacy) (📥 23K / month): +- [PyPi](https://pypi.org/project/opacus) (📥 15K / month): ``` - pip install tensorflow-privacy + pip install opacus ```
-
FATE (🥈22 · ⭐ 3.8K) - 工业级联邦学习框架。Apache-2 +
TensorFlow Privacy (🥈23 · ⭐ 1.6K) - Library for training machine learning models with.. Apache-2 -- [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 68 · 🔀 1.1K · 📋 1K - 33% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 49 · 🔀 350 · 📥 80 · 📋 150 - 43% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/FederatedAI/FATE + git clone https://github.com/tensorflow/privacy + ``` +- [PyPi](https://pypi.org/project/tensorflow-privacy) (📥 32K / month): + ``` + pip install tensorflow-privacy ```
-
Opacus (🥈22 · ⭐ 1K) - 使用不同的隐私训练PyTorch模型。Apache-2 +
FATE (🥉22 · ⭐ 4.4K) - An Industrial Grade Federated Learning Framework. Apache-2 -- [GitHub](https://github.com/pytorch/opacus) (👨‍💻 40 · 🔀 160 · 📥 40 · 📦 69 · 📋 110 - 15% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 74 · 🔀 1.3K · 📋 1.3K - 36% open · ⏱️ 15.04.2022): ``` - git clone https://github.com/pytorch/opacus - ``` -- [PyPi](https://pypi.org/project/opacus) (📥 4K / month): - ``` - pip install opacus + git clone https://github.com/FederatedAI/FATE ```
-
TFEncrypted (🥉19 · ⭐ 960 · 💀) - TensorFlow中的加密机器学习框架。Apache-2 +
TFEncrypted (🥉20 · ⭐ 1K) - A Framework for Encrypted Machine Learning in TensorFlow. Apache-2 -- [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 170 · 📦 58 · 📋 410 - 42% open · ⏱️ 19.08.2020): +- [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 180 · 📦 62 · 📋 420 - 37% open · ⏱️ 26.08.2022): ``` git clone https://github.com/tf-encrypted/tf-encrypted ``` -- [PyPi](https://pypi.org/project/tf-encrypted) (📥 570 / month): +- [PyPi](https://pypi.org/project/tf-encrypted) (📥 440 / month): ``` pip install tf-encrypted ```
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CrypTen (🥉17 · ⭐ 970) - 隐私保护的机器学习框架。MIT +
CrypTen (🥉18 · ⭐ 1.1K) - A framework for Privacy Preserving Machine Learning. MIT -- [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 25 · 🔀 160 · 📦 12 · 📋 110 - 16% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 29 · 🔀 180 · 📦 21 · 📋 160 - 12% open · ⏱️ 10.06.2022): ``` git clone https://github.com/facebookresearch/CrypTen ``` -- [PyPi](https://pypi.org/project/crypten) (📥 310 / month): +- [PyPi](https://pypi.org/project/crypten) (📥 230 / month): ``` pip install crypten ```

-## 工作流程和实验跟踪 +## Workflow & Experiment Tracking -Back to top +Back to top -_跟踪和可视化机器学习实验的工具库整理。_ +_Libraries to organize, track, and visualize machine learning experiments._ -
Tensorboard (🥇37 · ⭐ 5.7K) - TensorFlow的可视化工具包。Apache-2 +
Tensorboard (🥇37 · ⭐ 6K) - TensorFlow's Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 270 · 🔀 1.4K · 📦 88K · 📋 1.6K - 32% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 290 · 🔀 1.5K · 📦 120K · 📋 1.7K - 31% open · ⏱️ 25.08.2022): ``` git clone https://github.com/tensorflow/tensorboard ``` -- [PyPi](https://pypi.org/project/tensorboard) (📥 13M / month): +- [PyPi](https://pypi.org/project/tensorboard) (📥 14M / month): ``` pip install tensorboard ``` -- [Conda](https://anaconda.org/conda-forge/tensorboard) (📥 2.7M · ⏱️ 10.11.2021): +- [Conda](https://anaconda.org/conda-forge/tensorboard) (📥 3.2M · ⏱️ 11.08.2022): ``` conda install -c conda-forge tensorboard ```
-
SageMaker SDK (🥇32 · ⭐ 1.5K) - 一个用于训练和部署机器学习的库。Apache-2 +
SageMaker SDK (🥇33 · ⭐ 1.7K) - A library for training and deploying machine learning.. Apache-2 -- [GitHub](https://github.com/aws/sagemaker-python-sdk) (👨‍💻 240 · 🔀 700 · 📦 980 · 📋 930 - 31% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/aws/sagemaker-python-sdk) (👨‍💻 280 · 🔀 810 · 📦 1.6K · 📋 1.1K - 32% open · ⏱️ 24.08.2022): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` -- [PyPi](https://pypi.org/project/sagemaker) (📥 2.3M / month): +- [PyPi](https://pypi.org/project/sagemaker) (📥 8.4M / month): ``` pip install sagemaker ```
-
tensorboardX (🥇30 · ⭐ 7.2K) - pytorch（和链接器，mxnet，numpy，...）的张量板。MIT +
PyCaret (🥇32 · ⭐ 6.1K) - An open-source, low-code machine learning library in Python. MIT + +- [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 99 · 🔀 1.4K · 📥 610 · 📦 2.4K · 📋 1.7K - 15% open · ⏱️ 13.08.2022): + + ``` + git clone https://github.com/pycaret/pycaret + ``` +- [PyPi](https://pypi.org/project/pycaret) (📥 580K / month): + ``` + pip install pycaret + ``` +
+
wandb client (🥇32 · ⭐ 4.6K) - A tool for visualizing and tracking your machine learning.. MIT + +- [GitHub](https://github.com/wandb/wandb) (👨‍💻 120 · 🔀 340 · 📦 11K · 📋 1.9K - 24% open · ⏱️ 26.08.2022): + + ``` + git clone https://github.com/wandb/client + ``` +- [PyPi](https://pypi.org/project/wandb) (📥 1.7M / month): + ``` + pip install wandb + ``` +
+
tensorboardX (🥈31 · ⭐ 7.4K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT -- [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 67 · 🔀 830 · 📥 340 · 📦 16K · 📋 420 - 14% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 72 · 🔀 850 · 📥 350 · 📦 21K · 📋 430 - 15% open · ⏱️ 08.06.2022): ``` git clone https://github.com/lanpa/tensorboardX ``` -- [PyPi](https://pypi.org/project/tensorboardX) (📥 680K / month): +- [PyPi](https://pypi.org/project/tensorboardX) (📥 1.1M / month): ``` pip install tensorboardX ``` -- [Conda](https://anaconda.org/conda-forge/tensorboardx) (📥 630K · ⏱️ 10.08.2021): +- [Conda](https://anaconda.org/conda-forge/tensorboardx) (📥 780K · ⏱️ 07.06.2022): ``` conda install -c conda-forge tensorboardx ```
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mlflow (🥇27 · ⭐ 11K) - 机器学习生命周期的开源平台。Apache-2 +
mlflow (🥈30 · ⭐ 12K) - Open source platform for the machine learning lifecycle. Apache-2 -- [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 340 · 🔀 2.3K · 📋 2K - 40% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 470 · 🔀 2.8K · 📋 2.4K - 33% open · ⏱️ 26.08.2022): ``` git clone https://github.com/mlflow/mlflow ``` -- [PyPi](https://pypi.org/project/mlflow): +- [PyPi](https://pypi.org/project/mlflow) (📥 13M / month): ``` pip install mlflow ``` -- [Conda](https://anaconda.org/conda-forge/mlflow) (📥 460K · ⏱️ 08.12.2021): +- [Conda](https://anaconda.org/conda-forge/mlflow) (📥 740K · ⏱️ 19.08.2022): ``` conda install -c conda-forge mlflow ```
-
Catalyst (🥇27 · ⭐ 2.8K) - 加快深度学习研发。Apache-2 +
sacred (🥈30 · ⭐ 3.9K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT -- [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 350 · 📦 450 · 📋 320 - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/IDSIA/sacred) (👨‍💻 100 · 🔀 350 · 📦 1.5K · 📋 540 - 16% open · ⏱️ 15.08.2022): ``` - git clone https://github.com/catalyst-team/catalyst + git clone https://github.com/IDSIA/sacred ``` -- [PyPi](https://pypi.org/project/catalyst) (📥 11K / month): +- [PyPi](https://pypi.org/project/sacred) (📥 68K / month): ``` - pip install catalyst + pip install sacred + ``` +
+
ClearML (🥈29 · ⭐ 3.5K) - ClearML - Auto-Magical Suite of tools to streamline your ML.. Apache-2 + +- [GitHub](https://github.com/allegroai/clearml) (👨‍💻 52 · 🔀 460 · 📥 500 · 📦 290 · 📋 600 - 44% open · ⏱️ 23.08.2022): + + ``` + git clone https://github.com/allegroai/clearml + ``` +- [PyPi](https://pypi.org/project/clearml) (📥 94K / month): + ``` + pip install clearml + ``` +- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (📥 30K · ⏱️ 05.10.2020): + ``` + docker pull allegroai/trains ```
-
Metaflow (🥈26 · ⭐ 5.1K) - 轻松构建和管理现实生活中的数据科学项目。Apache-2 +
Metaflow (🥈28 · ⭐ 5.9K) - Build and manage real-life data science projects with ease. Apache-2 -- [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 42 · 🔀 420 · 📦 230 · 📋 350 - 45% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 54 · 🔀 500 · 📦 310 · 📋 420 - 45% open · ⏱️ 24.08.2022): ``` git clone https://github.com/Netflix/metaflow ``` -- [PyPi](https://pypi.org/project/metaflow): +- [PyPi](https://pypi.org/project/metaflow) (📥 62K / month): ``` pip install metaflow ``` -- [Conda](https://anaconda.org/conda-forge/metaflow) (📥 29K · ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/metaflow) (📥 63K · ⏱️ 25.08.2022): ``` conda install -c conda-forge metaflow ```
-
PyCaret (🥈26 · ⭐ 4.6K) - Python中的开源代码，低代码机器学习库。MIT +
VisualDL (🥈27 · ⭐ 4.4K) - Deep Learning Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 68 · 🔀 1K · 📥 500 · 📦 1.6K · 📋 1.2K - 15% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 32 · 🔀 590 · 📥 210 · 📦 1.3K · 📋 420 - 20% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/pycaret/pycaret + git clone https://github.com/PaddlePaddle/VisualDL ``` -- [PyPi](https://pypi.org/project/pycaret): +- [PyPi](https://pypi.org/project/visualdl) (📥 60K / month): ``` - pip install pycaret + pip install visualdl ```
-
wandb client (🥈26 · ⭐ 3.6K) - 用于可视化和跟踪机器学习的工具。MIT +
Catalyst (🥈27 · ⭐ 3K) - Accelerated deep learning R&D. Apache-2 -- [GitHub](https://github.com/wandb/client) (👨‍💻 97 · 🔀 280 · 📋 1.4K - 17% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 340 · 📦 600 · 📋 340 - 1% open · ⏱️ 29.04.2022): ``` - git clone https://github.com/wandb/client + git clone https://github.com/catalyst-team/catalyst ``` -- [PyPi](https://pypi.org/project/wandb) (📥 540K / month): +- [PyPi](https://pypi.org/project/catalyst) (📥 39K / month): ``` - pip install wandb + pip install catalyst ```
-
snakemake (🥈26 · ⭐ 1.2K) - 工作流管理系统snakemake。MIT +
snakemake (🥈27 · ⭐ 1.5K) - This is the development home of the workflow management system.. MIT -- [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 230 · 🔀 270 · 📦 990 · 📋 790 - 62% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 260 · 🔀 360 · 📦 1.2K · 📋 1.1K - 59% open · ⏱️ 25.08.2022): ``` git clone https://github.com/snakemake/snakemake ``` -- [PyPi](https://pypi.org/project/snakemake): +- [PyPi](https://pypi.org/project/snakemake) (📥 51K / month): ``` pip install snakemake ``` -- [Conda](https://anaconda.org/bioconda/snakemake) (📥 360K · ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/bioconda/snakemake) (📥 510K · ⏱️ 11.08.2022): ``` conda install -c bioconda snakemake ```
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VisualDL (🥈25 · ⭐ 4.3K) - 深度学习可视化工具包。Apache-2 +
ml-metadata (🥈26 · ⭐ 490) - For recording and retrieving metadata associated with ML.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 31 · 🔀 570 · 📥 160 · 📦 840 · 📋 390 - 14% open · ⏱️ 26.11.2021): +- [GitHub](https://github.com/google/ml-metadata) (👨‍💻 15 · 🔀 95 · 📥 1.7K · 📦 240 · 📋 91 - 26% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/PaddlePaddle/VisualDL + git clone https://github.com/google/ml-metadata ``` -- [PyPi](https://pypi.org/project/visualdl) (📥 53K / month): +- [PyPi](https://pypi.org/project/ml-metadata) (📥 480K / month): ``` - pip install visualdl + pip install ml-metadata ```
-
ClearML (🥈25 · ⭐ 2.9K) - ClearML-自动精简工具套件。Apache-2 +
DVC (🥈25 · ⭐ 10K) - Data Version Control | Git for Data & Models. Apache-2 -- [GitHub](https://github.com/allegroai/clearml) (👨‍💻 42 · 🔀 380 · 📥 380 · 📦 170 · 📋 420 - 32% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/iterative/dvc) (👨‍💻 270 · 🔀 950 · 📥 120K · 📋 3.8K - 16% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/allegroai/clearml + git clone https://github.com/iterative/dvc ``` -- [PyPi](https://pypi.org/project/clearml): +- [PyPi](https://pypi.org/project/dvc) (📥 530K / month): ``` - pip install clearml + pip install dvc ``` -- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (📥 30K · ⏱️ 05.10.2020): +- [Conda](https://anaconda.org/conda-forge/dvc) (📥 1.2M · ⏱️ 25.08.2022): ``` - docker pull allegroai/trains + conda install -c conda-forge dvc ```
-
AzureML SDK (🥈25 · ⭐ 2.8K) - 带有ML的Python笔记本和带有Azure的深度学习示例。MIT +
AzureML SDK (🥈25 · ⭐ 3.4K) - Python notebooks with ML and deep learning examples with Azure.. MIT -- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 57 · 🔀 1.9K · 📥 430 · 📋 1.2K - 16% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 60 · 🔀 2.1K · 📥 460 · 📋 1.3K - 21% open · ⏱️ 19.08.2022): ``` git clone https://github.com/Azure/MachineLearningNotebooks ``` -- [PyPi](https://pypi.org/project/azureml-sdk) (📥 1.9M / month): +- [PyPi](https://pypi.org/project/azureml-sdk) (📥 1.5M / month): ``` pip install azureml-sdk ```
-
DVC (🥈24 · ⭐ 9K) - 数据版本控制|针对数据和模型的Git。|) - 数据版本控制|针对数据和模型的Git。Apache-2 +
aim (🥉24 · ⭐ 2.7K) - Aim a super-easy way to record, search and compare 1000s of ML training.. Apache-2 -- [GitHub](https://github.com/iterative/dvc) (👨‍💻 250 · 🔀 850 · 📥 48K · 📋 3.4K - 16% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/aimhubio/aim) (👨‍💻 42 · 🔀 160 · 📦 100 · 📋 630 - 21% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/iterative/dvc - ``` -- [PyPi](https://pypi.org/project/dvc) (📥 360K / month): - ``` - pip install dvc + git clone https://github.com/aimhubio/aim ``` -- [Conda](https://anaconda.org/conda-forge/dvc) (📥 950K · ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/aim) (📥 34K / month): ``` - conda install -c conda-forge dvc + pip install aim ```
-
sacred (🥈24 · ⭐ 3.7K) - Sacred是可帮助您配置，组织，记录和复现的工具。MIT +
livelossplot (🥉23 · ⭐ 1.2K) - Live training loss plot in Jupyter Notebook for Keras,.. MIT -- [GitHub](https://github.com/IDSIA/sacred) (👨‍💻 95 · 🔀 340 · 📦 1.1K · 📋 520 - 17% open · ⏱️ 05.11.2021): +- [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 840 · 📋 75 - 6% open · ⏱️ 04.04.2022): ``` - git clone https://github.com/IDSIA/sacred + git clone https://github.com/stared/livelossplot ``` -- [PyPi](https://pypi.org/project/sacred): +- [PyPi](https://pypi.org/project/livelossplot) (📥 63K / month): ``` - pip install sacred + pip install livelossplot ```
-
livelossplot (🥉23 · ⭐ 1.1K) - Jupyter Notebook for Keras的实时训练loss图。MIT +
Labml (🥉23 · ⭐ 1.2K) - Monitor deep learning model training and hardware usage from your mobile.. MIT -- [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 690 · 📋 73 - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/labmlai/labml) (👨‍💻 7 · 🔀 78 · 📦 54 · 📋 29 - 44% open · ⏱️ 15.08.2022): ``` - git clone https://github.com/stared/livelossplot + git clone https://github.com/lab-ml/labml ``` -- [PyPi](https://pypi.org/project/livelossplot) (📥 79K / month): +- [PyPi](https://pypi.org/project/labml) (📥 3.2K / month): ``` - pip install livelossplot + pip install labml ```
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knockknock (🥉20 · ⭐ 2.3K · 💀) - 当您的训练结束后通知您。MIT +
knockknock (🥉22 · ⭐ 2.5K · 💀) - Knock Knock: Get notified when your training ends with only two.. MIT -- [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 190 · 📦 230 · 📋 37 - 37% open · ⏱️ 16.03.2020): +- [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 210 · 📦 380 · 📋 39 - 41% open · ⏱️ 16.03.2020): ``` git clone https://github.com/huggingface/knockknock ``` -- [PyPi](https://pypi.org/project/knockknock): +- [PyPi](https://pypi.org/project/knockknock) (📥 59K / month): ``` pip install knockknock ``` -- [Conda](https://anaconda.org/conda-forge/knockknock) (📥 8.3K · ⏱️ 17.03.2020): +- [Conda](https://anaconda.org/conda-forge/knockknock) (📥 10K · ⏱️ 17.03.2020): ``` conda install -c conda-forge knockknock ```
-
hiddenlayer (🥉20 · ⭐ 1.6K · 💀) - 神经网络图和训练指标。MIT +
kaggle (🥉21 · ⭐ 4.9K · 💀) - Official Kaggle API. Apache-2 -- [GitHub](https://github.com/waleedka/hiddenlayer) (👨‍💻 6 · 🔀 220 · 📦 88 · 📋 80 - 57% open · ⏱️ 24.04.2020): +- [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 940 · 📋 350 - 57% open · ⏱️ 15.03.2021): ``` - git clone https://github.com/waleedka/hiddenlayer - ``` -- [PyPi](https://pypi.org/project/hiddenlayer) (📥 1.9K / month): - ``` - pip install hiddenlayer + git clone https://github.com/Kaggle/kaggle-api ``` -
-
lore (🥉20 · ⭐ 1.5K · 💀) - lore使机器学习对软件工程师更易上手，对机器学习研究人员更可维护。MIT - -- [GitHub](https://github.com/instacart/lore) (👨‍💻 22 · 🔀 120 · 📦 17 · 📋 34 - 47% open · ⏱️ 11.05.2020): - +- [PyPi](https://pypi.org/project/kaggle) (📥 120K / month): ``` - git clone https://github.com/instacart/lore + pip install kaggle ``` -- [PyPi](https://pypi.org/project/lore) (📥 650 / month): +- [Conda](https://anaconda.org/conda-forge/kaggle) (📥 95K · ⏱️ 17.12.2021): ``` - pip install lore + conda install -c conda-forge kaggle ```
-
TNT (🥉20 · ⭐ 1.4K · 💤) - 用于记录和可视化，加载和训练的简单工具。BSD-3 +
Guild AI (🥉21 · ⭐ 730) - Experiment tracking, ML developer tools. Apache-2 -- [GitHub](https://github.com/pytorch/tnt) (👨‍💻 35 · 🔀 190 · 📋 58 - 39% open · ⏱️ 05.01.2021): +- [GitHub](https://github.com/guildai/guildai) (👨‍💻 21 · 🔀 66 · 📥 6 · 📦 58 · 📋 380 - 45% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/pytorch/tnt + git clone https://github.com/guildai/guildai ``` -- [PyPi](https://pypi.org/project/torchnet) (📥 17K / month): +- [PyPi](https://pypi.org/project/guildai) (📥 3.1K / month): ``` - pip install torchnet + pip install guildai ```
-
ml-metadata (🥉20 · ⭐ 410) - 用于记录和检索与ML相关的元数据。Apache-2 +
hiddenlayer (🥉20 · ⭐ 1.6K · 💀) - Neural network graphs and training metrics for.. MIT -- [GitHub](https://github.com/google/ml-metadata) (👨‍💻 13 · 🔀 75 · 📥 1.7K · 📦 170 · 📋 74 - 24% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/waleedka/hiddenlayer) (👨‍💻 6 · 🔀 230 · 📦 130 · 📋 85 - 58% open · ⏱️ 24.04.2020): ``` - git clone https://github.com/google/ml-metadata + git clone https://github.com/waleedka/hiddenlayer ``` -- [PyPi](https://pypi.org/project/ml-metadata): +- [PyPi](https://pypi.org/project/hiddenlayer) (📥 1.7K / month): ``` - pip install ml-metadata + pip install hiddenlayer ```
-
kaggle (🥉19 · ⭐ 4.5K · 💤) - 官方Kaggle API。Apache-2 +
TNT (🥉20 · ⭐ 1.4K) - Simple tools for logging and visualizing, loading and training. BSD-3 -- [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 870 · 📋 320 - 54% open · ⏱️ 15.03.2021): +- [GitHub](https://github.com/pytorch/tnt) (👨‍💻 53 · 🔀 200 · ⏱️ 18.08.2022): ``` - git clone https://github.com/Kaggle/kaggle-api - ``` -- [PyPi](https://pypi.org/project/kaggle): - ``` - pip install kaggle + git clone https://github.com/pytorch/tnt ``` -- [Conda](https://anaconda.org/conda-forge/kaggle) (📥 75K · ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/torchnet) (📥 8.8K / month): ``` - conda install -c conda-forge kaggle + pip install torchnet ```
-
TensorWatch (🥉19 · ⭐ 3.2K · 💤) - Python机器学习的调试，监视和可视化。MIT +
TensorWatch (🥉19 · ⭐ 3.2K · 💀) - Debugging, monitoring and visualization for Python Machine.. MIT -- [GitHub](https://github.com/microsoft/tensorwatch) (👨‍💻 13 · 🔀 340 · 📦 65 · 📋 65 - 76% open · ⏱️ 15.01.2021): +- [GitHub](https://github.com/microsoft/tensorwatch) (👨‍💻 13 · 🔀 340 · 📦 86 · 📋 67 - 77% open · ⏱️ 15.01.2021): ``` git clone https://github.com/microsoft/tensorwatch ``` -- [PyPi](https://pypi.org/project/tensorwatch) (📥 6.1K / month): +- [PyPi](https://pypi.org/project/tensorwatch) (📥 5.3K / month): ``` pip install tensorwatch ```
-
Guild AI (🥉19 · ⭐ 640) - 实验跟踪，ML开发人员工具库。Apache-2 - -- [GitHub](https://github.com/guildai/guildai) (👨‍💻 18 · 🔀 58 · 📦 38 · 📋 290 - 40% open · ⏱️ 15.12.2021): - - ``` - git clone https://github.com/guildai/guildai - ``` -- [PyPi](https://pypi.org/project/guildai) (📥 2.8K / month): - ``` - pip install guildai - ``` -
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MXBoard (🥉19 · ⭐ 330 · 💀) - MXNet日志记录器，以在TensorBoard中进行可视化。Apache-2 +
lore (🥉19 · ⭐ 1.5K) - Lore makes machine learning approachable for Software Engineers and.. MIT -- [GitHub](https://github.com/awslabs/mxboard) (👨‍💻 9 · 🔀 47 · 📦 130 · 📋 31 - 51% open · ⏱️ 24.01.2020): +- [GitHub](https://github.com/instacart/lore) (👨‍💻 26 · 🔀 120 · 📦 20 · 📋 35 - 45% open · ⏱️ 11.04.2022): ``` - git clone https://github.com/awslabs/mxboard + git clone https://github.com/instacart/lore ``` -- [PyPi](https://pypi.org/project/mxboard) (📥 5.2K / month): +- [PyPi](https://pypi.org/project/lore) (📥 530 / month): ``` - pip install mxboard + pip install lore ```
-
Labml (🥉18 · ⭐ 890) - 从您的手机监控深度学习模型训练和硬件使用情况。MIT +
gokart (🥉19 · ⭐ 260) - A wrapper of the data pipeline library luigi. MIT -- [GitHub](https://github.com/labmlai/labml) (👨‍💻 6 · 🔀 58 · 📦 39 · 📋 25 - 60% open · ⏱️ 06.09.2021): +- [GitHub](https://github.com/m3dev/gokart) (👨‍💻 34 · 🔀 45 · 📋 73 - 19% open · ⏱️ 02.08.2022): ``` - git clone https://github.com/lab-ml/labml + git clone https://github.com/m3dev/gokart ``` -- [PyPi](https://pypi.org/project/labml): +- [PyPi](https://pypi.org/project/gokart) (📥 1K / month): ``` - pip install labml + pip install gokart ```
-
Studio.ml (🥉17 · ⭐ 370) - Studio：简化和加快模型构建过程。Apache-2 +
Studio.ml (🥉18 · ⭐ 380 · 💤) - Studio: Simplify and expedite model building process. Apache-2 - [GitHub](https://github.com/studioml/studio) (👨‍💻 21 · 🔀 51 · 📦 5 · 📋 250 - 22% open · ⏱️ 14.09.2021): ``` git clone https://github.com/studioml/studio ``` -- [PyPi](https://pypi.org/project/studioml): +- [PyPi](https://pypi.org/project/studioml) (📥 35 / month): ``` pip install studioml ```
-
gokart (🥉17 · ⭐ 230) - 数据管道库luigi的包装。MIT +
MXBoard (🥉18 · ⭐ 330 · 💀) - Logging MXNet data for visualization in TensorBoard. Apache-2 -- [GitHub](https://github.com/m3dev/gokart) (👨‍💻 29 · 🔀 38 · 📋 62 - 17% open · ⏱️ 16.11.2021): +- [GitHub](https://github.com/awslabs/mxboard) (👨‍💻 9 · 🔀 46 · 📦 160 · 📋 31 - 51% open · ⏱️ 24.01.2020): ``` - git clone https://github.com/m3dev/gokart + git clone https://github.com/awslabs/mxboard ``` -- [PyPi](https://pypi.org/project/gokart): +- [PyPi](https://pypi.org/project/mxboard) (📥 7.7K / month): ``` - pip install gokart + pip install mxboard ```
-
aim (🥉16 · ⭐ 1.9K) - 以一种非常简单的方式来记录，搜索和比较数千次ML训练。Apache-2 +
quinn (🥉17 · ⭐ 350 · 💀) - pyspark methods to enhance developer productivity. ❗Unlicensed -- [GitHub](https://github.com/aimhubio/aim) (👨‍💻 22 · 🔀 110 · 📦 44 · 📋 260 - 33% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 47 · 📋 24 - 58% open · ⏱️ 09.02.2021): ``` - git clone https://github.com/aimhubio/aim + git clone https://github.com/MrPowers/quinn ``` -- [PyPi](https://pypi.org/project/aim): +- [PyPi](https://pypi.org/project/quinn) (📥 770K / month): ``` - pip install aim + pip install quinn ```
-
quinn (🥉16 · ⭐ 300 · 💤) - pyspark方法可提高开发人员的工作效率。❗Unlicensed +
TensorBoard Logger (🥉15 · ⭐ 620 · 💀) - Log TensorBoard events without touching TensorFlow. MIT -- [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 40 · 📋 23 - 60% open · ⏱️ 09.02.2021): +- [GitHub](https://github.com/TeamHG-Memex/tensorboard_logger) (👨‍💻 5 · 🔀 49 · 📋 24 - 37% open · ⏱️ 21.10.2019): ``` - git clone https://github.com/MrPowers/quinn + git clone https://github.com/TeamHG-Memex/tensorboard_logger ``` -- [PyPi](https://pypi.org/project/quinn) (📥 460K / month): +- [PyPi](https://pypi.org/project/tensorboard_logger) (📥 56K / month): ``` - pip install quinn + pip install tensorboard_logger ```
-
SKLL (🥉15 · ⭐ 530) - SciKit学习实验室（SKLL）使机器学习易于操作。❗Unlicensed +
datmo (🥉15 · ⭐ 340 · 💀) - Open source production model management tool for data scientists. MIT -- [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 36 · 🔀 63 · 📥 11 · 📦 34 · 📋 390 - 8% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/datmo/datmo) (👨‍💻 6 · 🔀 28 · 📦 5 · 📋 180 - 15% open · ⏱️ 29.11.2019): ``` - git clone https://github.com/EducationalTestingService/skll + git clone https://github.com/datmo/datmo ``` -- [PyPi](https://pypi.org/project/skll) (📥 400 / month): +- [PyPi](https://pypi.org/project/datmo) (📥 28 / month): ``` - pip install skll + pip install datmo ```
-
steppy (🥉14 · ⭐ 130 · 💀) - 轻量级的Python库，可进行快速且可重复的实验。MIT +
steppy (🥉15 · ⭐ 130 · 💀) - Lightweight, Python library for fast and reproducible experimentation. MIT -- [GitHub](https://github.com/minerva-ml/steppy) (👨‍💻 5 · 🔀 33 · 📦 42 · 📋 63 - 20% open · ⏱️ 23.11.2018): +- [GitHub](https://github.com/minerva-ml/steppy) (👨‍💻 5 · 🔀 33 · 📦 46 · 📋 63 - 20% open · ⏱️ 23.11.2018): ``` git clone https://github.com/minerva-ml/steppy ``` -- [PyPi](https://pypi.org/project/steppy): +- [PyPi](https://pypi.org/project/steppy) (📥 9 / month): ``` pip install steppy ```
-
datmo (🥉13 · ⭐ 340 · 💀) - 面向数据科学家的开源生产模型管理工具。MIT +
SKLL (🥉14 · ⭐ 530 · 💤) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗Unlicensed -- [GitHub](https://github.com/datmo/datmo) (👨‍💻 6 · 🔀 28 · 📦 5 · 📋 180 - 15% open · ⏱️ 29.11.2019): +- [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 37 · 🔀 65 · 📥 11 · 📦 38 · 📋 400 - 7% open · ⏱️ 21.12.2021): ``` - git clone https://github.com/datmo/datmo + git clone https://github.com/EducationalTestingService/skll ``` -- [PyPi](https://pypi.org/project/datmo): +- [PyPi](https://pypi.org/project/skll) (📥 140 / month): ``` - pip install datmo + pip install skll ```
-
ModelChimp (🥉13 · ⭐ 120) - 机器和深度学习项目的实验跟踪。BSD-2 +
ModelChimp (🥉14 · ⭐ 120 · 💤) - Experiment tracking for machine and deep learning projects. BSD-2 - [GitHub](https://github.com/ModelChimp/modelchimp) (👨‍💻 3 · 🔀 12 · 📋 14 - 28% open · ⏱️ 01.08.2021): ``` git clone https://github.com/ModelChimp/modelchimp ``` -- [PyPi](https://pypi.org/project/modelchimp): +- [PyPi](https://pypi.org/project/modelchimp) (📥 43 / month): ``` pip install modelchimp ``` -- [Docker Hub](https://hub.docker.com/r/modelchimp/modelchimp-server) (📥 650 · ⏱️ 09.04.2019): +- [Docker Hub](https://hub.docker.com/r/modelchimp/modelchimp-server) (📥 660 · ⏱️ 09.04.2019): ``` docker pull modelchimp/modelchimp-server ```
-
TensorBoard Logger (🥉12 · ⭐ 620 · 💀) - 简易TensorBoard日志记录库。MIT - -- [GitHub](https://github.com/TeamHG-Memex/tensorboard_logger) (👨‍💻 5 · 🔀 50 · 📋 23 - 34% open · ⏱️ 21.10.2019): - - ``` - git clone https://github.com/TeamHG-Memex/tensorboard_logger - ``` -- [PyPi](https://pypi.org/project/tensorboard_logger): - ``` - pip install tensorboard_logger - ``` -
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traintool (🥉7 · ⭐ 9 · 💤) - 一站式训练现成的机器学习模型。Apache-2 +
traintool (🥉7 · ⭐ 10 · 💀) - Train off-the-shelf machine learning models in one.. Apache-2 -- [GitHub](https://github.com/jrieke/traintool) (🔀 1 · ⏱️ 12.03.2021): +- [GitHub](https://github.com/jrieke/traintool) (⏱️ 12.03.2021): ``` git clone https://github.com/jrieke/traintool ``` -- [PyPi](https://pypi.org/project/traintool) (📥 20 / month): +- [PyPi](https://pypi.org/project/traintool) (📥 10 / month): ``` pip install traintool ```

-## 模型序列化和转换 +## Model Serialization & Conversion -Back to top +Back to top -_用于将模型序列化为文件，在各种模型格式之间进行转换以及优化模型以进行部署的库。_ +_Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment._ -
onnx (🥇35 · ⭐ 12K) - 机器学习互操作性的开放标准。Apache-2 +
onnx (🥇32 · ⭐ 13K) - Open standard for machine learning interoperability. Apache-2 -- [GitHub](https://github.com/onnx/onnx) (👨‍💻 220 · 🔀 2.2K · 📥 17K · 📦 5K · 📋 1.7K - 23% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/onnx/onnx) (👨‍💻 250 · 🔀 2.9K · 📥 18K · 📦 8.1K · 📋 2K - 11% open · ⏱️ 25.08.2022): ``` git clone https://github.com/onnx/onnx ``` -- [PyPi](https://pypi.org/project/onnx) (📥 1.2M / month): +- [PyPi](https://pypi.org/project/onnx) (📥 1.6M / month): ``` pip install onnx ``` -- [Conda](https://anaconda.org/conda-forge/onnx) (📥 330K · ⏱️ 14.12.2021): +- [Conda](https://anaconda.org/conda-forge/onnx) (📥 490K · ⏱️ 18.08.2022): ``` conda install -c conda-forge onnx ```
-
Core ML Tools (🥇25 · ⭐ 2.5K) - 核心ML工具包含用于核心ML模型的支持工具。BSD-3 +
Core ML Tools (🥇25 · ⭐ 2.8K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 -- [GitHub](https://github.com/apple/coremltools) (👨‍💻 120 · 🔀 370 · 📥 3.8K · 📦 700 · 📋 830 - 38% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/apple/coremltools) (👨‍💻 130 · 🔀 420 · 📥 4.4K · 📦 1K · 📋 970 - 28% open · ⏱️ 24.08.2022): ``` git clone https://github.com/apple/coremltools ``` -- [PyPi](https://pypi.org/project/coremltools) (📥 77K / month): +- [PyPi](https://pypi.org/project/coremltools) (📥 93K / month): ``` pip install coremltools ```
-
TorchServe (🥈24 · ⭐ 2.3K) - 在PyTorch上进行模型服务。Apache-2 +
m2cgen (🥇25 · ⭐ 2.2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT -- [GitHub](https://github.com/pytorch/serve) (👨‍💻 94 · 🔀 420 · 📥 720 · 📋 740 - 14% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/BayesWitnesses/m2cgen) (👨‍💻 13 · 🔀 200 · 📥 32 · 📦 59 · 📋 92 - 26% open · ⏱️ 14.08.2022): ``` - git clone https://github.com/pytorch/serve + git clone https://github.com/BayesWitnesses/m2cgen ``` -- [PyPi](https://pypi.org/project/torchserve): +- [PyPi](https://pypi.org/project/m2cgen) (📥 45K / month): ``` - pip install torchserve + pip install m2cgen ``` -- [Conda](https://anaconda.org/pytorch/torchserve) (📥 17K · ⏱️ 19.11.2021): +
+
TorchServe (🥈24 · ⭐ 2.8K) - Model Serving on PyTorch. Apache-2 + +- [GitHub](https://github.com/pytorch/serve) (👨‍💻 120 · 🔀 570 · 📥 2K · 📋 970 - 14% open · ⏱️ 25.08.2022): + ``` - conda install -c pytorch torchserve + git clone https://github.com/pytorch/serve ``` -- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (📥 950K · ⭐ 9 · ⏱️ 22.11.2021): +- [PyPi](https://pypi.org/project/torchserve) (📥 17K / month): ``` - docker pull pytorch/torchserve + pip install torchserve ``` -
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cortex (🥈23 · ⭐ 7.6K) - 具有成本效益的无服务器大规模计算。Apache-2 - -- [GitHub](https://github.com/cortexlabs/cortex) (👨‍💻 23 · 🔀 580 · 📋 1.1K - 9% open · ⏱️ 14.12.2021): - +- [Conda](https://anaconda.org/pytorch/torchserve) (📥 33K · ⏱️ 13.05.2022): ``` - git clone https://github.com/cortexlabs/cortex + conda install -c pytorch torchserve ``` -- [PyPi](https://pypi.org/project/cortex) (📥 1.2K / month): +- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (📥 1M · ⭐ 15 · ⏱️ 19.07.2022): ``` - pip install cortex + docker pull pytorch/torchserve ```
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mmdnn (🥈23 · ⭐ 5.5K · 💀) - MMdnn是一组工具，可以帮助用户在不同的深度学习框架之间进行互操作。MIT +
mmdnn (🥈23 · ⭐ 5.6K · 💀) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT -- [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 950 · 📥 3.5K · 📦 66 · 📋 610 - 52% open · ⏱️ 14.08.2020): +- [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 950 · 📥 3.6K · 📦 85 · 📋 610 - 52% open · ⏱️ 14.08.2020): ``` git clone https://github.com/Microsoft/MMdnn ``` -- [PyPi](https://pypi.org/project/mmdnn) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/mmdnn) (📥 580 / month): ``` pip install mmdnn ```
-
Hummingbird (🥉22 · ⭐ 2.7K) - 蜂鸟将训练有素的机器学习模型编译为张量计算，以用于..MIT +
cortex (🥉22 · ⭐ 7.8K) - Cost-effective serverless computing at scale. Apache-2 -- [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 27 · 🔀 200 · 📥 150 · 📦 20 · 📋 230 - 21% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/cortexlabs/cortex) (👨‍💻 24 · 🔀 580 · 📋 1.1K - 10% open · ⏱️ 23.04.2022): ``` - git clone https://github.com/microsoft/hummingbird + git clone https://github.com/cortexlabs/cortex ``` -- [PyPi](https://pypi.org/project/hummingbird-ml) (📥 3.1K / month): +- [PyPi](https://pypi.org/project/cortex) (📥 1.7K / month): ``` - pip install hummingbird-ml + pip install cortex ```
-
m2cgen (🥉22 · ⭐ 2K) - 将ML模型转换成本机代码（Java，C，Python，Go，JavaScript）等。MIT +
Hummingbird (🥉22 · ⭐ 3K) - Hummingbird compiles trained ML models into tensor computation for.. MIT -- [GitHub](https://github.com/BayesWitnesses/m2cgen) (👨‍💻 12 · 🔀 160 · 📦 7 · 📋 82 - 41% open · ⏱️ 25.11.2021): +- [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 31 · 🔀 240 · 📥 180 · 📦 39 · 📋 250 - 16% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/BayesWitnesses/m2cgen + git clone https://github.com/microsoft/hummingbird ``` -- [PyPi](https://pypi.org/project/m2cgen) (📥 54K / month): +- [PyPi](https://pypi.org/project/hummingbird-ml) (📥 3.9K / month): ``` - pip install m2cgen + pip install hummingbird-ml ```
-
sklearn-porter (🥉18 · ⭐ 1.1K · 💀) - 将经过训练的scikit-learn估计器转换为C，Java等。MIT +
sklearn-porter (🥉20 · ⭐ 1.2K) - Transpile trained scikit-learn estimators to C, Java,.. BSD-3 -- [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 11 · 🔀 140 · 📋 67 - 56% open · ⏱️ 18.12.2019): +- [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 12 · 🔀 160 · 📦 44 · 📋 68 - 50% open · ⏱️ 22.05.2022): ``` git clone https://github.com/nok/sklearn-porter ``` -- [PyPi](https://pypi.org/project/sklearn-porter) (📥 520 / month): +- [PyPi](https://pypi.org/project/sklearn-porter) (📥 340 / month): ``` pip install sklearn-porter ```
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Larq Compute Engine (🥉17 · ⭐ 180) - 高度优化的二值化推理引擎。Apache-2 +
pytorch2keras (🥉18 · ⭐ 810 · 💤) - PyTorch to Keras model convertor. MIT -- [GitHub](https://github.com/larq/compute-engine) (👨‍💻 18 · 🔀 28 · 📥 330 · 📦 4 · 📋 130 - 9% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 140 · 📦 51 · 📋 120 - 44% open · ⏱️ 06.08.2021): ``` - git clone https://github.com/larq/compute-engine + git clone https://github.com/nerox8664/pytorch2keras ``` -- [PyPi](https://pypi.org/project/larq-compute-engine) (📥 540 / month): +- [PyPi](https://pypi.org/project/pytorch2keras) (📥 480 / month): ``` - pip install larq-compute-engine + pip install pytorch2keras ```
-
pytorch2keras (🥉16 · ⭐ 760) - PyTorch到Keras模型转换器。MIT +
Larq Compute Engine (🥉17 · ⭐ 210) - Highly optimized inference engine for Binarized.. Apache-2 -- [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 130 · 📦 26 · 📋 120 - 42% open · ⏱️ 06.08.2021): +- [GitHub](https://github.com/larq/compute-engine) (👨‍💻 18 · 🔀 32 · 📥 730 · 📦 6 · 📋 140 - 9% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/nerox8664/pytorch2keras + git clone https://github.com/larq/compute-engine ``` -- [PyPi](https://pypi.org/project/pytorch2keras) (📥 710 / month): +- [PyPi](https://pypi.org/project/larq-compute-engine) (📥 870 / month): ``` - pip install pytorch2keras + pip install larq-compute-engine ```
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tfdeploy (🥉14 · ⭐ 340 · 💤) - 部署张量流图以进行快速评估并导出到无tensorflow环境中基于numpy运行。BSD-3 +
tfdeploy (🥉14 · ⭐ 350 · 💀) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 -- [GitHub](https://github.com/riga/tfdeploy) (👨‍💻 4 · 🔀 37 · 📋 34 - 32% open · ⏱️ 08.01.2021): +- [GitHub](https://github.com/riga/tfdeploy) (👨‍💻 4 · 🔀 36 · 📋 34 - 32% open · ⏱️ 08.01.2021): ``` git clone https://github.com/riga/tfdeploy ``` -- [PyPi](https://pypi.org/project/tfdeploy): +- [PyPi](https://pypi.org/project/tfdeploy) (📥 9 / month): ``` pip install tfdeploy ```

-## 模型的可解释性 +## Model Interpretability -Back to top +Back to top -_用于可视化，解释，调试，评估和解释机器学习模型的库。_ +_Libraries to visualize, explain, debug, evaluate, and interpret machine learning models._ -
shap (🥇36 · ⭐ 15K) - 用于解释任何机器学习模型的输出的一种博弈论方法实现。MIT +
shap (🥇36 · ⭐ 17K) - A game theoretic approach to explain the output of any machine learning model. MIT -- [GitHub](https://github.com/slundberg/shap) (👨‍💻 160 · 🔀 2.2K · 📦 4K · 📋 1.8K - 68% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/slundberg/shap) (👨‍💻 200 · 🔀 2.6K · 📦 6.4K · 📋 2K - 69% open · ⏱️ 16.06.2022): ``` git clone https://github.com/slundberg/shap ``` -- [PyPi](https://pypi.org/project/shap) (📥 4.3M / month): +- [PyPi](https://pypi.org/project/shap) (📥 3.7M / month): ``` pip install shap ``` -- [Conda](https://anaconda.org/conda-forge/shap) (📥 720K · ⏱️ 24.10.2021): +- [Conda](https://anaconda.org/conda-forge/shap) (📥 1.4M · ⏱️ 20.06.2022): ``` conda install -c conda-forge shap ```
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Lime (🥇30 · ⭐ 9.4K) - Lime：解释任何机器学习分类器的预测。BSD-2 +
Lime (🥇30 · ⭐ 10K · 💀) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 -- [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.5K · 📦 1.8K · 📋 550 - 3% open · ⏱️ 29.07.2021): +- [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.6K · 📦 2.6K · 📋 580 - 9% open · ⏱️ 29.07.2021): ``` git clone https://github.com/marcotcr/lime ``` -- [PyPi](https://pypi.org/project/lime) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/lime) (📥 560K / month): ``` pip install lime ``` -- [Conda](https://anaconda.org/conda-forge/lime) (📥 89K · ⏱️ 28.06.2020): +- [Conda](https://anaconda.org/conda-forge/lime) (📥 110K · ⏱️ 28.06.2020): ``` conda install -c conda-forge lime ```
-
pyLDAvis (🥇29 · ⭐ 1.6K · 💤) - 用于交互式主题模型可视化的Python库。BSD-3 +
pyLDAvis (🥇29 · ⭐ 1.6K · 💀) - Python library for interactive topic model visualization... BSD-3 -- [GitHub](https://github.com/bmabey/pyLDAvis) (👨‍💻 32 · 🔀 320 · 📦 2.9K · 📋 160 - 51% open · ⏱️ 24.03.2021): +- [GitHub](https://github.com/bmabey/pyLDAvis) (👨‍💻 32 · 🔀 330 · 📦 3.8K · 📋 160 - 51% open · ⏱️ 24.03.2021): ``` git clone https://github.com/bmabey/pyLDAvis ``` -- [PyPi](https://pypi.org/project/pyldavis) (📥 590K / month): +- [PyPi](https://pypi.org/project/pyldavis) (📥 640K / month): ``` pip install pyldavis ``` -- [Conda](https://anaconda.org/conda-forge/pyldavis) (📥 32K · ⏱️ 24.03.2021): +- [Conda](https://anaconda.org/conda-forge/pyldavis) (📥 46K · ⏱️ 24.03.2021): ``` conda install -c conda-forge pyldavis ```
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InterpretML (🥇27 · ⭐ 4.4K) - 拟合可解释的模型。对机器学习黑匣子进行解释。MIT +
InterpretML (🥇28 · ⭐ 4.9K) - Fit interpretable models. Explain blackbox machine learning. MIT -- [GitHub](https://github.com/interpretml/interpret) (👨‍💻 28 · 🔀 540 · 📦 140 · 📋 260 - 31% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/interpretml/interpret) (👨‍💻 31 · 🔀 590 · 📦 260 · 📋 300 - 32% open · ⏱️ 26.08.2022): ``` git clone https://github.com/interpretml/interpret ``` -- [PyPi](https://pypi.org/project/interpret) (📥 54K / month): +- [PyPi](https://pypi.org/project/interpret) (📥 90K / month): ``` pip install interpret ```
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Captum (🥇27 · ⭐ 2.8K) - PyTorch的模型可解释性和理解。BSD-3 +
dtreeviz (🥇28 · ⭐ 2.2K) - A python library for decision tree visualization and model interpretation. MIT -- [GitHub](https://github.com/pytorch/captum) (👨‍💻 77 · 🔀 290 · 📦 340 · 📋 300 - 21% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 21 · 🔀 280 · 📦 450 · 📋 120 - 19% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/pytorch/captum + git clone https://github.com/parrt/dtreeviz ``` -- [PyPi](https://pypi.org/project/captum) (📥 37K / month): +- [PyPi](https://pypi.org/project/dtreeviz) (📥 96K / month): ``` - pip install captum + pip install dtreeviz ```
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Model Analysis (🥈26 · ⭐ 1.1K) - TensorFlow的模型分析工具。Apache-2 +
arviz (🥇28 · ⭐ 1.3K) - Exploratory analysis of Bayesian models with Python. Apache-2 -- [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 36 · 🔀 220 · 📋 61 - 22% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 130 · 🔀 290 · 📥 110 · 📦 2.7K · 📋 760 - 20% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/tensorflow/model-analysis + git clone https://github.com/arviz-devs/arviz ``` -- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (📥 7M / month): +- [PyPi](https://pypi.org/project/arviz) (📥 740K / month): ``` - pip install tensorflow-model-analysis + pip install arviz + ``` +- [Conda](https://anaconda.org/conda-forge/arviz) (📥 810K · ⏱️ 13.07.2022): + ``` + conda install -c conda-forge arviz ```
-
arviz (🥈26 · ⭐ 1.1K) - 使用Python探索性分析贝叶斯模型。Apache-2 +
Captum (🥈27 · ⭐ 3.4K) - Model interpretability and understanding for PyTorch. BSD-3 -- [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 110 · 🔀 250 · 📥 110 · 📦 1.7K · 📋 690 - 19% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/pytorch/captum) (👨‍💻 88 · 🔀 350 · 📦 650 · 📋 380 - 24% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/arviz-devs/arviz - ``` -- [PyPi](https://pypi.org/project/arviz): - ``` - pip install arviz + git clone https://github.com/pytorch/captum ``` -- [Conda](https://anaconda.org/conda-forge/arviz) (📥 580K · ⏱️ 03.10.2021): +- [PyPi](https://pypi.org/project/captum) (📥 47K / month): ``` - conda install -c conda-forge arviz + pip install captum ```
-
scikit-plot (🥈25 · ⭐ 2.2K · 💀) - 一个直观的库，可向其中添加绘图功能。MIT +
scikit-plot (🥈26 · ⭐ 2.2K · 💀) - An intuitive library to add plotting functionality to.. MIT -- [GitHub](https://github.com/reiinakano/scikit-plot) (👨‍💻 13 · 🔀 260 · 📦 1.5K · 📋 58 - 32% open · ⏱️ 19.08.2018): +- [GitHub](https://github.com/reiinakano/scikit-plot) (👨‍💻 13 · 🔀 260 · 📦 2.3K · 📋 58 - 32% open · ⏱️ 19.08.2018): ``` git clone https://github.com/reiinakano/scikit-plot ``` -- [PyPi](https://pypi.org/project/scikit-plot) (📥 390K / month): +- [PyPi](https://pypi.org/project/scikit-plot) (📥 650K / month): ``` pip install scikit-plot ``` -- [Conda](https://anaconda.org/conda-forge/scikit-plot) (📥 100K · ⏱️ 05.06.2019): +- [Conda](https://anaconda.org/conda-forge/scikit-plot) (📥 120K · ⏱️ 05.06.2019): ``` conda install -c conda-forge scikit-plot ```
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Alibi (🥈25 · ⭐ 1.4K) - 监视和解释机器学习模型的算法。Apache-2 +
explainerdashboard (🥈26 · ⭐ 1.3K) - Quickly build Explainable AI dashboards that show the inner.. MIT -- [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 18 · 🔀 160 · 📦 120 · 📋 240 - 39% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/oegedijk/explainerdashboard) (👨‍💻 15 · 🔀 160 · 📦 160 · 📋 180 - 8% open · ⏱️ 16.06.2022): ``` - git clone https://github.com/SeldonIO/alibi + git clone https://github.com/oegedijk/explainerdashboard ``` -- [PyPi](https://pypi.org/project/alibi) (📥 15K / month): +- [PyPi](https://pypi.org/project/explainerdashboard) (📥 59K / month): ``` - pip install alibi + pip install explainerdashboard ```
-
Fairness 360 (🥈24 · ⭐ 1.6K) - 一整套用于数据集的公平度量标准。Apache-2 +
Model Analysis (🥈26 · ⭐ 1.2K) - Model analysis tools for TensorFlow. Apache-2 -- [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 46 · 🔀 500 · 📦 130 · 📋 110 - 47% open · ⏱️ 18.11.2021): +- [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 47 · 🔀 240 · 📋 65 - 24% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/Trusted-AI/AIF360 + git clone https://github.com/tensorflow/model-analysis ``` -- [PyPi](https://pypi.org/project/aif360) (📥 7.3K / month): +- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (📥 1M / month): ``` - pip install aif360 + pip install tensorflow-model-analysis + ``` +
+
Alibi (🥈25 · ⭐ 1.7K) - Algorithms for monitoring and explaining machine learning models. Apache-2 + +- [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 18 · 🔀 190 · 📦 190 · 📋 300 - 36% open · ⏱️ 24.08.2022): + + ``` + git clone https://github.com/SeldonIO/alibi + ``` +- [PyPi](https://pypi.org/project/alibi) (📥 15K / month): + ``` + pip install alibi ```
-
Lucid (🥈23 · ⭐ 4.3K · 💤) - 用于神经科学研究的基础设施和工具的集合。Apache-2 +
Lucid (🥈24 · ⭐ 4.4K · 💀) - A collection of infrastructure and tools for research in.. Apache-2 -- [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 580 · 📦 590 · 📋 170 - 41% open · ⏱️ 19.03.2021): +- [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 600 · 📦 650 · 📋 170 - 42% open · ⏱️ 19.03.2021): ``` git clone https://github.com/tensorflow/lucid ``` -- [PyPi](https://pypi.org/project/lucid) (📥 1K / month): +- [PyPi](https://pypi.org/project/lucid) (📥 2K / month): ``` pip install lucid ```
-
keras-vis (🥈23 · ⭐ 2.9K · 💀) - 用于Keras的神经网络可视化工具包。MIT +
Fairness 360 (🥈24 · ⭐ 1.8K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 -- [GitHub](https://github.com/raghakot/keras-vis) (👨‍💻 10 · 🔀 610 · 📦 1.5K · 📋 210 - 53% open · ⏱️ 20.04.2020): +- [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 52 · 🔀 580 · 📦 170 · 📋 140 - 54% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/raghakot/keras-vis + git clone https://github.com/Trusted-AI/AIF360 ``` -- [PyPi](https://pypi.org/project/keras-vis) (📥 3.6K / month): +- [PyPi](https://pypi.org/project/aif360) (📥 7.3K / month): ``` - pip install keras-vis + pip install aif360 ```
-
CausalNex (🥈23 · ⭐ 1.4K) - 一个可帮助数据科学家进行因果推断的Python库。Apache-2 +
CausalNex (🥈24 · ⭐ 1.6K) - A Python library that helps data scientists to infer.. Apache-2 -- [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 150 · 📦 33 · 📋 100 - 13% open · ⏱️ 11.11.2021): +- [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 180 · 📦 53 · 📋 110 - 17% open · ⏱️ 06.07.2022): ``` git clone https://github.com/quantumblacklabs/causalnex ``` -- [PyPi](https://pypi.org/project/causalnex) (📥 4.4K / month): +- [PyPi](https://pypi.org/project/causalnex) (📥 1.3K / month): ``` pip install causalnex ```
-
DoWhy (🥈22 · ⭐ 3.5K) - DoWhy是用于因果推断的Python库。MIT +
Explainability 360 (🥈24 · ⭐ 1.1K) - Interpretability and explainability of data and.. Apache-2 -- [GitHub](https://github.com/microsoft/dowhy) (👨‍💻 45 · 🔀 520 · 📥 24 · 📦 78 · 📋 160 - 29% open · ⏱️ 05.12.2021): +- [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 31 · 🔀 240 · 📦 55 · 📋 65 - 56% open · ⏱️ 26.07.2022): ``` - git clone https://github.com/Microsoft/dowhy + git clone https://github.com/Trusted-AI/AIX360 ``` -- [PyPi](https://pypi.org/project/dowhy): +- [PyPi](https://pypi.org/project/aix360) (📥 1.2K / month): ``` - pip install dowhy + pip install aix360 + ``` +
+
keras-vis (🥈23 · ⭐ 2.9K · 💀) - Neural network visualization toolkit for keras. MIT + +- [GitHub](https://github.com/raghakot/keras-vis) (👨‍💻 10 · 🔀 630 · 📦 2.1K · 📋 210 - 52% open · ⏱️ 20.04.2020): + + ``` + git clone https://github.com/raghakot/keras-vis ``` -- [Conda](https://anaconda.org/conda-forge/dowhy) (📥 4.1K · ⏱️ 28.04.2021): +- [PyPi](https://pypi.org/project/keras-vis) (📥 3.3K / month): ``` - conda install -c conda-forge dowhy + pip install keras-vis + ``` +
+
yellowbrick (🥈22 · ⭐ 3.7K) - Visual analysis and diagnostic tools to facilitate machine.. Apache-2 + +- [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 110 · 🔀 510 · 📋 670 - 11% open · ⏱️ 21.08.2022): + + ``` + git clone https://github.com/DistrictDataLabs/yellowbrick + ``` +- [PyPi](https://pypi.org/project/yellowbrick) (📥 580K / month): + ``` + pip install yellowbrick ```
-
eli5 (🥈22 · ⭐ 2.5K · 💀) - 一个用于调试/检查机器学习分类器的库。MIT +
eli5 (🥈22 · ⭐ 2.6K · 💀) - A library for debugging/inspecting machine learning classifiers and.. MIT - [GitHub](https://github.com/TeamHG-Memex/eli5) (👨‍💻 14 · 🔀 310 · 📋 250 - 55% open · ⏱️ 22.01.2020): ``` git clone https://github.com/TeamHG-Memex/eli5 ``` -- [PyPi](https://pypi.org/project/eli5) (📥 1.6M / month): +- [PyPi](https://pypi.org/project/eli5) (📥 480K / month): ``` pip install eli5 ``` -- [Conda](https://anaconda.org/conda-forge/eli5) (📥 110K · ⏱️ 25.01.2021): +- [Conda](https://anaconda.org/conda-forge/eli5) (📥 120K · ⏱️ 14.05.2022): ``` conda install -c conda-forge eli5 ```
-
dtreeviz (🥈22 · ⭐ 1.9K) - 用于决策树可视化和模型解释的python库。MIT +
imodels (🥈22 · ⭐ 890) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT -- [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 17 · 🔀 240 · 📦 270 · 📋 110 - 16% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/csinva/imodels) (👨‍💻 13 · 🔀 83 · 📦 20 · 📋 40 - 35% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/parrt/dtreeviz + git clone https://github.com/csinva/imodels ``` -- [PyPi](https://pypi.org/project/dtreeviz): +- [PyPi](https://pypi.org/project/imodels) (📥 19K / month): ``` - pip install dtreeviz + pip install imodels ```
-
Explainability 360 (🥈22 · ⭐ 1K) - 数据和机器学习的可解释性。Apache-2 +
DoWhy (🥉21 · ⭐ 5.1K) - DoWhy is a Python library for causal inference that supports explicit.. MIT -- [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 29 · 🔀 210 · 📦 36 · 📋 56 - 55% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/py-why/dowhy) (👨‍💻 60 · 🔀 700 · 📥 31 · 📋 250 - 31% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/Trusted-AI/AIX360 + git clone https://github.com/Microsoft/dowhy ``` -- [PyPi](https://pypi.org/project/aix360) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/dowhy) (📥 180K / month): ``` - pip install aix360 + pip install dowhy + ``` +- [Conda](https://anaconda.org/conda-forge/dowhy) (📥 8.2K · ⏱️ 19.07.2022): + ``` + conda install -c conda-forge dowhy ```
-
tf-explain (🥈22 · ⭐ 890) - 使用Tensorflow 2.x的tf.keras模型的可解释性方法。MIT +
checklist (🥉21 · ⭐ 1.7K) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT -- [GitHub](https://github.com/sicara/tf-explain) (👨‍💻 16 · 🔀 89 · 📦 92 · 📋 86 - 43% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/marcotcr/checklist) (👨‍💻 13 · 🔀 170 · 📦 150 · 📋 83 - 2% open · ⏱️ 12.08.2022): ``` - git clone https://github.com/sicara/tf-explain + git clone https://github.com/marcotcr/checklist ``` -- [PyPi](https://pypi.org/project/tf-explain) (📥 2.3K / month): +- [PyPi](https://pypi.org/project/checklist) (📥 7.8K / month): ``` - pip install tf-explain + pip install checklist ```
-
checklist (🥈21 · ⭐ 1.5K) - 超越准确性：使用CheckList对NLP模型进行行为测试。MIT +
fairlearn (🥉21 · ⭐ 1.4K) - A Python package to assess and improve fairness of machine.. MIT -- [GitHub](https://github.com/marcotcr/checklist) (👨‍💻 12 · 🔀 150 · 📦 58 · 📋 80 - 1% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/fairlearn/fairlearn) (👨‍💻 68 · 🔀 310 · 📋 360 - 39% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/marcotcr/checklist + git clone https://github.com/fairlearn/fairlearn ``` -- [PyPi](https://pypi.org/project/checklist) (📥 14K / month): +- [PyPi](https://pypi.org/project/fairlearn) (📥 230K / month): ``` - pip install checklist + pip install fairlearn + ``` +- [Conda](https://anaconda.org/conda-forge/fairlearn) (📥 20K · ⏱️ 07.07.2021): + ``` + conda install -c conda-forge fairlearn ```
-
keract (🥈21 · ⭐ 940) - 在Keras中分层输出和渐变。MIT +
DALEX (🥉21 · ⭐ 1.1K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 -- [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 110 · 📋 83 - 2% open · ⏱️ 28.07.2021): +- [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 140 · 📦 57 · 📋 370 - 5% open · ⏱️ 03.08.2022): ``` - git clone https://github.com/philipperemy/keract + git clone https://github.com/ModelOriented/DALEX ``` -- [PyPi](https://pypi.org/project/keract) (📥 1.3K / month): +- [PyPi](https://pypi.org/project/dalex) (📥 9.5K / month): ``` - pip install keract + pip install dalex ```
-
imodels (🥈21 · ⭐ 400) - 可解释的ML包，用于简洁，透明和准确的预测。MIT +
keract (🥉21 · ⭐ 990) - Layers Outputs and Gradients in Keras. Made easy. MIT -- [GitHub](https://github.com/csinva/imodels) (👨‍💻 7 · 🔀 40 · 📦 10 · 📋 17 - 17% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 140 · 📋 87 - 5% open · ⏱️ 23.07.2022): ``` - git clone https://github.com/csinva/imodels + git clone https://github.com/philipperemy/keract ``` -- [PyPi](https://pypi.org/project/imodels) (📥 1.6K / month): +- [PyPi](https://pypi.org/project/keract) (📥 900 / month): ``` - pip install imodels + pip install keract ```
-
yellowbrick (🥉20 · ⭐ 3.4K) - 可视化分析和诊断工具，方便机器使用。Apache-2 +
tf-explain (🥉21 · ⭐ 940) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT -- [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 100 · 🔀 490 · 📋 630 - 13% open · ⏱️ 10.11.2021): +- [GitHub](https://github.com/sicara/tf-explain) (👨‍💻 18 · 🔀 100 · 📦 130 · 📋 88 - 42% open · ⏱️ 30.06.2022): ``` - git clone https://github.com/DistrictDataLabs/yellowbrick + git clone https://github.com/sicara/tf-explain ``` -- [PyPi](https://pypi.org/project/yellowbrick) (📥 330K / month): +- [PyPi](https://pypi.org/project/tf-explain) (📥 1.1K / month): ``` - pip install yellowbrick + pip install tf-explain ```
-
Skater (🥉20 · ⭐ 1K · 💀) - 用于模型解释/说明的Python库。❗️UPL-1.0 +
random-forest-importances (🥉21 · ⭐ 510 · 💀) - Code to compute permutation and drop-column.. MIT -- [GitHub](https://github.com/oracle/Skater) (👨‍💻 34 · 🔀 160 · 📋 160 - 40% open · ⏱️ 29.06.2020): +- [GitHub](https://github.com/parrt/random-forest-importances) (👨‍💻 14 · 🔀 120 · 📦 100 · 📋 34 - 14% open · ⏱️ 30.01.2021): ``` - git clone https://github.com/oracle/Skater - ``` -- [PyPi](https://pypi.org/project/skater) (📥 2.4K / month): - ``` - pip install skater + git clone https://github.com/parrt/random-forest-importances ``` -- [Conda](https://anaconda.org/conda-forge/skater) (📥 46K · ⏱️ 15.11.2021): +- [PyPi](https://pypi.org/project/rfpimp) (📥 30K / month): ``` - conda install -c conda-forge skater + pip install rfpimp ```
-
DALEX (🥉20 · ⭐ 970) - 用于模型探索和扩展的模块。❗️GPL-3.0 +
sklearn-evaluation (🥉21 · ⭐ 340) - Machine learning model evaluation made easy: plots,.. MIT -- [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 120 · 📦 26 · 📋 330 - 4% open · ⏱️ 08.11.2021): +- [GitHub](https://github.com/ploomber/sklearn-evaluation) (👨‍💻 8 · 🔀 28 · 📦 49 · 📋 39 - 20% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/ModelOriented/DALEX + git clone https://github.com/edublancas/sklearn-evaluation ``` -- [PyPi](https://pypi.org/project/dalex) (📥 11K / month): +- [PyPi](https://pypi.org/project/sklearn-evaluation) (📥 1.7K / month): ``` - pip install dalex + pip install sklearn-evaluation ```
-
explainerdashboard (🥉20 · ⭐ 770) - 快速构建可显示内部信息的可解释AI仪表板。MIT +
DiCE (🥉20 · ⭐ 890) - Generate Diverse Counterfactual Explanations for any machine.. MIT -- [GitHub](https://github.com/oegedijk/explainerdashboard) (👨‍💻 12 · 🔀 91 · 📦 46 · 📋 130 - 15% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 14 · 🔀 120 · 📋 130 - 44% open · ⏱️ 06.07.2022): ``` - git clone https://github.com/oegedijk/explainerdashboard + git clone https://github.com/interpretml/DiCE ``` -- [PyPi](https://pypi.org/project/explainerdashboard): +- [PyPi](https://pypi.org/project/dice-ml) (📥 140K / month): ``` - pip install explainerdashboard + pip install dice-ml ```
-
fairlearn (🥉19 · ⭐ 1.1K) - 一个用于评估和改善机器公平性的Python程序包。MIT +
TreeInterpreter (🥉20 · ⭐ 720 · 💀) - Package for interpreting scikit-learn's decision tree.. BSD-3 -- [GitHub](https://github.com/fairlearn/fairlearn) (👨‍💻 61 · 🔀 270 · 📋 320 - 37% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 140 · 📦 280 · 📋 23 - 82% open · ⏱️ 28.02.2021): ``` - git clone https://github.com/fairlearn/fairlearn - ``` -- [PyPi](https://pypi.org/project/fairlearn): - ``` - pip install fairlearn + git clone https://github.com/andosa/treeinterpreter ``` -- [Conda](https://anaconda.org/conda-forge/fairlearn) (📥 16K · ⏱️ 07.07.2021): +- [PyPi](https://pypi.org/project/treeinterpreter) (📥 150K / month): ``` - conda install -c conda-forge fairlearn + pip install treeinterpreter ```
-
TreeInterpreter (🥉19 · ⭐ 690 · 💤) - 解释scikit-learn决策树的程序包。BSD-3 +
LIT (🥉19 · ⭐ 3K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 -- [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 130 · 📦 180 · 📋 23 - 82% open · ⏱️ 28.02.2021): +- [GitHub](https://github.com/PAIR-code/lit) (👨‍💻 18 · 🔀 310 · 📦 11 · 📋 110 - 37% open · ⏱️ 15.03.2022): ``` - git clone https://github.com/andosa/treeinterpreter + git clone https://github.com/PAIR-code/lit ``` -- [PyPi](https://pypi.org/project/treeinterpreter) (📥 200K / month): +- [PyPi](https://pypi.org/project/lit-nlp) (📥 820 / month): ``` - pip install treeinterpreter + pip install lit-nlp ```
-
What-If Tool (🥉19 · ⭐ 610) - What-If工具的源代码/网页/演示。Apache-2 +
What-If Tool (🥉19 · ⭐ 740 · 💤) - Source code/webpage/demos for the What-If Tool. Apache-2 -- [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 20 · 🔀 120 · 📋 94 - 51% open · ⏱️ 01.11.2021): +- [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 20 · 🔀 140 · 📋 110 - 52% open · ⏱️ 05.01.2022): ``` git clone https://github.com/PAIR-code/what-if-tool ``` -- [PyPi](https://pypi.org/project/witwidget): +- [PyPi](https://pypi.org/project/witwidget) (📥 11K / month): ``` pip install witwidget ``` -- [NPM](https://www.npmjs.com/package/wit-widget) (📥 4.3K / month): +- [NPM](https://www.npmjs.com/package/wit-widget) (📥 5.9K / month): ``` npm install wit-widget ```
-
deeplift (🥉19 · ⭐ 600) - Public facing deeplift repo。MIT +
deeplift (🥉19 · ⭐ 650 · 💤) - Public facing deeplift repo. MIT -- [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 130 · 📦 52 · 📋 81 - 40% open · ⏱️ 11.11.2021): +- [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 150 · 📦 62 · 📋 85 - 43% open · ⏱️ 11.11.2021): ``` git clone https://github.com/kundajelab/deeplift ``` -- [PyPi](https://pypi.org/project/deeplift) (📥 520 / month): +- [PyPi](https://pypi.org/project/deeplift) (📥 530 / month): ``` pip install deeplift ```
-
sklearn-evaluation (🥉19 · ⭐ 320) - 机器学习模型评估变得容易。MIT - -- [GitHub](https://github.com/edublancas/sklearn-evaluation) (👨‍💻 6 · 🔀 25 · 📦 33 · 📋 37 - 21% open · ⏱️ 17.10.2021): - - ``` - git clone https://github.com/edublancas/sklearn-evaluation - ``` -- [PyPi](https://pypi.org/project/sklearn-evaluation) (📥 910 / month): - ``` - pip install sklearn-evaluation - ``` -
-
aequitas (🥉18 · ⭐ 440 · 💤) - 偏差和公平审计工具包。MIT +
aequitas (🥉19 · ⭐ 490 · 💀) - Bias and Fairness Audit Toolkit. MIT -- [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 84 · 📦 87 · 📋 58 - 63% open · ⏱️ 27.05.2021): +- [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 90 · 📦 110 · 📋 61 - 65% open · ⏱️ 27.05.2021): ``` git clone https://github.com/dssg/aequitas ``` -- [PyPi](https://pypi.org/project/aequitas) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/aequitas) (📥 2K / month): ``` pip install aequitas ```
-
random-forest-importances (🥉17 · ⭐ 490 · 💤) - 随机森林特征重要度计算。MIT - -- [GitHub](https://github.com/parrt/random-forest-importances) (👨‍💻 14 · 🔀 110 · 📦 88 · 📋 34 - 17% open · ⏱️ 30.01.2021): - - ``` - git clone https://github.com/parrt/random-forest-importances - ``` -- [PyPi](https://pypi.org/project/rfpimp): - ``` - pip install rfpimp - ``` -
-
model-card-toolkit (🥉17 · ⭐ 240) - 模型解释与分析卡片工具库。Apache-2 +
model-card-toolkit (🥉19 · ⭐ 300) - a tool that leverages rich metadata and lineage.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 11 · 🔀 41 · 📦 5 · 📋 6 - 66% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 13 · 🔀 60 · 📦 10 · 📋 14 - 85% open · ⏱️ 28.04.2022): ``` git clone https://github.com/tensorflow/model-card-toolkit ``` -- [PyPi](https://pypi.org/project/model-card-toolkit): +- [PyPi](https://pypi.org/project/model-card-toolkit) (📥 850 / month): ``` pip install model-card-toolkit ```
-
fairness-indicators (🥉17 · ⭐ 240) - Tensorflow的公平性评估和可视化。Apache-2 +
fairness-indicators (🥉19 · ⭐ 270) - Tensorflow's Fairness Evaluation and Visualization.. Apache-2 -- [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 25 · 🔀 66 · 📋 10 - 20% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 33 · 🔀 68 · 📋 11 - 27% open · ⏱️ 26.07.2022): ``` git clone https://github.com/tensorflow/fairness-indicators ``` -- [PyPi](https://pypi.org/project/fairness-indicators): +- [PyPi](https://pypi.org/project/fairness-indicators) (📥 620 / month): ``` pip install fairness-indicators ```
-
LIT (🥉16 · ⭐ 2.7K) - 语言可解释性工具：交互式分析NLP模型。Apache-2 +
iNNvestigate (🥉18 · ⭐ 1K) - A toolbox to iNNvestigate neural networks' predictions!. BSD-2 -- [GitHub](https://github.com/PAIR-code/lit) (👨‍💻 17 · 🔀 270 · 📦 7 · 📋 86 - 29% open · ⏱️ 14.11.2021): +- [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 220 · 📥 16 · 📋 230 - 19% open · ⏱️ 01.08.2022): ``` - git clone https://github.com/PAIR-code/lit + git clone https://github.com/albermax/innvestigate ``` -- [PyPi](https://pypi.org/project/lit-nlp): +- [PyPi](https://pypi.org/project/innvestigate) (📥 440 / month): ``` - pip install lit-nlp + pip install innvestigate ```
-
XAI (🥉16 · ⭐ 740) - XAI-用于机器学习的可解释性工具箱。MIT +
Skater (🥉17 · ⭐ 1K) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 -- [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 110 · 📦 11 · 📋 8 - 12% open · ⏱️ 30.10.2021): +- [GitHub](https://github.com/oracle/Skater) (👨‍💻 36 · 🔀 170 · 📋 160 - 40% open · ⏱️ 11.02.2022): ``` - git clone https://github.com/EthicalML/xai + git clone https://github.com/oracle/Skater ``` -- [PyPi](https://pypi.org/project/xai): +- [PyPi](https://pypi.org/project/skater) (📥 3K / month): ``` - pip install xai + pip install skater + ``` +- [Conda](https://anaconda.org/conda-forge/skater) (📥 51K · ⏱️ 15.11.2021): + ``` + conda install -c conda-forge skater ```
-
DiCE (🥉16 · ⭐ 730) - 生成任何机器学习的各种反事实说明。MIT +
FlashTorch (🥉17 · ⭐ 680 · 💀) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT -- [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 12 · 🔀 96 · 📋 90 - 44% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 84 · 📦 10 · 📋 31 - 29% open · ⏱️ 27.04.2021): ``` - git clone https://github.com/interpretml/DiCE + git clone https://github.com/MisaOgura/flashtorch ``` -- [PyPi](https://pypi.org/project/dice-ml): +- [PyPi](https://pypi.org/project/flashtorch) (📥 160 / month): ``` - pip install dice-ml + pip install flashtorch ```
-
tcav (🥉16 · ⭐ 500) - TCAV ML可解释性项目的代码。Apache-2 +
tcav (🥉17 · ⭐ 530 · 💤) - Code for the TCAV ML interpretability project. Apache-2 -- [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 120 · 📦 11 · 📋 55 - 5% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 130 · 📦 14 · 📋 61 - 11% open · ⏱️ 16.09.2021): ``` git clone https://github.com/tensorflow/tcav ``` -- [PyPi](https://pypi.org/project/tcav): +- [PyPi](https://pypi.org/project/tcav) (📥 48 / month): ``` pip install tcav ```
-
iNNvestigate (🥉15 · ⭐ 920) - 神经网络预估分析工具箱。BSD-2 +
ExplainX.ai (🥉17 · ⭐ 320 · 💀) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 200 · 📋 230 - 28% open · ⏱️ 03.08.2021): +- [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 42 · 📥 4 · 📋 26 - 34% open · ⏱️ 02.02.2021): ``` - git clone https://github.com/albermax/innvestigate + git clone https://github.com/explainX/explainx ``` -- [PyPi](https://pypi.org/project/innvestigate) (📥 450 / month): +- [PyPi](https://pypi.org/project/explainx) (📥 1.9K / month): ``` - pip install innvestigate + pip install explainx ```
-
Anchor (🥉15 · ⭐ 680) - High-Precision Model-Agnostic Explanations论文代码。BSD-2 +
XAI (🥉15 · ⭐ 840 · 💤) - XAI - An eXplainability toolbox for machine learning. MIT -- [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 10 · 🔀 93 · 📋 67 - 23% open · ⏱️ 17.11.2021): +- [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 120 · 📦 19 · 📋 9 - 22% open · ⏱️ 30.10.2021): ``` - git clone https://github.com/marcotcr/anchor + git clone https://github.com/EthicalML/xai ``` -- [PyPi](https://pypi.org/project/anchor_exp) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/xai) (📥 120 / month): ``` - pip install anchor_exp + pip install xai ```
-
LOFO (🥉15 · ⭐ 420) - Leave One Feature Out特征重要度。MIT +
Anchor (🥉15 · ⭐ 720) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 -- [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 50 · 📦 6 · 📋 17 - 23% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 10 · 🔀 99 · 📋 70 - 27% open · ⏱️ 19.07.2022): ``` - git clone https://github.com/aerdem4/lofo-importance + git clone https://github.com/marcotcr/anchor ``` -- [PyPi](https://pypi.org/project/lofo-importance) (📥 330 / month): +- [PyPi](https://pypi.org/project/anchor_exp) (📥 1.2K / month): ``` - pip install lofo-importance + pip install anchor_exp ```
-
ExplainX.ai (🥉15 · ⭐ 250 · 💤) - 适用于数据科学家的可解释AI框架。MIT +
LOFO (🥉15 · ⭐ 480) - Leave One Feature Out Importance. MIT -- [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 36 · 📥 2 · 📋 24 - 29% open · ⏱️ 02.02.2021): +- [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 56 · 📦 19 · 📋 18 - 11% open · ⏱️ 27.04.2022): ``` - git clone https://github.com/explainX/explainx + git clone https://github.com/aerdem4/lofo-importance ``` -- [PyPi](https://pypi.org/project/explainx) (📥 600 / month): +- [PyPi](https://pypi.org/project/lofo-importance) (📥 310 / month): ``` - pip install explainx + pip install lofo-importance ```
-
FlashTorch (🥉13 · ⭐ 640 · 💤) - PyTorch中用于神经网络的可视化工具包。MIT +
contextual-ai (🥉13 · ⭐ 81 · 💤) - Contextual AI adds explainability to different stages of.. Apache-2 -- [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 77 · 📦 8 · 📋 29 - 24% open · ⏱️ 27.04.2021): +- [GitHub](https://github.com/SAP/contextual-ai) (👨‍💻 12 · 🔀 10 · 📋 12 - 8% open · ⏱️ 11.11.2021): ``` - git clone https://github.com/MisaOgura/flashtorch + git clone https://github.com/SAP/contextual-ai ``` -- [PyPi](https://pypi.org/project/flashtorch): +- [PyPi](https://pypi.org/project/contextual-ai) (📥 65 / month): ``` - pip install flashtorch + pip install contextual-ai ```
-
Attribution Priors (🥉12 · ⭐ 90 · 💤) - 训练可解释模型的工具。MIT +
Attribution Priors (🥉11 · ⭐ 100 · 💀) - Tools for training explainable models using.. MIT -- [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 10 · 📦 3 · 📋 4 - 25% open · ⏱️ 19.03.2021): +- [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 10 · 📦 3 · 📋 5 - 40% open · ⏱️ 19.03.2021): ``` git clone https://github.com/suinleelab/attributionpriors ``` -- [PyPi](https://pypi.org/project/attributionpriors) (📥 27 / month): +- [PyPi](https://pypi.org/project/attributionpriors) (📥 18 / month): ``` pip install attributionpriors ```
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contextual-ai (🥉12 · ⭐ 74) - AI 模型可解释性工具。Apache-2 - -- [GitHub](https://github.com/SAP/contextual-ai) (👨‍💻 12 · 🔀 9 · 📋 12 - 8% open · ⏱️ 11.11.2021): - - ``` - git clone https://github.com/SAP/contextual-ai - ``` -- [PyPi](https://pypi.org/project/contextual-ai): - ``` - pip install contextual-ai - ``` -
-
bias-detector (🥉12 · ⭐ 36) - Bias Detector是用于检测机器偏差的python软件包。MIT +
bias-detector (🥉11 · ⭐ 40 · 💤) - Bias Detector is a python package for detecting bias in machine.. MIT -- [GitHub](https://github.com/intuit/bias-detector) (👨‍💻 4 · 🔀 9 · ⏱️ 27.10.2021): +- [GitHub](https://github.com/intuit/bias-detector) (👨‍💻 4 · 🔀 11 · ⏱️ 20.12.2021): ``` git clone https://github.com/intuit/bias-detector ``` -- [PyPi](https://pypi.org/project/bias-detector) (📥 40 / month): +- [PyPi](https://pypi.org/project/bias-detector) (📥 48 / month): ``` pip install bias-detector ```

-## 向量相似度搜索（ANN） +## Vector Similarity Search (ANN) -Back to top +Back to top -_用于近似最近邻居搜索和向量索引/相似性搜索的库。_ +_Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search._ -🔗 ANN Benchmarks ( ⭐ 2.7K) - Benchmarks of approximate nearest neighbor libraries in Python. +🔗 ANN Benchmarks ( ⭐ 3K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Milvus (🥇27 · ⭐ 9K) - 一个开源的embedding嵌入向量相似度搜索引擎。Apache-2 +
Annoy (🥇31 · ⭐ 10K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 -- [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 180 · 🔀 1.3K · 📥 6.1K · 📋 4.1K - 4% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/spotify/annoy) (👨‍💻 82 · 🔀 1K · 📦 2.2K · 📋 350 - 10% open · ⏱️ 08.08.2022): ``` - git clone https://github.com/milvus-io/milvus - ``` -- [PyPi](https://pypi.org/project/pymilvus): - ``` - pip install pymilvus + git clone https://github.com/spotify/annoy ``` -- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (📥 660K · ⭐ 16 · ⏱️ 26.11.2021): +- [PyPi](https://pypi.org/project/annoy) (📥 1.5M / month): ``` - docker pull milvusdb/milvus + pip install annoy ```
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Faiss (🥇26 · ⭐ 16K) - 一个用于高效相似性搜索和密集向量聚类的库。MIT +
Milvus (🥇29 · ⭐ 12K) - An open source embedding vector similarity search engine powered by.. Apache-2 -- [GitHub](https://github.com/facebookresearch/faiss) (👨‍💻 90 · 🔀 2.4K · 📦 520 · 📋 1.7K - 12% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 220 · 🔀 1.4K · 📥 44K · 📋 5.7K - 4% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/facebookresearch/faiss + git clone https://github.com/milvus-io/milvus ``` -- [PyPi](https://pypi.org/project/pymilvus): +- [PyPi](https://pypi.org/project/pymilvus) (📥 130K / month): ``` pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/faiss) (📥 230K · ⏱️ 20.11.2021): +- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (📥 1.3M · ⭐ 21 · ⏱️ 26.08.2022): ``` - conda install -c conda-forge faiss + docker pull milvusdb/milvus ```
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NMSLIB (🥇26 · ⭐ 2.7K) - 非度量空间库（NMSLIB）：一种有效的相似度搜索。Apache-2 +
NMSLIB (🥈28 · ⭐ 2.8K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 -- [GitHub](https://github.com/nmslib/nmslib) (👨‍💻 45 · 🔀 370 · 📦 520 · 📋 380 - 14% open · ⏱️ 19.09.2021): +- [GitHub](https://github.com/nmslib/nmslib) (👨‍💻 48 · 🔀 400 · 📦 660 · 📋 400 - 14% open · ⏱️ 31.05.2022): ``` git clone https://github.com/nmslib/nmslib ``` -- [PyPi](https://pypi.org/project/nmslib): +- [PyPi](https://pypi.org/project/nmslib) (📥 120K / month): ``` pip install nmslib ``` -- [Conda](https://anaconda.org/conda-forge/nmslib) (📥 46K · ⏱️ 22.11.2021): +- [Conda](https://anaconda.org/conda-forge/nmslib) (📥 61K · ⏱️ 15.04.2022): ``` conda install -c conda-forge nmslib ```
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PyNNDescent (🥈25 · ⭐ 530) - 适用于近似最近邻查找的Python库。BSD-2 +
PyNNDescent (🥈28 · ⭐ 660) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 -- [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 18 · 🔀 68 · 📦 1K · 📋 88 - 44% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 21 · 🔀 88 · 📦 2K · 📋 110 - 47% open · ⏱️ 21.07.2022): ``` git clone https://github.com/lmcinnes/pynndescent ``` -- [PyPi](https://pypi.org/project/pynndescent): +- [PyPi](https://pypi.org/project/pynndescent) (📥 610K / month): ``` pip install pynndescent ``` -- [Conda](https://anaconda.org/conda-forge/pynndescent) (📥 420K · ⏱️ 15.10.2021): +- [Conda](https://anaconda.org/conda-forge/pynndescent) (📥 850K · ⏱️ 15.05.2022): ``` conda install -c conda-forge pynndescent ```
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Annoy (🥈24 · ⭐ 9.3K) - C++/Python中的近似最近邻居实现，并针对内存使用进行了优化。Apache-2 +
Faiss (🥈27 · ⭐ 18K) - A library for efficient similarity search and clustering of dense vectors. MIT -- [GitHub](https://github.com/spotify/annoy) (👨‍💻 75 · 🔀 950 · 📦 1.9K · 📋 340 - 11% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/facebookresearch/faiss) (👨‍💻 100 · 🔀 2.6K · 📦 720 · 📋 1.9K - 11% open · ⏱️ 08.08.2022): ``` - git clone https://github.com/spotify/annoy + git clone https://github.com/facebookresearch/faiss + ``` +- [PyPi](https://pypi.org/project/pymilvus) (📥 130K / month): ``` -- [PyPi](https://pypi.org/project/annoy): + pip install pymilvus ``` - pip install annoy +- [Conda](https://anaconda.org/conda-forge/faiss) (📥 450K · ⏱️ 09.02.2022): + ``` + conda install -c conda-forge faiss ```
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hnswlib (🥉22 · ⭐ 1.8K) - 仅标头的C++/python库，用于快速近似最近邻查找。Apache-2 +
hnswlib (🥈27 · ⭐ 2.1K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 -- [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 52 · 🔀 340 · 📦 180 · 📋 220 - 46% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 56 · 🔀 380 · 📦 280 · 📋 250 - 50% open · ⏱️ 16.04.2022): ``` git clone https://github.com/nmslib/hnswlib ``` -- [PyPi](https://pypi.org/project/hnswlib): +- [PyPi](https://pypi.org/project/hnswlib) (📥 430K / month): ``` pip install hnswlib ```
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Magnitude (🥉19 · ⭐ 1.5K · 💀) - 快速，高效的通用向量嵌入实用程序包。MIT +
Magnitude (🥉22 · ⭐ 1.5K · 💀) - A fast, efficient universal vector embedding utility package. MIT -- [GitHub](https://github.com/plasticityai/magnitude) (👨‍💻 4 · 🔀 100 · 📦 210 · 📋 80 - 36% open · ⏱️ 17.07.2020): +- [GitHub](https://github.com/plasticityai/magnitude) (👨‍💻 4 · 🔀 110 · 📦 240 · 📋 83 - 38% open · ⏱️ 17.07.2020): ``` git clone https://github.com/plasticityai/magnitude ``` -- [PyPi](https://pypi.org/project/pymagnitude): +- [PyPi](https://pypi.org/project/pymagnitude) (📥 3.1K / month): ``` pip install pymagnitude ```
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NearPy (🥉16 · ⭐ 690 · 💀) - 用于快速（近似）最近邻搜索的Python框架。MIT +
NGT (🥉19 · ⭐ 930) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 -- [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 63 · 📋 62 - 38% open · ⏱️ 21.10.2018): +- [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 14 · 🔀 94 · 📋 100 - 11% open · ⏱️ 15.08.2022): ``` - git clone https://github.com/pixelogik/NearPy + git clone https://github.com/yahoojapan/NGT ``` -- [PyPi](https://pypi.org/project/NearPy): +- [PyPi](https://pypi.org/project/ngt) (📥 16K / month): ``` - pip install NearPy + pip install ngt ```
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N2 (🥉16 · ⭐ 500 · 💤) - TOROS N2-快速运行的轻量级近似最近邻库。Apache-2 +
NearPy (🥉19 · ⭐ 710 · 💀) - Python framework for fast (approximated) nearest neighbour search in.. MIT -- [GitHub](https://github.com/kakao/n2) (👨‍💻 18 · 🔀 61 · 📦 22 · 📋 30 - 33% open · ⏱️ 20.05.2021): +- [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 70 · 📋 62 - 38% open · ⏱️ 21.10.2018): ``` - git clone https://github.com/kakao/n2 + git clone https://github.com/pixelogik/NearPy ``` -- [PyPi](https://pypi.org/project/n2): +- [PyPi](https://pypi.org/project/NearPy) (📥 1.3K / month): ``` - pip install n2 + pip install NearPy ```
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NGT (🥉14 · ⭐ 830) - 最近邻搜索算法实现包。Apache-2 +
N2 (🥉18 · ⭐ 520 · 💀) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 -- [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 12 · 🔀 82 · 📋 83 - 9% open · ⏱️ 25.10.2021): +- [GitHub](https://github.com/kakao/n2) (👨‍💻 18 · 🔀 64 · 📦 23 · 📋 33 - 33% open · ⏱️ 20.05.2021): ``` - git clone https://github.com/yahoojapan/NGT + git clone https://github.com/kakao/n2 ``` -- [PyPi](https://pypi.org/project/ngt): +- [PyPi](https://pypi.org/project/n2) (📥 860 / month): ``` - pip install ngt + pip install n2 ```
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PySparNN (🥉11 · ⭐ 890 · 💀) - C++/Python中的近似最近邻居实现，并针对内存使用进行了优化。BSD-3 +
PySparNN (🥉11 · ⭐ 900 · 💀) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3 -- [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 150 · 📋 29 - 51% open · ⏱️ 31.01.2018): +- [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 140 · 📋 29 - 51% open · ⏱️ 31.01.2018): ``` git clone https://github.com/facebookresearch/pysparnn @@ -9301,293 +9301,293 @@ _用于近似最近邻居搜索和向量索引/相似性搜索的库。_

-## 概率统计 +## Probabilistics & Statistics -Back to top +Back to top -_提供概率编程/推理，贝叶斯推理，高斯过程或统计信息的功能的库。_ +_Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics._ -
hmmlearn (🥇29 · ⭐ 2.4K) - Python中的隐马尔可夫模型，具有类似于scikit-learn的API。BSD-3 +
Pyro (🥇30 · ⭐ 7.6K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 -- [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 38 · 🔀 650 · 📦 1.1K · 📋 360 - 14% open · ⏱️ 12.12.2021): +- [GitHub](https://github.com/pyro-ppl/pyro) (👨‍💻 130 · 🔀 900 · 📦 820 · 📋 970 - 20% open · ⏱️ 05.08.2022): ``` - git clone https://github.com/hmmlearn/hmmlearn + git clone https://github.com/pyro-ppl/pyro ``` -- [PyPi](https://pypi.org/project/hmmlearn) (📥 550K / month): +- [PyPi](https://pypi.org/project/pyro-ppl) (📥 460K / month): ``` - pip install hmmlearn + pip install pyro-ppl + ``` +
+
GPyTorch (🥇29 · ⭐ 2.8K) - A highly efficient and modular implementation of Gaussian Processes.. MIT + +- [GitHub](https://github.com/cornellius-gp/gpytorch) (👨‍💻 99 · 🔀 420 · 📦 680 · 📋 1.1K - 24% open · ⏱️ 24.08.2022): + ``` -- [Conda](https://anaconda.org/conda-forge/hmmlearn) (📥 110K · ⏱️ 13.11.2021): + git clone https://github.com/cornellius-gp/gpytorch ``` - conda install -c conda-forge hmmlearn +- [PyPi](https://pypi.org/project/gpytorch) (📥 260K / month): + ``` + pip install gpytorch ```
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filterpy (🥇28 · ⭐ 2K · 💤) - Python卡尔曼过滤和最佳估计库。MIT +
filterpy (🥇28 · ⭐ 2.4K) - Python Kalman filtering and optimal estimation library. Implements.. MIT -- [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 36 · 🔀 470 · 📦 1.1K · 📋 190 - 20% open · ⏱️ 04.05.2021): +- [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 43 · 🔀 520 · 📦 1.6K · 📋 200 - 23% open · ⏱️ 22.08.2022): ``` git clone https://github.com/rlabbe/filterpy ``` -- [PyPi](https://pypi.org/project/filterpy) (📥 650K / month): +- [PyPi](https://pypi.org/project/filterpy) (📥 760K / month): ``` pip install filterpy ``` -- [Conda](https://anaconda.org/conda-forge/filterpy) (📥 70K · ⏱️ 05.05.2020): +- [Conda](https://anaconda.org/conda-forge/filterpy) (📥 140K · ⏱️ 05.05.2020): ``` conda install -c conda-forge filterpy ```
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GPflow (🥇26 · ⭐ 1.5K) - TensorFlow中的高斯过程。Apache-2 +
GPflow (🥇28 · ⭐ 1.7K) - Gaussian processes in TensorFlow. Apache-2 -- [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 72 · 🔀 400 · 📦 310 · 📋 720 - 13% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 78 · 🔀 410 · 📦 390 · 📋 780 - 15% open · ⏱️ 17.08.2022): ``` git clone https://github.com/GPflow/GPflow ``` -- [PyPi](https://pypi.org/project/gpflow): +- [PyPi](https://pypi.org/project/gpflow) (📥 16K / month): ``` pip install gpflow ``` -- [Conda](https://anaconda.org/conda-forge/gpflow) (📥 9.8K · ⏱️ 06.11.2018): +- [Conda](https://anaconda.org/conda-forge/gpflow) (📥 15K · ⏱️ 24.05.2022): ``` conda install -c conda-forge gpflow ```
-
pomegranate (🥈25 · ⭐ 2.8K) - 在Python中快速，灵活且易于使用的概率建模。MIT +
pingouin (🥈27 · ⭐ 1.2K) - Statistical package in Python based on Pandas. ❗️GPL-3.0 -- [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 65 · 🔀 510 · 📦 590 · 📋 640 - 5% open · ⏱️ 20.11.2021): +- [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 33 · 🔀 110 · 📦 680 · 📋 220 - 14% open · ⏱️ 18.07.2022): ``` - git clone https://github.com/jmschrei/pomegranate + git clone https://github.com/raphaelvallat/pingouin ``` -- [PyPi](https://pypi.org/project/pomegranate): +- [PyPi](https://pypi.org/project/pingouin) (📥 59K / month): ``` - pip install pomegranate + pip install pingouin ``` -- [Conda](https://anaconda.org/conda-forge/pomegranate) (📥 77K · ⏱️ 16.11.2021): +- [Conda](https://anaconda.org/conda-forge/pingouin) (📥 66K · ⏱️ 24.06.2022): ``` - conda install -c conda-forge pomegranate + conda install -c conda-forge pingouin ```
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patsy (🥈25 · ⭐ 810) - 使用符号公式描述Python中的统计模型。❗Unlicensed +
patsy (🥈27 · ⭐ 850) - Describing statistical models in Python using symbolic formulas. ❗Unlicensed -- [GitHub](https://github.com/pydata/patsy) (👨‍💻 16 · 🔀 85 · 📦 45K · 📋 130 - 46% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/pydata/patsy) (👨‍💻 17 · 🔀 88 · 📦 56K · 📋 130 - 46% open · ⏱️ 16.08.2022): ``` git clone https://github.com/pydata/patsy ``` -- [PyPi](https://pypi.org/project/patsy): +- [PyPi](https://pypi.org/project/patsy) (📥 7.5M / month): ``` pip install patsy ``` -- [Conda](https://anaconda.org/conda-forge/patsy) (📥 4M · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/patsy) (📥 5.5M · ⏱️ 26.09.2021): ``` conda install -c conda-forge patsy ```
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Pyro (🥈24 · ⭐ 7.2K) - 使用Python和PyTorch进行深度通用概率编程。Apache-2 - -- [GitHub](https://github.com/pyro-ppl/pyro) (👨‍💻 120 · 🔀 850 · 📦 590 · 📋 900 - 17% open · ⏱️ 14.12.2021): - - ``` - git clone https://github.com/pyro-ppl/pyro - ``` -- [PyPi](https://pypi.org/project/pyro-ppl): - ``` - pip install pyro-ppl - ``` -
-
PyMC3 (🥈24 · ⭐ 6.2K) - Python中的概率编程。❗Unlicensed +
PyMC3 (🥈26 · ⭐ 6.9K) - Probabilistic Programming in Python: Bayesian Modeling and.. ❗Unlicensed -- [GitHub](https://github.com/pymc-devs/pymc) (👨‍💻 350 · 🔀 1.4K · 📥 1.2K · 📦 570 · 📋 2.5K - 8% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/pymc-devs/pymc) (👨‍💻 410 · 🔀 1.6K · 📥 1.9K · 📦 690 · 📋 2.8K - 6% open · ⏱️ 25.08.2022): ``` git clone https://github.com/pymc-devs/pymc3 ``` -- [PyPi](https://pypi.org/project/pymc3): +- [PyPi](https://pypi.org/project/pymc3) (📥 410K / month): ``` pip install pymc3 ``` -- [Conda](https://anaconda.org/conda-forge/pymc3) (📥 360K · ⏱️ 12.10.2021): +- [Conda](https://anaconda.org/conda-forge/pymc3) (📥 440K · ⏱️ 20.05.2022): ``` conda install -c conda-forge pymc3 ```
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tensorflow-probability (🥈24 · ⭐ 3.6K) - 概率推理与统计分析。Apache-2 +
pomegranate (🥈26 · ⭐ 2.9K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT -- [GitHub](https://github.com/tensorflow/probability) (👨‍💻 430 · 🔀 910 · 📋 1.1K - 42% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 66 · 🔀 530 · 📦 740 · 📋 670 - 8% open · ⏱️ 04.07.2022): ``` - git clone https://github.com/tensorflow/probability - ``` -- [PyPi](https://pypi.org/project/tensorflow-probability) (📥 1.5M / month): - ``` - pip install tensorflow-probability - ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (📥 48K · ⏱️ 22.10.2021): - ``` - conda install -c conda-forge tensorflow-probability + git clone https://github.com/jmschrei/pomegranate ``` -
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GPyTorch (🥈24 · ⭐ 2.6K) - 高斯过程的高效和模块化实现。MIT - -- [GitHub](https://github.com/cornellius-gp/gpytorch) (👨‍💻 89 · 🔀 370 · 📦 450 · 📋 1K - 22% open · ⏱️ 15.12.2021): - +- [PyPi](https://pypi.org/project/pomegranate) (📥 53K / month): ``` - git clone https://github.com/cornellius-gp/gpytorch + pip install pomegranate ``` -- [PyPi](https://pypi.org/project/gpytorch): +- [Conda](https://anaconda.org/conda-forge/pomegranate) (📥 95K · ⏱️ 16.11.2021): ``` - pip install gpytorch + conda install -c conda-forge pomegranate ```
-
pingouin (🥈24 · ⭐ 870) - 基于Pandas的Python统计软件包。❗️GPL-3.0 +
hmmlearn (🥈26 · ⭐ 2.6K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 -- [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 23 · 🔀 76 · 📦 410 · 📋 180 - 13% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 41 · 🔀 660 · 📦 1.4K · 📋 390 - 13% open · ⏱️ 04.07.2022): ``` - git clone https://github.com/raphaelvallat/pingouin + git clone https://github.com/hmmlearn/hmmlearn ``` -- [PyPi](https://pypi.org/project/pingouin): +- [PyPi](https://pypi.org/project/hmmlearn) (📥 110K / month): ``` - pip install pingouin + pip install hmmlearn ``` -- [Conda](https://anaconda.org/conda-forge/pingouin) (📥 49K · ⏱️ 29.10.2021): +- [Conda](https://anaconda.org/conda-forge/hmmlearn) (📥 130K · ⏱️ 12.02.2022): ``` - conda install -c conda-forge pingouin + conda install -c conda-forge hmmlearn ```
-
pgmpy (🥉21 · ⭐ 1.9K) - 用于学习（结构和参数）和推理的Python库。MIT +
pgmpy (🥉25 · ⭐ 2.1K) - Python Library for learning (Structure and Parameter) and inference.. MIT -- [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 100 · 🔀 610 · 📥 120 · 📦 300 · 📋 730 - 25% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 110 · 🔀 630 · 📥 160 · 📦 400 · 📋 770 - 24% open · ⏱️ 22.08.2022): ``` git clone https://github.com/pgmpy/pgmpy ``` -- [PyPi](https://pypi.org/project/pgmpy): +- [PyPi](https://pypi.org/project/pgmpy) (📥 57K / month): ``` pip install pgmpy ```
-
SALib (🥉21 · ⭐ 550) - Python（Numpy）中的灵敏度分析库。MIT +
tensorflow-probability (🥉24 · ⭐ 3.8K) - Probabilistic reasoning and statistical analysis in.. Apache-2 -- [GitHub](https://github.com/SALib/SALib) (👨‍💻 34 · 🔀 160 · 📋 260 - 15% open · ⏱️ 25.11.2021): +- [GitHub](https://github.com/tensorflow/probability) (👨‍💻 460 · 🔀 960 · 📋 1.2K - 42% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/SALib/SALib + git clone https://github.com/tensorflow/probability ``` -- [PyPi](https://pypi.org/project/salib): +- [PyPi](https://pypi.org/project/tensorflow-probability) (📥 910K / month): ``` - pip install salib + pip install tensorflow-probability ``` -- [Conda](https://anaconda.org/conda-forge/salib) (📥 74K · ⏱️ 04.09.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (📥 70K · ⏱️ 08.08.2022): ``` - conda install -c conda-forge salib + conda install -c conda-forge tensorflow-probability ```
-
Edward (🥉20 · ⭐ 4.7K · 💀) - TensorFlow中的一种概率编程语言。❗Unlicensed +
Edward (🥉23 · ⭐ 4.7K · 💀) - A probabilistic programming language in TensorFlow. Deep.. ❗Unlicensed -- [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 750 · 📥 15 · 📦 250 · 📋 510 - 36% open · ⏱️ 25.07.2018): +- [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 750 · 📥 15 · 📦 270 · 📋 510 - 36% open · ⏱️ 25.07.2018): ``` git clone https://github.com/blei-lab/edward ``` -- [PyPi](https://pypi.org/project/edward): +- [PyPi](https://pypi.org/project/edward) (📥 1.3K / month): ``` pip install edward ```
-
scikit-posthocs (🥉19 · ⭐ 220) - Python中的多个成对比较（Post Hoc）测试。MIT +
Orbit (🥉21 · ⭐ 1.5K) - A Python package for Bayesian forecasting with object-oriented.. ❗Unlicensed -- [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 8 · 🔀 23 · 📥 23 · 📋 43 - 9% open · ⏱️ 26.11.2021): +- [GitHub](https://github.com/uber/orbit) (👨‍💻 18 · 🔀 110 · 📦 9 · 📋 370 - 12% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/maximtrp/scikit-posthocs + git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/scikit-posthocs) (📥 38K / month): +- [PyPi](https://pypi.org/project/orbit-ml) (📥 300K / month): ``` - pip install scikit-posthocs + pip install orbit-ml ```
-
Orbit (🥉18 · ⭐ 840) - 用于贝叶斯预测的Python软件包，具有面向对象的设计。❗Unlicensed +
bambi (🥉20 · ⭐ 820) - BAyesian Model-Building Interface (Bambi) in Python. MIT -- [GitHub](https://github.com/uber/orbit) (👨‍💻 14 · 🔀 61 · 📦 5 · 📋 300 - 12% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/bambinos/bambi) (👨‍💻 26 · 🔀 89 · 📦 32 · 📋 270 - 18% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/uber/orbit + git clone https://github.com/bambinos/bambi ``` -- [PyPi](https://pypi.org/project/orbit-ml) (📥 3.1K / month): +- [PyPi](https://pypi.org/project/bambi) (📥 6.7K / month): ``` - pip install orbit-ml + pip install bambi ```
-
Baal (🥉18 · ⭐ 490) - 在深度网络中使用近似贝叶斯后验进行主动学习。Apache-2 +
SALib (🥉20 · ⭐ 620) - Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,.. MIT -- [GitHub](https://github.com/ElementAI/baal) (👨‍💻 11 · 🔀 48 · 📋 62 - 29% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/SALib/SALib) (👨‍💻 37 · 🔀 190 · 📋 280 - 15% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/ElementAI/baal + git clone https://github.com/SALib/SALib ``` -- [PyPi](https://pypi.org/project/baal) (📥 530 / month): +- [PyPi](https://pypi.org/project/salib) (📥 160K / month): ``` - pip install baal + pip install salib + ``` +- [Conda](https://anaconda.org/conda-forge/salib) (📥 90K · ⏱️ 04.09.2021): + ``` + conda install -c conda-forge salib ```
-
bambi (🥉17 · ⭐ 700) - Python中的贝叶斯模型构建接口（Bambi）。MIT +
scikit-posthocs (🥉20 · ⭐ 250) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT -- [GitHub](https://github.com/bambinos/bambi) (👨‍💻 21 · 🔀 67 · 📦 18 · 📋 210 - 14% open · ⏱️ 01.12.2021): +- [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 10 · 🔀 28 · 📥 25 · 📋 47 - 12% open · ⏱️ 21.08.2022): ``` - git clone https://github.com/bambinos/bambi + git clone https://github.com/maximtrp/scikit-posthocs ``` -- [PyPi](https://pypi.org/project/bambi): +- [PyPi](https://pypi.org/project/scikit-posthocs) (📥 40K / month): ``` - pip install bambi + pip install scikit-posthocs ```
-
Funsor (🥉17 · ⭐ 180) - 用于概率编程的函数张量。Apache-2 +
Funsor (🥉19 · ⭐ 200) - Functional tensors for probabilistic programming. Apache-2 -- [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 9 · 🔀 14 · 📦 20 · 📋 140 - 47% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 10 · 🔀 17 · 📦 32 · 📋 140 - 47% open · ⏱️ 08.04.2022): ``` git clone https://github.com/pyro-ppl/funsor ``` -- [PyPi](https://pypi.org/project/funsor): +- [PyPi](https://pypi.org/project/funsor) (📥 1.2K / month): ``` pip install funsor ```
-
pyhsmm (🥉16 · ⭐ 500 · 💀) - HSMM和HMM中的贝叶斯推断。MIT +
Baal (🥉18 · ⭐ 630) - Using approximate bayesian posteriors in deep nets for active learning. Apache-2 -- [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 23 · 📋 95 - 36% open · ⏱️ 24.08.2020): +- [GitHub](https://github.com/baal-org/baal) (👨‍💻 16 · 🔀 60 · 📋 84 - 27% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/mattjj/pyhsmm + git clone https://github.com/ElementAI/baal ``` -- [PyPi](https://pypi.org/project/pyhsmm): +- [PyPi](https://pypi.org/project/baal) (📥 740 / month): ``` - pip install pyhsmm + pip install baal ```
-
PyStan (🥉15 · ⭐ 140) - PyStan是Stan的Python接口。ISC +
PyStan (🥉18 · ⭐ 200) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC -- [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 10 · 🔀 34 · 📋 160 - 3% open · ⏱️ 21.10.2021): +- [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 10 · 🔀 39 · 📋 180 - 2% open · ⏱️ 07.07.2022): ``` git clone https://github.com/stan-dev/pystan ``` -- [PyPi](https://pypi.org/project/pystan): +- [PyPi](https://pypi.org/project/pystan) (📥 2.8M / month): ``` pip install pystan ``` -- [Conda](https://anaconda.org/conda-forge/pystan) (📥 1.3M · ⏱️ 21.09.2021): +- [Conda](https://anaconda.org/conda-forge/pystan) (📥 1.6M · ⏱️ 25.07.2022): ``` conda install -c conda-forge pystan ```
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ZhuSuan (🥉14 · ⭐ 2.1K · 💀) - TensorFlow中的一种概率编程语言。MIT +
pyhsmm (🥉17 · ⭐ 520 · 💀) - Bayesian inference in HSMMs and HMMs. MIT + +- [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 25 · 📋 96 - 37% open · ⏱️ 24.08.2020): + + ``` + git clone https://github.com/mattjj/pyhsmm + ``` +- [PyPi](https://pypi.org/project/pyhsmm) (📥 85 / month): + ``` + pip install pyhsmm + ``` +
+
ZhuSuan (🥉14 · ⭐ 2.1K · 💀) - A probabilistic programming library for Bayesian deep learning,.. MIT - [GitHub](https://github.com/thu-ml/zhusuan) (👨‍💻 20 · 🔀 400 · 📋 60 - 11% open · ⏱️ 05.08.2019): @@ -9597,719 +9597,719 @@ _提供概率编程/推理，贝叶斯推理，高斯过程或统计信息的功

-## 对抗学习与鲁棒性 +## Adversarial Robustness -Back to top +Back to top -_用于测试机器学习模型抵抗攻击性/恶意示例的鲁棒性的库。_ +_Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples._ -
CleverHans (🥇25 · ⭐ 5.4K) - 一个用于构造攻击的对抗性示例库。MIT +
Foolbox (🥇27 · ⭐ 2.3K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT -- [GitHub](https://github.com/cleverhans-lab/cleverhans) (👨‍💻 130 · 🔀 1.3K · 📦 280 · 📋 440 - 4% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 400 · 📦 320 · 📋 350 - 5% open · ⏱️ 25.05.2022): ``` - git clone https://github.com/cleverhans-lab/cleverhans + git clone https://github.com/bethgelab/foolbox ``` -- [PyPi](https://pypi.org/project/cleverhans): +- [PyPi](https://pypi.org/project/foolbox) (📥 5.4K / month): ``` - pip install cleverhans + pip install foolbox ```
-
Foolbox (🥈23 · ⭐ 2.1K) - 一个Python工具箱，用于创建欺骗神经网络的对抗示例。MIT +
CleverHans (🥈26 · ⭐ 5.6K · 💤) - An adversarial example library for constructing attacks,.. MIT -- [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 360 · 📦 260 · 📋 330 - 18% open · ⏱️ 05.06.2021): +- [GitHub](https://github.com/cleverhans-lab/cleverhans) (👨‍💻 130 · 🔀 1.3K · 📦 350 · 📋 450 - 5% open · ⏱️ 23.09.2021): ``` - git clone https://github.com/bethgelab/foolbox + git clone https://github.com/cleverhans-lab/cleverhans ``` -- [PyPi](https://pypi.org/project/foolbox): +- [PyPi](https://pypi.org/project/cleverhans) (📥 1.3K / month): ``` - pip install foolbox + pip install cleverhans ```
-
TextAttack (🥈23 · ⭐ 1.8K) - TextAttack是用于对抗攻击，数据的Python框架。MIT +
TextAttack (🥈26 · ⭐ 2.1K) - TextAttack is a Python framework for adversarial attacks, data.. MIT -- [GitHub](https://github.com/QData/TextAttack) (👨‍💻 46 · 🔀 210 · 📦 48 · 📋 170 - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/QData/TextAttack) (👨‍💻 53 · 🔀 250 · 📦 93 · 📋 220 - 9% open · ⏱️ 14.08.2022): ``` git clone https://github.com/QData/TextAttack ``` -- [PyPi](https://pypi.org/project/textattack): +- [PyPi](https://pypi.org/project/textattack) (📥 6.6K / month): ``` pip install textattack ```
-
ART (🥉20 · ⭐ 2.6K) - 对抗性鲁棒性工具箱（ART）- 用于机器学习的Python库。MIT +
ART (🥉24 · ⭐ 3.2K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT -- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (👨‍💻 87 · 🔀 730 · 📦 170 · 📋 610 - 11% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (👨‍💻 110 · 🔀 850 · 📦 250 · 📋 710 - 12% open · ⏱️ 25.08.2022): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` -- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox): +- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (📥 5.6K / month): ``` pip install adversarial-robustness-toolbox ```
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robustness (🥉18 · ⭐ 640) - 一个用于实验，训练和评估神经网络的库。MIT +
advertorch (🥉18 · ⭐ 1.1K) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 -- [GitHub](https://github.com/MadryLab/robustness) (👨‍💻 13 · 🔀 120 · 📦 67 · 📋 67 - 19% open · ⏱️ 30.11.2021): +- [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 21 · 🔀 170 · 📦 85 · 📋 52 - 34% open · ⏱️ 29.05.2022): ``` - git clone https://github.com/MadryLab/robustness + git clone https://github.com/BorealisAI/advertorch ``` -- [PyPi](https://pypi.org/project/robustness) (📥 880 / month): +- [PyPi](https://pypi.org/project/advertorch) (📥 340 / month): ``` - pip install robustness + pip install advertorch ```
-
advertorch (🥉16 · ⭐ 980) - 对抗性鲁棒性研究的工具箱。❗️GPL-3.0 +
robustness (🥉17 · ⭐ 720) - A library for experimenting with, training and evaluating neural.. MIT -- [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 18 · 🔀 160 · 📦 57 · 📋 48 - 31% open · ⏱️ 30.07.2021): +- [GitHub](https://github.com/MadryLab/robustness) (👨‍💻 13 · 🔀 140 · 📦 81 · 📋 75 - 25% open · ⏱️ 14.02.2022): ``` - git clone https://github.com/BorealisAI/advertorch + git clone https://github.com/MadryLab/robustness ``` -- [PyPi](https://pypi.org/project/advertorch): +- [PyPi](https://pypi.org/project/robustness) (📥 640 / month): ``` - pip install advertorch + pip install robustness ```
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AdvBox (🥉14 · ⭐ 1.2K · 💤) - Advbox是一个工具箱，用于生成对抗示例。Apache-2 +
AdvBox (🥉15 · ⭐ 1.2K) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 -- [GitHub](https://github.com/advboxes/AdvBox) (👨‍💻 19 · 🔀 240 · 📋 35 - 17% open · ⏱️ 03.05.2021): +- [GitHub](https://github.com/advboxes/AdvBox) (👨‍💻 19 · 🔀 240 · 📋 38 - 21% open · ⏱️ 08.08.2022): ``` git clone https://github.com/advboxes/AdvBox ``` -- [PyPi](https://pypi.org/project/advbox): +- [PyPi](https://pypi.org/project/advbox) (📥 17 / month): ``` pip install advbox ```

-## GPU实用程序 +## GPU Utilities -Back to top +Back to top -_需要并利用CUDA / GPU系统功能来优化数据处理和机器学习任务的库。_ +_Libraries that require and make use of CUDA/GPU system capabilities to optimize data handling and machine learning tasks._ -
CuPy (🥇32 · ⭐ 5.6K) - CUDA加速了与NumPy兼容的数组库。MIT +
CuPy (🥇32 · ⭐ 6.3K) - A NumPy-compatible array library accelerated by CUDA. MIT -- [GitHub](https://github.com/cupy/cupy) (👨‍💻 290 · 🔀 510 · 📥 23K · 📦 890 · 📋 1.6K - 19% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/cupy/cupy) (👨‍💻 310 · 🔀 590 · 📥 42K · 📦 1.2K · 📋 1.8K - 21% open · ⏱️ 23.08.2022): ``` git clone https://github.com/cupy/cupy ``` -- [PyPi](https://pypi.org/project/cupy) (📥 110K / month): +- [PyPi](https://pypi.org/project/cupy) (📥 20K / month): ``` pip install cupy ``` -- [Conda](https://anaconda.org/conda-forge/cupy) (📥 1.1M · ⏱️ 15.12.2021): +- [Conda](https://anaconda.org/conda-forge/cupy) (📥 1.8M · ⏱️ 29.07.2022): ``` conda install -c conda-forge cupy ``` -- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (📥 53K · ⭐ 7 · ⏱️ 09.12.2021): +- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (📥 55K · ⭐ 8 · ⏱️ 28.07.2022): ``` docker pull cupy/cupy ```
-
gpustat (🥇27 · ⭐ 2.7K) - 一个简单的命令行实用程序，用于查询和监控GPU状态。MIT +
gpustat (🥇28 · ⭐ 3K) - A simple command-line utility for querying and monitoring GPU status. MIT -- [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 12 · 🔀 210 · 📦 1.5K · 📋 75 - 25% open · ⏱️ 13.08.2021): +- [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 14 · 🔀 220 · 📦 2.1K · 📋 86 - 22% open · ⏱️ 09.08.2022): ``` git clone https://github.com/wookayin/gpustat ``` -- [PyPi](https://pypi.org/project/gpustat) (📥 400K / month): +- [PyPi](https://pypi.org/project/gpustat) (📥 820K / month): ``` pip install gpustat ``` -- [Conda](https://anaconda.org/conda-forge/gpustat) (📥 100K · ⏱️ 24.11.2020): +- [Conda](https://anaconda.org/conda-forge/gpustat) (📥 140K · ⏱️ 24.11.2020): ``` conda install -c conda-forge gpustat ```
-
Apex (🥈23 · ⭐ 6K) - PyTorch扩展：易于实现混合精度和分布式的工具。BSD-3 +
ArrayFire (🥈25 · ⭐ 3.9K) - ArrayFire: a general purpose GPU library. BSD-3 -- [GitHub](https://github.com/NVIDIA/apex) (👨‍💻 88 · 🔀 850 · 📦 830 · 📋 900 - 56% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 81 · 🔀 490 · 📥 2.7K · 📋 1.5K - 16% open · ⏱️ 09.07.2022): ``` - git clone https://github.com/NVIDIA/apex + git clone https://github.com/arrayfire/arrayfire ``` -- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (📥 71K · ⏱️ 22.04.2021): +- [PyPi](https://pypi.org/project/arrayfire) (📥 130K / month): ``` - conda install -c conda-forge nvidia-apex + pip install arrayfire ```
-
GPUtil (🥈23 · ⭐ 800 · 💀) - 一个Python模块，用于从NVIDA GPU获取GPU状态。MIT +
GPUtil (🥈25 · ⭐ 900 · 💀) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT -- [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 85 · 📦 1.6K · 📋 25 - 44% open · ⏱️ 16.08.2019): +- [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 98 · 📦 2.3K · 📋 26 - 46% open · ⏱️ 16.08.2019): ``` git clone https://github.com/anderskm/gputil ``` -- [PyPi](https://pypi.org/project/gputil) (📥 430K / month): +- [PyPi](https://pypi.org/project/gputil) (📥 480K / month): ``` pip install gputil ```
-
py3nvml (🥈20 · ⭐ 200) - NVML库的Python3接口。在内部获取NVIDIA GPU状态。BSD-3 +
Apex (🥈24 · ⭐ 6.6K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 -- [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 8 · 🔀 28 · 📦 360 · 📋 12 - 16% open · ⏱️ 06.09.2021): +- [GitHub](https://github.com/NVIDIA/apex) (👨‍💻 100 · 🔀 1K · 📦 1.2K · 📋 1K - 53% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/fbcotter/py3nvml - ``` -- [PyPi](https://pypi.org/project/py3nvml): - ``` - pip install py3nvml + git clone https://github.com/NVIDIA/apex ``` -- [Conda](https://anaconda.org/conda-forge/py3nvml) (📥 24K · ⏱️ 19.11.2021): +- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (📥 100K · ⏱️ 06.04.2022): ``` - conda install -c conda-forge py3nvml + conda install -c conda-forge nvidia-apex ```
-
cuDF (🥈19 · ⭐ 4.4K) - cuDF-GPU DataFrame库。Apache-2 +
py3nvml (🥈23 · ⭐ 210) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 -- [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 230 · 🔀 570 · 📋 4.2K - 14% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 9 · 🔀 30 · 📦 510 · 📋 13 - 7% open · ⏱️ 14.04.2022): ``` - git clone https://github.com/rapidsai/cudf + git clone https://github.com/fbcotter/py3nvml ``` -- [PyPi](https://pypi.org/project/cudf) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/py3nvml) (📥 110K / month): ``` - pip install cudf + pip install py3nvml + ``` +- [Conda](https://anaconda.org/conda-forge/py3nvml) (📥 31K · ⏱️ 20.06.2022): + ``` + conda install -c conda-forge py3nvml ```
-
ArrayFire (🥈19 · ⭐ 3.7K) - ArrayFire：通用GPU库。❗Unlicensed +
PyCUDA (🥈22 · ⭐ 1.4K) - CUDA integration for Python, plus shiny features. ❗Unlicensed -- [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 81 · 🔀 480 · 📥 1.7K · 📋 1.5K - 15% open · ⏱️ 15.10.2021): +- [GitHub](https://github.com/inducer/pycuda) (👨‍💻 76 · 🔀 250 · 📦 1.5K · 📋 220 - 27% open · ⏱️ 16.08.2022): ``` - git clone https://github.com/arrayfire/arrayfire + git clone https://github.com/inducer/pycuda ``` -- [PyPi](https://pypi.org/project/arrayfire) (📥 520 / month): +- [PyPi](https://pypi.org/project/pycuda) (📥 35K / month): ``` - pip install arrayfire + pip install pycuda ```
-
cuML (🥉18 · ⭐ 2.5K) - cuML-RAPIDS机器学习库。Apache-2 +
cuDF (🥉20 · ⭐ 4.9K) - cuDF - GPU DataFrame Library. Apache-2 -- [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 140 · 🔀 370 · 📋 1.9K - 32% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 250 · 🔀 630 · 📋 4.8K - 12% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/rapidsai/cuml + git clone https://github.com/rapidsai/cudf ``` -- [PyPi](https://pypi.org/project/cuml) (📥 750 / month): +- [PyPi](https://pypi.org/project/cudf) (📥 1.8K / month): ``` - pip install cuml + pip install cudf ```
-
DALI (🥉17 · ⭐ 3.6K) - GPU加速的库，其中包含高度优化的构建块。Apache-2 +
scikit-cuda (🥉20 · ⭐ 910) - Python interface to GPU-powered libraries. ❗Unlicensed -- [GitHub](https://github.com/NVIDIA/DALI) (👨‍💻 67 · 🔀 450 · 📋 1.1K - 13% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 46 · 🔀 170 · 📦 200 · 📋 220 - 22% open · ⏱️ 31.03.2022): ``` - git clone https://github.com/NVIDIA/DALI + git clone https://github.com/lebedov/scikit-cuda + ``` +- [PyPi](https://pypi.org/project/scikit-cuda) (📥 490 / month): + ``` + pip install scikit-cuda ```
-
BlazingSQL (🥉17 · ⭐ 1.6K) - BlazingSQL是一种用于GPU的轻量级，GPU加速的引擎。Apache-2 +
cuML (🥉19 · ⭐ 2.9K) - cuML - RAPIDS Machine Learning Library. Apache-2 -- [GitHub](https://github.com/BlazingDB/blazingsql) (👨‍💻 47 · 🔀 160 · 📋 710 - 17% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 160 · 🔀 420 · 📋 2.1K - 32% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/BlazingDB/blazingsql + git clone https://github.com/rapidsai/cuml ``` -- [Conda](https://anaconda.org/blazingsql/blazingsql-protocol) (📥 940 · ⏱️ 11.11.2019): +- [PyPi](https://pypi.org/project/cuml) (📥 940 / month): ``` - conda install -c blazingsql blazingsql-protocol + pip install cuml ```
-
PyCUDA (🥉17 · ⭐ 1.2K) - 适用于Python的CUDA集成，有着出色的功能。❗Unlicensed +
Vulkan Kompute (🥉18 · ⭐ 920) - General purpose GPU compute framework for cross vendor.. Apache-2 -- [GitHub](https://github.com/inducer/pycuda) (👨‍💻 74 · 🔀 240 · 📦 1.1K · 📋 210 - 26% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 19 · 🔀 64 · 📥 170 · 📦 4 · 📋 180 - 32% open · ⏱️ 21.06.2022): ``` - git clone https://github.com/inducer/pycuda + git clone https://github.com/EthicalML/vulkan-kompute ``` -- [PyPi](https://pypi.org/project/pycuda): +- [PyPi](https://pypi.org/project/kp) (📥 87 / month): ``` - pip install pycuda + pip install kp ```
-
cuGraph (🥉17 · ⭐ 870) - cuGraph-RAPIDS图形分析库。Apache-2 +
DALI (🥉17 · ⭐ 4K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 -- [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 70 · 🔀 170 · 📋 730 - 8% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/NVIDIA/DALI) (👨‍💻 77 · 🔀 500 · 📋 1.2K - 15% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/rapidsai/cugraph - ``` -- [PyPi](https://pypi.org/project/cugraph) (📥 200 / month): - ``` - pip install cugraph + git clone https://github.com/NVIDIA/DALI ```
-
scikit-cuda (🥉17 · ⭐ 870) - GPU工具库的python接口。❗Unlicensed +
nvidia-ml-py3 (🥉17 · ⭐ 86 · 💀) - Python 3 Bindings for the NVIDIA Management Library. ❗Unlicensed -- [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 45 · 🔀 170 · 📦 150 · 📋 220 - 23% open · ⏱️ 13.07.2021): +- [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 18 · 📦 6.2K · ⏱️ 06.03.2019): ``` - git clone https://github.com/lebedov/scikit-cuda + git clone https://github.com/nicolargo/nvidia-ml-py3 ``` -- [PyPi](https://pypi.org/project/scikit-cuda): +- [PyPi](https://pypi.org/project/nvidia-ml-py3) (📥 970K / month): ``` - pip install scikit-cuda + pip install nvidia-ml-py3 ```
-
Vulkan Kompute (🥉17 · ⭐ 620) - 适用于跨供应商的通用GPU计算框架。Apache-2 +
cuGraph (🥉16 · ⭐ 1.1K) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 -- [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 16 · 🔀 49 · 📥 100 · 📦 2 · 📋 160 - 32% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 90 · 🔀 210 · 📋 990 - 20% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/EthicalML/vulkan-kompute + git clone https://github.com/rapidsai/cugraph ``` -- [PyPi](https://pypi.org/project/kp) (📥 96 / month): +- [PyPi](https://pypi.org/project/cugraph) (📥 100 / month): ``` - pip install kp + pip install cugraph ```
-
cuSignal (🥉14 · ⭐ 550) - GPU加速信号处理。Apache-2 +
BlazingSQL (🥉15 · ⭐ 1.8K · 💤) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 -- [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 36 · 🔀 80 · 📋 120 - 9% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/BlazingDB/blazingsql) (👨‍💻 49 · 🔀 170 · 📋 710 - 17% open · ⏱️ 30.09.2021): ``` - git clone https://github.com/rapidsai/cusignal + git clone https://github.com/BlazingDB/blazingsql + ``` +- [Conda](https://anaconda.org/blazingsql/blazingsql-protocol) (📥 950 · ⏱️ 11.11.2019): + ``` + conda install -c blazingsql blazingsql-protocol ```
-
SpeedTorch (🥉13 · ⭐ 640 · 💀) - 用于更快的Pytorch中CPU-GPU传输的工具库。MIT +
SpeedTorch (🥉14 · ⭐ 660 · 💀) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT -- [GitHub](https://github.com/Santosh-Gupta/SpeedTorch) (👨‍💻 3 · 🔀 39 · 📦 3 · 📋 6 - 66% open · ⏱️ 21.02.2020): +- [GitHub](https://github.com/Santosh-Gupta/SpeedTorch) (👨‍💻 3 · 🔀 39 · 📦 4 · 📋 6 - 66% open · ⏱️ 21.02.2020): ``` git clone https://github.com/Santosh-Gupta/SpeedTorch ``` -- [PyPi](https://pypi.org/project/SpeedTorch): +- [PyPi](https://pypi.org/project/SpeedTorch) (📥 22 / month): ``` pip install SpeedTorch ```
-
nvidia-ml-py3 (🥉11 · ⭐ 71 · 💀) - NVIDIA Management Library的Python3接口。❗Unlicensed +
cuSignal (🥉14 · ⭐ 610) - GPU accelerated signal processing. Apache-2 -- [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 15 · 📦 4.6K · ⏱️ 06.03.2019): +- [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 39 · 🔀 96 · 📋 140 - 11% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/nicolargo/nvidia-ml-py3 - ``` -- [PyPi](https://pypi.org/project/nvidia-ml-py3): - ``` - pip install nvidia-ml-py3 + git clone https://github.com/rapidsai/cusignal ```
-
ipyexperiments (🥉10 · ⭐ 140) - jupyter/ipython实验容器。❗Unlicensed +
ipyexperiments (🥉11 · ⭐ 150 · 💤) - jupyter/ipython experiment containers for GPU and.. ❗Unlicensed -- [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 10 · 📦 5 · ⏱️ 07.12.2021): +- [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 11 · 📦 6 · ⏱️ 07.12.2021): ``` git clone https://github.com/stas00/ipyexperiments ``` -- [PyPi](https://pypi.org/project/ipyexperiments): +- [PyPi](https://pypi.org/project/ipyexperiments) (📥 100 / month): ``` pip install ipyexperiments ```

-## Tensorflow实用程序 +## Tensorflow Utilities -Back to top +Back to top -_TensorFlow的拓展工具库。_ +_Libraries that extend TensorFlow with additional capabilities._ -
tensorflow-hub (🥇28 · ⭐ 3K) - 通过重用部分库来进行迁移学习的库。Apache-2 +
TF Addons (🥇33 · ⭐ 1.6K) - Useful extra functionality for TensorFlow 2.x maintained by.. Apache-2 -- [GitHub](https://github.com/tensorflow/hub) (👨‍💻 83 · 🔀 1.6K · 📦 9.5K · 📋 630 - 2% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/tensorflow/addons) (👨‍💻 200 · 🔀 530 · 📦 7.2K · 📋 920 - 21% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/tensorflow/hub - ``` -- [PyPi](https://pypi.org/project/tensorflow-hub): - ``` - pip install tensorflow-hub + git clone https://github.com/tensorflow/addons ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (📥 59K · ⏱️ 18.04.2021): +- [PyPi](https://pypi.org/project/tensorflow-addons) (📥 2.2M / month): ``` - conda install -c conda-forge tensorflow-hub + pip install tensorflow-addons ```
-
tensor2tensor (🥇27 · ⭐ 12K) - 设计深度学习模型和数据集的库。Apache-2 +
tensor2tensor (🥇31 · ⭐ 13K) - Library of deep learning models and datasets designed to.. Apache-2 -- [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 2.9K · 📦 1.1K · 📋 1.2K - 45% open · ⏱️ 02.12.2021): +- [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 3K · 📦 1.2K · 📋 1.2K - 45% open · ⏱️ 09.08.2022): ``` git clone https://github.com/tensorflow/tensor2tensor ``` -- [PyPi](https://pypi.org/project/tensor2tensor): +- [PyPi](https://pypi.org/project/tensor2tensor) (📥 8.9K / month): ``` pip install tensor2tensor ```
-
TF Addons (🥇27 · ⭐ 1.4K · 📉) - 由TensorFlow 2.x维护的有用额外功能。Apache-2 +
tensorflow-hub (🥇31 · ⭐ 3.2K) - A library for transfer learning by reusing parts of.. Apache-2 -- [GitHub](https://github.com/tensorflow/addons) (👨‍💻 180 · 🔀 480 · 📦 4.9K · 📋 860 - 19% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/tensorflow/hub) (👨‍💻 94 · 🔀 1.6K · 📦 13K · 📋 650 - 2% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/tensorflow/addons + git clone https://github.com/tensorflow/hub ``` -- [PyPi](https://pypi.org/project/tensorflow-addons): +- [PyPi](https://pypi.org/project/tensorflow-hub) (📥 3.3M / month): ``` - pip install tensorflow-addons + pip install tensorflow-hub + ``` +- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (📥 67K · ⏱️ 18.04.2021): + ``` + conda install -c conda-forge tensorflow-hub ```
-
TF Model Optimization (🥈24 · ⭐ 1.2K) - 用于优化ML模型以进行部署的工具包。Apache-2 +
TensorFlow Transform (🥈30 · ⭐ 930 · 📈) - Input pipeline framework. Apache-2 -- [GitHub](https://github.com/tensorflow/model-optimization) (👨‍💻 64 · 🔀 250 · 📦 1.4K · 📋 260 - 45% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 190 · 📦 1K · 📋 190 - 17% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/tensorflow/model-optimization + git clone https://github.com/tensorflow/transform ``` -- [PyPi](https://pypi.org/project/tensorflow-model-optimization): +- [PyPi](https://pypi.org/project/tensorflow-transform) (📥 3.3M / month): ``` - pip install tensorflow-model-optimization + pip install tensorflow-transform ```
-
efficientnet (🥈22 · ⭐ 1.9K) - EfficientNet模型的实现。Apache-2 +
TF Model Optimization (🥈29 · ⭐ 1.3K) - A toolkit to optimize ML models for deployment for.. Apache-2 -- [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 430 · 📥 200K · 📦 830 · 📋 110 - 48% open · ⏱️ 16.07.2021): +- [GitHub](https://github.com/tensorflow/model-optimization) (👨‍💻 71 · 🔀 280 · 📦 2K · 📋 300 - 48% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/qubvel/efficientnet + git clone https://github.com/tensorflow/model-optimization ``` -- [PyPi](https://pypi.org/project/efficientnet): +- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (📥 140K / month): ``` - pip install efficientnet + pip install tensorflow-model-optimization ```
-
TensorFlow Transform (🥈22 · ⭐ 900 · 📉) - 输入管道框架。Apache-2 +
Neural Structured Learning (🥉26 · ⭐ 930) - Training neural models with structured signals. Apache-2 -- [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 180 · 📦 640 · 📋 170 - 11% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 34 · 🔀 170 · 📦 260 · 📋 65 - 3% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/tensorflow/transform + git clone https://github.com/tensorflow/neural-structured-learning ``` -- [PyPi](https://pypi.org/project/tensorflow-transform): +- [PyPi](https://pypi.org/project/neural-structured-learning) (📥 16K / month): ``` - pip install tensorflow-transform + pip install neural-structured-learning ```
-
Neural Structured Learning (🥉20 · ⭐ 890) - 用结构化信号训练神经模型。Apache-2 +
TensorFlow I/O (🥉25 · ⭐ 570) - Dataset, streaming, and file system extensions.. Apache-2 -- [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 30 · 🔀 160 · 📦 150 · 📋 59 - 3% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/tensorflow/io) (👨‍💻 94 · 🔀 210 · 📋 530 - 36% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/tensorflow/neural-structured-learning + git clone https://github.com/tensorflow/io ``` -- [PyPi](https://pypi.org/project/neural-structured-learning): +- [PyPi](https://pypi.org/project/tensorflow-io) (📥 440K / month): ``` - pip install neural-structured-learning + pip install tensorflow-io ```
-
TensorFlow I/O (🥉19 · ⭐ 520) - Dataset, streaming, and file system extensions.. Apache-2 +
efficientnet (🥉24 · ⭐ 2K · 💀) - Implementation of EfficientNet model. Keras and.. Apache-2 -- [GitHub](https://github.com/tensorflow/io) (👨‍💻 83 · 🔀 200 · 📋 480 - 31% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 450 · 📥 240K · 📦 1.1K · 📋 110 - 48% open · ⏱️ 16.07.2021): ``` - git clone https://github.com/tensorflow/io + git clone https://github.com/qubvel/efficientnet ``` -- [PyPi](https://pypi.org/project/tensorflow-io): +- [PyPi](https://pypi.org/project/efficientnet) (📥 53K / month): ``` - pip install tensorflow-io + pip install efficientnet ```
-
TensorFlow Cloud (🥉19 · ⭐ 320) - TensorFlow Cloud存储库提供的API。Apache-2 +
TensorFlow Cloud (🥉23 · ⭐ 330) - The TensorFlow Cloud repository provides APIs that.. Apache-2 -- [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 25 · 🔀 64 · 📦 120 · 📋 80 - 67% open · ⏱️ 07.09.2021): +- [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 27 · 🔀 71 · 📦 170 · 📋 82 - 68% open · ⏱️ 24.03.2022): ``` git clone https://github.com/tensorflow/cloud ``` -- [PyPi](https://pypi.org/project/tensorflow-cloud): +- [PyPi](https://pypi.org/project/tensorflow-cloud) (📥 150K / month): ``` pip install tensorflow-cloud ```
-
TensorNets (🥉17 · ⭐ 1K · 💤) - 具有预先训练的权重的高级网络定义。MIT +
TensorNets (🥉20 · ⭐ 1K · 💀) - High level network definitions with pre-trained weights in.. MIT -- [GitHub](https://github.com/taehoonlee/tensornets) (👨‍💻 6 · 🔀 190 · 📦 42 · 📋 58 - 27% open · ⏱️ 02.01.2021): +- [GitHub](https://github.com/taehoonlee/tensornets) (👨‍💻 6 · 🔀 180 · 📦 52 · 📋 58 - 27% open · ⏱️ 02.01.2021): ``` git clone https://github.com/taehoonlee/tensornets ``` -- [PyPi](https://pypi.org/project/tensornets): +- [PyPi](https://pypi.org/project/tensornets) (📥 150 / month): ``` pip install tensornets ```
-
TF Compression (🥉15 · ⭐ 550) - TensorFlow中的数据压缩。Apache-2 +
TF Compression (🥉19 · ⭐ 640) - Data compression in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/compression) (👨‍💻 10 · 🔀 200 · 📋 76 - 3% open · ⏱️ 26.10.2021): +- [GitHub](https://github.com/tensorflow/compression) (👨‍💻 16 · 🔀 210 · 📋 87 - 2% open · ⏱️ 25.08.2022): ``` git clone https://github.com/tensorflow/compression ``` -- [PyPi](https://pypi.org/project/tensorflow-compression): +- [PyPi](https://pypi.org/project/tensorflow-compression) (📥 1K / month): ``` pip install tensorflow-compression ```
-
tffm (🥉14 · ⭐ 770 · 💀) - 任意阶乘分解机的TensorFlow实现。MIT +
Saliency (🥉17 · ⭐ 810) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 -- [GitHub](https://github.com/geffy/tffm) (👨‍💻 10 · 🔀 180 · 📦 11 · 📋 39 - 43% open · ⏱️ 22.05.2020): +- [GitHub](https://github.com/PAIR-code/saliency) (👨‍💻 15 · 🔀 170 · 📦 41 · ⏱️ 13.05.2022): ``` - git clone https://github.com/geffy/tffm + git clone https://github.com/PAIR-code/saliency ``` -- [PyPi](https://pypi.org/project/tffm): +- [PyPi](https://pypi.org/project/saliency) (📥 1.3K / month): ``` - pip install tffm + pip install saliency ```
-
Saliency (🥉14 · ⭐ 750) - 与框架无关的实现，可实现最新的显着性。Apache-2 +
tffm (🥉17 · ⭐ 780 · 💤) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT -- [GitHub](https://github.com/PAIR-code/saliency) (👨‍💻 14 · 🔀 160 · 📦 19 · ⏱️ 28.07.2021): +- [GitHub](https://github.com/geffy/tffm) (👨‍💻 10 · 🔀 180 · 📦 11 · 📋 40 - 45% open · ⏱️ 17.01.2022): ``` - git clone https://github.com/PAIR-code/saliency + git clone https://github.com/geffy/tffm ``` -- [PyPi](https://pypi.org/project/saliency): +- [PyPi](https://pypi.org/project/tffm) (📥 1.5K / month): ``` - pip install saliency + pip install tffm ```

-## Sklearn实用程序 +## Sklearn Utilities -Back to top +Back to top -_scikit-learn的拓展工具库。_ +_Libraries that extend scikit-learn with additional capabilities._ -
imbalanced-learn (🥇31 · ⭐ 5.6K) - 一个解决不平衡类别数据建模的Python程序包。MIT +
imbalanced-learn (🥇32 · ⭐ 6K) - A Python Package to Tackle the Curse of Imbalanced.. MIT -- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (👨‍💻 61 · 🔀 1.1K · 📦 8.4K · 📋 480 - 8% open · ⏱️ 07.12.2021): +- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (👨‍💻 63 · 🔀 1.1K · 📦 12K · 📋 510 - 8% open · ⏱️ 16.05.2022): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` -- [PyPi](https://pypi.org/project/imbalanced-learn) (📥 2.8M / month): +- [PyPi](https://pypi.org/project/imbalanced-learn) (📥 3.2M / month): ``` pip install imbalanced-learn ``` -- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (📥 170K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (📥 250K · ⏱️ 16.05.2022): ``` conda install -c conda-forge imbalanced-learn ```
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category_encoders (🥇30 · ⭐ 1.8K · 📈) - A library of sklearn compatible categorical variable.. BSD-3 +
MLxtend (🥇30 · ⭐ 4.1K) - A library of extension and helper modules for Python's data.. ❗Unlicensed -- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (👨‍💻 48 · 🔀 330 · 📦 2.8K · 📋 220 - 28% open · ⏱️ 16.11.2021): +- [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 90 · 🔀 760 · 📦 6.6K · 📋 420 - 25% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/scikit-learn-contrib/category_encoders + git clone https://github.com/rasbt/mlxtend ``` -- [PyPi](https://pypi.org/project/category_encoders) (📥 980K / month): +- [PyPi](https://pypi.org/project/mlxtend) (📥 1.4M / month): ``` - pip install category_encoders + pip install mlxtend ``` -- [Conda](https://anaconda.org/conda-forge/category_encoders) (📥 130K · ⏱️ 13.10.2021): +- [Conda](https://anaconda.org/conda-forge/mlxtend) (📥 220K · ⏱️ 27.05.2022): ``` - conda install -c conda-forge category_encoders + conda install -c conda-forge mlxtend ```
-
MLxtend (🥈27 · ⭐ 3.7K) - 用于Python数据的扩展和帮助程序模块库。❗Unlicensed +
category_encoders (🥇30 · ⭐ 2K) - A library of sklearn compatible categorical variable.. BSD-3 -- [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 85 · 🔀 720 · 📦 4.8K · 📋 390 - 23% open · ⏱️ 29.11.2021): +- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (👨‍💻 52 · 🔀 360 · 📦 3.8K · 📋 250 - 25% open · ⏱️ 02.06.2022): ``` - git clone https://github.com/rasbt/mlxtend + git clone https://github.com/scikit-learn-contrib/category_encoders ``` -- [PyPi](https://pypi.org/project/mlxtend): +- [PyPi](https://pypi.org/project/category_encoders) (📥 950K / month): ``` - pip install mlxtend + pip install category_encoders ``` -- [Conda](https://anaconda.org/conda-forge/mlxtend) (📥 190K · ⏱️ 03.09.2021): +- [Conda](https://anaconda.org/conda-forge/category_encoders) (📥 180K · ⏱️ 02.06.2022): ``` - conda install -c conda-forge mlxtend + conda install -c conda-forge category_encoders ```
-
sklearn-contrib-lightning (🥈21 · ⭐ 1.5K) - 大规模线性分类，回归分析等。❗Unlicensed +
fancyimpute (🥈25 · ⭐ 1.1K · 💤) - Multivariate imputation and matrix completion.. Apache-2 -- [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 170 · 📥 100 · 📦 96 · 📋 85 - 52% open · ⏱️ 15.06.2021): +- [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 12 · 🔀 160 · 📦 1.2K · 📋 110 - 1% open · ⏱️ 21.10.2021): ``` - git clone https://github.com/scikit-learn-contrib/lightning - ``` -- [PyPi](https://pypi.org/project/sklearn-contrib-lightning): - ``` - pip install sklearn-contrib-lightning + git clone https://github.com/iskandr/fancyimpute ``` -- [Conda](https://anaconda.org/conda-forge/sklearn-contrib-lightning) (📥 160K · ⏱️ 13.11.2021): +- [PyPi](https://pypi.org/project/fancyimpute) (📥 16K / month): ``` - conda install -c conda-forge sklearn-contrib-lightning + pip install fancyimpute ```
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fancyimpute (🥈21 · ⭐ 1K) - 多元插补和矩阵补全算法。Apache-2 +
scikit-multilearn (🥈24 · ⭐ 770) - A scikit-learn based module for multi-label et. al... BSD-2 -- [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 12 · 🔀 160 · 📦 1.1K · 📋 110 - 0% open · ⏱️ 21.10.2021): +- [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 17 · 🔀 140 · 📦 820 · 📋 180 - 46% open · ⏱️ 09.07.2022): ``` - git clone https://github.com/iskandr/fancyimpute + git clone https://github.com/scikit-multilearn/scikit-multilearn ``` -- [PyPi](https://pypi.org/project/fancyimpute): +- [PyPi](https://pypi.org/project/scikit-multilearn) (📥 87K / month): ``` - pip install fancyimpute + pip install scikit-multilearn ```
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scikit-opt (🥈20 · ⭐ 2.8K) - 遗传算法，粒子群优化等实现。MIT +
scikit-opt (🥈23 · ⭐ 3.5K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT -- [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 13 · 🔀 660 · 📦 55 · 📋 130 - 22% open · ⏱️ 04.12.2021): +- [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 16 · 🔀 800 · 📦 83 · 📋 150 - 30% open · ⏱️ 15.07.2022): ``` git clone https://github.com/guofei9987/scikit-opt ``` -- [PyPi](https://pypi.org/project/scikit-opt): +- [PyPi](https://pypi.org/project/scikit-opt) (📥 1.6K / month): ``` pip install scikit-opt ```
-
scikit-lego (🥈19 · ⭐ 670) - scikit学习管道的额外块。MIT +
scikit-lego (🥈22 · ⭐ 880) - Extra blocks for scikit-learn pipelines. MIT -- [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 48 · 🔀 75 · 📦 39 · 📋 230 - 13% open · ⏱️ 09.12.2021): +- [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 52 · 🔀 90 · 📦 59 · 📋 240 - 9% open · ⏱️ 18.08.2022): ``` git clone https://github.com/koaning/scikit-lego ``` -- [PyPi](https://pypi.org/project/scikit-lego): +- [PyPi](https://pypi.org/project/scikit-lego) (📥 23K / month): ``` pip install scikit-lego ``` -- [Conda](https://anaconda.org/conda-forge/scikit-lego) (📥 16K · ⏱️ 09.12.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-lego) (📥 23K · ⏱️ 06.06.2022): ``` conda install -c conda-forge scikit-lego ```
-
scikit-multilearn (🥉18 · ⭐ 710 · 💀) - 基于scikit-learn的多标签等模块。BSD-2 +
iterative-stratification (🥈22 · ⭐ 710) - scikit-learn cross validators for iterative.. BSD-3 -- [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 15 · 🔀 130 · 📦 610 · 📋 170 - 43% open · ⏱️ 21.05.2019): +- [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 7 · 🔀 64 · 📦 220 · 📋 20 - 5% open · ⏱️ 06.06.2022): ``` - git clone https://github.com/scikit-multilearn/scikit-multilearn + git clone https://github.com/trent-b/iterative-stratification ``` -- [PyPi](https://pypi.org/project/scikit-multilearn): +- [PyPi](https://pypi.org/project/iterative-stratification) (📥 35K / month): ``` - pip install scikit-multilearn + pip install iterative-stratification ```
-
iterative-stratification (🥉18 · ⭐ 610) - scikit-learn交叉验证器。BSD-3 +
sklearn-crfsuite (🥈22 · ⭐ 410 · 💀) - scikit-learn inspired API for CRFsuite. ❗Unlicensed -- [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 6 · 🔀 56 · 📦 180 · 📋 19 - 21% open · ⏱️ 11.11.2021): +- [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 190 · 📦 4K · 📋 56 - 58% open · ⏱️ 05.12.2019): ``` - git clone https://github.com/trent-b/iterative-stratification + git clone https://github.com/TeamHG-Memex/sklearn-crfsuite ``` -- [PyPi](https://pypi.org/project/iterative-stratification): +- [PyPi](https://pypi.org/project/sklearn-crfsuite) (📥 200K / month): ``` - pip install iterative-stratification + pip install sklearn-crfsuite ```
-
combo (🥉17 · ⭐ 560) - （AAAI'20）用于机器学习模型的Python工具箱。BSD-2 xgboost +
combo (🥉20 · ⭐ 590) - (AAAI' 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost -- [GitHub](https://github.com/yzhao062/combo) (🔀 93 · 📦 440 · 📋 12 - 75% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/yzhao062/combo) (👨‍💻 2 · 🔀 100 · 📦 480 · 📋 13 - 76% open · ⏱️ 07.07.2022): ``` git clone https://github.com/yzhao062/combo ``` -- [PyPi](https://pypi.org/project/combo): +- [PyPi](https://pypi.org/project/combo) (📥 35K / month): ``` pip install combo ```
-
sklearn-crfsuite (🥉16 · ⭐ 380 · 💀) - 用于CRFsuite的scikit-learn启发式API。❗Unlicensed +
skope-rules (🥉20 · ⭐ 480 · 💀) - machine learning with logical rules in Python. ❗Unlicensed -- [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 180 · 📦 3.3K · 📋 53 - 56% open · ⏱️ 05.12.2019): +- [GitHub](https://github.com/scikit-learn-contrib/skope-rules) (👨‍💻 18 · 🔀 79 · 📦 130 · 📋 31 - 80% open · ⏱️ 23.10.2020): ``` - git clone https://github.com/TeamHG-Memex/sklearn-crfsuite + git clone https://github.com/scikit-learn-contrib/skope-rules ``` -- [PyPi](https://pypi.org/project/sklearn-crfsuite): +- [PyPi](https://pypi.org/project/skope-rules) (📥 96K / month): ``` - pip install sklearn-crfsuite + pip install skope-rules ```
-
skggm (🥉16 · ⭐ 190 · 💤) - 通用图形模型的Scikit学习兼容估计。MIT +
sklearn-contrib-lightning (🥉19 · ⭐ 1.6K · 💤) - Large-scale linear classification, regression and.. ❗Unlicensed -- [GitHub](https://github.com/skggm/skggm) (👨‍💻 5 · 🔀 34 · 📦 8 · 📋 75 - 37% open · ⏱️ 24.12.2020): +- [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 180 · 📥 230 · 📦 100 · 📋 88 - 52% open · ⏱️ 30.01.2022): ``` - git clone https://github.com/skggm/skggm + git clone https://github.com/scikit-learn-contrib/lightning ``` -- [PyPi](https://pypi.org/project/skggm): +- [PyPi](https://pypi.org/project/sklearn-contrib-lightning) (📥 1.7K / month): ``` - pip install skggm + pip install sklearn-contrib-lightning + ``` +- [Conda](https://anaconda.org/conda-forge/sklearn-contrib-lightning) (📥 170K · ⏱️ 13.11.2021): + ``` + conda install -c conda-forge sklearn-contrib-lightning ```
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DESlib (🥉15 · ⭐ 370) - 一个用于动态分类器和集成选择的Python库。BSD-3 +
DESlib (🥉17 · ⭐ 420) - A Python library for dynamic classifier and ensemble selection. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (👨‍💻 13 · 🔀 56 · 📦 22 · 📋 140 - 8% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (👨‍💻 14 · 🔀 63 · 📦 29 · 📋 150 - 10% open · ⏱️ 07.06.2022): ``` git clone https://github.com/scikit-learn-contrib/DESlib ``` -- [PyPi](https://pypi.org/project/deslib): +- [PyPi](https://pypi.org/project/deslib) (📥 340 / month): ``` pip install deslib ```
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scikit-tda (🥉15 · ⭐ 320) - Python的拓扑数据分析。❗Unlicensed +
celer (🥉17 · ⭐ 160) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 -- [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 3 · 🔀 38 · 📦 24 · 📋 16 - 75% open · ⏱️ 03.08.2021): +- [GitHub](https://github.com/mathurinm/celer) (👨‍💻 11 · 🔀 25 · 📦 13 · 📋 90 - 20% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/scikit-tda/scikit-tda + git clone https://github.com/mathurinm/celer ``` -- [PyPi](https://pypi.org/project/scikit-tda): +- [PyPi](https://pypi.org/project/celer) (📥 620 / month): ``` - pip install scikit-tda + pip install celer ```
-
skope-rules (🥉14 · ⭐ 420 · 💀) - 使用Python中的逻辑规则进行机器学习。❗Unlicensed +
scikit-tda (🥉16 · ⭐ 360) - Topological Data Analysis for Python. ❗Unlicensed -- [GitHub](https://github.com/scikit-learn-contrib/skope-rules) (👨‍💻 18 · 🔀 69 · 📦 58 · 📋 27 - 81% open · ⏱️ 23.10.2020): +- [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 4 · 🔀 44 · 📦 33 · 📋 19 - 78% open · ⏱️ 13.03.2022): ``` - git clone https://github.com/scikit-learn-contrib/skope-rules + git clone https://github.com/scikit-tda/scikit-tda ``` -- [PyPi](https://pypi.org/project/skope-rules): +- [PyPi](https://pypi.org/project/scikit-tda) (📥 1.6K / month): ``` - pip install skope-rules + pip install scikit-tda ```
-
celer (🥉14 · ⭐ 130) - L1型问题的快速求解器：Lasso，稀疏Logisitic回归等BSD-3 +
skggm (🥉16 · ⭐ 210) - Scikit-learn compatible estimation of general graphical models. MIT -- [GitHub](https://github.com/mathurinm/celer) (👨‍💻 9 · 🔀 23 · 📦 10 · 📋 69 - 20% open · ⏱️ 10.12.2021): +- [GitHub](https://github.com/skggm/skggm) (👨‍💻 6 · 🔀 36 · 📦 8 · 📋 75 - 37% open · ⏱️ 11.03.2022): ``` - git clone https://github.com/mathurinm/celer + git clone https://github.com/skggm/skggm ``` -- [PyPi](https://pypi.org/project/celer): +- [PyPi](https://pypi.org/project/skggm) (📥 61 / month): ``` - pip install celer + pip install skggm ```
-
dabl (🥉12 · ⭐ 110) - 数据分析基准库。BSD-3 +
dabl (🥉13 · ⭐ 120 · 💀) - Data Analysis Baseline Library. BSD-3 -- [GitHub](https://github.com/amueller/dabl) (👨‍💻 21 · 🔀 9 · ⏱️ 09.07.2021): +- [GitHub](https://github.com/amueller/dabl) (👨‍💻 21 · 🔀 10 · ⏱️ 09.07.2021): ``` git clone https://github.com/amueller/dabl @@ -10321,368 +10321,368 @@ _scikit-learn的拓展工具库。_

-## Pytorch实用程序 +## Pytorch Utilities -Back to top +Back to top -_Pytorch的拓展工具库。_ +_Libraries that extend Pytorch with additional capabilities._ -
PML (🥇27 · ⭐ 3.9K) - 在应用程序中使用深度度量学习的最简单方法。MIT +
PML (🥇28 · ⭐ 4.7K) - The easiest way to use deep metric learning in your application. Modular,.. MIT -- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 21 · 🔀 480 · 📦 180 · 📋 310 - 12% open · ⏱️ 08.12.2021): +- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 27 · 🔀 560 · 📦 320 · 📋 380 - 13% open · ⏱️ 13.08.2022): ``` git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` -- [PyPi](https://pypi.org/project/pytorch-metric-learning) (📥 150K / month): +- [PyPi](https://pypi.org/project/pytorch-metric-learning) (📥 90K / month): ``` pip install pytorch-metric-learning ``` -- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (📥 5.1K · ⏱️ 28.11.2021): +- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (📥 8K · ⏱️ 03.08.2022): ``` conda install -c metric-learning pytorch-metric-learning ```
-
pytorch-summary (🥇24 · ⭐ 3.3K · 💤) - PyTorch中的模型摘要类似于`model.summary（）`。MIT +
pretrainedmodels (🥇27 · ⭐ 8.6K · 💀) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 -- [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 370 · 📦 3.9K · 📋 130 - 70% open · ⏱️ 10.05.2021): +- [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.8K · 📦 1.8K · 📋 180 - 46% open · ⏱️ 16.04.2020): ``` - git clone https://github.com/sksq96/pytorch-summary + git clone https://github.com/Cadene/pretrained-models.pytorch ``` -- [PyPi](https://pypi.org/project/torchsummary) (📥 84K / month): +- [PyPi](https://pypi.org/project/pretrainedmodels) (📥 170K / month): ``` - pip install torchsummary + pip install pretrainedmodels ```
-
pytorch-optimizer (🥇23 · ⭐ 2.2K) - torch-optimizer - pytorch的优化器集合。Apache-2 +
pytorch-optimizer (🥇26 · ⭐ 2.5K · 💤) - torch-optimizer -- collection of optimizers for.. Apache-2 -- [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 25 · 🔀 210 · 📦 410 · 📋 43 - 34% open · ⏱️ 11.11.2021): +- [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 25 · 🔀 240 · 📦 670 · 📋 50 - 42% open · ⏱️ 11.11.2021): ``` git clone https://github.com/jettify/pytorch-optimizer ``` -- [PyPi](https://pypi.org/project/torch_optimizer): +- [PyPi](https://pypi.org/project/torch_optimizer) (📥 48K / month): ``` pip install torch_optimizer ```
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pretrainedmodels (🥈22 · ⭐ 8.3K · 💀) - pytorch预训练的ConvNets：NASNet，ResNeXt等BSD-3 +
pytorch-summary (🥈25 · ⭐ 3.6K · 💀) - Model summary in PyTorch similar to `model.summary()`.. MIT -- [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.7K · 📦 1.3K · 📋 170 - 46% open · ⏱️ 16.04.2020): +- [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 400 · 📦 5.7K · 📋 140 - 69% open · ⏱️ 10.05.2021): ``` - git clone https://github.com/Cadene/pretrained-models.pytorch + git clone https://github.com/sksq96/pytorch-summary ``` -- [PyPi](https://pypi.org/project/pretrainedmodels): +- [PyPi](https://pypi.org/project/torchsummary) (📥 100K / month): ``` - pip install pretrainedmodels + pip install torchsummary ```
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EfficientNet-PyTorch (🥈22 · ⭐ 6.7K · 💤) - EfficientNet等模型的PyTorch实现Apache-2 +
torchdiffeq (🥈24 · ⭐ 4.2K) - Differentiable ODE solvers with full GPU support and.. MIT -- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.3K · 📥 1M · 📋 260 - 49% open · ⏱️ 15.04.2021): +- [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 21 · 🔀 720 · 📦 300 · 📋 180 - 21% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/lukemelas/EfficientNet-PyTorch + git clone https://github.com/rtqichen/torchdiffeq ``` -- [PyPi](https://pypi.org/project/efficientnet-pytorch) (📥 240K / month): +- [PyPi](https://pypi.org/project/torchdiffeq) (📥 25K / month): ``` - pip install efficientnet-pytorch + pip install torchdiffeq ```
-
SRU (🥈22 · ⭐ 2K · 💤) - 与CNN一样快地训练RNN（https://arxiv.org/abs/1709.02755）。MIT +
SRU (🥈22 · ⭐ 2.1K · 💀) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT -- [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 290 · 📦 17 · 📋 120 - 44% open · ⏱️ 19.05.2021): +- [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 300 · 📦 18 · 📋 130 - 46% open · ⏱️ 19.05.2021): ``` git clone https://github.com/asappresearch/sru ``` -- [PyPi](https://pypi.org/project/sru) (📥 3K / month): +- [PyPi](https://pypi.org/project/sru) (📥 2.7K / month): ``` pip install sru ```
-
reformer-pytorch (🥈22 · ⭐ 1.6K) - Reformer，Pytorch中高效的transformer实现。MIT +
EfficientNet-PyTorch (🥈21 · ⭐ 7.1K · 💀) - A PyTorch implementation of EfficientNet and.. Apache-2 -- [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 10 · 🔀 220 · 📋 120 - 10% open · ⏱️ 06.11.2021): +- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.4K · 📥 1.9M · 📋 280 - 50% open · ⏱️ 15.04.2021): ``` - git clone https://github.com/lucidrains/reformer-pytorch + git clone https://github.com/lukemelas/EfficientNet-PyTorch ``` -- [PyPi](https://pypi.org/project/reformer-pytorch) (📥 16K / month): +- [PyPi](https://pypi.org/project/efficientnet-pytorch) (📥 100K / month): ``` - pip install reformer-pytorch + pip install efficientnet-pytorch ```
-
torchdiffeq (🥈21 · ⭐ 3.8K) - 具有完整GPU支持的可微分ODE求解器。MIT +
TabNet (🥈21 · ⭐ 1.8K) - PyTorch implementation of TabNet paper :.. MIT -- [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 20 · 🔀 660 · 📦 180 · 📋 160 - 17% open · ⏱️ 22.09.2021): +- [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 19 · 🔀 370 · 📋 230 - 7% open · ⏱️ 27.06.2022): ``` - git clone https://github.com/rtqichen/torchdiffeq + git clone https://github.com/dreamquark-ai/tabnet ``` -- [PyPi](https://pypi.org/project/torchdiffeq) (📥 8.2K / month): +- [PyPi](https://pypi.org/project/pytorch-tabnet) (📥 20K / month): ``` - pip install torchdiffeq + pip install pytorch-tabnet ```
-
Torchmeta (🥈21 · ⭐ 1.5K) - 少量学习的扩展程序和数据加载器的集合。MIT +
EfficientNets (🥈21 · ⭐ 1.5K · 💀) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 -- [GitHub](https://github.com/tristandeleu/pytorch-meta) (👨‍💻 12 · 🔀 180 · 📦 78 · 📋 120 - 26% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 200 · 📦 120 · 📋 54 - 5% open · ⏱️ 08.07.2021): ``` - git clone https://github.com/tristandeleu/pytorch-meta + git clone https://github.com/rwightman/gen-efficientnet-pytorch ``` -- [PyPi](https://pypi.org/project/torchmeta) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/geffnet) (📥 15K / month): ``` - pip install torchmeta + pip install geffnet ```
-
TabNet (🥈21 · ⭐ 1.5K) - Efficient Neural Architecture Search的Pytorch实现。MIT +
Pytorch Toolbelt (🥈21 · ⭐ 1.3K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT -- [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 18 · 🔀 290 · 📋 180 - 8% open · ⏱️ 12.11.2021): +- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 7 · 🔀 100 · 📋 24 - 8% open · ⏱️ 20.08.2022): ``` - git clone https://github.com/dreamquark-ai/tabnet + git clone https://github.com/BloodAxe/pytorch-toolbelt ``` -- [PyPi](https://pypi.org/project/pytorch-tabnet) (📥 33K / month): +- [PyPi](https://pypi.org/project/pytorch_toolbelt) (📥 15K / month): ``` - pip install pytorch-tabnet + pip install pytorch_toolbelt ```
-
Pytorch Toolbelt (🥈21 · ⭐ 1.2K) - PyTorch扩展用于快速研发原型和Kaggle实验。MIT +
PyTorch Sparse (🥈21 · ⭐ 710) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT -- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 6 · 🔀 85 · 📋 22 - 18% open · ⏱️ 06.12.2021): +- [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 32 · 🔀 100 · 📋 200 - 13% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/BloodAxe/pytorch-toolbelt + git clone https://github.com/rusty1s/pytorch_sparse ``` -- [PyPi](https://pypi.org/project/pytorch_toolbelt) (📥 14K / month): +- [PyPi](https://pypi.org/project/torch-sparse) (📥 27K / month): ``` - pip install pytorch_toolbelt + pip install torch-sparse ```
-
torch-scatter (🥉20 · ⭐ 840) - 优化图聚类的PyTorch扩展库MIT +
reformer-pytorch (🥉20 · ⭐ 1.8K) - Reformer, the efficient Transformer, in Pytorch. MIT -- [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 18 · 🔀 86 · 📋 230 - 8% open · ⏱️ 13.11.2021): +- [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 11 · 🔀 240 · 📋 120 - 11% open · ⏱️ 24.06.2022): ``` - git clone https://github.com/rusty1s/pytorch_scatter + git clone https://github.com/lucidrains/reformer-pytorch ``` -- [PyPi](https://pypi.org/project/torch-scatter) (📥 32K / month): +- [PyPi](https://pypi.org/project/reformer-pytorch) (📥 1.9K / month): ``` - pip install torch-scatter + pip install reformer-pytorch ```
-
PyTorch Sparse (🥉20 · ⭐ 540) - 优化图聚类的PyTorch扩展库MIT +
Torchmeta (🥉20 · ⭐ 1.7K · 💤) - A collection of extensions and data-loaders for few-shot.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 17 · 🔀 68 · 📋 150 - 16% open · ⏱️ 13.11.2021): +- [GitHub](https://github.com/tristandeleu/pytorch-meta) (👨‍💻 12 · 🔀 220 · 📦 97 · 📋 130 - 32% open · ⏱️ 20.09.2021): ``` - git clone https://github.com/rusty1s/pytorch_sparse + git clone https://github.com/tristandeleu/pytorch-meta ``` -- [PyPi](https://pypi.org/project/torch-sparse) (📥 20K / month): +- [PyPi](https://pypi.org/project/torchmeta) (📥 1.4K / month): ``` - pip install torch-sparse + pip install torchmeta ```
-
Poutyne (🥉20 · ⭐ 510) - PyTorch的简化框架和实用程序。❗️LGPL-3.0 +
torch-scatter (🥉20 · ⭐ 1.1K) - PyTorch Extension Library of Optimized Scatter Operations. MIT -- [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 16 · 🔀 56 · 📦 73 · 📋 44 - 13% open · ⏱️ 09.11.2021): +- [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 22 · 🔀 120 · 📋 270 - 6% open · ⏱️ 18.08.2022): ``` - git clone https://github.com/GRAAL-Research/poutyne + git clone https://github.com/rusty1s/pytorch_scatter ``` -- [PyPi](https://pypi.org/project/poutyne) (📥 5.8K / month): +- [PyPi](https://pypi.org/project/torch-scatter) (📥 30K / month): ``` - pip install poutyne + pip install torch-scatter ```
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Antialiased CNNs (🥉19 · ⭐ 1.5K) - pip安装antialiased-cnns以提高稳定性等。❗️CC BY-NC-SA 4.0 +
Performer Pytorch (🥉20 · ⭐ 860) - An implementation of Performer, a linear attention-.. MIT -- [GitHub](https://github.com/adobe/antialiased-cnns) (👨‍💻 6 · 🔀 180 · 📦 12 · 📋 41 - 24% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 6 · 🔀 120 · 📦 49 · 📋 78 - 44% open · ⏱️ 02.02.2022): ``` - git clone https://github.com/adobe/antialiased-cnns + git clone https://github.com/lucidrains/performer-pytorch ``` -- [PyPi](https://pypi.org/project/antialiased-cnns) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/performer-pytorch) (📥 75K / month): ``` - pip install antialiased-cnns + pip install performer-pytorch ```
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EfficientNets (🥉19 · ⭐ 1.4K) - 预训练的EfficientNet，EfficientNet-Lite，MixNet等Apache-2 +
Poutyne (🥉20 · ⭐ 530) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 -- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 190 · 📦 87 · 📋 51 - 3% open · ⏱️ 08.07.2021): +- [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 18 · 🔀 62 · 📦 91 · 📋 53 - 15% open · ⏱️ 16.07.2022): ``` - git clone https://github.com/rwightman/gen-efficientnet-pytorch + git clone https://github.com/GRAAL-Research/poutyne ``` -- [PyPi](https://pypi.org/project/geffnet) (📥 7.2K / month): +- [PyPi](https://pypi.org/project/poutyne) (📥 5.3K / month): ``` - pip install geffnet + pip install poutyne ```
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Higher (🥉19 · ⭐ 1.3K) - Higher是一个pytorch库，允许用户在跨训练循环而不是单个训练步骤的损失上获得更高阶的梯度。Apache-2 +
AdaBound (🥉19 · ⭐ 2.9K · 💀) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 -- [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 95 · 📦 100 · 📋 95 - 47% open · ⏱️ 26.10.2021): +- [GitHub](https://github.com/Luolc/AdaBound) (👨‍💻 2 · 🔀 320 · 📦 140 · 📋 25 - 72% open · ⏱️ 06.03.2019): ``` - git clone https://github.com/facebookresearch/higher + git clone https://github.com/Luolc/AdaBound ``` -- [PyPi](https://pypi.org/project/higher) (📥 33K / month): +- [PyPi](https://pypi.org/project/adabound) (📥 1.4K / month): ``` - pip install higher + pip install adabound ```
-
Performer Pytorch (🥉19 · ⭐ 760) - Performer的实现。MIT +
Antialiased CNNs (🥉19 · ⭐ 1.6K · 💤) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 -- [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 6 · 🔀 99 · 📦 34 · 📋 68 - 39% open · ⏱️ 07.11.2021): +- [GitHub](https://github.com/adobe/antialiased-cnns) (👨‍💻 6 · 🔀 200 · 📦 29 · 📋 44 - 29% open · ⏱️ 29.09.2021): ``` - git clone https://github.com/lucidrains/performer-pytorch + git clone https://github.com/adobe/antialiased-cnns ``` -- [PyPi](https://pypi.org/project/performer-pytorch) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/antialiased-cnns) (📥 1.5K / month): ``` - pip install performer-pytorch + pip install antialiased-cnns ```
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Tez (🥉18 · ⭐ 730) - Tez是用于PyTorch的超级简单且轻巧的Trainer。Apache-2 +
Higher (🥉19 · ⭐ 1.4K · 💤) - higher is a pytorch library allowing users to obtain higher.. Apache-2 -- [GitHub](https://github.com/abhishekkrthakur/tez) (🔀 110 · 📦 17 · 📋 26 - 61% open · ⏱️ 27.09.2021): +- [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 100 · 📦 160 · 📋 100 - 50% open · ⏱️ 26.10.2021): ``` - git clone https://github.com/abhishekkrthakur/tez + git clone https://github.com/facebookresearch/higher ``` -- [PyPi](https://pypi.org/project/tez) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/higher) (📥 110K / month): ``` - pip install tez + pip install higher ```
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Pywick (🥉18 · ⭐ 360) - 更高层次的pytorch神经网络训练库。❗Unlicensed +
tinygrad (🥉17 · ⭐ 6.5K) - You like pytorch? You like micrograd? You love tinygrad!. MIT -- [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 38 · 📦 5 · 📋 13 - 7% open · ⏱️ 22.10.2021): +- [GitHub](https://github.com/geohot/tinygrad) (👨‍💻 62 · 🔀 650 · 📦 3 · 📋 110 - 14% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/achaiah/pywick - ``` -- [PyPi](https://pypi.org/project/pywick) (📥 5.1K / month): - ``` - pip install pywick + git clone https://github.com/geohot/tinygrad ```
-
tinygrad (🥉16 · ⭐ 5.1K) - You like pytorch? You like micrograd? You love tinygrad!. MIT +
Tensor Sensor (🥉17 · ⭐ 650) - The goal of this library is to generate more helpful.. MIT -- [GitHub](https://github.com/geohot/tinygrad) (👨‍💻 52 · 🔀 570 · 📦 1 · 📋 86 - 3% open · ⏱️ 12.12.2021): +- [GitHub](https://github.com/parrt/tensor-sensor) (👨‍💻 4 · 🔀 34 · 📦 7 · 📋 23 - 34% open · ⏱️ 07.04.2022): ``` - git clone https://github.com/geohot/tinygrad + git clone https://github.com/parrt/tensor-sensor + ``` +- [PyPi](https://pypi.org/project/tensor-sensor) (📥 1.8K / month): + ``` + pip install tensor-sensor ```
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AdaBound (🥉16 · ⭐ 2.9K · 💀) - 训练速度与Adam一样快且与SGD一样好的优化器。Apache-2 +
micrograd (🥉16 · ⭐ 2.4K · 💀) - A tiny scalar-valued autograd engine and a neural net library.. MIT -- [GitHub](https://github.com/Luolc/AdaBound) (👨‍💻 2 · 🔀 320 · 📦 120 · 📋 24 - 70% open · ⏱️ 06.03.2019): +- [GitHub](https://github.com/karpathy/micrograd) (👨‍💻 2 · 🔀 210 · 📦 7 · 📋 5 - 40% open · ⏱️ 18.04.2020): ``` - git clone https://github.com/Luolc/AdaBound + git clone https://github.com/karpathy/micrograd ``` -- [PyPi](https://pypi.org/project/adabound): +- [PyPi](https://pypi.org/project/micrograd) (📥 360 / month): ``` - pip install adabound + pip install micrograd ```
-
Lambda Networks (🥉16 · ⭐ 1.5K · 💀) - LambdaNetworks的实现。MIT +
Lambda Networks (🥉16 · ⭐ 1.5K · 💀) - Implementation of LambdaNetworks, a new approach to.. MIT -- [GitHub](https://github.com/lucidrains/lambda-networks) (👨‍💻 3 · 🔀 150 · 📦 3 · 📋 27 - 44% open · ⏱️ 18.11.2020): +- [GitHub](https://github.com/lucidrains/lambda-networks) (👨‍💻 3 · 🔀 160 · 📦 6 · 📋 28 - 46% open · ⏱️ 18.11.2020): ``` git clone https://github.com/lucidrains/lambda-networks ``` -- [PyPi](https://pypi.org/project/lambda-networks) (📥 85 / month): +- [PyPi](https://pypi.org/project/lambda-networks) (📥 45 / month): ``` pip install lambda-networks ```
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Tensor Sensor (🥉16 · ⭐ 620) - 该库的目标是为numpy/pytorch矩阵代数表达式生成更有用的异常消息。MIT +
Tez (🥉16 · ⭐ 1.1K) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 -- [GitHub](https://github.com/parrt/tensor-sensor) (👨‍💻 3 · 🔀 31 · 📦 7 · 📋 23 - 34% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/abhishekkrthakur/tez) (👨‍💻 2 · 🔀 140 · 📦 33 · 📋 37 - 54% open · ⏱️ 10.08.2022): ``` - git clone https://github.com/parrt/tensor-sensor + git clone https://github.com/abhishekkrthakur/tez ``` -- [PyPi](https://pypi.org/project/tensor-sensor): +- [PyPi](https://pypi.org/project/tez) (📥 1.8K / month): ``` - pip install tensor-sensor + pip install tez ```
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torchsde (🥉15 · ⭐ 880) - 具有GPU支持且高效的可微分SDE求解器。Apache-2 +
torchsde (🥉16 · ⭐ 1K · 💀) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 -- [GitHub](https://github.com/google-research/torchsde) (👨‍💻 5 · 🔀 96 · 📦 9 · 📋 41 - 17% open · ⏱️ 26.07.2021): +- [GitHub](https://github.com/google-research/torchsde) (👨‍💻 5 · 🔀 110 · 📦 19 · 📋 50 - 18% open · ⏱️ 26.07.2021): ``` git clone https://github.com/google-research/torchsde ```
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Torch-Struct (🥉14 · ⭐ 1K) - 快速，通用和经过测试的微分结构化预测。MIT +
Pywick (🥉14 · ⭐ 370 · 💤) - High-level batteries-included neural network training.. ❗Unlicensed -- [GitHub](https://github.com/harvardnlp/pytorch-struct) (👨‍💻 13 · 🔀 76 · 📋 49 - 42% open · ⏱️ 04.11.2021): +- [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 39 · 📦 7 · 📋 14 - 7% open · ⏱️ 22.10.2021): ``` - git clone https://github.com/harvardnlp/pytorch-struct + git clone https://github.com/achaiah/pywick + ``` +- [PyPi](https://pypi.org/project/pywick) (📥 36 / month): + ``` + pip install pywick ```
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micrograd (🥉12 · ⭐ 1.8K · 💀) - 一个微型的标量值autograd引擎和一个神经网络库。MIT +
Torch-Struct (🥉13 · ⭐ 1K · 💤) - Fast, general, and tested differentiable structured.. MIT -- [GitHub](https://github.com/karpathy/micrograd) (👨‍💻 2 · 🔀 140 · 📦 4 · 📋 5 - 40% open · ⏱️ 18.04.2020): +- [GitHub](https://github.com/harvardnlp/pytorch-struct) (👨‍💻 16 · 🔀 83 · 📋 54 - 44% open · ⏱️ 30.01.2022): ``` - git clone https://github.com/karpathy/micrograd - ``` -- [PyPi](https://pypi.org/project/micrograd): - ``` - pip install micrograd + git clone https://github.com/harvardnlp/pytorch-struct ```

-## 数据库客户端 +## Database Clients -Back to top +Back to top -_用于连接，操作和查询数据库的库。_ +_Libraries for connecting to, operating, and querying databases._ -🔗 Python DB Clients ( ⭐ 2) - Collection of database clients for python. +🔗 Python DB Clients ( ⭐ 7 · 💤) - Collection of database clients for python.
-## 中文自然语言处理 +## Chinese NLP -Back to top +Back to top -
jieba (🥇31 · ⭐ 28K · 💀) - Chinese Words Segementation Utilities. MIT +
jieba (🥇32 · ⭐ 29K · 💀) - Chinese Words Segementation Utilities. MIT -- [GitHub](https://github.com/fxsjy/jieba) (👨‍💻 48 · 🔀 6.2K · 📦 12K · 📋 790 - 73% open · ⏱️ 15.02.2020): +- [GitHub](https://github.com/fxsjy/jieba) (👨‍💻 48 · 🔀 6.3K · 📦 14K · 📋 810 - 73% open · ⏱️ 15.02.2020): ``` git clone https://github.com/fxsjy/jieba ``` -- [PyPi](https://pypi.org/project/jieba) (📥 450K / month): +- [PyPi](https://pypi.org/project/jieba) (📥 440K / month): ``` pip install jieba ``` -- [Conda](https://anaconda.org/conda-forge/jieba) (📥 100K · ⏱️ 30.05.2021): +- [Conda](https://anaconda.org/conda-forge/jieba) (📥 120K · ⏱️ 30.05.2021): ``` conda install -c conda-forge jieba ```
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snownlp (🥉22 · ⭐ 5.6K · 💀) - Python library for processing Chinese text. MIT +
snownlp (🥉22 · ⭐ 5.9K · 💀) - Python library for processing Chinese text. MIT -- [GitHub](https://github.com/isnowfy/snownlp) (👨‍💻 8 · 🔀 1.3K · 📦 750 · 📋 100 - 37% open · ⏱️ 19.01.2020): +- [GitHub](https://github.com/isnowfy/snownlp) (👨‍💻 8 · 🔀 1.3K · 📦 930 · 📋 100 - 38% open · ⏱️ 19.01.2020): ``` git clone https://github.com/isnowfy/snownlp ``` -- [PyPi](https://pypi.org/project/snownlp) (📥 8.8K / month): +- [PyPi](https://pypi.org/project/snownlp) (📥 3.6K / month): ``` pip install snownlp ``` @@ -10691,452 +10691,452 @@ _用于连接，操作和查询数据库的库。_ ## Others -Back to top +Back to top -
scipy (🥇39 · ⭐ 8.9K) - 用于数学，科学和工程的开源软件生态系统。BSD-3 +
scipy (🥇38 · ⭐ 10K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 -- [GitHub](https://github.com/scipy/scipy) (👨‍💻 1.2K · 🔀 3.9K · 📥 330K · 📦 440K · 📋 7.8K - 18% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/scipy/scipy) (👨‍💻 1.3K · 🔀 4.3K · 📥 350K · 📦 560K · 📋 8.4K - 16% open · ⏱️ 25.08.2022): ``` git clone https://github.com/scipy/scipy ``` -- [PyPi](https://pypi.org/project/scipy): +- [PyPi](https://pypi.org/project/scipy) (📥 43M / month): ``` pip install scipy ``` -- [Conda](https://anaconda.org/conda-forge/scipy) (📥 20M · ⏱️ 25.11.2021): +- [Conda](https://anaconda.org/conda-forge/scipy) (📥 26M · ⏱️ 30.07.2022): ``` conda install -c conda-forge scipy ```
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SymPy (🥇33 · ⭐ 8.7K) - 用纯Python编写的计算机代数系统。❗Unlicensed +
SymPy (🥇35 · ⭐ 9.5K) - A computer algebra system written in pure Python. ❗Unlicensed -- [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.1K · 🔀 3.5K · 📥 440K · 📦 38K · 📋 11K - 32% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.2K · 🔀 3.6K · 📥 460K · 📦 45K · 📋 12K - 32% open · ⏱️ 26.08.2022): ``` git clone https://github.com/sympy/sympy ``` -- [PyPi](https://pypi.org/project/sympy): +- [PyPi](https://pypi.org/project/sympy) (📥 2.6M / month): ``` pip install sympy ``` -- [Conda](https://anaconda.org/conda-forge/sympy) (📥 1.8M · ⏱️ 06.11.2021): +- [Conda](https://anaconda.org/conda-forge/sympy) (📥 2.3M · ⏱️ 23.08.2022): ``` conda install -c conda-forge sympy ```
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PyOD (🥇31 · ⭐ 5.1K) - （JMLR'19）用于可扩展离群值检测的Python工具箱。BSD-2 +
PyOD (🥇31 · ⭐ 6.1K) - (JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 -- [GitHub](https://github.com/yzhao062/pyod) (👨‍💻 31 · 🔀 990 · 📦 1K · 📋 220 - 48% open · ⏱️ 01.11.2021): +- [GitHub](https://github.com/yzhao062/pyod) (👨‍💻 41 · 🔀 1.1K · 📦 1.5K · 📋 260 - 47% open · ⏱️ 29.07.2022): ``` git clone https://github.com/yzhao062/pyod ``` -- [PyPi](https://pypi.org/project/pyod) (📥 540K / month): +- [PyPi](https://pypi.org/project/pyod) (📥 370K / month): ``` pip install pyod ```
-
DeepChem (🥇27 · ⭐ 3.3K) - 在药物发现，量子化学，材料科学和生物学方面普及深度学习。MIT +
Streamlit (🥇30 · ⭐ 20K · 📈) - Streamlit The fastest way to build data apps in Python. Apache-2 -- [GitHub](https://github.com/deepchem/deepchem) (👨‍💻 180 · 🔀 1.2K · 📦 65 · 📋 1.4K - 27% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 150 · 🔀 1.8K · 📦 380 · 📋 2.6K - 23% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/deepchem/deepchem + git clone https://github.com/streamlit/streamlit ``` -- [PyPi](https://pypi.org/project/deepchem) (📥 4K / month): +- [PyPi](https://pypi.org/project/streamlit) (📥 810K / month): ``` - pip install deepchem + pip install streamlit ```
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hdbscan (🥇27 · ⭐ 2K) - HDBSCAN群集的高性能实现。BSD-3 +
Gradio (🥇30 · ⭐ 8.5K) - Wrap UIs around any model, share with anyone. Apache-2 -- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 74 · 🔀 360 · 📦 1.1K · 📋 400 - 62% open · ⏱️ 24.11.2021): +- [GitHub](https://github.com/gradio-app/gradio) (👨‍💻 92 · 🔀 530 · 📦 1.1K · 📋 1K - 18% open · ⏱️ 25.08.2022): ``` - git clone https://github.com/scikit-learn-contrib/hdbscan - ``` -- [PyPi](https://pypi.org/project/hdbscan): - ``` - pip install hdbscan + git clone https://github.com/gradio-app/gradio ``` -- [Conda](https://anaconda.org/conda-forge/hdbscan) (📥 990K · ⏱️ 14.02.2021): +- [PyPi](https://pypi.org/project/gradio) (📥 150K / month): ``` - conda install -c conda-forge hdbscan + pip install gradio ```
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Cython BLIS (🥇27 · ⭐ 180) - 快速矩阵乘法库。❗Unlicensed +
Autograd (🥈29 · ⭐ 5.9K) - Efficiently computes derivatives of numpy code. MIT -- [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 10 · 🔀 29 · 📦 15K · 📋 27 - 18% open · ⏱️ 17.11.2021): +- [GitHub](https://github.com/HIPS/autograd) (👨‍💻 52 · 🔀 800 · 📦 3.8K · 📋 370 - 39% open · ⏱️ 15.06.2022): ``` - git clone https://github.com/explosion/cython-blis + git clone https://github.com/HIPS/autograd ``` -- [PyPi](https://pypi.org/project/blis) (📥 5.5M / month): +- [PyPi](https://pypi.org/project/autograd) (📥 1.2M / month): ``` - pip install blis + pip install autograd ``` -- [Conda](https://anaconda.org/conda-forge/cython-blis) (📥 1.2M · ⏱️ 04.11.2021): +- [Conda](https://anaconda.org/conda-forge/autograd) (📥 230K · ⏱️ 29.06.2022): ``` - conda install -c conda-forge cython-blis + conda install -c conda-forge autograd ```
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Pythran (🥈26 · ⭐ 1.7K) - 用于数字内核的时间编译器。BSD-3 +
Datasette (🥈28 · ⭐ 6.4K) - An open source multi-tool for exploring and publishing data. Apache-2 -- [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 64 · 🔀 160 · 📦 89 · 📋 730 - 13% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/simonw/datasette) (👨‍💻 67 · 🔀 410 · 📥 39 · 📦 730 · 📋 1.4K - 27% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/serge-sans-paille/pythran - ``` -- [PyPi](https://pypi.org/project/pythran) (📥 320K / month): - ``` - pip install pythran + git clone https://github.com/simonw/datasette ``` -- [Conda](https://anaconda.org/conda-forge/pythran) (📥 210K · ⏱️ 14.12.2021): +- [PyPi](https://pypi.org/project/datasette) (📥 240K / month): ``` - conda install -c conda-forge pythran + pip install datasette ```
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agate (🥈26 · ⭐ 1.1K) - 为人而不是为机器优化的Python数据分析库。MIT +
DeepChem (🥈28 · ⭐ 3.8K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT -- [GitHub](https://github.com/wireservice/agate) (👨‍💻 49 · 🔀 130 · 📦 690 · 📋 640 - 0% open · ⏱️ 15.07.2021): +- [GitHub](https://github.com/deepchem/deepchem) (👨‍💻 200 · 🔀 1.3K · 📦 120 · 📋 1.4K - 29% open · ⏱️ 26.08.2022): ``` - git clone https://github.com/wireservice/agate - ``` -- [PyPi](https://pypi.org/project/agate) (📥 930K / month): - ``` - pip install agate + git clone https://github.com/deepchem/deepchem ``` -- [Conda](https://anaconda.org/conda-forge/agate) (📥 74K · ⏱️ 16.07.2021): +- [PyPi](https://pypi.org/project/deepchem) (📥 8.9K / month): ``` - conda install -c conda-forge agate + pip install deepchem ```
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PaddleHub (🥈25 · ⭐ 7.3K) - 基于PaddlePaddle的出色的预训练模型工具包。Apache-2 +
hdbscan (🥈28 · ⭐ 2.2K) - A high performance implementation of HDBSCAN clustering. BSD-3 -- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 48 · 🔀 1.4K · 📥 560 · 📦 600 · 📋 970 - 36% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 80 · 🔀 390 · 📦 1.5K · 📋 440 - 63% open · ⏱️ 23.08.2022): ``` - git clone https://github.com/PaddlePaddle/PaddleHub + git clone https://github.com/scikit-learn-contrib/hdbscan ``` -- [PyPi](https://pypi.org/project/paddlehub) (📥 9.5K / month): +- [PyPi](https://pypi.org/project/hdbscan) (📥 450K / month): ``` - pip install paddlehub + pip install hdbscan + ``` +- [Conda](https://anaconda.org/conda-forge/hdbscan) (📥 1.2M · ⏱️ 11.02.2022): + ``` + conda install -c conda-forge hdbscan ```
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Autograd (🥈25 · ⭐ 5.6K · 💤) - 高效地计算导数的numpy代码。MIT +
agate (🥈28 · ⭐ 1.1K · 💀) - A Python data analysis library that is optimized for humans instead of.. MIT -- [GitHub](https://github.com/HIPS/autograd) (👨‍💻 51 · 🔀 770 · 📦 2.8K · 📋 360 - 39% open · ⏱️ 03.03.2021): +- [GitHub](https://github.com/wireservice/agate) (👨‍💻 49 · 🔀 140 · 📦 1.1K · 📋 640 - 1% open · ⏱️ 15.07.2021): ``` - git clone https://github.com/HIPS/autograd + git clone https://github.com/wireservice/agate ``` -- [PyPi](https://pypi.org/project/autograd): +- [PyPi](https://pypi.org/project/agate) (📥 1.6M / month): ``` - pip install autograd + pip install agate ``` -- [Conda](https://anaconda.org/conda-forge/autograd) (📥 200K · ⏱️ 25.07.2019): +- [Conda](https://anaconda.org/conda-forge/agate) (📥 91K · ⏱️ 16.07.2021): ``` - conda install -c conda-forge autograd + conda install -c conda-forge agate ```
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pyclustering (🥈25 · ⭐ 900 · 💤) - pyclustring是Python，C++数据挖掘库。BSD-3 +
Cython BLIS (🥈28 · ⭐ 190) - Fast matrix-multiplication as a self-contained Python.. ❗Unlicensed -- [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 210 · 📥 380 · 📦 260 · 📋 640 - 8% open · ⏱️ 12.02.2021): +- [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 12 · 🔀 34 · 📦 20K · 📋 28 - 17% open · ⏱️ 04.08.2022): ``` - git clone https://github.com/annoviko/pyclustering + git clone https://github.com/explosion/cython-blis ``` -- [PyPi](https://pypi.org/project/pyclustering) (📥 45K / month): +- [PyPi](https://pypi.org/project/blis) (📥 3.8M / month): ``` - pip install pyclustering + pip install blis ``` -- [Conda](https://anaconda.org/conda-forge/pyclustering) (📥 32K · ⏱️ 13.09.2021): +- [Conda](https://anaconda.org/conda-forge/cython-blis) (📥 1.6M · ⏱️ 05.08.2022): ``` - conda install -c conda-forge pyclustering + conda install -c conda-forge cython-blis ```
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pyjanitor (🥈25 · ⭐ 780) - 用于数据清理的API。MIT +
PaddleHub (🥈27 · ⭐ 8.3K) - Awesome pre-trained models toolkit based on.. Apache-2 -- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 95 · 🔀 130 · 📦 130 · 📋 420 - 20% open · ⏱️ 22.11.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 62 · 🔀 1.7K · 📥 580 · 📦 890 · 📋 1.1K - 41% open · ⏱️ 19.08.2022): ``` - git clone https://github.com/ericmjl/pyjanitor - ``` -- [PyPi](https://pypi.org/project/pyjanitor) (📥 13K / month): - ``` - pip install pyjanitor + git clone https://github.com/PaddlePaddle/PaddleHub ``` -- [Conda](https://anaconda.org/conda-forge/pyjanitor) (📥 110K · ⏱️ 22.11.2021): +- [PyPi](https://pypi.org/project/paddlehub) (📥 14K / month): ``` - conda install -c conda-forge pyjanitor + pip install paddlehub ```
-
carla (🥈24 · ⭐ 7K) - 用于自动驾驶研究的开源模拟器。MIT +
carla (🥈27 · ⭐ 8.2K · 💤) - Open-source simulator for autonomous driving research. ❗Unlicensed -- [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 140 · 🔀 2K · 📦 110 · 📋 3.6K - 12% open · ⏱️ 19.11.2021): +- [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 140 · 🔀 2.4K · 📦 230 · 📋 4K - 16% open · ⏱️ 19.11.2021): ``` git clone https://github.com/carla-simulator/carla ``` -- [PyPi](https://pypi.org/project/carla): +- [PyPi](https://pypi.org/project/carla) (📥 26K / month): ``` pip install carla ```
-
Datasette (🥈24 · ⭐ 5.6K) - 用于探索和发布数据的开源多功能工具。Apache-2 +
Pythran (🥈27 · ⭐ 1.8K) - Ahead of Time compiler for numeric kernels. BSD-3 -- [GitHub](https://github.com/simonw/datasette) (👨‍💻 60 · 🔀 360 · 📥 34 · 📦 560 · 📋 1.2K - 26% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 66 · 🔀 170 · 📦 220 · 📋 760 - 14% open · ⏱️ 19.07.2022): ``` - git clone https://github.com/simonw/datasette - ``` -- [PyPi](https://pypi.org/project/datasette): - ``` - pip install datasette + git clone https://github.com/serge-sans-paille/pythran ``` -
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Gradio (🥈24 · ⭐ 4.3K) - 对任何模型做UI封装并与他人共享。Apache-2 - -- [GitHub](https://github.com/gradio-app/gradio) (👨‍💻 36 · 🔀 260 · 📦 450 · 📋 230 - 14% open · ⏱️ 15.12.2021): - +- [PyPi](https://pypi.org/project/pythran) (📥 370K / month): ``` - git clone https://github.com/gradio-app/gradio + pip install pythran ``` -- [PyPi](https://pypi.org/project/gradio): +- [Conda](https://anaconda.org/conda-forge/pythran) (📥 260K · ⏱️ 31.07.2022): ``` - pip install gradio + conda install -c conda-forge pythran ```
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causalml (🥉23 · ⭐ 2.5K) - 利用机器学习提升建模和因果推理。❗Unlicensed +
pyjanitor (🥈27 · ⭐ 960) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT -- [GitHub](https://github.com/uber/causalml) (👨‍💻 31 · 🔀 380 · 📦 33 · 📋 230 - 16% open · ⏱️ 14.12.2021): +- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 100 · 🔀 150 · 📦 220 · 📋 490 - 20% open · ⏱️ 24.08.2022): ``` - git clone https://github.com/uber/causalml - ``` -- [PyPi](https://pypi.org/project/causalml) (📥 41K / month): - ``` - pip install causalml + git clone https://github.com/ericmjl/pyjanitor ``` -
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PySwarms (🥉23 · ⭐ 870) - 用于Python中粒子群优化的研究工具包。MIT - -- [GitHub](https://github.com/ljvmiranda921/pyswarms) (👨‍💻 43 · 🔀 280 · 📦 150 · 📋 200 - 8% open · ⏱️ 23.06.2021): - +- [PyPi](https://pypi.org/project/pyjanitor) (📥 29K / month): ``` - git clone https://github.com/ljvmiranda921/pyswarms + pip install pyjanitor ``` -- [PyPi](https://pypi.org/project/pyswarms) (📥 39K / month): +- [Conda](https://anaconda.org/conda-forge/pyjanitor) (📥 130K · ⏱️ 22.11.2021): ``` - pip install pyswarms + conda install -c conda-forge pyjanitor ```
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Streamlit (🥉22 · ⭐ 17K) - Streamlit用Python构建数据应用程序的最快方法。Apache-2 +
metric-learn (🥉26 · ⭐ 1.3K) - Metric learning algorithms in Python. MIT -- [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 130 · 🔀 1.5K · 📦 190 · 📋 2.1K - 23% open · ⏱️ 15.12.2021): +- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 22 · 🔀 220 · 📦 230 · 📋 160 - 26% open · ⏱️ 21.06.2022): ``` - git clone https://github.com/streamlit/streamlit + git clone https://github.com/scikit-learn-contrib/metric-learn ``` -- [PyPi](https://pypi.org/project/streamlit): +- [PyPi](https://pypi.org/project/metric-learn) (📥 44K / month): ``` - pip install streamlit + pip install metric-learn ```
-
Trax (🥉22 · ⭐ 6.7K) - 借助清晰的代码和速度来进行深度学习。Apache-2 +
Trax (🥉25 · ⭐ 7.1K) - Trax Deep Learning with Clear Code and Speed. Apache-2 -- [GitHub](https://github.com/google/trax) (👨‍💻 74 · 🔀 660 · 📦 40 · 📋 200 - 41% open · ⏱️ 03.12.2021): +- [GitHub](https://github.com/google/trax) (👨‍💻 78 · 🔀 720 · 📦 75 · 📋 210 - 41% open · ⏱️ 08.08.2022): ``` git clone https://github.com/google/trax ``` -- [PyPi](https://pypi.org/project/trax): +- [PyPi](https://pypi.org/project/trax) (📥 4K / month): ``` pip install trax ```
-
TabPy (🥉22 · ⭐ 1.2K) - 快速执行Python代码，并在Tableau可视化文件中显示结果。MIT +
TabPy (🥉25 · ⭐ 1.3K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT -- [GitHub](https://github.com/tableau/TabPy) (👨‍💻 43 · 🔀 440 · 📦 79 · 📋 280 - 5% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/tableau/TabPy) (👨‍💻 47 · 🔀 480 · 📦 93 · 📋 290 - 1% open · ⏱️ 10.06.2022): ``` git clone https://github.com/tableau/TabPy ``` -- [PyPi](https://pypi.org/project/tabpy): +- [PyPi](https://pypi.org/project/tabpy) (📥 19K / month): ``` pip install tabpy ```
-
metric-learn (🥉21 · ⭐ 1.2K) - Python中的度量学习算法。MIT +
causalml (🥉24 · ⭐ 3.2K) - Uplift modeling and causal inference with machine learning.. ❗Unlicensed -- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 21 · 🔀 210 · 📦 180 · 📋 160 - 27% open · ⏱️ 17.11.2021): +- [GitHub](https://github.com/uber/causalml) (👨‍💻 44 · 🔀 520 · 📦 52 · 📋 280 - 21% open · ⏱️ 22.08.2022): ``` - git clone https://github.com/scikit-learn-contrib/metric-learn + git clone https://github.com/uber/causalml ``` -- [PyPi](https://pypi.org/project/metric-learn): +- [PyPi](https://pypi.org/project/causalml) (📥 48K / month): ``` - pip install metric-learn + pip install causalml ```
-
StreamAlert (🥉20 · ⭐ 2.6K) - StreamAlert是无服务器的实时数据分析框架。Apache-2 +
pyclustering (🥉24 · ⭐ 990 · 💀) - pyclustring is a Python, C++ data mining library. BSD-3 -- [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 33 · 🔀 310 · 📋 340 - 24% open · ⏱️ 04.11.2021): +- [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 220 · 📥 410 · 📦 350 · 📋 650 - 9% open · ⏱️ 12.02.2021): ``` - git clone https://github.com/airbnb/streamalert + git clone https://github.com/annoviko/pyclustering + ``` +- [PyPi](https://pypi.org/project/pyclustering) (📥 50K / month): + ``` + pip install pyclustering + ``` +- [Conda](https://anaconda.org/conda-forge/pyclustering) (📥 41K · ⏱️ 13.09.2021): + ``` + conda install -c conda-forge pyclustering ```
-
cleanlab (🥉20 · ⭐ 2.5K) - 机器学习的标准软件包。❗️AGPL-3.0 +
PySwarms (🥉23 · ⭐ 960) - A research toolkit for particle swarm optimization in Python. MIT -- [GitHub](https://github.com/cleanlab/cleanlab) (👨‍💻 6 · 🔀 240 · 📦 24 · 📋 81 - 41% open · ⏱️ 08.11.2021): +- [GitHub](https://github.com/ljvmiranda921/pyswarms) (👨‍💻 44 · 🔀 300 · 📦 180 · 📋 210 - 3% open · ⏱️ 03.07.2022): ``` - git clone https://github.com/cgnorthcutt/cleanlab + git clone https://github.com/ljvmiranda921/pyswarms ``` -- [PyPi](https://pypi.org/project/cleanlab) (📥 5.7K / month): +- [PyPi](https://pypi.org/project/pyswarms) (📥 18K / month): ``` - pip install cleanlab + pip install pyswarms ```
-
gplearn (🥉20 · ⭐ 1K) - 使用scikit-learn启发式API进行Python遗传编程。BSD-3 +
gplearn (🥉22 · ⭐ 1.2K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 -- [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 10 · 🔀 180 · 📦 210 · 📋 170 - 26% open · ⏱️ 18.10.2021): +- [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 10 · 🔀 200 · 📦 280 · 📋 190 - 7% open · ⏱️ 04.08.2022): ``` git clone https://github.com/trevorstephens/gplearn ``` -- [PyPi](https://pypi.org/project/gplearn) (📥 2.6K / month): +- [PyPi](https://pypi.org/project/gplearn) (📥 5.3K / month): ``` pip install gplearn ```
-
pyopencl (🥉20 · ⭐ 860) - 适用于Python的OpenCL集成。❗Unlicensed +
pyopencl (🥉22 · ⭐ 910) - OpenCL integration for Python, plus shiny features. ❗Unlicensed -- [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 90 · 🔀 210 · 📦 590 · 📋 290 - 20% open · ⏱️ 13.12.2021): +- [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 92 · 🔀 220 · 📦 800 · 📋 300 - 20% open · ⏱️ 23.08.2022): ``` git clone https://github.com/inducer/pyopencl ``` -- [PyPi](https://pypi.org/project/pyopencl) (📥 16K / month): +- [PyPi](https://pypi.org/project/pyopencl) (📥 34K / month): ``` pip install pyopencl ``` -- [Conda](https://anaconda.org/conda-forge/pyopencl) (📥 540K · ⏱️ 06.12.2021): +- [Conda](https://anaconda.org/conda-forge/pyopencl) (📥 670K · ⏱️ 22.06.2022): ``` conda install -c conda-forge pyopencl ```
-
Prince (🥉20 · ⭐ 740) - Python因子分析库（PCA，CA，MCA，MFA，FAMD）。MIT +
Prince (🥉22 · ⭐ 850 · 💤) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT -- [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 10 · 🔀 130 · 📦 170 · 📋 100 - 33% open · ⏱️ 11.12.2021): +- [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 12 · 🔀 150 · 📦 240 · 📋 110 - 35% open · ⏱️ 28.12.2021): ``` git clone https://github.com/MaxHalford/prince ``` -- [PyPi](https://pypi.org/project/prince) (📥 18K / month): +- [PyPi](https://pypi.org/project/prince) (📥 45K / month): ``` pip install prince ```
-
findspark (🥉20 · ⭐ 420) - 查找pyspark并导入的工具库。BSD-3 +
findspark (🥉22 · ⭐ 440) - Find pyspark to make it importable. BSD-3 -- [GitHub](https://github.com/minrk/findspark) (👨‍💻 14 · 🔀 66 · 📦 2.1K · 📋 21 - 52% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/minrk/findspark) (👨‍💻 15 · 🔀 68 · 📦 2.7K · 📋 22 - 50% open · ⏱️ 11.02.2022): ``` git clone https://github.com/minrk/findspark ``` -- [PyPi](https://pypi.org/project/findspark): +- [PyPi](https://pypi.org/project/findspark) (📥 2.1M / month): ``` pip install findspark ``` -- [Conda](https://anaconda.org/conda-forge/findspark) (📥 600K · ⏱️ 06.07.2018): +- [Conda](https://anaconda.org/conda-forge/findspark) (📥 690K · ⏱️ 11.02.2022): ``` conda install -c conda-forge findspark ```
-
River (🥉19 · ⭐ 3K) - Python中的在线机器学习。BSD-3 +
River (🥉20 · ⭐ 3.6K) - Online machine learning in Python. BSD-3 -- [GitHub](https://github.com/online-ml/river) (👨‍💻 70 · 🔀 320 · 📦 56 · 📋 330 - 1% open · ⏱️ 16.12.2021): +- [GitHub](https://github.com/online-ml/river) (👨‍💻 81 · 🔀 380 · 📦 160 · 📋 370 - 1% open · ⏱️ 24.08.2022): ``` git clone https://github.com/online-ml/river ```
-
impyute (🥉19 · ⭐ 300) - 数据插补库可对缺少数据的数据集进行预处理。MIT +
BioPandas (🥉20 · ⭐ 500) - Working with molecular structures in pandas DataFrames. BSD-3 -- [GitHub](https://github.com/eltonlaw/impyute) (👨‍💻 11 · 🔀 43 · 📦 120 · 📋 64 - 42% open · ⏱️ 06.11.2021): +- [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 10 · 🔀 100 · 📦 120 · 📋 47 - 42% open · ⏱️ 06.08.2022): ``` - git clone https://github.com/eltonlaw/impyute + git clone https://github.com/rasbt/biopandas ``` -- [PyPi](https://pypi.org/project/impyute) (📥 2.5K / month): +- [PyPi](https://pypi.org/project/biopandas) (📥 5.3K / month): ``` - pip install impyute + pip install biopandas + ``` +- [Conda](https://anaconda.org/conda-forge/biopandas) (📥 120K · ⏱️ 13.05.2022): + ``` + conda install -c conda-forge biopandas ```
-
AstroML (🥉16 · ⭐ 790 · 💤) - 天文学和天体物理学的机器学习，统计和数据挖掘.BSD-2 +
StreamAlert (🥉19 · ⭐ 2.7K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 -- [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 260 · 📋 140 - 37% open · ⏱️ 07.04.2021): +- [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 33 · 🔀 320 · 📋 340 - 24% open · ⏱️ 20.07.2022): ``` - git clone https://github.com/astroML/astroML + git clone https://github.com/airbnb/streamalert ``` -- [PyPi](https://pypi.org/project/astroML) (📥 1.1K / month): +
+
SUOD (🥉19 · ⭐ 330) - (MLSys' 21) An Acceleration System for Large-scare Unsupervised.. BSD-2 + +- [GitHub](https://github.com/yzhao062/SUOD) (👨‍💻 2 · 🔀 41 · 📦 430 · 📋 9 - 66% open · ⏱️ 07.07.2022): + ``` - pip install astroML + git clone https://github.com/yzhao062/SUOD ``` -- [Conda](https://anaconda.org/conda-forge/astroml) (📥 27K · ⏱️ 16.02.2020): +- [PyPi](https://pypi.org/project/suod) (📥 29K / month): ``` - conda install -c conda-forge astroml + pip install suod ```
-
BioPandas (🥉16 · ⭐ 400) - 在pandas DataFrames中处理分子结构。BSD-3 +
impyute (🥉19 · ⭐ 320 · 💤) - Data imputations library to preprocess datasets with missing data. MIT -- [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 8 · 🔀 89 · 📋 39 - 38% open · ⏱️ 24.09.2021): +- [GitHub](https://github.com/eltonlaw/impyute) (👨‍💻 11 · 🔀 46 · 📦 140 · 📋 64 - 42% open · ⏱️ 06.11.2021): ``` - git clone https://github.com/rasbt/biopandas - ``` -- [PyPi](https://pypi.org/project/biopandas) (📥 2.5K / month): - ``` - pip install biopandas + git clone https://github.com/eltonlaw/impyute ``` -- [Conda](https://anaconda.org/conda-forge/biopandas) (📥 93K · ⏱️ 31.08.2021): +- [PyPi](https://pypi.org/project/impyute) (📥 8.2K / month): ``` - conda install -c conda-forge biopandas + pip install impyute ```
-
SUOD (🥉16 · ⭐ 300) - （MLSys' 21）大型无人驾驶加速系统。BSD-2 +
AstroML (🥉17 · ⭐ 840) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 -- [GitHub](https://github.com/yzhao062/SUOD) (🔀 36 · 📦 400 · 📋 6 - 66% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 270 · 📋 150 - 37% open · ⏱️ 17.08.2022): ``` - git clone https://github.com/yzhao062/SUOD + git clone https://github.com/astroML/astroML ``` -- [PyPi](https://pypi.org/project/suod): +- [PyPi](https://pypi.org/project/astroML) (📥 1.3K / month): ``` - pip install suod + pip install astroML + ``` +- [Conda](https://anaconda.org/conda-forge/astroml) (📥 31K · ⏱️ 02.03.2022): + ``` + conda install -c conda-forge astroml ```
-
Feature Engine (🥉12 · ⭐ 9) - 具有sklearn类功能的功能工程包。BSD-3 +
Feature Engine (🥉16 · ⭐ 22) - Feature engineering package with sklearn like functionality. BSD-3 -- [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 24 · 🔀 6 · ⏱️ 06.08.2021): +- [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 36 · 🔀 8 · ⏱️ 05.07.2022): ``` git clone https://github.com/solegalli/feature_engine ``` -- [PyPi](https://pypi.org/project/feature_engine): +- [PyPi](https://pypi.org/project/feature_engine) (📥 93K / month): ``` pip install feature_engine ``` -- [Conda](https://anaconda.org/conda-forge/feature_engine) (📥 6.7K · ⏱️ 01.09.2021): +- [Conda](https://anaconda.org/conda-forge/feature_engine) (📥 14K · ⏱️ 14.06.2022): ``` conda install -c conda-forge feature_engine ```
+
cleanlab (🥉13 · ⭐ 49 · 🐣) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 + +- [GitHub](https://github.com/cgnorthcutt/cleanlab) (👨‍💻 10 · 🔀 9 · ⏱️ 21.08.2022): + + ``` + git clone https://github.com/cgnorthcutt/cleanlab + ``` +- [PyPi](https://pypi.org/project/cleanlab) (📥 7.2K / month): + ``` + pip install cleanlab + ``` +
--- diff --git a/history/2022-08-26_changes.md b/history/2022-08-26_changes.md new file mode 100644 index 0000000..6d22bba --- /dev/null +++ b/history/2022-08-26_changes.md @@ -0,0 +1,20 @@ +## 📈 Trending Up + +_Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ + +- Pillow (🥇36 · ⭐ 10K · 📈) - The friendly PIL fork (Python Imaging Library). ❗️PIL +- Streamlit (🥇30 · ⭐ 20K · 📈) - Streamlit The fastest way to build data apps in Python. Apache-2 +- pmdarima (🥇30 · ⭐ 1.2K · 📈) - A statistical library designed to fill the void in Python's time.. MIT +- TensorFlow Transform (🥈30 · ⭐ 930 · 📈) - Input pipeline framework. Apache-2 +- opencv-python (🥈25 · ⭐ 2.9K · 📈) - Automated CI toolchain to produce precompiled opencv-python,.. MIT + +## 📉 Trending Down + +_Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ + +- pytorch-lightning (🥈29 · ⭐ 20K · 📉) - The lightweight PyTorch wrapper for high-performance.. Apache-2 +- Seaborn (🥈29 · ⭐ 9.7K · 📉) - Statistical data visualization using matplotlib. BSD-3 +- audioread (🥉19 · ⭐ 410 · 📉) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT +- Torch Points 3D (🥉14 · ⭐ 93 · 💤) - Pytorch framework for doing deep learning on point.. BSD-3 +- cleanlab (🥉13 · ⭐ 49 · 🐣) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 + diff --git a/history/2022-08-26_projects.csv b/history/2022-08-26_projects.csv new file mode 100644 index 0000000..277ce3e --- /dev/null +++ b/history/2022-08-26_projects.csv @@ -0,0 +1,822 @@ +,name,show,github_id,resource,category,github_url,homepage,license,created_at,updated_at,last_commit_pushed_at,fork_count,open_issue_count,closed_issue_count,star_count,commit_count,description,contributor_count,projectrank,latest_stable_release_published_at,latest_stable_release_number,release_count,updated_github_id,pypi_id,conda_id,dockerhub_id,docs_url,labels,dependent_project_count,github_dependent_project_count,pypi_url,pypi_monthly_downloads,monthly_downloads,conda_url,conda_latest_release_published_at,conda_total_downloads,dockerhub_url,dockerhub_latest_release_published_at,dockerhub_stars,dockerhub_pulls,projectrank_placing,github_release_downloads,trending,npm_id,npm_url,npm_monthly_downloads,helm_id,snap_id,brew_id,dnf_id,yay_id,maven_id,maven_url,apt_id,yum_id,gitlab_id,gitlab_url +0,ANN Benchmarks,True,erikbern/ann-benchmarks,True,nn-search,https://github.com/erikbern/ann-benchmarks,https://github.com/erikbern/ann-benchmarks,MIT,2015-05-28 13:21:43.000,2022-08-15 12:39:01.000000,2022-08-15 12:39:01,453.0,43.0,79.0,3024,1301.0,Benchmarks of approximate nearest neighbor libraries in Python.,71.0,0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +1,Python Web Scraping,True,ml-tooling/best-of-web-python,True,web-scraping,https://github.com/ml-tooling/best-of-web-python,https://github.com/ml-tooling/best-of-web-python,CC-BY-SA-4.0,2021-01-05 13:09:27.000,2022-08-25 16:43:05.000000,2022-08-25 16:43:04,123.0,,2.0,1639,,Collection of web-scraping and crawling libraries.,8.0,0,2022-08-25 16:43:17,2022.08.25,53.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +2,Python DB Clients,True,HanXinzi2020/awesome-python-resources,True,db-clients,https://github.com/HanXinzi-AI/awesome-python-resources,https://github.com/HanXinzi2020/awesome-python-resources#数据库,,2021-04-24 13:42:10.000,2022-08-26 04:18:21.000000,2021-12-30 03:32:22,1.0,,,7,43.0,Collection of database clients for python.,2.0,0,,,,HanXinzi-AI/awesome-python-resources,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +3,Tensorflow,True,tensorflow/tensorflow,,ml-frameworks,https://github.com/tensorflow/tensorflow,https://github.com/tensorflow/tensorflow,Apache-2.0,2015-11-07 01:19:20.000,2022-08-26 03:22:32.000000,2022-08-26 03:22:18,70298.0,2116.0,33303.0,169397,134167.0,An Open Source Machine Learning Framework for Everyone.,4099.0,44,2022-05-23 17:00:13,2.9.1,100.0,,tensorflow,conda-forge/tensorflow,tensorflow/tensorflow,https://www.tensorflow.org/overview,['tensorflow'],212562.0,212562.0,https://pypi.org/project/tensorflow,13605603.0,14484716.0,https://anaconda.org/conda-forge/tensorflow,2022-07-20 02:50:33.065,3563076.0,https://hub.docker.com/r/tensorflow/tensorflow,2022-08-25 15:22:48.685361,2047.0,67460063.0,1.0,,,,,,,,,,,,,,,, +4,scikit-learn,True,scikit-learn/scikit-learn,,ml-frameworks,https://github.com/scikit-learn/scikit-learn,https://github.com/scikit-learn/scikit-learn,BSD-3-Clause,2010-08-17 09:43:38.000,2022-08-26 03:01:29.000000,2022-08-26 00:27:55,22554.0,1538.0,8049.0,51178,,scikit-learn: machine learning in Python.,2710.0,39,2022-08-05 22:48:17,1.1.2,35.0,,scikit-learn,conda-forge/scikit-learn,,,['sklearn'],385426.0,385426.0,https://pypi.org/project/scikit-learn,31358734.0,31556260.0,https://anaconda.org/conda-forge/scikit-learn,2022-08-05 23:30:56.710,14813714.0,,,,,1.0,810.0,,,,,,,,,,,,,,, +5,pandas,True,pandas-dev/pandas,,data-containers,https://github.com/pandas-dev/pandas,https://github.com/pandas-dev/pandas,BSD-3-Clause,2010-08-24 01:37:33.000,2022-08-26 02:31:25.000000,2022-08-25 22:27:20,14508.0,3376.0,19536.0,35021,,Flexible and powerful data analysis / manipulation library for..,3078.0,39,2022-06-23 13:29:00,1.4.3,87.0,,pandas,conda-forge/pandas,,,['pandas'],798842.0,798842.0,https://pypi.org/project/pandas,101805867.0,102189690.0,https://anaconda.org/conda-forge/pandas,2022-08-24 17:19:33.541,28670717.0,,,,,1.0,159352.0,,,,,,,,,,,,,,, +6,spaCy,True,explosion/spaCy,,nlp,https://github.com/explosion/spaCy,https://github.com/explosion/spaCy,MIT,2014-07-03 15:15:40.000,2022-08-26 03:57:52.000000,2022-08-23 11:09:36,3823.0,72.0,5129.0,24051,15580.0,Industrial-strength Natural Language Processing (NLP) in Python.,699.0,38,2022-07-26 13:08:23,3.4.1,100.0,,spacy,conda-forge/spacy,,,,42511.0,42511.0,https://pypi.org/project/spacy,4670012.0,4711743.0,https://anaconda.org/conda-forge/spacy,2022-07-27 17:54:46.471,2751342.0,,,,,1.0,3146.0,,,,,,,,,,,,,,, +7,numpy,True,numpy/numpy,,data-containers,https://github.com/numpy/numpy,https://github.com/numpy/numpy,BSD-3-Clause,2010-09-13 23:02:39.000,2022-08-25 22:29:46.000000,2022-08-24 04:19:44,7048.0,2017.0,8801.0,21285,,The fundamental package for scientific computing with Python.,1488.0,38,2022-08-14 18:32:45,1.23.2,89.0,,numpy,conda-forge/numpy,,,,1189609.0,1189609.0,https://pypi.org/project/numpy,131615635.0,132133457.0,https://anaconda.org/conda-forge/numpy,2022-08-16 19:23:15.408,38233472.0,,,,,1.0,555027.0,,,,,,,,,,,,,,, +8,scipy,True,scipy/scipy,,others,https://github.com/scipy/scipy,https://github.com/scipy/scipy,BSD-3-Clause,2011-03-09 18:52:03.000,2022-08-25 21:48:14.000000,2022-08-25 09:10:57,4252.0,1392.0,7024.0,10117,,"Ecosystem of open-source software for mathematics, science, and engineering.",1341.0,38,2022-07-29 13:54:16,1.9.0,69.0,,scipy,conda-forge/scipy,,,,555717.0,555717.0,https://pypi.org/project/scipy,42672339.0,43028793.0,https://anaconda.org/conda-forge/scipy,2022-07-30 10:53:47.560,26421610.0,,,,,1.0,354181.0,,,,,,,,,,,,,,, +9,transformers,True,huggingface/transformers,,nlp,https://github.com/huggingface/transformers,https://github.com/huggingface/transformers,Apache-2.0,2018-10-29 13:56:00.000,2022-08-26 03:07:20.000000,2022-08-25 16:08:05,15254.0,404.0,9472.0,69049,,Transformers: State-of-the-art Natural Language..,1448.0,37,2022-08-24 15:28:51,4.21.2,99.0,,transformers,conda-forge/transformers,,,"['pytorch', 'tensorflow']",33848.0,33848.0,https://pypi.org/project/transformers,6127229.0,6138169.0,https://anaconda.org/conda-forge/transformers,2022-08-25 04:07:25.381,370864.0,,,,,1.0,1525.0,,,,,,,,,,,,,,, +10,XGBoost,True,dmlc/xgboost,,ml-frameworks,https://github.com/dmlc/xgboost,https://github.com/dmlc/xgboost,Apache-2.0,2014-02-06 17:28:03.000,2022-08-25 22:14:35.000000,2022-08-25 06:41:48,7906.0,269.0,4241.0,23113,5907.0,"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or..",573.0,37,2022-08-23 13:05:54,1.6.2,43.0,,xgboost,conda-forge/xgboost,,https://xgboost.readthedocs.io/en/latest/,,35212.0,35212.0,https://pypi.org/project/xgboost,8319095.0,8364421.0,https://anaconda.org/conda-forge/xgboost,2022-08-12 07:39:35.276,2943062.0,,,,,1.0,4960.0,,,,,,,,,,,,,,, +11,Faker,True,joke2k/faker,,data-loading,https://github.com/joke2k/faker,https://github.com/joke2k/faker,MIT,2012-11-12 23:00:09.000,2022-08-18 13:49:13.271000,2022-08-17 15:30:30,1604.0,14.0,564.0,14662,2997.0,Faker is a Python package that generates fake data for you.,467.0,37,2022-08-17 15:31:21,14.1.0,154.0,,Faker,conda-forge/faker,,,,67328.0,67328.0,https://pypi.org/project/Faker,6562120.0,6571710.0,https://anaconda.org/conda-forge/faker,2022-08-18 13:49:13.271,623414.0,,,,,1.0,,,,,,,,,,,,,,,, +12,Tensorboard,True,tensorflow/tensorboard,,ml-experiments,https://github.com/tensorflow/tensorboard,https://github.com/tensorflow/tensorboard,Apache-2.0,2017-05-15 20:08:07.000,2022-08-26 00:05:19.000000,2022-08-25 16:28:47,1474.0,534.0,1138.0,5965,5166.0,TensorFlow's Visualization Toolkit.,286.0,37,2022-08-10 19:44:48,2.10.0,43.0,,tensorboard,conda-forge/tensorboard,,,['tensorflow'],121002.0,121002.0,https://pypi.org/project/tensorboard,14478509.0,14534525.0,https://anaconda.org/conda-forge/tensorboard,2022-08-11 03:39:08.506,3192942.0,,,,,1.0,,,,,,,,,,,,,,,, +13,OpenAI Gym,True,openai/gym,,reinforcement-learning,https://github.com/openai/gym,https://github.com/openai/gym,MIT,2016-04-27 14:59:16.000,2022-08-25 14:05:47.000000,2022-08-24 16:20:24,7451.0,15.0,1628.0,28360,1721.0,A toolkit for developing and comparing reinforcement learning..,376.0,36,2022-08-18 17:41:14,0.25.2,16.0,,gym,,,,,31815.0,31815.0,https://pypi.org/project/gym,618484.0,618484.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +14,Celery,True,celery/celery,,data-pipelines,https://github.com/celery/celery,https://github.com/celery/celery,,2009-04-24 11:31:24.000,2022-08-25 13:35:55.000000,2022-08-25 13:35:55,4183.0,503.0,4228.0,19950,11996.0,Asynchronous task queue/job queue based on distributed message passing.,1237.0,36,2022-08-01 11:20:41,5.3.0b1,37.0,,celery,conda-forge/celery,,,,74589.0,74589.0,https://pypi.org/project/celery,5949182.0,5961272.0,https://anaconda.org/conda-forge/celery,2022-05-29 18:35:32.713,930975.0,,,,,1.0,,,,,,,,,,,,,,,, +15,shap,True,slundberg/shap,,interpretability,https://github.com/slundberg/shap,https://github.com/slundberg/shap,MIT,2016-11-22 19:17:08.000,2022-08-23 14:39:08.000000,2022-06-16 14:46:20,2561.0,1407.0,606.0,17307,2277.0,A game theoretic approach to explain the output of any machine learning model.,205.0,36,2022-06-16 00:31:04,0.41.0,47.0,,shap,conda-forge/shap,,,,6389.0,6389.0,https://pypi.org/project/shap,3675466.0,3705427.0,https://anaconda.org/conda-forge/shap,2022-06-20 09:35:07.854,1438170.0,,,,,1.0,,,,,,,,,,,,,,,, +16,Matplotlib,True,matplotlib/matplotlib,,data-viz,https://github.com/matplotlib/matplotlib,https://github.com/matplotlib/matplotlib,,2011-02-19 03:17:12.000,2022-08-26 03:41:28.000000,2022-08-26 00:41:07,6287.0,1521.0,7289.0,16015,,matplotlib: plotting with Python.,1399.0,36,2022-08-11 04:02:38,3.5.3,64.0,,matplotlib,conda-forge/matplotlib,,,,610646.0,610646.0,https://pypi.org/project/matplotlib,27509064.0,27668795.0,https://anaconda.org/conda-forge/matplotlib,2022-08-25 15:45:20.398,13257692.0,,,,,1.0,,,,,,,,,,,,,,,, +17,gensim,True,RaRe-Technologies/gensim,,nlp,https://github.com/RaRe-Technologies/gensim,https://github.com/RaRe-Technologies/gensim,LGPL-2.1,2011-02-10 07:43:04.000,2022-08-22 12:56:01.000000,2022-08-22 12:56:01,4031.0,361.0,1398.0,13470,4375.0,Topic Modelling for Humans.,431.0,36,2022-05-01 08:38:45,4.2.0,41.0,,gensim,conda-forge/gensim,,,,35798.0,35798.0,https://pypi.org/project/gensim,4900636.0,4915309.0,https://anaconda.org/conda-forge/gensim,2022-07-29 07:43:10.680,862980.0,,,,,1.0,3831.0,,,,,,,,,,,,,,, +18,Pillow,True,python-pillow/Pillow,,image,https://github.com/python-pillow/Pillow,https://github.com/python-pillow/Pillow,PIL,2012-07-24 21:38:39.000,2022-08-26 01:05:21.000000,2022-08-25 07:05:11,1742.0,103.0,2489.0,10075,,The friendly PIL fork (Python Imaging Library).,408.0,36,2022-07-01 18:32:05,9.2.0,47.0,,Pillow,conda-forge/pillow,,,,823693.0,823693.0,https://pypi.org/project/Pillow,45263071.0,45498543.0,https://anaconda.org/conda-forge/pillow,2022-08-13 11:08:07.290,17895884.0,,,,,1.0,,12.0,,,,,,,,,,,,,, +19,h5py,True,h5py/h5py,,data-containers,https://github.com/h5py/h5py,https://github.com/h5py/h5py,BSD-3-Clause,2012-09-21 00:40:02.000,2022-08-18 21:00:46.000000,2022-07-01 13:41:39,453.0,215.0,1114.0,1766,4043.0,HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5..,185.0,36,2022-05-24 08:51:43,3.7.0,32.0,,h5py,conda-forge/h5py,,,,174446.0,174446.0,https://pypi.org/project/h5py,11540189.0,11654132.0,https://anaconda.org/conda-forge/h5py,2022-08-14 15:00:36.936,8771218.0,,,,,1.0,2105.0,,,,,,,,,,,,,,, +20,Ray,True,ray-project/ray,,distributed-ml,https://github.com/ray-project/ray,https://github.com/ray-project/ray,Apache-2.0,2016-10-25 19:38:30.000,2022-08-26 03:49:52.000000,2022-08-26 02:52:43,3727.0,2436.0,8651.0,21731,14061.0,"An open source framework that provides a simple, universal API for..",743.0,35,2022-08-23 04:57:08,ray-2.0.0,59.0,,ray,,,,,5685.0,5685.0,https://pypi.org/project/ray,1796011.0,1796011.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +21,LightGBM,True,microsoft/LightGBM,,ml-frameworks,https://github.com/microsoft/LightGBM,https://github.com/microsoft/LightGBM,MIT,2016-08-05 05:45:50.000,2022-08-26 02:32:55.000000,2022-08-25 17:27:12,3501.0,197.0,2573.0,14107,3055.0,"A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,..",267.0,35,2022-01-07 14:53:52,3.3.2,24.0,,lightgbm,conda-forge/lightgbm,,,,14905.0,14905.0,https://pypi.org/project/lightgbm,5973092.0,5994754.0,https://anaconda.org/conda-forge/lightgbm,2022-01-08 00:29:45.463,1168021.0,,,,,1.0,161016.0,,,,,,,,,,,,,,, +22,pydeck,True,visgl/deck.gl,,geospatial-data,https://github.com/visgl/deck.gl,https://github.com/visgl/deck.gl,MIT,2015-12-15 08:38:29.000,2022-08-25 22:08:21.000000,2022-08-24 19:18:33,1746.0,144.0,2343.0,10132,4191.0,WebGL2 powered geospatial visualization layers.,204.0,35,2022-08-22 17:07:27,8.8.9,100.0,,pydeck,conda-forge/pydeck,,,['jupyter'],4515.0,4515.0,https://pypi.org/project/pydeck,785300.0,1114358.0,https://anaconda.org/conda-forge/pydeck,2021-10-26 00:42:05.329,165622.0,,,,,1.0,,,deck.gl,https://www.npmjs.com/package/deck.gl,323538.0,,,,,,,,,,, +23,SymPy,True,sympy/sympy,,others,https://github.com/sympy/sympy,https://github.com/sympy/sympy,,2010-04-30 20:37:14.000,2022-08-26 02:25:53.000000,2022-08-26 02:25:53,3632.0,3925.0,8073.0,9506,51826.0,A computer algebra system written in pure Python.,1166.0,35,2022-08-23 23:36:12,sympy-1.11,42.0,,sympy,conda-forge/sympy,,,,45464.0,45464.0,https://pypi.org/project/sympy,2606566.0,2641639.0,https://anaconda.org/conda-forge/sympy,2022-08-23 23:56:28.223,2313453.0,,,,,1.0,460767.0,,,,,,,,,,,,,,, +24,Fastai,True,fastai/fastai,,ml-frameworks,https://github.com/fastai/fastai,https://github.com/fastai/fastai,Apache-2.0,2017-09-09 17:43:36.000,2022-08-19 04:56:39.000000,2022-08-19 04:56:35,7090.0,106.0,1546.0,22672,2512.0,The fastai deep learning library.,213.0,34,2022-08-02 19:19:53,2.7.8,46.0,,fastai,,,,['pytorch'],10946.0,10946.0,https://pypi.org/project/fastai,277270.0,277270.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +25,luigi,True,spotify/luigi,,data-pipelines,https://github.com/spotify/luigi,https://github.com/spotify/luigi,Apache-2.0,2012-09-20 15:06:38.000,2022-08-21 07:13:49.000000,2022-08-18 09:25:35,2257.0,69.0,872.0,15925,4050.0,Luigi is a Python module that helps you build complex pipelines of batch..,592.0,34,2022-08-18 09:37:08,3.1.1,53.0,,luigi,luigi,,,,1812.0,1812.0,https://pypi.org/project/luigi,667833.0,667972.0,https://anaconda.org/anaconda/luigi,2022-05-02 20:23:54.609,10844.0,,,,,1.0,,,,,,stable/luigi,,,,,,,,,, +26,MoviePy,True,Zulko/moviepy,,image,https://github.com/Zulko/moviepy,https://github.com/Zulko/moviepy,MIT,2013-08-12 09:39:28.000,2022-08-24 10:25:05.000000,2022-06-01 11:58:49,1228.0,296.0,895.0,9532,1079.0,Video editing with Python.,149.0,34,2020-05-07 16:29:35,1.0.3,14.0,,moviepy,conda-forge/moviepy,,,,17745.0,17745.0,https://pypi.org/project/moviepy,2518712.0,2520799.0,https://anaconda.org/conda-forge/moviepy,2022-04-16 23:09:18.943,127336.0,,,,,1.0,,,,,,,,,,,,,,,, +27,sentence-transformers,True,UKPLab/sentence-transformers,,nlp,https://github.com/UKPLab/sentence-transformers,https://github.com/UKPLab/sentence-transformers,Apache-2.0,2019-07-24 10:53:51.000,2022-08-21 19:19:14.000000,2022-08-15 13:13:10,1613.0,770.0,730.0,8322,1142.0,Sentence Embeddings with BERT & XLNet.,93.0,34,2022-06-26 19:52:06,2.2.2,32.0,,sentence-transformers,,,,['pytorch'],4006.0,4006.0,https://pypi.org/project/sentence-transformers,1482432.0,1482432.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +28,Optuna,True,optuna/optuna,,hyperopt,https://github.com/optuna/optuna,https://github.com/optuna/optuna,MIT,2018-02-21 06:12:56.000,2022-08-26 01:15:35.000000,2022-08-26 01:15:35,733.0,90.0,1153.0,6814,13756.0,A hyperparameter optimization framework.,203.0,34,2022-06-13 05:38:25,2.10.1,48.0,,optuna,conda-forge/optuna,,,,4025.0,4025.0,https://pypi.org/project/optuna,1463663.0,1473289.0,https://anaconda.org/conda-forge/optuna,2022-07-06 03:46:47.901,317672.0,,,,,1.0,,,,,,,,,,,,,,,, +29,Thinc,True,explosion/thinc,,ml-frameworks,https://github.com/explosion/thinc,https://github.com/explosion/thinc,MIT,2014-10-16 16:34:59.000,2022-08-25 11:06:49.000000,2022-08-05 11:46:12,245.0,14.0,106.0,2575,5153.0,"A refreshing functional take on deep learning, compatible with your favorite..",53.0,34,2022-07-08 13:54:53,8.1.0,60.0,,thinc,conda-forge/thinc,,,,23419.0,23419.0,https://pypi.org/project/thinc,4086805.0,4120100.0,https://anaconda.org/conda-forge/thinc,2022-07-08 17:40:18.742,2197491.0,,,,,1.0,,,,,,,,,,,,,,,, +30,PyTorch,True,pytorch/pytorch,,ml-frameworks,https://github.com/pytorch/pytorch,https://github.com/pytorch/pytorch,BSD-3-Clause,2016-08-13 05:26:41.000,2022-08-26 03:58:22.000000,2022-08-26 03:11:46,15702.0,9096.0,18809.0,58235,51123.0,Tensors and Dynamic neural networks in Python with strong GPU..,3469.0,33,2022-08-05 19:35:19,1.12.1,41.0,,torch,pytorch/pytorch,,https://pytorch.org/docs/stable/index.html,['pytorch'],,,https://pypi.org/project/torch,8459273.0,10151619.0,https://anaconda.org/pytorch/pytorch,2022-08-04 21:19:08.482,18614944.0,,,,,2.0,5620.0,,,,,,,,,,,,,,, +31,dlib,True,davisking/dlib,,ml-frameworks,https://github.com/davisking/dlib,https://github.com/davisking/dlib,BSL-1.0,2014-01-29 00:45:33.000,2022-08-26 01:35:24.000000,2022-08-26 01:35:24,2668.0,35.0,2036.0,11359,8113.0,A toolkit for making real world machine learning and data analysis..,177.0,33,2022-05-08 14:48:09,19.24,25.0,,dlib,conda-forge/dlib,,,,15724.0,15724.0,https://pypi.org/project/dlib,90908.0,97689.0,https://anaconda.org/conda-forge/dlib,2022-05-08 19:10:58.732,460911.0,,,,,2.0,25006.0,,,,,,,,,,,,,,, +32,AllenNLP,True,allenai/allennlp,,nlp,https://github.com/allenai/allennlp,https://github.com/allenai/allennlp,Apache-2.0,2017-05-15 15:52:41.000,2022-08-24 22:15:06.000000,2022-08-24 22:14:09,2136.0,82.0,2453.0,11161,2357.0,"An open-source NLP research library, built on PyTorch.",264.0,33,2022-07-14 18:35:21,2.10.0,58.0,,allennlp,,,,['pytorch'],2694.0,2694.0,https://pypi.org/project/allennlp,72251.0,72251.0,,,,,,,,1.0,47.0,,,,,,,,,,,,,,, +33,nltk,True,nltk/nltk,,nlp,https://github.com/nltk/nltk,https://github.com/nltk/nltk,Apache-2.0,2009-09-07 10:53:58.000,2022-08-25 08:45:58.000000,2022-07-29 02:21:56,2510.0,219.0,1420.0,10996,,Suite of libraries and programs for symbolic and statistical natural language processing for English.,427.0,33,,,14.0,,nltk,conda-forge/nltk,,,,153268.0,153268.0,https://pypi.org/project/nltk,11611365.0,11631221.0,https://anaconda.org/conda-forge/nltk,2021-12-29 03:25:44.981,1429652.0,,,,,1.0,,,,,,,,,,,,,,,, +34,Arrow,True,apache/arrow,,data-containers,https://github.com/apache/arrow,https://github.com/apache/arrow,Apache-2.0,2016-02-17 08:00:23.000,2022-08-26 01:55:15.000000,2022-08-25 15:12:29,2369.0,52.0,786.0,10055,12152.0,Apache Arrow is a cross-language development platform for in-..,926.0,33,,,34.0,,pyarrow,conda-forge/arrow,,,,77.0,77.0,https://pypi.org/project/pyarrow,68047938.0,68062968.0,https://anaconda.org/conda-forge/arrow,2022-01-27 20:04:47.163,1127251.0,,,,,2.0,,,,,,,,,,,,,,,, +35,pandas-profiling,True,pandas-profiling/pandas-profiling,,data-viz,https://github.com/ydataai/pandas-profiling,https://github.com/ydataai/pandas-profiling,MIT,2016-01-09 23:47:55.000,2022-08-25 16:13:30.000000,2022-08-25 15:47:08,1335.0,113.0,470.0,9412,1015.0,Create HTML profiling reports from pandas DataFrame..,92.0,33,2022-05-02 02:53:44,3.2.0,32.0,ydataai/pandas-profiling,pandas-profiling,conda-forge/pandas-profiling,,,"['jupyter', 'pandas']",8835.0,8835.0,https://pypi.org/project/pandas-profiling,1160461.0,1164233.0,https://anaconda.org/conda-forge/pandas-profiling,2022-05-02 10:58:37.618,271641.0,,,,,1.0,,,,,,,,,,,,,,,, +36,Altair,True,altair-viz/altair,,data-viz,https://github.com/altair-viz/altair,https://github.com/altair-viz/altair,BSD-3-Clause,2015-09-19 03:14:04.000,2022-08-24 05:08:11.000000,2022-08-23 02:54:34,653.0,213.0,1415.0,7707,3232.0,Declarative statistical visualization library for Python.,138.0,33,2021-12-29 13:30:58,4.2.0,20.0,,altair,conda-forge/altair,,,,31787.0,31787.0,https://pypi.org/project/altair,7274483.0,7292504.0,https://anaconda.org/conda-forge/altair,2021-12-29 17:47:26.885,1315544.0,,,,,1.0,,,,,,,,,,,,,,,, +37,sentencepiece,True,google/sentencepiece,,nlp,https://github.com/google/sentencepiece,https://github.com/google/sentencepiece,Apache-2.0,2017-03-07 10:03:48.000,2022-08-21 03:44:43.000000,2022-08-21 03:44:31,810.0,16.0,523.0,6123,816.0,Unsupervised text tokenizer for Neural Network-based text..,68.0,33,2022-08-06 16:03:48,0.1.97,22.0,,sentencepiece,conda-forge/sentencepiece,,,,17372.0,17372.0,https://pypi.org/project/sentencepiece,5583610.0,5593013.0,https://anaconda.org/conda-forge/sentencepiece,2022-04-08 22:58:03.701,223871.0,,,,,1.0,21586.0,,,,,,,,,,,,,,, +38,joblib,True,joblib/joblib,,data-pipelines,https://github.com/joblib/joblib,https://github.com/joblib/joblib,BSD-3-Clause,2010-05-07 06:48:26.000,2022-08-17 13:12:14.000000,2022-05-20 16:57:04,326.0,307.0,403.0,2899,1407.0,Computing with Python functions.,110.0,33,,,23.0,,joblib,conda-forge/joblib,,,,207513.0,207513.0,https://pypi.org/project/joblib,22517590.0,22668261.0,https://anaconda.org/conda-forge/joblib,2021-10-07 20:15:36.705,10998999.0,,,,,1.0,,,,,,,,,,,,,,,, +39,SageMaker SDK,True,aws/sagemaker-python-sdk,,ml-experiments,https://github.com/aws/sagemaker-python-sdk,https://github.com/aws/sagemaker-python-sdk,Apache-2.0,2017-11-14 01:03:33.000,2022-08-25 17:04:40.000000,2022-08-24 15:57:53,814.0,355.0,722.0,1683,2643.0,A library for training and deploying machine learning..,279.0,33,2022-08-24 02:22:06,2.106.0,100.0,,sagemaker,,,,"['mxnet', 'tensorflow']",1615.0,1615.0,https://pypi.org/project/sagemaker,8421413.0,8421413.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +40,TF Addons,True,tensorflow/addons,,tensorflow-utils,https://github.com/tensorflow/addons,https://github.com/tensorflow/addons,Apache-2.0,2018-11-26 23:57:17.000,2022-08-25 03:56:06.000000,2022-08-24 21:06:35,528.0,201.0,716.0,1556,1477.0,Useful extra functionality for TensorFlow 2.x maintained by..,197.0,33,2022-06-14 01:12:29,0.17.1,32.0,,tensorflow-addons,,,,['tensorflow'],7178.0,7178.0,https://pypi.org/project/tensorflow-addons,2151052.0,2151052.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +41,imageio,True,imageio/imageio,,image,https://github.com/imageio/imageio,https://github.com/imageio/imageio,BSD-2-Clause,2013-05-04 22:56:45.000,2022-08-25 14:07:11.000000,2022-08-24 18:30:26,220.0,59.0,408.0,1096,1410.0,Python library for reading and writing image data.,91.0,33,2022-08-08 11:24:27,2.21.1,36.0,,imageio,conda-forge/imageio,,,,67210.0,67210.0,https://pypi.org/project/imageio,12176525.0,12228084.0,https://anaconda.org/conda-forge/imageio,2022-08-08 16:11:05.404,3454017.0,,,,,1.0,356.0,,,,,,,,,,,,,,, +42,Keras,True,keras-team/keras,,ml-frameworks,https://github.com/keras-team/keras,https://github.com/keras-team/keras,Apache-2.0,2015-03-28 00:35:42.000,2022-08-26 03:58:35.000000,2022-08-26 03:58:31,18294.0,244.0,11179.0,56001,7290.0,Deep Learning for humans.,1100.0,32,2022-05-13 20:03:15,2.9.0,39.0,,keras,conda-forge/keras,,https://keras.io,['tensorflow'],,,https://pypi.org/project/keras,8363174.0,8397762.0,https://anaconda.org/conda-forge/keras,2022-05-19 01:56:08.499,2490369.0,,,,,2.0,,,,,,,,,,,,,,,, +43,PySpark,True,apache/spark,,ml-frameworks,https://github.com/apache/spark,https://github.com/apache/spark,Apache-2.0,2014-02-25 08:00:08.000,2022-08-26 03:04:19.000000,2022-08-26 02:39:30,24916.0,,,33720,33949.0,Apache Spark Python API.,2716.0,32,,,27.0,,pyspark,conda-forge/pyspark,,,['spark'],,,https://pypi.org/project/pyspark,24969943.0,24999374.0,https://anaconda.org/conda-forge/pyspark,2022-07-27 06:26:20.797,1913076.0,,,,,2.0,,,,,,stable/spark,,,,,,,,,, +44,jieba,True,fxsjy/jieba,,chinese-nlp,https://github.com/fxsjy/jieba,https://github.com/fxsjy/jieba,MIT,2012-09-29 07:52:01.000,2022-07-17 00:34:33.000000,2020-02-15 08:33:35,6346.0,595.0,212.0,29127,523.0,Chinese Words Segementation Utilities.,48.0,32,2020-01-20 14:23:50,0.42.1,9.0,,jieba,conda-forge/jieba,,,,14338.0,14338.0,https://pypi.org/project/jieba,441908.0,443721.0,https://anaconda.org/conda-forge/jieba,2021-05-30 19:33:02.597,116087.0,,,,,1.0,,,,,,,,,,,,,,,, +45,PaddlePaddle,True,PaddlePaddle/Paddle,,ml-frameworks,https://github.com/PaddlePaddle/Paddle,https://github.com/PaddlePaddle/Paddle,Apache-2.0,2016-08-15 06:59:08.000,2022-08-26 03:55:20.000000,2022-08-26 03:48:40,4526.0,2139.0,13067.0,18759,15069.0,PArallel Distributed Deep LEarning: Machine Learning..,806.0,32,2022-08-16 08:23:49,2.3.2,56.0,,paddlepaddle,,,,['paddle'],137.0,137.0,https://pypi.org/project/paddlepaddle,79006.0,79218.0,,,,,,,,2.0,15319.0,,,,,,,,,,,,,,, +46,dash,True,plotly/dash,,data-viz,https://github.com/plotly/dash,https://github.com/plotly/dash,MIT,2015-04-10 01:53:08.000,2022-08-22 20:02:59.000000,2022-08-19 16:00:04,1684.0,626.0,692.0,17194,6399.0,"Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript..",121.0,32,2022-08-02 18:10:36,2.6.1,85.0,,dash,conda-forge/dash,,,,217.0,217.0,https://pypi.org/project/dash,999429.0,1010976.0,https://anaconda.org/conda-forge/dash,2022-08-03 10:34:17.016,588934.0,,,,,1.0,,,,,,,,,,,,,,,, +47,Jina,True,jina-ai/jina,,ml-frameworks,https://github.com/jina-ai/jina,https://github.com/jina-ai/jina,Apache-2.0,2020-02-13 17:04:44.000,2022-08-25 18:22:02.000000,2022-08-25 18:22:01,1920.0,29.0,1562.0,15775,7809.0,An easier way to build neural search on the cloud.,151.0,32,2022-08-22 13:53:01,3.7.14,100.0,,jina,,jinaai/jina,,,349.0,349.0,https://pypi.org/project/jina,87891.0,124412.0,,,,https://hub.docker.com/r/jinaai/jina,2022-08-23 15:45:34.900444,7.0,1095636.0,2.0,,,,,,,,,,,,,,,, +48,Datasets,True,huggingface/datasets,,data-loading,https://github.com/huggingface/datasets,https://github.com/huggingface/datasets,Apache-2.0,2020-03-26 09:23:22.000,2022-08-25 18:34:23.000000,2022-08-25 18:34:23,1768.0,465.0,1261.0,13994,,The largest hub of ready-to-use NLP datasets for ML models with..,442.0,32,2022-07-25 13:41:59,2.4.0,53.0,,datasets,,,,,5964.0,5964.0,https://pypi.org/project/datasets,1229090.0,1229090.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +49,onnx,True,onnx/onnx,,model-serialisation,https://github.com/onnx/onnx,https://github.com/onnx/onnx,Apache-2.0,2017-09-07 04:53:45.000,2022-08-26 03:59:49.000000,2022-08-25 17:54:01,2884.0,235.0,1796.0,13139,,Open standard for machine learning interoperability.,248.0,32,2022-06-18 02:58:18,1.12.0,22.0,,onnx,conda-forge/onnx,,,,8089.0,8089.0,https://pypi.org/project/onnx,1584032.0,1592909.0,https://anaconda.org/conda-forge/onnx,2022-08-18 20:33:15.885,488521.0,,,,,1.0,17855.0,,,,,,,,,,,,,,, +50,imgaug,True,aleju/imgaug,,image,https://github.com/aleju/imgaug,https://github.com/aleju/imgaug,MIT,2015-07-10 20:31:33.000,2022-06-15 13:04:48.000000,2020-06-01 14:58:26,2266.0,272.0,221.0,12894,2913.0,Image augmentation for machine learning experiments.,36.0,32,2020-02-06 06:18:40,0.4.0,3.0,,imgaug,conda-forge/imgaug,,,,10947.0,10947.0,https://pypi.org/project/imgaug,385932.0,388120.0,https://anaconda.org/conda-forge/imgaug,2021-12-31 00:20:29.231,83178.0,,,,,1.0,,,,,,,,,,,,,,,, +51,ChatterBot,True,gunthercox/ChatterBot,,nlp,https://github.com/gunthercox/ChatterBot,https://github.com/gunthercox/ChatterBot,BSD-3-Clause,2014-09-28 14:49:00.000,2022-08-03 21:53:09.000000,2021-06-01 10:43:00,4014.0,304.0,1254.0,12484,1848.0,"ChatterBot is a machine learning, conversational dialog engine..",103.0,32,2020-08-22 18:42:43,1.0.8,86.0,,chatterbot,,,,,4543.0,4543.0,https://pypi.org/project/chatterbot,71207.0,71207.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +52,Plotly,True,plotly/plotly.py,,data-viz,https://github.com/plotly/plotly.py,https://github.com/plotly/plotly.py,MIT,2013-11-21 05:53:08.000,2022-08-23 18:20:52.000000,2022-08-11 14:39:59,2145.0,1167.0,1212.0,11996,5599.0,The interactive graphing library for Python (includes Plotly Express).,201.0,32,2022-08-11 14:41:24,5.10.0,86.0,,plotly,conda-forge/plotly,,,,12.0,12.0,https://pypi.org/project/plotly,8586530.0,8674159.0,https://anaconda.org/conda-forge/plotly,2022-08-14 12:44:46.659,3032753.0,,,,,1.0,,,plotlywidget,https://www.npmjs.com/package/plotlywidget,45508.0,,,,,,,,,,, +53,networkx,True,networkx/networkx,,graph,https://github.com/networkx/networkx,https://github.com/networkx/networkx,,2010-09-06 00:53:44.000,2022-08-25 18:52:06.000000,2022-08-23 15:35:45,2609.0,165.0,2636.0,11468,,Network Analysis in Python.,613.0,32,2022-08-22 13:43:23,networkx-2.8.6,45.0,,networkx,conda-forge/networkx,,,,116059.0,116059.0,https://pypi.org/project/networkx,19333329.0,19444123.0,https://anaconda.org/conda-forge/networkx,2022-08-22 18:30:33.145,7755641.0,,,,,1.0,60.0,,,,,,,,,,,,,,, +54,Albumentations,True,albumentations-team/albumentations,,image,https://github.com/albumentations-team/albumentations,https://github.com/albumentations-team/albumentations,MIT,2018-06-06 03:10:50.000,2022-08-25 18:03:05.000000,2022-08-24 17:12:23,1357.0,270.0,385.0,10744,747.0,Fast image augmentation library and an easy-to-use wrapper..,111.0,32,2022-07-12 13:42:54,1.2.1,16.0,,albumentations,conda-forge/albumentations,,,['pytorch'],9058.0,9058.0,https://pypi.org/project/albumentations,372904.0,374203.0,https://anaconda.org/conda-forge/albumentations,2022-07-12 19:10:52.763,49369.0,,,,,1.0,,,,,,,,,,,,,,,, +55,dask,True,dask/dask,,distributed-ml,https://github.com/dask/dask,https://github.com/dask/dask,BSD-3-Clause,2015-01-04 18:50:00.000,2022-08-25 22:27:38.000000,2022-08-25 22:27:38,1484.0,668.0,3759.0,10246,,Parallel computing with task scheduling.,554.0,32,,,126.0,,dask,conda-forge/dask,,,,39400.0,39400.0,https://pypi.org/project/dask,7067979.0,7152757.0,https://anaconda.org/conda-forge/dask,2022-08-19 23:36:51.157,6358399.0,,,,,1.0,,,,,,stable/dask,,,,,,,,,, +56,rq,True,rq/rq,,data-pipelines,https://github.com/rq/rq,https://github.com/rq/rq,,2011-11-14 10:53:48.000,2022-08-25 06:51:46.000000,2022-08-21 06:50:00,1282.0,186.0,790.0,8451,1658.0,Simple job queues for Python.,266.0,32,2022-07-31 10:45:17,1.11,20.0,,rq,conda-forge/rq,,,,10884.0,10884.0,https://pypi.org/project/rq,679711.0,680753.0,https://anaconda.org/conda-forge/rq,2021-06-30 09:49:43.099,76118.0,,,,,1.0,,,,,,,,,,,,,,,, +57,StatsModels,True,statsmodels/statsmodels,,ml-frameworks,https://github.com/statsmodels/statsmodels,https://github.com/statsmodels/statsmodels,BSD-3-Clause,2011-06-12 17:04:50.000,2022-08-26 03:40:02.000000,2022-08-23 10:41:02,2382.0,2234.0,2553.0,7684,,Statsmodels: statistical modeling and econometrics in Python.,381.0,32,2022-02-08 18:06:37,0.13.2,20.0,,statsmodels,conda-forge/statsmodels,,,,68491.0,68491.0,https://pypi.org/project/statsmodels,8841115.0,8935748.0,https://anaconda.org/conda-forge/statsmodels,2022-06-09 15:31:18.577,7002886.0,,,,,2.0,26.0,,,,,,,,,,,,,,, +58,Kornia,True,kornia/kornia,,image,https://github.com/kornia/kornia,https://github.com/kornia/kornia,Apache-2.0,2018-08-22 10:31:37.000,2022-08-26 01:41:03.000000,2022-08-24 15:48:41,681.0,161.0,437.0,6957,2089.0,Open Source Differentiable Computer Vision Library for PyTorch.,170.0,32,2022-07-16 09:16:59,0.6.6,29.0,,kornia,,,,['pytorch'],1661.0,1661.0,https://pypi.org/project/kornia,469302.0,469311.0,,,,,,,,1.0,429.0,,,,,,,,,,,,,,, +59,CuPy,True,cupy/cupy,,gpu-utilities,https://github.com/cupy/cupy,https://github.com/cupy/cupy,MIT,2016-11-01 09:54:45.000,2022-08-26 03:51:53.000000,2022-08-23 06:54:37,587.0,380.0,1391.0,6267,25688.0,A NumPy-compatible array library accelerated by CUDA.,308.0,32,2022-07-28 07:58:34,11.0.0,100.0,,cupy,conda-forge/cupy,cupy/cupy,,,1186.0,1186.0,https://pypi.org/project/cupy,20126.0,74115.0,https://anaconda.org/conda-forge/cupy,2022-07-29 02:06:47.365,1781962.0,https://hub.docker.com/r/cupy/cupy,2022-07-28 08:01:43.084374,8.0,55087.0,1.0,42178.0,,,,,,,,,,,,,,, +60,PyCaret,True,pycaret/pycaret,,ml-experiments,https://github.com/pycaret/pycaret,https://github.com/pycaret/pycaret,MIT,2019-11-23 18:40:48.000,2022-08-25 10:01:17.000000,2022-08-13 12:22:59,1396.0,269.0,1447.0,6149,3997.0,"An open-source, low-code machine learning library in Python.",99.0,32,2022-04-10 22:12:29,2.3.10,19.0,,pycaret,,,,,2440.0,2440.0,https://pypi.org/project/pycaret,578410.0,578434.0,,,,,,,,1.0,606.0,,,,,,,,,,,,,,, +61,imbalanced-learn,True,scikit-learn-contrib/imbalanced-learn,,sklearn-utils,https://github.com/scikit-learn-contrib/imbalanced-learn,https://github.com/scikit-learn-contrib/imbalanced-learn,MIT,2014-08-16 05:08:26.000,2022-06-18 04:32:30.000000,2022-05-16 18:51:43,1137.0,43.0,464.0,6025,771.0,A Python Package to Tackle the Curse of Imbalanced..,63.0,32,2022-05-16 18:44:33,0.9.1,30.0,,imbalanced-learn,conda-forge/imbalanced-learn,,,['sklearn'],12188.0,12188.0,https://pypi.org/project/imbalanced-learn,3192388.0,3196784.0,https://anaconda.org/conda-forge/imbalanced-learn,2022-05-16 19:16:17.050,254968.0,,,,,1.0,,,,,,,,,,,,,,,, +62,UMAP,True,lmcinnes/umap,,data-viz,https://github.com/lmcinnes/umap,https://github.com/lmcinnes/umap,BSD-3-Clause,2017-07-02 01:11:17.000,2022-08-23 16:41:12.000000,2022-08-23 16:41:12,629.0,335.0,300.0,5741,1594.0,Uniform Manifold Approximation and Projection.,103.0,32,2022-04-13 21:19:42,0.5.3,26.0,,umap-learn,,,,,6020.0,6020.0,https://pypi.org/project/umap-learn,651712.0,651712.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +63,Dagster,True,dagster-io/dagster,,data-pipelines,https://github.com/dagster-io/dagster,https://github.com/dagster-io/dagster,Apache-2.0,2018-04-30 16:30:04.000,2022-08-26 01:29:47.000000,2022-08-25 22:05:07,654.0,1037.0,3364.0,5298,11380.0,"A data orchestrator for machine learning, analytics, and ETL.",230.0,32,2022-08-19 00:19:38,1.0.4,107.0,,dagster,conda-forge/dagster,,,,502.0,502.0,https://pypi.org/project/dagster,479756.0,498321.0,https://anaconda.org/conda-forge/dagster,2022-08-12 23:46:16.746,612652.0,,,,,1.0,,,,,,,,,,,,,,,, +64,scikit-image,True,scikit-image/scikit-image,,image,https://github.com/scikit-image/scikit-image,https://github.com/scikit-image/scikit-image,,2011-07-07 22:07:20.000,2022-08-26 02:30:57.000000,2022-08-23 21:09:05,1954.0,440.0,1856.0,5023,,Image processing in Python.,564.0,32,2022-06-12 18:12:41,0.19.3,20.0,,scikit-image,conda-forge/scikit-image,,,,111031.0,111031.0,https://pypi.org/project/scikit-image,5299328.0,5350499.0,https://anaconda.org/conda-forge/scikit-image,2022-08-10 20:08:06.478,3837833.0,,,,,1.0,,,,,,,,,,,,,,,, +65,wandb client,True,wandb/client,,ml-experiments,https://github.com/wandb/wandb,https://github.com/wandb/wandb,MIT,2017-03-24 05:46:23.000,2022-08-26 03:51:04.000000,2022-08-26 00:31:38,344.0,477.0,1453.0,4610,4792.0,A tool for visualizing and tracking your machine learning..,120.0,32,2022-08-22 20:04:49,0.13.2,100.0,wandb/wandb,wandb,,,,,11282.0,11282.0,https://pypi.org/project/wandb,1662559.0,1662559.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +66,Tablib,True,jazzband/tablib,,data-loading,https://github.com/jazzband/tablib,https://github.com/jazzband/tablib,MIT,2011-03-28 02:36:50.000,2022-07-11 10:43:45.000000,2022-07-11 10:43:45,543.0,29.0,210.0,4152,1144.0,"Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c.",116.0,32,2022-04-09 14:17:22,3.2.1,13.0,,tablib,conda-forge/tablib,,,,15086.0,15086.0,https://pypi.org/project/tablib,1150818.0,1151905.0,https://anaconda.org/conda-forge/tablib,2022-04-09 19:03:08.769,75051.0,,,,,1.0,,,,,,,,,,,,,,,, +67,geopy,True,geopy/geopy,,geospatial-data,https://github.com/geopy/geopy,https://github.com/geopy/geopy,MIT,2010-03-04 22:05:28.000,2022-08-17 07:43:46.000000,2022-08-07 09:28:49,576.0,19.0,238.0,3713,1090.0,Geocoding library for Python.,128.0,32,2021-07-11 12:18:10,2.2.0,34.0,,geopy,conda-forge/geopy,,,,41397.0,41397.0,https://pypi.org/project/geopy,5002380.0,5012570.0,https://anaconda.org/conda-forge/geopy,2021-07-12 18:34:05.605,784691.0,,,,,1.0,,,,,,,,,,,,,,,, +68,Wand,True,emcconville/wand,,image,https://github.com/emcconville/wand,https://github.com/emcconville/wand,MIT,2011-09-30 21:36:38.000,2022-08-22 11:21:13.000000,2022-08-22 08:34:44,194.0,16.0,363.0,1200,1782.0,The ctypes-based simple ImageMagick binding for Python.,101.0,32,2022-08-15 01:14:48,0.6.10,22.0,,wand,,,,,12281.0,12281.0,https://pypi.org/project/wand,451627.0,451814.0,,,,,,,,1.0,8458.0,,,,,,,,,,,,,,, +69,fastText,True,facebookresearch/fastText,,nlp,https://github.com/facebookresearch/fastText,https://github.com/facebookresearch/fastText,MIT,2016-07-16 13:38:42.000,2022-08-09 22:59:21.000000,2022-03-04 15:19:01,4328.0,428.0,606.0,23862,379.0,Library for fast text representation and classification.,59.0,31,2020-04-28 09:51:33,0.9.2,4.0,,fasttext,conda-forge/fasttext,,,,3220.0,3220.0,https://pypi.org/project/fasttext,812833.0,813457.0,https://anaconda.org/conda-forge/fasttext,2022-04-16 18:03:36.665,36200.0,,,,,1.0,,,,,,,,,,,,,,,, +70,PyTorch Image Models,True,rwightman/pytorch-image-models,,image,https://github.com/rwightman/pytorch-image-models,https://github.com/rwightman/pytorch-image-models,Apache-2.0,2019-02-02 05:51:12.000,2022-08-26 00:21:10.000000,2022-08-24 19:24:32,3300.0,56.0,513.0,20502,1476.0,"PyTorch image models, scripts, pretrained weights --..",79.0,31,2022-08-24 18:03:56,0.1-weights-maxx,35.0,,,,,,['pytorch'],4279.0,4279.0,,,42422.0,,,,,,,,2.0,1654472.0,,,,,,,,,,,,,,, +71,jax,True,google/jax,,ml-frameworks,https://github.com/google/jax,https://github.com/google/jax,Apache-2.0,2018-10-25 21:25:02.000,2022-08-26 03:55:10.000000,2022-08-26 00:26:04,1769.0,839.0,2588.0,19964,,"Composable transformations of Python+NumPy programs: differentiate,..",437.0,31,2022-08-12 00:01:15,jax-v0.3.16,47.0,,jax,conda-forge/jaxlib,,,,5318.0,5318.0,https://pypi.org/project/jax,606910.0,617879.0,https://anaconda.org/conda-forge/jaxlib,2022-08-25 23:05:09.618,405863.0,,,,,2.0,,,,,,,,,,,,,,,, +72,EasyOCR,True,JaidedAI/EasyOCR,,ocr,https://github.com/JaidedAI/EasyOCR,https://github.com/JaidedAI/EasyOCR,Apache-2.0,2020-03-14 11:46:39.000,2022-08-25 09:36:41.000000,2022-08-25 09:36:40,2153.0,102.0,536.0,15631,539.0,Ready-to-use OCR with 80+ supported languages and all popular writing..,106.0,31,2022-08-24 03:50:25,1.6.0,18.0,,easyocr,,,,,1477.0,1477.0,https://pypi.org/project/easyocr,83920.0,162143.0,,,,,,,,1.0,2033799.0,,,,,,,,,,,,,,, +73,tensor2tensor,True,tensorflow/tensor2tensor,,tensorflow-utils,https://github.com/tensorflow/tensor2tensor,https://github.com/tensorflow/tensor2tensor,Apache-2.0,2017-06-15 16:57:39.000,2022-08-09 19:07:42.000000,2022-08-09 19:07:41,3024.0,567.0,669.0,12543,4372.0,Library of deep learning models and datasets designed to..,240.0,31,2020-06-17 16:10:01,1.15.7,75.0,,tensor2tensor,,,,['tensorflow'],1226.0,1226.0,https://pypi.org/project/tensor2tensor,8945.0,8945.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +74,Annoy,True,spotify/annoy,,nn-search,https://github.com/spotify/annoy,https://github.com/spotify/annoy,Apache-2.0,2013-04-01 20:29:40.000,2022-08-19 02:15:01.000000,2022-08-08 09:31:20,1021.0,37.0,314.0,10141,842.0,Approximate Nearest Neighbors in C++/Python optimized for memory usage..,82.0,31,2022-08-08 09:33:59,1.17.1,18.0,,annoy,,,,,2222.0,2222.0,https://pypi.org/project/annoy,1497542.0,1497542.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +75,TextBlob,True,sloria/TextBlob,,nlp,https://github.com/sloria/TextBlob,https://github.com/sloria/TextBlob,MIT,2013-06-30 18:29:18.000,2021-12-09 03:19:59.000000,2021-10-22 03:17:05,1041.0,94.0,155.0,8257,535.0,"Simple, Pythonic, text processing--Sentiment analysis, part-of-speech..",35.0,31,2013-09-26 02:29:01,0.7.0,7.0,,textblob,conda-forge/textblob,,,,22437.0,22437.0,https://pypi.org/project/textblob,863947.0,866356.0,https://anaconda.org/conda-forge/textblob,2019-02-24 23:32:55.233,173506.0,,,,,1.0,100.0,,,,,,,,,,,,,,, +76,tensorboardX,True,lanpa/tensorboardX,,ml-experiments,https://github.com/lanpa/tensorboardX,https://github.com/lanpa/tensorboardX,MIT,2017-06-13 13:54:19.000,2022-06-22 05:15:36.000000,2022-06-08 14:21:58,847.0,65.0,368.0,7410,491.0,"tensorboard for pytorch (and chainer, mxnet, numpy, ...).",72.0,31,2022-06-05 10:13:32,2.5,15.0,,tensorboardX,conda-forge/tensorboardx,,,,21421.0,21421.0,https://pypi.org/project/tensorboardX,1070952.0,1085107.0,https://anaconda.org/conda-forge/tensorboardx,2022-06-07 21:45:23.917,778254.0,,,,,2.0,349.0,,,,,,,,,,,,,,, +77,PyOD,True,yzhao062/pyod,,others,https://github.com/yzhao062/pyod,https://github.com/yzhao062/pyod,BSD-2-Clause,2017-10-03 20:29:04.000,2022-08-21 23:16:05.000000,2022-07-29 22:31:14,1145.0,121.0,134.0,6134,1584.0,(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly..,41.0,31,2022-07-29 22:36:09,1.0.4,31.0,,pyod,,,,,1506.0,1506.0,https://pypi.org/project/pyod,367450.0,367450.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +78,Beam,True,apache/beam,,data-pipelines,https://github.com/apache/beam,https://github.com/apache/beam,Apache-2.0,2016-02-02 08:00:06.000,2022-08-26 03:58:05.000000,2022-08-25 23:23:41,3472.0,3897.0,454.0,5792,36852.0,"Unified programming model to define and execute data processing pipelines, including ETL, batch and stream processing.",1320.0,31,2022-08-23 19:07:04,2.41.0,24.0,,apache-beam,,,,,,,https://pypi.org/project/apache-beam,6615545.0,6615545.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +79,Chainer,True,chainer/chainer,,ml-frameworks,https://github.com/chainer/chainer,https://github.com/chainer/chainer,MIT,2015-06-05 05:50:37.000,2022-08-19 09:12:07.000000,2022-06-29 08:16:52,1322.0,10.0,2030.0,5715,30606.0,A flexible framework of neural networks for deep learning.,319.0,31,2022-06-29 08:19:03,7.8.1.post1,100.0,,chainer,,,,,2738.0,2738.0,https://pypi.org/project/chainer,22677.0,22677.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +80,xmltodict,True,martinblech/xmltodict,,data-loading,https://github.com/martinblech/xmltodict,https://github.com/martinblech/xmltodict,MIT,2012-04-17 14:38:21.000,2022-07-17 08:50:35.000000,2022-05-08 16:31:38,434.0,61.0,157.0,4884,220.0,Python module that makes working with XML feel like you are..,49.0,31,,,4.0,,xmltodict,conda-forge/xmltodict,,,,42335.0,42335.0,https://pypi.org/project/xmltodict,18169223.0,18194995.0,https://anaconda.org/conda-forge/xmltodict,2022-05-08 14:42:37.794,1855649.0,,,,,2.0,,,,,,,,,,,,,,,, +81,tensorflow-hub,True,tensorflow/hub,,tensorflow-utils,https://github.com/tensorflow/hub,https://github.com/tensorflow/hub,Apache-2.0,2018-03-12 07:55:42.000,2022-08-23 03:41:16.000000,2022-08-23 03:41:14,1639.0,14.0,638.0,3176,1086.0,A library for transfer learning by reusing parts of..,94.0,31,2021-04-14 13:17:26,0.12.0,15.0,,tensorflow-hub,conda-forge/tensorflow-hub,,,['tensorflow'],12941.0,12941.0,https://pypi.org/project/tensorflow-hub,3267073.0,3268412.0,https://anaconda.org/conda-forge/tensorflow-hub,2021-04-18 18:01:14.779,66991.0,,,,,1.0,,,,,,,,,,,,,,,, +82,Shapely,True,Toblerity/Shapely,,geospatial-data,https://github.com/shapely/shapely,https://github.com/shapely/shapely,BSD-3-Clause,2011-12-31 19:43:11.000,2022-08-25 10:48:19.000000,2022-08-23 22:31:31,464.0,161.0,749.0,2939,,Manipulation and analysis of geometric objects.,134.0,31,2022-08-17 21:23:55,1.8.4,19.0,shapely/shapely,shapely,conda-forge/shapely,,,,32403.0,32403.0,https://pypi.org/project/shapely,7962588.0,8014711.0,https://anaconda.org/conda-forge/shapely,2022-08-18 05:54:21.849,4272338.0,,,,,1.0,221.0,,,,,,,,,,,,,,, +83,Geocoder,True,DenisCarriere/geocoder,,geospatial-data,https://github.com/DenisCarriere/geocoder,https://github.com/DenisCarriere/geocoder,MIT,2014-01-13 04:19:21.000,2022-08-17 17:00:40.000000,2018-10-12 15:53:05,264.0,74.0,217.0,1465,1251.0,Python Geocoder.,73.0,31,2016-09-05 17:57:51,1.17.3,18.0,,geocoder,conda-forge/geocoder,,,,5346.0,5346.0,https://pypi.org/project/geocoder,584779.0,586392.0,https://anaconda.org/conda-forge/geocoder,2019-06-27 16:40:50.469,106470.0,,,,,1.0,,,,,,,geocoder,,,,,,,,, +84,NIPYPE,True,nipy/nipype,,medical-data,https://github.com/nipy/nipype,https://github.com/nipy/nipype,Apache-2.0,2010-07-22 17:06:49.000,2022-08-22 16:42:37.000000,2022-08-22 16:42:32,459.0,362.0,918.0,643,14588.0,Workflows and interfaces for neuroimaging packages.,237.0,31,2022-07-14 15:35:17,1.8.3,43.0,,nipype,conda-forge/nipype,,,,1025.0,1025.0,https://pypi.org/project/nipype,54022.0,60795.0,https://anaconda.org/conda-forge/nipype,2022-07-14 16:27:14.100,494479.0,,,,,1.0,,,,,,,,,,,,,,,, +85,Streamlit,True,streamlit/streamlit,,others,https://github.com/streamlit/streamlit,https://github.com/streamlit/streamlit,Apache-2.0,2019-08-24 00:14:52.000,2022-08-26 00:22:55.000000,2022-08-25 22:04:06,1816.0,609.0,2023.0,20419,,Streamlit The fastest way to build data apps in Python.,151.0,30,2022-08-26 00:36:51,1.12.2,44.0,,streamlit,,,,,375.0,375.0,https://pypi.org/project/streamlit,812809.0,812809.0,,,,,,,,1.0,,8.0,,,,,,,,,,,,,, +86,DeepSpeech,True,mozilla/DeepSpeech,,audio,https://github.com/mozilla/DeepSpeech,https://github.com/mozilla/DeepSpeech,MPL-2.0,2016-06-02 15:04:53.000,2022-08-18 19:38:42.000000,2021-11-17 17:52:52,3419.0,105.0,1963.0,20084,3466.0,"DeepSpeech is an open source embedded (offline, on-..",162.0,30,2020-12-10 15:58:47,0.9.3,100.0,,deepspeech,,,,['tensorflow'],805.0,805.0,https://pypi.org/project/deepspeech,9403.0,28191.0,,,,,,,,1.0,883060.0,,,,,,,,,,,,,,, +87,zipline,True,quantopian/zipline,,financial-data,https://github.com/quantopian/zipline,https://github.com/quantopian/zipline,Apache-2.0,2012-10-19 15:50:29.000,2022-07-20 11:57:42.000000,2020-10-14 16:36:49,4024.0,321.0,652.0,15398,6226.0,"Zipline, a Pythonic Algorithmic Trading Library.",155.0,30,2020-10-05 15:43:07,1.4.1,13.0,,zipline,,,,,879.0,879.0,https://pypi.org/project/zipline,3058.0,3058.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +88,horovod,True,horovod/horovod,,distributed-ml,https://github.com/horovod/horovod,https://github.com/horovod/horovod,,2017-08-09 19:39:59.000,2022-08-26 02:52:23.000000,2022-08-17 22:09:44,2042.0,318.0,1735.0,12675,1225.0,"Distributed training framework for TensorFlow, Keras, PyTorch, and..",155.0,30,2022-06-21 09:19:16,0.25.0,19.0,,horovod,,,,,651.0,651.0,https://pypi.org/project/horovod,72965.0,72965.0,,,,,,,,1.0,,,,,,stable/horovod,,,,,,,,,, +89,mlflow,True,mlflow/mlflow,,ml-experiments,https://github.com/mlflow/mlflow,https://github.com/mlflow/mlflow,Apache-2.0,2018-06-05 16:05:58.000,2022-08-26 03:58:39.000000,2022-08-26 00:55:57,2795.0,810.0,1611.0,12491,3079.0,Open source platform for the machine learning lifecycle.,473.0,30,2022-08-11 10:07:43,1.28.0,56.0,,mlflow,conda-forge/mlflow,,,,,,https://pypi.org/project/mlflow,12783841.0,12802241.0,https://anaconda.org/conda-forge/mlflow,2022-08-19 06:19:56.811,736033.0,,,,,2.0,,,,,,,,,,,,,,,, +90,flair,True,flairNLP/flair,,nlp,https://github.com/flairNLP/flair,https://github.com/flairNLP/flair,,2018-06-11 11:04:18.000,2022-08-25 09:36:29.000000,2022-08-18 08:53:48,1599.0,120.0,1828.0,11962,4694.0,A very simple framework for state-of-the-art Natural Language Processing..,232.0,30,2022-04-10 20:35:57,0.11,20.0,,flair,,,,['pytorch'],1557.0,1557.0,https://pypi.org/project/flair,167776.0,167776.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +91,NNI,True,microsoft/nni,,hyperopt,https://github.com/microsoft/nni,https://github.com/microsoft/nni,MIT,2018-06-01 05:51:44.000,2022-08-26 04:07:52.000000,2022-08-24 02:55:47,1641.0,298.0,1399.0,11842,2781.0,"An open source AutoML toolkit for automate machine learning lifecycle,..",181.0,30,2022-06-22 04:57:13,2.8,36.0,,nni,,,,,262.0,262.0,https://pypi.org/project/nni,10188.0,10188.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +92,Lime,True,marcotcr/lime,,interpretability,https://github.com/marcotcr/lime,https://github.com/marcotcr/lime,BSD-2-Clause,2016-03-15 22:18:10.000,2022-08-15 13:28:57.000000,2021-07-29 23:17:25,1586.0,53.0,529.0,10029,531.0,Lime: Explaining the predictions of any machine learning classifier.,61.0,30,2020-04-03 22:05:03,0.2.0.0,18.0,,lime,conda-forge/lime,,,,2608.0,2608.0,https://pypi.org/project/lime,560437.0,562093.0,https://anaconda.org/conda-forge/lime,2020-06-28 01:02:41.538,112646.0,,,,,1.0,,,,,,,,,,,,,,,, +93,Theano,True,Theano/Theano,,ml-frameworks,https://github.com/Theano/Theano,https://github.com/Theano/Theano,,2011-08-10 03:48:06.000,2022-03-16 06:30:00.008000,2021-11-23 08:52:10,2400.0,583.0,2086.0,9610,28127.0,"Theano is a Python library that allows you to define, optimize, and..",384.0,30,,,8.0,,theano,conda-forge/theano,,,,12804.0,12804.0,https://pypi.org/project/theano,268725.0,297462.0,https://anaconda.org/conda-forge/theano,2022-03-16 06:30:00.008,2097870.0,,,,,2.0,,,,,,,,,,,,,,,, +94,fuzzywuzzy,True,seatgeek/fuzzywuzzy,,nlp,https://github.com/seatgeek/fuzzywuzzy,https://github.com/seatgeek/fuzzywuzzy,GPL-2.0,2011-07-08 19:32:34.000,2021-11-02 23:56:01.000000,2021-09-09 20:54:41,867.0,80.0,103.0,8739,384.0,Fuzzy String Matching in Python.,70.0,30,2020-02-13 22:14:12,0.18.0,23.0,,fuzzywuzzy,conda-forge/fuzzywuzzy,,,,14086.0,14086.0,https://pypi.org/project/fuzzywuzzy,7286475.0,7291739.0,https://anaconda.org/conda-forge/fuzzywuzzy,2020-11-18 12:59:01.409,384291.0,,,,,2.0,,,,,,,,,,,,,,,, +95,AutoKeras,True,keras-team/autokeras,,hyperopt,https://github.com/keras-team/autokeras,https://github.com/keras-team/autokeras,Apache-2.0,2017-11-19 23:18:20.000,2022-08-25 23:58:29.000000,2022-08-25 23:58:28,1337.0,93.0,744.0,8591,1326.0,AutoML library for deep learning.,136.0,30,2022-04-30 05:35:07,1.0.19,56.0,,autokeras,,,,['tensorflow'],353.0,353.0,https://pypi.org/project/autokeras,16984.0,17113.0,,,,,,,,1.0,7357.0,,,,,,,,,,,,,,, +96,Gradio,True,gradio-app/gradio,,others,https://github.com/gradio-app/gradio,https://github.com/gradio-app/gradio,Apache-2.0,2018-12-19 08:24:04.000,2022-08-26 04:04:46.000000,2022-08-25 22:26:27,528.0,193.0,850.0,8461,3966.0,"Wrap UIs around any model, share with anyone.",92.0,30,2022-08-23 16:13:58,3.1.8b,25.0,,gradio,,,,,1143.0,1143.0,https://pypi.org/project/gradio,154136.0,154136.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +97,Pyro,True,pyro-ppl/pyro,,probabilistics,https://github.com/pyro-ppl/pyro,https://github.com/pyro-ppl/pyro,Apache-2.0,2017-06-16 05:03:47.000,2022-08-09 21:05:33.000000,2022-08-05 12:40:16,904.0,197.0,771.0,7568,2321.0,Deep universal probabilistic programming with Python and PyTorch.,129.0,30,2022-03-24 14:48:23,1.8.1,28.0,,pyro-ppl,,,,['pytorch'],817.0,817.0,https://pypi.org/project/pyro-ppl,463066.0,463066.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +98,yfinance,True,ranaroussi/yfinance,,financial-data,https://github.com/ranaroussi/yfinance,https://github.com/ranaroussi/yfinance,Apache-2.0,2017-05-21 10:16:15.000,2022-08-25 14:48:13.000000,2022-07-11 22:20:47,1589.0,462.0,352.0,7512,,Yahoo! Finance market data downloader (+faster Pandas Datareader).,60.0,30,2022-07-11 22:21:12,0.1.74,10.0,,yfinance,ranaroussi/yfinance,,,,13329.0,13329.0,https://pypi.org/project/yfinance,495722.0,499656.0,https://anaconda.org/ranaroussi/yfinance,2021-07-10 20:29:09.532,51146.0,,,,,1.0,,,,,,,,,,,,,,,, +99,Pydub,True,jiaaro/pydub,,audio,https://github.com/jiaaro/pydub,https://github.com/jiaaro/pydub,MIT,2011-05-02 18:42:38.000,2022-07-30 07:39:20.000000,2022-05-14 13:22:02,839.0,231.0,261.0,6323,743.0,Manipulate audio with a simple and easy high level interface.,92.0,30,2021-03-10 02:10:41,0.25.1,31.0,,pydub,conda-forge/pydub,,,,13830.0,13830.0,https://pypi.org/project/pydub,1609467.0,1610096.0,https://anaconda.org/conda-forge/pydub,2021-03-13 05:16:50.142,27683.0,,,,,1.0,,,,,,,,,,,,,,,, +100,einops,True,arogozhnikov/einops,,ml-frameworks,https://github.com/arogozhnikov/einops,https://github.com/arogozhnikov/einops,MIT,2018-09-22 00:45:08.000,2022-08-24 03:41:03.000000,2022-08-24 03:41:03,243.0,33.0,83.0,5503,449.0,"Deep learning operations reinvented (for pytorch, tensorflow, jax and..",20.0,30,2022-03-04 09:31:30,0.4.1,6.0,,einops,conda-forge/einops,,,,3862.0,3862.0,https://pypi.org/project/einops,1007972.0,1008679.0,https://anaconda.org/conda-forge/einops,2022-03-04 10:57:10.315,24768.0,,,,,2.0,,,,,,,,,,,,,,,, +101,dbt,True,fishtown-analytics/dbt,,data-pipelines,https://github.com/dbt-labs/dbt-core,https://github.com/dbt-labs/dbt-core,Apache-2.0,2016-03-10 02:38:00.000,2022-08-26 01:59:49.000000,2022-08-25 13:00:46,961.0,322.0,2692.0,5385,2481.0,dbt (data build tool) enables data analysts and engineers to transform..,233.0,30,2022-08-25 19:17:56,1.2.1,100.0,dbt-labs/dbt-core,dbt,conda-forge/dbt,,,,665.0,665.0,https://pypi.org/project/dbt,169565.0,172628.0,https://anaconda.org/conda-forge/dbt,2021-12-09 22:07:39.668,210630.0,,,,,2.0,521.0,,,,,,,dbt,,,,,,,, +102,MLxtend,True,rasbt/mlxtend,,sklearn-utils,https://github.com/rasbt/mlxtend,https://github.com/rasbt/mlxtend,,2014-08-14 01:56:16.000,2022-08-19 08:21:11.000000,2022-08-10 22:37:38,758.0,109.0,312.0,4051,1424.0,A library of extension and helper modules for Python's data..,90.0,30,2022-05-27 02:02:36,0.20.0,25.0,,mlxtend,conda-forge/mlxtend,,,['sklearn'],6644.0,6644.0,https://pypi.org/project/mlxtend,1437312.0,1440939.0,https://anaconda.org/conda-forge/mlxtend,2022-05-27 14:04:50.178,221306.0,,,,,1.0,,,,,,,,,,,,,,,, +103,sacred,True,IDSIA/sacred,,ml-experiments,https://github.com/IDSIA/sacred,https://github.com/IDSIA/sacred,MIT,2014-03-31 18:05:29.000,2022-08-15 10:36:22.000000,2022-08-15 10:36:22,346.0,89.0,451.0,3890,1322.0,"Sacred is a tool to help you configure, organize, log and reproduce..",100.0,30,2022-03-28 13:51:55,0.8.3,11.0,,sacred,,,,,1533.0,1533.0,https://pypi.org/project/sacred,67966.0,67966.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +104,GeoPandas,True,geopandas/geopandas,,geospatial-data,https://github.com/geopandas/geopandas,https://github.com/geopandas/geopandas,BSD-3-Clause,2013-06-27 17:03:47.000,2022-08-25 19:09:30.000000,2022-08-25 19:09:30,698.0,355.0,965.0,3283,,Python tools for geographic data.,175.0,30,2022-07-24 11:19:18,0.11.1,25.0,,geopandas,conda-forge/geopandas,,,['pandas'],15193.0,15193.0,https://pypi.org/project/geopandas,2901186.0,2925979.0,https://anaconda.org/conda-forge/geopandas,2022-07-24 18:57:53.018,1907512.0,,,,,2.0,1583.0,,,,,,,,,,,,,,, +105,Keras Tuner,True,keras-team/keras-tuner,,hyperopt,https://github.com/keras-team/keras-tuner,https://github.com/keras-team/keras-tuner,Apache-2.0,2019-06-06 22:38:21.000,2022-08-26 00:05:48.000000,2022-08-25 23:57:36,334.0,176.0,227.0,2593,908.0,Hyperparameter tuning for humans.,50.0,30,2022-07-16 04:22:02,1.1.3,14.0,,keras-tuner,,,,['tensorflow'],1600.0,1600.0,https://pypi.org/project/keras-tuner,613515.0,613515.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +106,scikit-optimize,True,scikit-optimize/scikit-optimize,,hyperopt,https://github.com/scikit-optimize/scikit-optimize,https://github.com/scikit-optimize/scikit-optimize,BSD-3-Clause,2016-03-20 21:10:54.000,2022-07-22 09:53:11.000000,2021-10-12 13:32:38,423.0,215.0,387.0,2375,1570.0,Sequential model-based optimization with a `scipy.optimize`..,76.0,30,2021-10-12 15:33:19,0.9.0,23.0,,scikit-optimize,conda-forge/scikit-optimize,,,,3050.0,3050.0,https://pypi.org/project/scikit-optimize,791430.0,800820.0,https://anaconda.org/conda-forge/scikit-optimize,2021-12-15 05:01:56.230,572800.0,,,,,1.0,,,,,,,,,,,,,,,, +107,category_encoders,True,scikit-learn-contrib/category_encoders,,sklearn-utils,https://github.com/scikit-learn-contrib/category_encoders,https://github.com/scikit-learn-contrib/category_encoders,BSD-3-Clause,2015-11-29 19:32:37.000,2022-08-22 09:58:47.000000,2022-06-02 14:42:09,355.0,63.0,186.0,2022,794.0,A library of sklearn compatible categorical variable encoders.,52.0,30,2022-06-02 14:44:54,2.5.0,15.0,,category_encoders,conda-forge/category_encoders,,,['sklearn'],3821.0,3821.0,https://pypi.org/project/category_encoders,946696.0,949140.0,https://anaconda.org/conda-forge/category_encoders,2022-06-02 22:08:38.573,178446.0,,,,,1.0,,,,,,,,,,,,,,,, +108,Lifelines,True,CamDavidsonPilon/lifelines,,medical-data,https://github.com/CamDavidsonPilon/lifelines,https://github.com/CamDavidsonPilon/lifelines,MIT,2013-08-28 00:16:42.000,2022-08-25 19:30:09.000000,2022-07-17 13:16:06,475.0,225.0,648.0,1940,2199.0,Survival analysis in Python.,101.0,30,2022-06-26 02:12:26,0.27.1,100.0,,lifelines,conda-forge/lifelines,,,,1023.0,1023.0,https://pypi.org/project/lifelines,374186.0,377008.0,https://anaconda.org/conda-forge/lifelines,2022-05-18 22:54:56.806,208893.0,,,,,1.0,,,,,,,,,,,,,,,, +109,dask.distributed,True,dask/distributed,,distributed-ml,https://github.com/dask/distributed,https://github.com/dask/distributed,BSD-3-Clause,2015-09-13 18:42:29.000,2022-08-26 03:04:19.000000,2022-08-26 00:49:29,620.0,967.0,1959.0,1390,,A distributed task scheduler for Dask.,285.0,30,,,146.0,,distributed,conda-forge/distributed,,,,24717.0,24717.0,https://pypi.org/project/distributed,4926633.0,5029992.0,https://anaconda.org/conda-forge/distributed,2022-08-19 23:15:11.293,7751974.0,,,,,1.0,,,,,,,,,,,,,,,, +110,ipyleaflet,True,jupyter-widgets/ipyleaflet,,geospatial-data,https://github.com/jupyter-widgets/ipyleaflet,https://github.com/jupyter-widgets/ipyleaflet,MIT,2014-05-07 16:32:10.000,2022-08-23 15:32:17.000000,2022-08-23 09:30:51,320.0,184.0,316.0,1289,1129.0,A Jupyter - Leaflet.js bridge.,80.0,30,2022-08-23 09:10:35,0.17.1,64.0,,ipyleaflet,conda-forge/ipyleaflet,,,['jupyter'],2634.0,2634.0,https://pypi.org/project/ipyleaflet,110666.0,172022.0,https://anaconda.org/conda-forge/ipyleaflet,2022-08-23 09:37:45.585,873126.0,,,,,2.0,,,jupyter-leaflet,https://www.npmjs.com/package/jupyter-leaflet,49715.0,,,,,,,,,,, +111,Graphviz,True,xflr6/graphviz,,data-viz,https://github.com/xflr6/graphviz,https://github.com/xflr6/graphviz,MIT,2014-01-12 17:49:29.000,2022-07-27 21:06:33.000000,2022-07-27 21:04:14,180.0,6.0,133.0,1260,1173.0,Simple Python interface for Graphviz.,19.0,30,,,,,graphviz,,,,,34176.0,34176.0,https://pypi.org/project/graphviz,10190767.0,10190767.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +112,pmdarima,True,alkaline-ml/pmdarima,,time-series-data,https://github.com/alkaline-ml/pmdarima,https://github.com/alkaline-ml/pmdarima,MIT,2017-03-30 14:58:30.000,2022-08-23 18:43:42.000000,2022-08-23 11:55:51,211.0,26.0,259.0,1240,1063.0,A statistical library designed to fill the void in Python's time series..,21.0,30,2022-08-23 15:13:51,2.0.1,40.0,,pmdarima,,,,,2482.0,2482.0,https://pypi.org/project/pmdarima,1528180.0,1528180.0,,,,,,,,1.0,,8.0,,,,,,,,,,,,,, +113,Fiona,True,Toblerity/Fiona,,geospatial-data,https://github.com/Toblerity/Fiona,https://github.com/Toblerity/Fiona,BSD-3-Clause,2011-12-31 19:47:00.000,2022-08-02 13:05:57.000000,2022-03-01 20:04:14,173.0,74.0,608.0,941,1294.0,Fiona reads and writes geographic data files.,66.0,30,2022-02-07 17:34:18,1.8.21,40.0,,fiona,conda-forge/fiona,,,,9414.0,9414.0,https://pypi.org/project/fiona,3075392.0,3117821.0,https://anaconda.org/conda-forge/fiona,2022-05-30 12:36:18.405,3267101.0,,,,,2.0,,,,,,,,,,,,,,,, +114,TensorFlow Transform,True,tensorflow/transform,,tensorflow-utils,https://github.com/tensorflow/transform,https://github.com/tensorflow/transform,Apache-2.0,2017-02-10 00:36:53.000,2022-08-25 21:28:01.000000,2022-08-25 21:13:31,188.0,32.0,155.0,930,815.0,Input pipeline framework.,27.0,30,2022-08-25 21:28:01,1.10.0,40.0,,tensorflow-transform,,,,['tensorflow'],1008.0,1008.0,https://pypi.org/project/tensorflow-transform,3315397.0,3315397.0,,,,,,,,2.0,,8.0,,,,,,,,,,,,,, +115,Airflow,True,apache/airflow,,data-pipelines,https://github.com/apache/airflow,https://github.com/apache/airflow,Apache-2.0,2015-04-13 18:04:58.000,2022-08-26 03:35:02.000000,2022-08-25 22:31:18,10703.0,702.0,5299.0,27527,,"Platform to programmatically author, schedule, and monitor workflows.",2525.0,29,2022-08-23 14:41:06,2.3.4,52.0,,apache-airflow,conda-forge/airflow,apache/airflow,,,,,https://pypi.org/project/apache-airflow,8900957.0,9852469.0,https://anaconda.org/conda-forge/airflow,2022-08-25 02:11:05.730,695435.0,https://hub.docker.com/r/apache/airflow,2022-08-23 12:48:46.602165,383.0,82408508.0,2.0,337178.0,,,,,stable/airflow,,,,,,,,,, +116,MXNet,True,apache/incubator-mxnet,,ml-frameworks,https://github.com/apache/incubator-mxnet,https://github.com/apache/incubator-mxnet,Apache-2.0,2015-04-30 16:21:15.000,2022-08-25 12:39:40.000000,2022-08-23 13:33:02,6527.0,1784.0,7742.0,20069,11886.0,"Lightweight, Portable, Flexible Distributed/Mobile Deep Learning..",980.0,29,2022-05-10 20:10:05,1.9.1,34.0,,mxnet,mxnet,,,['mxnet'],,,https://pypi.org/project/mxnet,411080.0,411561.0,https://anaconda.org/anaconda/mxnet,2022-05-02 19:57:38.379,8025.0,,,,,2.0,25388.0,,,,,,,,,,,,,,, +117,pytorch-lightning,True,PyTorchLightning/pytorch-lightning,,ml-frameworks,https://github.com/Lightning-AI/lightning,https://github.com/Lightning-AI/lightning,Apache-2.0,2019-03-31 00:45:57.000,2022-08-26 03:20:24.000000,2022-08-25 18:57:48,2499.0,446.0,4843.0,19814,7471.0,The lightweight PyTorch wrapper for high-performance..,743.0,29,2022-08-25 19:06:42,1.7.3,100.0,Lightning-AI/lightning,pytorch-lightning,conda-forge/pytorch-lightning,,,['pytorch'],,,https://pypi.org/project/pytorch-lightning,1847536.0,1867712.0,https://anaconda.org/conda-forge/pytorch-lightning,2022-08-18 05:29:54.287,518966.0,,,,,2.0,7992.0,-6.0,,,,,,,,,,,,,, +118,fairseq,True,pytorch/fairseq,,nlp,https://github.com/facebookresearch/fairseq,https://github.com/facebookresearch/fairseq,MIT,2017-08-29 16:26:12.000,2022-08-26 01:52:07.000000,2022-08-24 18:06:45,4652.0,642.0,2896.0,18982,,Facebook AI Research Sequence-to-Sequence Toolkit written in Python.,399.0,29,2022-06-27 19:32:58,0.12.2,16.0,facebookresearch/fairseq,fairseq,,,,['pytorch'],917.0,917.0,https://pypi.org/project/fairseq,40057.0,40062.0,,,,,,,,2.0,261.0,,,,,,,,,,,,,,, +119,Milvus,True,milvus-io/milvus,,nn-search,https://github.com/milvus-io/milvus,https://github.com/milvus-io/milvus,Apache-2.0,2019-09-16 06:43:43.000,2022-08-26 04:08:09.000000,2022-08-26 02:10:54,1448.0,260.0,5446.0,11754,15380.0,An open source embedding vector similarity search engine powered by..,219.0,29,2022-08-15 01:20:34,2.1.1,100.0,,pymilvus,,milvusdb/milvus,,,,,https://pypi.org/project/pymilvus,129509.0,171595.0,,,,https://hub.docker.com/r/milvusdb/milvus,2022-08-26 02:22:18.806047,21.0,1279749.0,1.0,44183.0,,,,,,,,,,,,,,, +120,dgl,True,dmlc/dgl,,graph,https://github.com/dmlc/dgl,https://github.com/dmlc/dgl,Apache-2.0,2018-04-20 14:49:09.000,2022-08-26 01:13:46.000000,2022-08-25 15:16:44,2376.0,224.0,1464.0,10183,2432.0,"Python package built to ease deep learning on graph, on top of existing..",227.0,29,2022-07-18 15:43:47,0.9.0,26.0,,dgl,,,,,30.0,30.0,https://pypi.org/project/dgl,32489.0,32489.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +121,Seaborn,True,mwaskom/seaborn,,data-viz,https://github.com/mwaskom/seaborn,https://github.com/mwaskom/seaborn,BSD-3-Clause,2012-06-18 18:41:19.000,2022-08-26 02:40:14.000000,2022-08-26 02:19:09,1564.0,98.0,1996.0,9729,3011.0,Statistical data visualization using matplotlib.,173.0,29,2021-08-16 00:39:03,0.11.2,30.0,,seaborn,conda-forge/seaborn,,,,,,https://pypi.org/project/seaborn,7566871.0,7629242.0,https://anaconda.org/conda-forge/seaborn,2021-08-16 06:42:17.619,4490605.0,,,,,2.0,230.0,-6.0,,,,,,,,,,,,,, +122,TPOT,True,EpistasisLab/tpot,,hyperopt,https://github.com/EpistasisLab/tpot,https://github.com/EpistasisLab/tpot,LGPL-3.0,2015-11-03 21:08:40.000,2022-08-25 21:48:14.000000,2022-07-29 17:42:53,1466.0,253.0,605.0,8707,2390.0,A Python Automated Machine Learning tool that optimizes machine..,112.0,29,2021-01-06 15:19:33,0.11.7,27.0,,tpot,conda-forge/tpot,,,['sklearn'],1583.0,1583.0,https://pypi.org/project/tpot,40618.0,42948.0,https://anaconda.org/conda-forge/tpot,2021-03-05 04:04:38.005,165490.0,,,,,2.0,,,,,,,,,,,,,,,, +123,Modin,True,modin-project/modin,,data-containers,https://github.com/modin-project/modin,https://github.com/modin-project/modin,Apache-2.0,2018-06-21 21:35:05.000,2022-08-25 23:24:15.000000,2022-08-25 22:22:34,537.0,864.0,1997.0,7709,1929.0,Modin: Speed up your Pandas workflows by changing a single line of..,102.0,29,2022-06-25 00:03:34,0.15.2,53.0,,modin,,,,['pandas'],708.0,708.0,https://pypi.org/project/modin,183465.0,187468.0,,,,,,,,2.0,196158.0,,,,,,,,,,,,,,, +124,auto-sklearn,True,automl/auto-sklearn,,hyperopt,https://github.com/automl/auto-sklearn,https://github.com/automl/auto-sklearn,BSD-3-Clause,2015-07-02 15:38:10.000,2022-08-24 16:22:23.000000,2022-08-22 11:54:57,1155.0,110.0,806.0,6453,2627.0,Automated Machine Learning with scikit-learn.,86.0,29,2022-08-18 18:55:56,0.14.7,34.0,,auto-sklearn,,,,['sklearn'],313.0,313.0,https://pypi.org/project/auto-sklearn,40500.0,40500.0,,,,,,,,2.0,37.0,,,,,,,,,,,,,,, +125,Bayesian Optimization,True,fmfn/BayesianOptimization,,hyperopt,https://github.com/fmfn/BayesianOptimization,https://github.com/fmfn/BayesianOptimization,MIT,2014-06-06 08:18:56.000,2022-08-25 23:47:34.000000,2022-08-17 23:22:03,1301.0,19.0,240.0,6217,236.0,A Python implementation of global optimization with..,35.0,29,2020-05-16 16:03:51,1.2.0,7.0,,bayesian-optimization,,,,,1326.0,1326.0,https://pypi.org/project/bayesian-optimization,204917.0,204918.0,,,,,,,,2.0,96.0,,,,,,,,,,,,,,, +126,Autograd,True,HIPS/autograd,,others,https://github.com/HIPS/autograd,https://github.com/HIPS/autograd,MIT,2014-11-24 15:50:23.000,2022-06-29 14:53:21.163000,2022-06-15 10:28:52,797.0,146.0,225.0,5947,1381.0,Efficiently computes derivatives of numpy code.,52.0,29,2015-03-05 19:30:11,1.0,5.0,,autograd,conda-forge/autograd,,,,3818.0,3818.0,https://pypi.org/project/autograd,1169672.0,1172845.0,https://anaconda.org/conda-forge/autograd,2022-06-29 14:53:21.163,228501.0,,,,,2.0,,,,,,,,,,,,,,,, +127,espnet,True,espnet/espnet,,audio,https://github.com/espnet/espnet,https://github.com/espnet/espnet,Apache-2.0,2017-12-13 00:45:11.000,2022-08-26 03:54:33.000000,2022-08-24 09:42:04,1600.0,304.0,1597.0,5399,15615.0,End-to-End Speech Processing Toolkit.,285.0,29,2022-08-02 01:00:13,.202207,45.0,,espnet,,,,,67.0,67.0,https://pypi.org/project/espnet,11117.0,11118.0,,,,,,,,1.0,76.0,,,,,,,,,,,,,,, +128,GluonCV,True,dmlc/gluon-cv,,image,https://github.com/dmlc/gluon-cv,https://github.com/dmlc/gluon-cv,Apache-2.0,2018-02-26 01:33:21.000,2022-08-14 03:28:00.000000,2022-08-11 16:47:31,1154.0,45.0,765.0,5294,899.0,Gluon CV Toolkit.,117.0,29,2021-03-09 00:20:06,0.10.0,10.0,,gluoncv,,,,['mxnet'],843.0,843.0,https://pypi.org/project/gluoncv,571263.0,571263.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +129,ClearML,True,allegroai/clearml,,ml-experiments,https://github.com/allegroai/clearml,https://github.com/allegroai/clearml,Apache-2.0,2019-06-10 08:18:32.000,2022-08-23 20:19:20.000000,2022-08-23 20:19:15,456.0,268.0,333.0,3529,1772.0,ClearML - Auto-Magical Suite of tools to streamline your ML..,52.0,29,2022-08-10 18:22:29,1.6.4,66.0,,clearml,,allegroai/trains,,,293.0,293.0,https://pypi.org/project/clearml,94116.0,94921.0,,,,https://hub.docker.com/r/allegroai/trains,2020-10-05 10:16:46.865671,,30125.0,2.0,503.0,,,,,,,,,,,,,,, +130,TextDistance,True,life4/textdistance,,nlp,https://github.com/life4/textdistance,https://github.com/life4/textdistance,MIT,2017-05-05 08:46:10.000,2022-08-21 20:28:18.519000,2022-08-21 06:56:46,230.0,,,2934,334.0,"Compute distance between sequences. 30+ algorithms, pure python..",12.0,29,2022-08-21 07:00:39,4.4.0,10.0,,textdistance,conda-forge/textdistance,,,,2646.0,2646.0,https://pypi.org/project/textdistance,640577.0,644080.0,https://anaconda.org/conda-forge/textdistance,2022-08-21 20:28:18.519,177902.0,,,,,2.0,831.0,,,,,,,,,,,,,,, +131,GPyTorch,True,cornellius-gp/gpytorch,,probabilistics,https://github.com/cornellius-gp/gpytorch,https://github.com/cornellius-gp/gpytorch,MIT,2017-06-09 14:48:20.000,2022-08-24 21:55:15.000000,2022-08-24 21:55:14,418.0,283.0,857.0,2839,3672.0,A highly efficient and modular implementation of Gaussian Processes..,99.0,29,2022-08-08 21:24:31,1.8.1,28.0,,gpytorch,,,,['pytorch'],683.0,683.0,https://pypi.org/project/gpytorch,262344.0,262344.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +132,datashader,True,holoviz/datashader,,data-viz,https://github.com/holoviz/datashader,https://github.com/holoviz/datashader,BSD-3-Clause,2015-12-23 18:02:20.000,2022-08-10 15:56:58.260000,2022-08-10 14:48:29,343.0,118.0,385.0,2816,1360.0,Quickly and accurately render even the largest data.,49.0,29,2022-08-10 16:21:44,0.14.2,27.0,,datashader,conda-forge/datashader,,,,1325.0,1325.0,https://pypi.org/project/datashader,42191.0,48750.0,https://anaconda.org/conda-forge/datashader,2022-08-10 15:56:58.260,373902.0,,,,,2.0,,,,,,,,,,,,,,,, +133,xarray,True,pydata/xarray,,data-containers,https://github.com/pydata/xarray,https://github.com/pydata/xarray,Apache-2.0,2013-09-30 17:21:10.000,2022-08-25 15:56:11.000000,2022-08-25 15:56:11,801.0,875.0,2481.0,2655,,N-D labeled arrays and datasets in Python.,390.0,29,2022-07-22 16:24:17,2022.06.0,68.0,,xarray,conda-forge/xarray,,,,11828.0,11828.0,https://pypi.org/project/xarray,1595916.0,1670257.0,https://anaconda.org/conda-forge/xarray,2022-07-26 14:02:33.934,5724297.0,,,,,2.0,,,,,,,,,,,,,,,, +134,sklearn-pandas,True,scikit-learn-contrib/sklearn-pandas,,data-containers,https://github.com/scikit-learn-contrib/sklearn-pandas,https://github.com/scikit-learn-contrib/sklearn-pandas,Zlib,2013-04-22 22:55:20.000,2022-08-08 04:41:44.000000,2022-07-17 20:23:59,379.0,25.0,127.0,2639,289.0,Pandas integration with sklearn.,39.0,29,2021-05-08 08:32:08,2.1.0,3.0,,sklearn-pandas,,,,"['sklearn', 'pandas']",4415.0,4415.0,https://pypi.org/project/sklearn-pandas,578735.0,578735.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +135,mrjob,True,Yelp/mrjob,,data-pipelines,https://github.com/Yelp/mrjob,https://github.com/Yelp/mrjob,Apache-2.0,2010-10-13 18:35:21.000,2022-07-14 07:58:49.000000,2020-11-16 22:20:52,576.0,204.0,1093.0,2582,8622.0,Run MapReduce jobs on Hadoop or Amazon Web Services.,142.0,29,,,13.0,,mrjob,conda-forge/mrjob,,,,1058.0,1058.0,https://pypi.org/project/mrjob,76329.0,83184.0,https://anaconda.org/conda-forge/mrjob,2022-02-06 18:33:13.189,486769.0,,,,,2.0,,,,,,,,,,,,,,,, +136,ImageHash,True,JohannesBuchner/imagehash,,image,https://github.com/JohannesBuchner/imagehash,https://github.com/JohannesBuchner/imagehash,BSD-2-Clause,2013-03-02 23:32:48.000,2022-08-08 21:57:11.000000,2021-09-07 19:15:32,299.0,15.0,94.0,2478,209.0,A Python Perceptual Image Hashing Module.,20.0,29,2021-03-25 13:49:48,4.1.0,6.0,,ImageHash,conda-forge/imagehash,,,,5754.0,5754.0,https://pypi.org/project/ImageHash,1382212.0,1385529.0,https://anaconda.org/conda-forge/imagehash,2021-07-15 15:00:27.543,228922.0,,,,,2.0,,,,,,,,,,,,,,,, +137,python-magic,True,ahupp/python-magic,,data-loading,https://github.com/ahupp/python-magic,https://github.com/ahupp/python-magic,,2010-03-31 22:40:33.000,2022-06-20 14:28:19.000000,2022-06-20 14:28:18,238.0,28.0,155.0,2172,311.0,A python wrapper for libmagic.,55.0,29,,,7.0,,python-magic,conda-forge/python-magic,,,,30569.0,30569.0,https://pypi.org/project/python-magic,5921333.0,5923831.0,https://anaconda.org/conda-forge/python-magic,2022-06-10 14:18:00.350,159928.0,,,,,2.0,,,,,,,,,,,,,,,, +138,xlrd,True,python-excel/xlrd,,data-loading,https://github.com/python-excel/xlrd,https://github.com/python-excel/xlrd,,2012-03-07 04:50:48.000,2022-03-07 22:18:34.000000,2021-08-21 19:45:33,424.0,,,2009,503.0,Please use openpyxl where you can...,51.0,29,,,4.0,,xlrd,conda-forge/xlrd,,,,100848.0,100848.0,https://pypi.org/project/xlrd,18012488.0,18052538.0,https://anaconda.org/conda-forge/xlrd,2021-01-09 20:35:27.639,2603310.0,,,,,2.0,,,,,,,,,,,,,,,, +139,datasketch,True,ekzhu/datasketch,,data-containers,https://github.com/ekzhu/datasketch,https://github.com/ekzhu/datasketch,MIT,2015-03-20 01:21:46.000,2022-08-21 03:02:54.000000,2022-08-19 15:44:41,241.0,35.0,104.0,1786,209.0,"MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,..",24.0,29,2022-08-21 03:02:55,1.5.8,25.0,,datasketch,,,,,439.0,439.0,https://pypi.org/project/datasketch,722932.0,722932.0,,,,,,,,2.0,19.0,,,,,,,,,,,,,,, +140,pyLDAvis,True,bmabey/pyLDAvis,,interpretability,https://github.com/bmabey/pyLDAvis,https://github.com/bmabey/pyLDAvis,BSD-3-Clause,2015-04-09 22:48:03.000,2022-06-22 04:24:13.000000,2021-03-24 13:03:31,326.0,84.0,78.0,1634,240.0,Python library for interactive topic model visualization. Port of..,32.0,29,2021-03-24 13:05:21,3.3.1,5.0,,pyldavis,conda-forge/pyldavis,,,['jupyter'],3812.0,3812.0,https://pypi.org/project/pyldavis,639247.0,640166.0,https://anaconda.org/conda-forge/pyldavis,2021-03-24 15:17:07.309,45957.0,,,,,1.0,,,,,,,,,,,,,,,, +141,TF Model Optimization,True,tensorflow/model-optimization,,tensorflow-utils,https://github.com/tensorflow/model-optimization,https://github.com/tensorflow/model-optimization,Apache-2.0,2018-10-31 20:34:28.000,2022-08-23 13:59:49.000000,2022-08-23 13:59:42,276.0,149.0,156.0,1283,772.0,A toolkit to optimize ML models for deployment for..,71.0,29,2022-07-20 20:42:08,0.7.3,18.0,,tensorflow-model-optimization,,,,['tensorflow'],2044.0,2044.0,https://pypi.org/project/tensorflow-model-optimization,143586.0,143586.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +142,TensorFlow Text,True,tensorflow/text,,nlp,https://github.com/tensorflow/text,https://github.com/tensorflow/text,Apache-2.0,2019-05-29 22:10:03.000,2022-08-22 20:37:31.000000,2022-08-22 20:35:42,227.0,33.0,142.0,980,724.0,Making text a first-class citizen in TensorFlow.,91.0,29,2022-05-18 02:27:52,2.9.0,41.0,,tensorflow-text,,,,['tensorflow'],2169.0,2169.0,https://pypi.org/project/tensorflow-text,2238731.0,2238731.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +143,pyproj,True,pyproj4/pyproj,,geospatial-data,https://github.com/pyproj4/pyproj,https://github.com/pyproj4/pyproj,MIT,2014-12-29 21:38:25.000,2022-08-26 01:27:23.000000,2022-08-26 01:25:09,181.0,10.0,495.0,782,,Python interface to PROJ (cartographic projections and coordinate..,52.0,29,2022-04-22 01:47:17,3.3.1,40.0,,pyproj,conda-forge/pyproj,,,,15517.0,15517.0,https://pypi.org/project/pyproj,4986964.0,5037373.0,https://anaconda.org/conda-forge/pyproj,2022-06-17 07:26:21.099,4032728.0,,,,,2.0,,,,,,,,,,,,,,,, +144,Bottleneck,True,pydata/bottleneck,,data-containers,https://github.com/pydata/bottleneck,https://github.com/pydata/bottleneck,BSD-2-Clause,2010-11-27 23:21:22.000,2022-07-03 00:00:33.345000,2022-07-02 18:32:46,80.0,35.0,190.0,777,1258.0,Fast NumPy array functions written in C.,25.0,29,,,11.0,,Bottleneck,conda-forge/bottleneck,,,,34812.0,34812.0,https://pypi.org/project/Bottleneck,430586.0,464135.0,https://anaconda.org/conda-forge/bottleneck,2022-07-03 00:00:33.345,2516243.0,,,,,2.0,,,,,,,,,,,,,,,, +145,Bokeh,True,bokeh/bokeh,,data-viz,https://github.com/bokeh/bokeh,https://github.com/bokeh/bokeh,BSD-3-Clause,2012-03-26 15:40:01.000,2022-08-24 18:52:45.000000,2022-08-24 17:39:26,3878.0,684.0,6273.0,16627,,"Interactive Data Visualization in the browser, from Python.",612.0,28,,,45.0,,bokeh,conda-forge/bokeh,,,,151.0,151.0,https://pypi.org/project/bokeh,3685342.0,3814327.0,https://anaconda.org/conda-forge/bokeh,2022-08-15 18:06:05.668,8255057.0,,,,,2.0,,,,,,,,,,,,,,,, +146,PyTorch Geometric,True,rusty1s/pytorch_geometric,,graph,https://github.com/pyg-team/pytorch_geometric,https://github.com/pyg-team/pytorch_geometric,MIT,2017-10-06 16:03:03.000,2022-08-26 01:10:45.000000,2022-08-25 08:44:57,2702.0,950.0,1692.0,15342,5749.0,Geometric Deep Learning Extension Library for PyTorch.,303.0,28,2022-08-17 10:32:00,2.1.0,32.0,pyg-team/pytorch_geometric,torch-geometric,,,,['pytorch'],,,https://pypi.org/project/torch-geometric,91559.0,91559.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +147,pyecharts,True,pyecharts/pyecharts,,data-viz,https://github.com/pyecharts/pyecharts,https://github.com/pyecharts/pyecharts,MIT,2017-06-22 02:50:25.000,2022-06-20 01:10:59.000000,2022-04-25 06:07:07,2674.0,22.0,1588.0,12654,1523.0,Python Echarts Plotting Library.,30.0,28,,,,,pyecharts,,,https://github.com/pyecharts/pyecharts/blob/master/README.en.md,['jupyter'],2448.0,2448.0,https://pypi.org/project/pyecharts,44340.0,44340.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +148,Prefect,True,PrefectHQ/prefect,,data-pipelines,https://github.com/PrefectHQ/prefect,https://github.com/PrefectHQ/prefect,Apache-2.0,2018-06-29 21:59:26.000,2022-08-26 02:16:57.000000,2022-08-25 21:26:44,954.0,656.0,1919.0,9893,,The easiest way to automate your data.,60.0,28,2022-08-23 18:19:19,2.2.0,116.0,,prefect,conda-forge/prefect,,,,1099.0,1099.0,https://pypi.org/project/prefect,395970.0,403535.0,https://anaconda.org/conda-forge/prefect,2022-08-23 22:15:51.972,310172.0,,,,,2.0,,,,,,,,,,,,,,,, +149,Vowpal Wabbit,True,VowpalWabbit/vowpal_wabbit,,ml-frameworks,https://github.com/VowpalWabbit/vowpal_wabbit,https://github.com/VowpalWabbit/vowpal_wabbit,BSD-3-Clause,2009-07-31 19:36:58.000,2022-08-25 20:56:59.000000,2022-08-25 20:44:37,1714.0,126.0,1064.0,8027,10006.0,Vowpal Wabbit is a machine learning system which pushes the..,322.0,28,2022-08-10 13:59:34,9.3.0,23.0,,vowpalwabbit,,,,,,,https://pypi.org/project/vowpalwabbit,92494.0,92494.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +150,DeepSpeed,True,microsoft/DeepSpeed,,distributed-ml,https://github.com/microsoft/DeepSpeed,https://github.com/microsoft/DeepSpeed,MIT,2020-01-23 18:35:18.000,2022-08-26 00:20:30.000000,2022-08-25 19:19:44,828.0,470.0,509.0,7694,1096.0,DeepSpeed is a deep learning optimization library that makes..,127.0,28,2022-08-25 19:20:36,0.7.2,36.0,,deepspeed,,deepspeed/deepspeed,,['pytorch'],344.0,344.0,https://pypi.org/project/deepspeed,222645.0,223098.0,,,,https://hub.docker.com/r/deepspeed/deepspeed,2022-06-06 22:20:20.884439,3.0,14069.0,2.0,,,,,,,,,,,,,,,, +151,Kedro,True,quantumblacklabs/kedro,,data-pipelines,https://github.com/kedro-org/kedro,https://github.com/kedro-org/kedro,Apache-2.0,2019-04-18 10:29:56.000,2022-08-25 23:09:32.000000,2022-08-25 09:17:43,680.0,151.0,722.0,7519,,"A Python framework for creating reproducible, maintainable and modular..",160.0,28,2022-07-08 15:55:34,0.18.2,32.0,kedro-org/kedro,kedro,,,,,1010.0,1010.0,https://pypi.org/project/kedro,418419.0,418419.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +152,Catboost,True,catboost/catboost,,ml-frameworks,https://github.com/catboost/catboost,https://github.com/catboost/catboost,Apache-2.0,2017-07-18 05:29:04.000,2022-08-23 10:34:43.000000,2022-08-21 14:01:38,993.0,405.0,1447.0,6699,23728.0,"A fast, scalable, high performance Gradient Boosting on Decision..",1015.0,28,2022-05-19 07:31:43,1.0.6,79.0,,catboost,conda-forge/catboost,,,,,,https://pypi.org/project/catboost,2657927.0,2681064.0,https://anaconda.org/conda-forge/catboost,2022-05-19 10:30:35.525,1105936.0,,,,,2.0,85700.0,,,,,,,,,,,,,,, +153,Datasette,True,simonw/datasette,,others,https://github.com/simonw/datasette,https://github.com/simonw/datasette,Apache-2.0,2017-10-23 00:39:03.000,2022-08-24 00:11:59.000000,2022-08-24 00:11:45,414.0,371.0,997.0,6376,2062.0,An open source multi-tool for exploring and publishing data.,67.0,28,2022-08-14 17:43:05,0.62,100.0,,datasette,,,,,732.0,732.0,https://pypi.org/project/datasette,240948.0,240948.0,,,,,,,,2.0,39.0,,,,,,,datasette,,,,,,,, +154,Hyperopt,True,hyperopt/hyperopt,,hyperopt,https://github.com/hyperopt/hyperopt,https://github.com/hyperopt/hyperopt,,2011-09-06 22:24:59.000,2022-07-12 10:19:09.000000,2021-11-29 10:21:36,860.0,371.0,235.0,6357,1194.0,Distributed Asynchronous Hyperparameter Optimization in Python.,93.0,28,,,7.0,,hyperopt,conda-forge/hyperopt,,,,7442.0,7442.0,https://pypi.org/project/hyperopt,1771360.0,1781970.0,https://anaconda.org/conda-forge/hyperopt,2022-04-30 16:43:00.797,498681.0,,,,,2.0,,,,,,,,,,,,,,,, +155,Metaflow,True,Netflix/metaflow,,ml-experiments,https://github.com/Netflix/metaflow,https://github.com/Netflix/metaflow,Apache-2.0,2019-09-17 17:48:25.000,2022-08-25 14:55:14.427000,2022-08-24 23:05:26,504.0,192.0,232.0,5918,547.0,Build and manage real-life data science projects with ease.,54.0,28,2022-08-25 03:46:17,2.7.7,56.0,,metaflow,conda-forge/metaflow,,,,311.0,311.0,https://pypi.org/project/metaflow,61990.0,63965.0,https://anaconda.org/conda-forge/metaflow,2022-08-25 14:55:14.427,63204.0,,,,,2.0,,,,,,,,,,,,,,,, +156,folium,True,python-visualization/folium,,geospatial-data,https://github.com/python-visualization/folium,https://github.com/python-visualization/folium,MIT,2013-05-09 04:21:35.000,2022-05-19 13:05:50.000000,2022-05-06 07:27:35,2079.0,212.0,726.0,5866,,Python Data. Leaflet.js Maps.,129.0,28,2021-11-19 21:01:43,0.12.1.post1,22.0,,folium,conda-forge/folium,,,,17664.0,17664.0,https://pypi.org/project/folium,816149.0,829827.0,https://anaconda.org/conda-forge/folium,2021-12-03 19:47:05.533,1053266.0,,,,,2.0,,,,,,,,,,,,,,,, +157,csvkit,True,wireservice/csvkit,,data-loading,https://github.com/wireservice/csvkit,https://github.com/wireservice/csvkit,MIT,2011-04-01 03:00:30.000,2022-07-26 09:39:48.000000,2022-04-11 19:28:23,564.0,69.0,789.0,5082,1784.0,"A suite of utilities for converting to and working with CSV, the king of..",102.0,28,,,7.0,,csvkit,conda-forge/csvkit,,,,1135.0,1135.0,https://pypi.org/project/csvkit,157652.0,158682.0,https://anaconda.org/conda-forge/csvkit,2022-03-20 15:46:37.102,66950.0,,,,,2.0,,,,,,,,,,,,,,,, +158,InterpretML,True,interpretml/interpret,,interpretability,https://github.com/interpretml/interpret,https://github.com/interpretml/interpret,MIT,2019-05-03 05:47:52.000,2022-08-26 03:18:48.000000,2022-08-26 02:59:46,594.0,99.0,204.0,4917,1791.0,Fit interpretable models. Explain blackbox machine learning.,31.0,28,2021-09-23 20:41:03,0.2.7,31.0,,interpret,,,,['jupyter'],264.0,264.0,https://pypi.org/project/interpret,90135.0,90135.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +159,PML,True,KevinMusgrave/pytorch-metric-learning,,pytorch-utils,https://github.com/KevinMusgrave/pytorch-metric-learning,https://github.com/KevinMusgrave/pytorch-metric-learning,MIT,2019-10-23 17:20:35.000,2022-08-13 12:42:43.000000,2022-08-13 12:41:33,559.0,52.0,325.0,4688,963.0,"The easiest way to use deep metric learning in your application. Modular,..",27.0,28,2022-08-03 17:49:14,1.5.2,50.0,,pytorch-metric-learning,metric-learning/pytorch-metric-learning,,,['pytorch'],324.0,324.0,https://pypi.org/project/pytorch-metric-learning,90059.0,90317.0,https://anaconda.org/metric-learning/pytorch-metric-learning,2022-08-03 17:34:45.209,8026.0,,,,,1.0,,,,,,,,,,,,,,,, +160,imutils,True,jrosebr1/imutils,,image,https://github.com/PyImageSearch/imutils,https://github.com/PyImageSearch/imutils,MIT,2015-01-11 20:05:39.000,2022-08-26 03:57:39.151000,2022-01-27 13:24:16,983.0,88.0,77.0,4164,139.0,A series of convenience functions to make basic image processing..,21.0,28,,,3.0,PyImageSearch/imutils,imutils,conda-forge/imutils,,,,27315.0,27315.0,https://pypi.org/project/imutils,326987.0,329550.0,https://anaconda.org/conda-forge/imutils,2022-08-26 03:57:39.151,97421.0,,,,,2.0,,,,,,,,,,,,,,,, +161,DeepChem,True,deepchem/deepchem,,others,https://github.com/deepchem/deepchem,https://github.com/deepchem/deepchem,MIT,2015-09-24 23:20:28.000,2022-08-26 03:43:28.000000,2022-08-26 02:28:37,1311.0,421.0,1016.0,3794,7919.0,"Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,..",201.0,28,2022-01-18 21:26:19,2.6.1,16.0,,deepchem,,,,['tensorflow'],120.0,120.0,https://pypi.org/project/deepchem,8924.0,8924.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +162,Flax,True,google/flax,,ml-frameworks,https://github.com/google/flax,https://github.com/google/flax,Apache-2.0,2020-01-10 09:48:37.000,2022-08-25 19:06:42.000000,2022-08-25 14:58:44,381.0,96.0,452.0,3456,,Flax is a neural network library for JAX that is designed for..,169.0,28,2022-08-17 06:38:26,0.6.0,19.0,,flax,,,,['jax'],1289.0,1289.0,https://pypi.org/project/flax,306537.0,306538.0,,,,,,,,2.0,42.0,,,,,,,,,,,,,,, +163,TensorFlow Datasets,True,tensorflow/datasets,,data-loading,https://github.com/tensorflow/datasets,https://github.com/tensorflow/datasets,Apache-2.0,2018-09-10 21:27:22.000,2022-08-25 16:05:28.000000,2022-08-25 16:05:21,1255.0,361.0,622.0,3358,4993.0,TFDS is a collection of datasets ready to use with..,264.0,28,2022-06-02 09:21:23,4.6.0,22.0,,tensorflow-datasets,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-datasets,1171057.0,1171057.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +164,dyNET,True,clab/dynet,,ml-frameworks,https://github.com/clab/dynet,https://github.com/clab/dynet,Apache-2.0,2015-02-08 23:09:21.000,2022-08-14 17:11:48.000000,2022-08-14 17:11:42,671.0,257.0,665.0,3314,3272.0,DyNet: The Dynamic Neural Network Toolkit.,159.0,28,2020-10-21 13:39:07,2.1.2,9.0,,dyNET,,,,,219.0,219.0,https://pypi.org/project/dyNET,20143.0,20241.0,,,,,,,,2.0,6874.0,,,,,,,,,,,,,,, +165,missingno,True,ResidentMario/missingno,,data-viz,https://github.com/ResidentMario/missingno,https://github.com/ResidentMario/missingno,MIT,2016-03-27 15:18:50.000,2022-02-27 20:46:03.000000,2022-02-27 20:46:03,412.0,8.0,114.0,3290,186.0,Missing data visualization module for Python.,17.0,28,2022-02-27 20:38:13,0.5.1,5.0,,missingno,conda-forge/missingno,,,,8336.0,8336.0,https://pypi.org/project/missingno,1009681.0,1013160.0,https://anaconda.org/conda-forge/missingno,2020-02-15 10:07:41.253,212268.0,,,,,2.0,,,,,,,,,,,,,,,, +166,Koalas,True,databricks/koalas,,data-containers,https://github.com/databricks/koalas,https://github.com/databricks/koalas,Apache-2.0,2019-01-03 21:46:54.000,2021-10-26 06:53:37.000000,2021-10-21 22:12:35,329.0,97.0,485.0,3184,1547.0,Koalas: pandas API on Apache Spark.,51.0,28,2021-10-19 22:26:46,1.8.2,47.0,,koalas,conda-forge/koalas,,,"['spark', 'pandas']",218.0,218.0,https://pypi.org/project/koalas,1619756.0,1624408.0,https://anaconda.org/conda-forge/koalas,2021-10-20 00:43:43.868,180518.0,,,,,2.0,1012.0,,,,,,,,,,,,,,, +167,Blaze,True,blaze/blaze,,data-containers,https://github.com/blaze/blaze,https://github.com/blaze/blaze,BSD-3-Clause,2012-10-26 14:25:22.000,2020-02-01 19:33:09.000000,2019-08-15 21:14:59,355.0,250.0,500.0,3094,7496.0,NumPy and Pandas interface to Big Data.,65.0,28,2016-07-19 20:40:03,0.11.0,14.0,,blaze,conda-forge/blaze,,,,8309.0,8309.0,https://pypi.org/project/blaze,8067.0,11375.0,https://anaconda.org/conda-forge/blaze,2018-07-15 22:16:17.685,198522.0,,,,,2.0,,,,,,,,,,,,,,,, +168,gpustat,True,wookayin/gpustat,,gpu-utilities,https://github.com/wookayin/gpustat,https://github.com/wookayin/gpustat,MIT,2016-04-24 10:46:43.000,2022-08-25 07:10:40.000000,2022-08-09 18:52:21,225.0,19.0,67.0,2983,185.0,A simple command-line utility for querying and monitoring GPU status.,14.0,28,2019-07-22 06:37:00,0.6.0,8.0,,gpustat,conda-forge/gpustat,,,,2132.0,2132.0,https://pypi.org/project/gpustat,822631.0,826098.0,https://anaconda.org/conda-forge/gpustat,2020-11-24 19:59:04.772,142159.0,,,,,1.0,,,,,,,,,,,,,,,, +169,NMSLIB,True,nmslib/nmslib,,nn-search,https://github.com/nmslib/nmslib,https://github.com/nmslib/nmslib,Apache-2.0,2013-07-10 11:06:06.000,2022-06-06 16:07:07.000000,2022-05-31 03:18:45,397.0,59.0,341.0,2845,1556.0,Non-Metric Space Library (NMSLIB): An efficient similarity search..,48.0,28,2021-02-03 16:40:09,2.1.1,19.0,,nmslib,conda-forge/nmslib,,,,657.0,657.0,https://pypi.org/project/nmslib,124129.0,126321.0,https://anaconda.org/conda-forge/nmslib,2022-04-15 23:08:32.465,61403.0,,,,,2.0,,,,,,,,,,,,,,,, +170,GluonNLP,True,dmlc/gluon-nlp,,nlp,https://github.com/dmlc/gluon-nlp,https://github.com/dmlc/gluon-nlp,Apache-2.0,2018-04-04 20:57:13.000,2022-08-11 07:28:36.000000,2021-08-24 19:11:38,493.0,233.0,296.0,2434,840.0,"Toolkit that enables easy text preprocessing, datasets loading and neural models building to help you speed up your..",82.0,28,2020-08-13 19:16:27,0.10.0,15.0,,gluonnlp,,,,['mxnet'],916.0,916.0,https://pypi.org/project/gluonnlp,159717.0,159717.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +171,filterpy,True,rlabbe/filterpy,,probabilistics,https://github.com/rlabbe/filterpy,https://github.com/rlabbe/filterpy,MIT,2014-07-15 02:15:19.000,2022-08-22 18:21:14.000000,2022-08-22 18:21:12,515.0,48.0,157.0,2378,586.0,Python Kalman filtering and optimal estimation library. Implements..,43.0,28,,,5.0,,filterpy,conda-forge/filterpy,,,,1579.0,1579.0,https://pypi.org/project/filterpy,759025.0,761208.0,https://anaconda.org/conda-forge/filterpy,2020-05-05 21:13:59.073,135374.0,,,,,1.0,,,,,,,,,,,,,,,, +172,hdbscan,True,scikit-learn-contrib/hdbscan,,others,https://github.com/scikit-learn-contrib/hdbscan,https://github.com/scikit-learn-contrib/hdbscan,BSD-3-Clause,2015-04-22 13:32:37.000,2022-08-23 16:40:20.000000,2022-08-23 16:40:20,386.0,281.0,159.0,2226,957.0,A high performance implementation of HDBSCAN clustering.,80.0,28,2022-02-08 17:15:41,0.8.28.wheels,40.0,,hdbscan,conda-forge/hdbscan,,,['sklearn'],1501.0,1501.0,https://pypi.org/project/hdbscan,449254.0,465742.0,https://anaconda.org/conda-forge/hdbscan,2022-02-11 21:21:32.499,1203654.0,,,,,2.0,,,,,,,,,,,,,,,, +173,dtreeviz,True,parrt/dtreeviz,,interpretability,https://github.com/parrt/dtreeviz,https://github.com/parrt/dtreeviz,MIT,2018-08-13 21:45:15.000,2022-08-23 16:43:29.000000,2022-08-23 16:43:29,275.0,24.0,101.0,2208,402.0,A python library for decision tree visualization and model interpretation.,21.0,28,2022-07-08 19:37:21,1.3.7,26.0,,dtreeviz,,,,,451.0,451.0,https://pypi.org/project/dtreeviz,96112.0,96112.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +174,GPflow,True,GPflow/GPflow,,probabilistics,https://github.com/GPflow/GPflow,https://github.com/GPflow/GPflow,Apache-2.0,2016-01-14 11:29:24.000,2022-08-25 15:58:04.000000,2022-08-17 15:27:47,412.0,119.0,656.0,1651,2350.0,Gaussian processes in TensorFlow.,78.0,28,2022-05-10 10:29:01,2.5.2,37.0,,gpflow,conda-forge/gpflow,,,['tensorflow'],391.0,391.0,https://pypi.org/project/gpflow,16120.0,16405.0,https://anaconda.org/conda-forge/gpflow,2022-05-24 14:05:38.796,14547.0,,,,,1.0,,,,,,,,,,,,,,,, +175,ogb,True,snap-stanford/ogb,,graph,https://github.com/snap-stanford/ogb,https://github.com/snap-stanford/ogb,MIT,2019-11-22 22:13:57.000,2022-08-22 09:12:46.000000,2022-08-22 09:12:46,312.0,1.0,226.0,1429,626.0,"Benchmark datasets, data loaders, and evaluators for graph machine learning.",23.0,28,2022-08-20 11:06:28,1.3.4,14.0,,ogb,,,,,382.0,382.0,https://pypi.org/project/ogb,79605.0,79605.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +176,arviz,True,arviz-devs/arviz,,interpretability,https://github.com/arviz-devs/arviz,https://github.com/arviz-devs/arviz,Apache-2.0,2015-07-29 11:51:10.000,2022-08-25 12:55:02.000000,2022-08-17 08:44:37,287.0,158.0,597.0,1257,,Exploratory analysis of Bayesian models with Python.,129.0,28,2022-05-13 16:05:00,0.12.1,26.0,,arviz,conda-forge/arviz,,,,2690.0,2690.0,https://pypi.org/project/arviz,740667.0,761542.0,https://anaconda.org/conda-forge/arviz,2022-07-13 00:49:21.932,814064.0,,,,,1.0,113.0,,,,,,,,,,,,,,, +177,agate,True,wireservice/agate,,others,https://github.com/wireservice/agate,https://github.com/wireservice/agate,MIT,2014-04-25 13:59:09.000,2022-07-01 12:06:11.000000,2021-07-15 17:22:49,137.0,11.0,630.0,1101,1466.0,A Python data analysis library that is optimized for humans instead of machines.,49.0,28,,,5.0,,agate,conda-forge/agate,,,,1098.0,1098.0,https://pypi.org/project/agate,1561278.0,1562663.0,https://anaconda.org/conda-forge/agate,2021-07-16 07:46:42.405,91466.0,,,,,2.0,,,,,,,,,,,,,,,, +178,petl,True,petl-developers/petl,,data-pipelines,https://github.com/petl-developers/petl,https://github.com/petl-developers/petl,MIT,2011-08-19 09:51:03.000,2022-08-22 00:25:07.600000,2022-08-21 18:57:30,174.0,75.0,367.0,1045,1257.0,Python Extract Transform and Load Tables of Data.,55.0,28,2022-08-21 19:09:06,1.7.11,43.0,,petl,conda-forge/petl,,http://petl.readthedocs.org,,793.0,793.0,https://pypi.org/project/petl,280037.0,281759.0,https://anaconda.org/conda-forge/petl,2022-08-22 00:25:07.600,122299.0,,,,,2.0,,,,,,,,,,,,,,,, +179,PyNNDescent,True,lmcinnes/pynndescent,,nn-search,https://github.com/lmcinnes/pynndescent,https://github.com/lmcinnes/pynndescent,BSD-2-Clause,2018-02-07 23:23:54.000,2022-08-24 10:52:05.000000,2022-07-21 14:56:54,88.0,51.0,56.0,656,623.0,A Python nearest neighbor descent for approximate nearest neighbors.,21.0,28,2022-05-14 02:50:28,0.5.7,19.0,,pynndescent,conda-forge/pynndescent,,,,1987.0,1987.0,https://pypi.org/project/pynndescent,611694.0,633962.0,https://anaconda.org/conda-forge/pynndescent,2022-05-15 21:11:06.816,846192.0,,,,,2.0,,,,,,,,,,,,,,,, +180,NiBabel,True,nipy/nibabel,,medical-data,https://github.com/nipy/nibabel,https://github.com/nipy/nibabel,,2010-07-22 16:28:30.000,2022-08-22 12:31:20.000000,2022-08-20 17:25:29,231.0,115.0,325.0,491,5186.0,Python package to access a cacophony of neuro-imaging file formats.,94.0,28,2022-06-17 23:19:01,4.0.0,35.0,,nibabel,conda-forge/nibabel,,,,7912.0,7912.0,https://pypi.org/project/nibabel,232890.0,239134.0,https://anaconda.org/conda-forge/nibabel,2022-06-18 21:54:55.369,468338.0,,,,,2.0,,,,,,,,,,,,,,,, +181,Cython BLIS,True,explosion/cython-blis,,others,https://github.com/explosion/cython-blis,https://github.com/explosion/cython-blis,,2017-10-15 09:56:16.000,2022-08-05 07:27:36.089000,2022-08-04 10:34:46,34.0,5.0,23.0,190,548.0,Fast matrix-multiplication as a self-contained Python library no..,12.0,28,2022-08-04 13:36:44,0.9.1,13.0,,blis,conda-forge/cython-blis,,,,20134.0,20134.0,https://pypi.org/project/blis,3848050.0,3887934.0,https://anaconda.org/conda-forge/cython-blis,2022-08-05 07:27:36.089,1635275.0,,,,,2.0,,,,,,,,,,,,,,,, +182,PaddleOCR,True,PaddlePaddle/PaddleOCR,,ocr,https://github.com/PaddlePaddle/PaddleOCR,https://github.com/PaddlePaddle/PaddleOCR,Apache-2.0,2020-05-08 10:38:16.000,2022-08-26 03:56:32.000000,2022-08-26 03:11:30,4892.0,1325.0,3802.0,24174,,Awesome multilingual OCR toolkits based on PaddlePaddle..,110.0,27,2022-08-24 09:04:27,2.6.0,6.0,,paddleocr,,,,['paddle'],779.0,779.0,https://pypi.org/project/paddleocr,37630.0,37630.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +183,MMDetection,True,open-mmlab/mmdetection,,image,https://github.com/open-mmlab/mmdetection,https://github.com/open-mmlab/mmdetection,Apache-2.0,2018-08-22 07:06:06.000,2022-08-26 02:14:17.000000,2022-07-28 06:57:27,6883.0,566.0,5650.0,21022,2113.0,OpenMMLab Detection Toolbox and Benchmark.,350.0,27,2022-07-28 15:43:37,2.25.1,35.0,,,,,,['pytorch'],551.0,551.0,,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +184,PyFlink,True,apache/flink,,ml-frameworks,https://github.com/apache/flink,https://github.com/apache/flink,Apache-2.0,2014-06-07 07:00:10.000,2022-08-26 03:27:58.000000,2022-08-26 03:27:58,10855.0,,,19616,31724.0,Apache Flink Python API.,1609.0,27,,,,,apache-flink,,,,,,,https://pypi.org/project/apache-flink,53773.0,53773.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +185,Magenta,True,magenta/magenta,,audio,https://github.com/magenta/magenta,https://github.com/magenta/magenta,Apache-2.0,2016-05-05 20:10:40.000,2022-08-08 16:41:11.000000,2022-08-08 16:41:04,3515.0,310.0,581.0,17850,,Magenta: Music and Art Generation with Machine Intelligence.,153.0,27,2022-08-01 18:18:44,2.1.4,48.0,,magenta,,,,['tensorflow'],380.0,380.0,https://pypi.org/project/magenta,3941.0,3941.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +186,Faiss,True,facebookresearch/faiss,,nn-search,https://github.com/facebookresearch/faiss,https://github.com/facebookresearch/faiss,MIT,2017-02-07 16:07:05.000,2022-08-25 15:35:11.000000,2022-08-08 15:32:33,2609.0,210.0,1644.0,17729,,A library for efficient similarity search and clustering of dense vectors.,101.0,27,2022-01-10 12:19:49,1.7.2,13.0,,pymilvus,conda-forge/faiss,,,,720.0,720.0,https://pypi.org/project/pymilvus,129509.0,146164.0,https://anaconda.org/conda-forge/faiss,2022-02-09 02:10:28.516,449700.0,,,,,2.0,,,,,,,,,,,,,,,, +187,torchvision,True,pytorch/vision,,image,https://github.com/pytorch/vision,https://github.com/pytorch/vision,BSD-3-Clause,2016-11-09 23:11:43.000,2022-08-25 17:18:24.000000,2022-08-25 17:06:10,6027.0,590.0,1898.0,12287,,"Datasets, Transforms and Models specific to Computer Vision.",497.0,27,2022-08-05 20:19:15,0.13.1,30.0,,torchvision,conda-forge/torchvision,,,['pytorch'],,,https://pypi.org/project/torchvision,3889538.0,3895711.0,https://anaconda.org/conda-forge/torchvision,2022-07-24 12:57:15.567,336108.0,,,,,2.0,11028.0,,,,,,,,,,,,,,, +188,TFlearn,True,tflearn/tflearn,,ml-frameworks,https://github.com/tflearn/tflearn,https://github.com/tflearn/tflearn,,2016-03-31 12:05:53.000,2021-01-25 09:41:59.000000,2020-11-30 04:34:51,2320.0,548.0,362.0,9577,613.0,Deep learning library featuring a higher-level API for TensorFlow.,128.0,27,2020-11-11 19:26:11,0.5.0,8.0,,tflearn,,,,['tensorflow'],4053.0,4053.0,https://pypi.org/project/tflearn,16148.0,16148.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +189,glfw,True,glfw/glfw,,image,https://github.com/glfw/glfw,https://github.com/glfw/glfw,Zlib,2013-04-18 15:24:53.000,2022-08-25 21:13:14.000000,2022-08-22 17:17:12,3468.0,398.0,1192.0,9474,4595.0,"A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input.",184.0,27,2022-07-22 13:50:50,3.3.8,19.0,,glfw,conda-forge/glfw,,,,1.0,1.0,https://pypi.org/project/glfw,216624.0,250483.0,https://anaconda.org/conda-forge/glfw,2022-07-23 14:48:23.443,68158.0,,,,,2.0,2869135.0,,,,,,,,,,,,,,, +190,Sonnet,True,deepmind/sonnet,,ml-frameworks,https://github.com/deepmind/sonnet,https://github.com/deepmind/sonnet,Apache-2.0,2017-04-03 11:34:35.000,2022-08-23 20:09:04.000000,2022-08-23 20:08:58,1245.0,26.0,154.0,9356,,TensorFlow-based neural network library.,54.0,27,2020-03-27 10:36:19,2.0.0,13.0,,dm-sonnet,conda-forge/sonnet,,,['tensorflow'],896.0,896.0,https://pypi.org/project/dm-sonnet,24283.0,24777.0,https://anaconda.org/conda-forge/sonnet,2020-11-14 18:13:23.843,16314.0,,,,,3.0,,,,,,,,,,,,,,,, +191,backtrader,True,mementum/backtrader,,financial-data,https://github.com/mementum/backtrader,https://github.com/mementum/backtrader,GPL-3.0,2015-01-10 07:14:52.000,2022-08-14 22:48:30.000000,2021-07-17 22:17:12,2732.0,,,9224,2385.0,Python Backtesting library for trading strategies.,52.0,27,,,,,backtrader,,,,,1131.0,1131.0,https://pypi.org/project/backtrader,12906.0,12906.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +192,pretrainedmodels,True,Cadene/pretrained-models.pytorch,,pytorch-utils,https://github.com/Cadene/pretrained-models.pytorch,https://github.com/Cadene/pretrained-models.pytorch,BSD-3-Clause,2017-04-09 15:54:23.000,2022-04-22 09:08:45.000000,2020-04-16 08:02:22,1766.0,81.0,94.0,8611,154.0,"Pretrained ConvNets for pytorch: NASNet, ResNeXt,..",22.0,27,,,,,pretrainedmodels,,,,['pytorch'],1768.0,1768.0,https://pypi.org/project/pretrainedmodels,167839.0,167839.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +193,Ludwig,True,ludwig-ai/ludwig,,ml-frameworks,https://github.com/ludwig-ai/ludwig,https://github.com/ludwig-ai/ludwig,Apache-2.0,2018-12-27 23:58:12.000,2022-08-26 01:30:40.000000,2022-08-25 17:42:06,955.0,195.0,624.0,8488,2811.0,Ludwig is a toolbox that allows to train and evaluate deep..,127.0,27,2022-08-02 19:29:53,0.5.5,20.0,,ludwig,,,,['tensorflow'],129.0,129.0,https://pypi.org/project/ludwig,1798.0,1798.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +194,PaddleHub,True,PaddlePaddle/PaddleHub,,others,https://github.com/PaddlePaddle/PaddleHub,https://github.com/PaddlePaddle/PaddleHub,Apache-2.0,2018-12-21 06:00:48.000,2022-08-26 03:52:50.000000,2022-08-19 11:40:37,1670.0,459.0,649.0,8296,,Awesome pre-trained models toolkit based on PaddlePaddle.300+..,62.0,27,2021-04-16 08:20:11,2.1.0,27.0,,paddlehub,,,,['paddle'],894.0,894.0,https://pypi.org/project/paddlehub,13547.0,13561.0,,,,,,,,2.0,578.0,,,,,,,,,,,,,,, +195,carla,True,carla-simulator/carla,,others,https://github.com/carla-simulator/carla,https://github.com/carla-simulator/carla,,2017-10-24 09:06:23.000,2022-08-25 09:56:45.000000,2021-11-19 11:13:47,2364.0,637.0,3344.0,8160,5439.0,Open-source simulator for autonomous driving research.,138.0,27,2021-11-16 19:51:12,0.9.13,24.0,,carla,,,,,233.0,233.0,https://pypi.org/project/carla,25946.0,25946.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +196,tensorpack,True,tensorpack/tensorpack,,ml-frameworks,https://github.com/tensorpack/tensorpack,https://github.com/tensorpack/tensorpack,Apache-2.0,2015-12-25 23:08:44.000,2022-05-04 12:19:58.000000,2022-05-04 12:19:51,1802.0,9.0,1339.0,6226,2939.0,"A Neural Net Training Interface on TensorFlow, with focus on..",58.0,27,2019-01-18 19:18:13,doc-v0.9.0.1,3.0,,tensorpack,,,,['tensorflow'],1081.0,1081.0,https://pypi.org/project/tensorpack,18763.0,18765.0,,,,,,,,3.0,141.0,,,,,,,,,,,,,,, +197,DeepPavlov,True,deepmipt/DeepPavlov,,nlp,https://github.com/deepmipt/DeepPavlov,https://github.com/deepmipt/DeepPavlov,Apache-2.0,2017-11-17 14:35:29.000,2022-08-24 13:15:46.000000,2022-05-31 12:00:18,1034.0,54.0,565.0,5839,2615.0,An open source library for deep learning end-to-end dialog..,67.0,27,2022-05-31 12:02:13,0.17.4,51.0,,deeppavlov,,,,['tensorflow'],275.0,275.0,https://pypi.org/project/deeppavlov,7983.0,7983.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +198,OpenNMT,True,OpenNMT/OpenNMT-py,,nlp,https://github.com/OpenNMT/OpenNMT-py,https://github.com/OpenNMT/OpenNMT-py,MIT,2017-02-22 19:01:50.000,2022-08-18 12:16:00.000000,2022-08-18 12:16:00,1986.0,90.0,1227.0,5682,2591.0,Open Source Neural Machine Translation in PyTorch.,175.0,27,2021-09-14 08:48:31,2.2.0,32.0,,OpenNMT-py,,,,['pytorch'],149.0,149.0,https://pypi.org/project/OpenNMT-py,5179.0,5179.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +199,sktime,True,alan-turing-institute/sktime,,time-series-data,https://github.com/alan-turing-institute/sktime,https://github.com/alan-turing-institute/sktime,BSD-3-Clause,2018-11-06 15:08:24.000,2022-08-25 23:16:41.000000,2022-08-25 21:25:30,892.0,429.0,863.0,5644,,A unified framework for machine learning with time series.,194.0,27,2022-08-24 06:20:31,0.13.2,29.0,,sktime,,,,['sklearn'],561.0,561.0,https://pypi.org/project/sktime,264756.0,264757.0,,,,,,,,1.0,76.0,,,,,,,,,,,,,,, +200,DEAP,True,deap/deap,,distributed-ml,https://github.com/DEAP/deap,https://github.com/DEAP/deap,LGPL-3.0,2014-05-21 20:07:39.000,2022-08-20 10:30:18.000000,2022-08-08 11:09:11,979.0,204.0,263.0,4791,2218.0,Distributed Evolutionary Algorithms in Python.,79.0,27,,,5.0,,deap,conda-forge/deap,,,,2839.0,2839.0,https://pypi.org/project/deap,163610.0,166328.0,https://anaconda.org/conda-forge/deap,2022-08-08 17:58:14.179,201189.0,,,,,2.0,,,,,,,,,,,,,,,, +201,VisualDL,True,PaddlePaddle/VisualDL,,ml-experiments,https://github.com/PaddlePaddle/VisualDL,https://github.com/PaddlePaddle/VisualDL,Apache-2.0,2017-12-20 12:34:31.000,2022-08-25 11:34:57.000000,2022-08-23 08:11:25,592.0,85.0,336.0,4414,,Deep Learning Visualization Toolkit.,32.0,27,2022-08-23 10:17:56,2.4.0,13.0,,visualdl,,,,['paddle'],1329.0,1329.0,https://pypi.org/project/visualdl,60413.0,60420.0,,,,,,,,2.0,206.0,,,,,,,,,,,,,,, +202,D-Tale,True,man-group/dtale,,data-viz,https://github.com/man-group/dtale,https://github.com/man-group/dtale,LGPL-2.1,2019-07-15 09:34:48.000,2022-08-14 19:16:00.000000,2022-08-07 17:10:54,294.0,42.0,431.0,3602,618.0,Visualizer for pandas data structures.,27.0,27,2022-08-07 19:29:08,2.7.1,112.0,,dtale,conda-forge/dtale,,,"['pandas', 'jupyter']",456.0,456.0,https://pypi.org/project/dtale,99657.0,104503.0,https://anaconda.org/conda-forge/dtale,2022-08-07 22:53:15.855,145394.0,,,,,2.0,,,,,,,,,,,,,,,, +203,Captum,True,pytorch/captum,,interpretability,https://github.com/pytorch/captum,https://github.com/pytorch/captum,BSD-3-Clause,2019-08-27 15:34:41.000,2022-08-24 16:48:37.000000,2022-08-23 19:45:39,348.0,94.0,287.0,3383,951.0,Model interpretability and understanding for PyTorch.,88.0,27,2022-03-04 00:37:56,0.5.0,7.0,,captum,,,,['pytorch'],650.0,650.0,https://pypi.org/project/captum,47452.0,47452.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +204,bqplot,True,bqplot/bqplot,,data-viz,https://github.com/bqplot/bqplot,https://github.com/bqplot/bqplot,Apache-2.0,2015-09-26 04:02:18.000,2022-08-22 19:17:03.000000,2022-08-22 18:51:06,438.0,211.0,360.0,3339,3532.0,Plotting library for IPython/Jupyter notebooks.,59.0,27,2022-08-22 14:47:27,0.12.34,57.0,,bqplot,conda-forge/bqplot,,,['jupyter'],34.0,34.0,https://pypi.org/project/bqplot,80993.0,103971.0,https://anaconda.org/conda-forge/bqplot,2022-08-22 19:02:03.194,1022268.0,,,,,2.0,,,bqplot,https://www.npmjs.com/package/bqplot,9348.0,,,,,,,,,,, +205,Catalyst,True,catalyst-team/catalyst,,ml-experiments,https://github.com/catalyst-team/catalyst,https://github.com/catalyst-team/catalyst,Apache-2.0,2018-08-20 07:56:13.000,2022-08-17 10:02:52.000000,2022-04-29 04:19:24,341.0,5.0,334.0,2978,1698.0,Accelerated deep learning R&D.,103.0,27,2022-04-29 04:45:11,22.04,41.0,,catalyst,,,,['pytorch'],603.0,603.0,https://pypi.org/project/catalyst,39270.0,39270.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +206,spark-nlp,True,JohnSnowLabs/spark-nlp,,nlp,https://github.com/JohnSnowLabs/spark-nlp,https://github.com/JohnSnowLabs/spark-nlp,Apache-2.0,2017-09-24 19:36:44.000,2022-08-25 21:12:32.000000,2022-08-24 12:58:50,571.0,36.0,662.0,2883,24736.0,State of the Art Natural Language Processing.,129.0,27,2022-08-24 15:35:49,4.1.0,100.0,,spark-nlp,,,,['spark'],,,https://pypi.org/project/spark-nlp,2372936.0,2372936.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +207,TF-Agents,True,tensorflow/agents,,reinforcement-learning,https://github.com/tensorflow/agents,https://github.com/tensorflow/agents,Apache-2.0,2018-11-17 00:29:12.000,2022-08-24 08:05:41.000000,2022-08-24 08:04:57,615.0,128.0,435.0,2341,2108.0,"TF-Agents: A reliable, scalable and easy to use TensorFlow..",124.0,27,,,,,tf-agents,,,,['tensorflow'],883.0,883.0,https://pypi.org/project/tf-agents,149315.0,149315.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +208,Foolbox,True,bethgelab/foolbox,,adversarial,https://github.com/bethgelab/foolbox,https://github.com/bethgelab/foolbox,MIT,2017-06-14 13:05:48.000,2022-07-29 13:00:12.000000,2022-05-25 09:55:55,399.0,21.0,331.0,2284,1696.0,A Python toolbox to create adversarial examples that fool neural networks..,32.0,27,2022-04-02 15:26:25,3.3.3,58.0,,foolbox,,,,,318.0,318.0,https://pypi.org/project/foolbox,5436.0,5436.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +209,hnswlib,True,nmslib/hnswlib,,nn-search,https://github.com/nmslib/hnswlib,https://github.com/nmslib/hnswlib,Apache-2.0,2017-07-06 13:08:46.000,2022-08-25 10:26:37.000000,2022-04-16 02:58:29,383.0,125.0,125.0,2116,379.0,Header-only C++/python library for fast approximate nearest neighbors.,56.0,27,2022-02-14 22:10:46,0.6.2,7.0,,hnswlib,,,,,275.0,275.0,https://pypi.org/project/hnswlib,426144.0,426144.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +210,MNE,True,mne-tools/mne-python,,medical-data,https://github.com/mne-tools/mne-python,https://github.com/mne-tools/mne-python,BSD-3-Clause,2011-01-28 03:31:13.000,2022-08-26 01:29:19.000000,2022-08-25 09:24:20,1047.0,415.0,3793.0,2004,,MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python.,310.0,27,2022-08-24 15:27:56,1.1.1,44.0,,mne,conda-forge/mne,,,,1813.0,1813.0,https://pypi.org/project/mne,48070.0,51455.0,https://anaconda.org/conda-forge/mne,2022-08-24 16:35:15.426,223460.0,,,,,2.0,,,,,,,,,,,,,,,, +211,torchaudio,True,pytorch/audio,,audio,https://github.com/pytorch/audio,https://github.com/pytorch/audio,BSD-2-Clause,2017-05-05 00:38:05.000,2022-08-26 00:54:54.000000,2022-08-26 00:51:56,447.0,133.0,509.0,1820,1168.0,Data manipulation and transformation for audio signal..,171.0,27,2022-08-05 21:15:34,0.12.1,20.0,,torchaudio,,,,['pytorch'],,,https://pypi.org/project/torchaudio,726047.0,726047.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +212,Rasterio,True,mapbox/rasterio,,geospatial-data,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,,2013-11-04 16:36:27.000,2022-08-26 04:04:21.000000,2022-08-18 03:59:02,467.0,135.0,1431.0,1801,,Rasterio reads and writes geospatial raster datasets.,130.0,27,2022-08-19 18:48:01,1.3.2,76.0,rasterio/rasterio,rasterio,conda-forge/rasterio,,,,5403.0,5403.0,https://pypi.org/project/rasterio,603592.0,625777.0,https://anaconda.org/conda-forge/rasterio,2022-08-19 22:33:35.528,1707590.0,,,,,3.0,761.0,,,,,,,,,,,,,,, +213,Pythran,True,serge-sans-paille/pythran,,others,https://github.com/serge-sans-paille/pythran,https://github.com/serge-sans-paille/pythran,BSD-3-Clause,2012-05-29 08:02:14.000,2022-07-31 22:41:48.286000,2022-07-19 16:04:14,173.0,107.0,651.0,1779,3552.0,Ahead of Time compiler for numeric kernels.,66.0,27,,,24.0,,pythran,conda-forge/pythran,,,,219.0,219.0,https://pypi.org/project/pythran,373410.0,378527.0,https://anaconda.org/conda-forge/pythran,2022-07-31 22:41:48.286,260971.0,,,,,2.0,,,,,,,,,pythran,python-pythran,,,,,, +214,petastorm,True,uber/petastorm,,distributed-ml,https://github.com/uber/petastorm,https://github.com/uber/petastorm,Apache-2.0,2018-06-15 23:15:29.000,2022-08-24 23:59:26.000000,2022-08-24 22:25:03,249.0,141.0,142.0,1482,684.0,Petastorm library enables single machine or distributed training..,45.0,27,2022-08-25 00:20:43,0.12.0,44.0,,petastorm,,,,,74.0,74.0,https://pypi.org/project/petastorm,63375.0,63381.0,,,,,,,,2.0,337.0,,,,,,,,,,,,,,, +215,snakemake,True,snakemake/snakemake,,ml-experiments,https://github.com/snakemake/snakemake,https://github.com/snakemake/snakemake,MIT,2015-10-17 15:43:54.867,2022-08-26 00:14:24.000000,2022-08-25 14:23:07,357.0,630.0,429.0,1456,,This is the development home of the workflow management system..,259.0,27,2022-08-25 14:24:22,7.13.0,178.0,,snakemake,bioconda/snakemake,,,,1190.0,1190.0,https://pypi.org/project/snakemake,50718.0,56927.0,https://anaconda.org/bioconda/snakemake,2022-08-11 09:11:50.024,509170.0,,,,,2.0,,,,,,,,,,,,,,,, +216,pingouin,True,raphaelvallat/pingouin,,probabilistics,https://github.com/raphaelvallat/pingouin,https://github.com/raphaelvallat/pingouin,GPL-3.0,2018-04-01 01:10:22.000,2022-08-26 00:43:23.000000,2022-07-18 19:20:20,108.0,32.0,192.0,1155,1198.0,Statistical package in Python based on Pandas.,33.0,27,2022-06-24 18:07:38,0.5.2,37.0,,pingouin,conda-forge/pingouin,,,,679.0,679.0,https://pypi.org/project/pingouin,59175.0,60686.0,https://anaconda.org/conda-forge/pingouin,2022-06-24 21:24:35.163,66496.0,,,,,2.0,,,,,,,,,,,,,,,, +217,spacy-transformers,True,explosion/spacy-transformers,,nlp,https://github.com/explosion/spacy-transformers,https://github.com/explosion/spacy-transformers,MIT,2019-07-26 19:12:34.000,2022-08-25 09:11:44.000000,2022-08-23 13:07:25,139.0,,,1144,1409.0,"Use pretrained transformers like BERT, XLNet and GPT-2..",18.0,27,2022-08-25 07:03:24,1.1.7,31.0,,spacy-transformers,,,,['spacy'],610.0,610.0,https://pypi.org/project/spacy-transformers,104400.0,104400.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +218,igraph,True,igraph/python-igraph,,graph,https://github.com/igraph/python-igraph,https://github.com/igraph/python-igraph,GPL-2.0,2015-01-08 23:55:16.000,2022-08-24 14:00:52.000000,2022-08-24 13:58:46,218.0,39.0,375.0,1001,1923.0,Python interface for igraph.,61.0,27,2022-06-08 20:43:44,0.9.11,16.0,,python-igraph,conda-forge/igraph,,,,847.0,847.0,https://pypi.org/project/python-igraph,256012.0,267420.0,https://anaconda.org/conda-forge/igraph,2022-06-13 09:43:51.605,315143.0,,,,,2.0,455986.0,,,,,,,,,,,,,,, +219,pyjanitor,True,ericmjl/pyjanitor,,others,https://github.com/pyjanitor-devs/pyjanitor,https://github.com/pyjanitor-devs/pyjanitor,MIT,2018-03-04 22:43:33.000,2022-08-26 04:00:39.000000,2022-08-24 12:23:05,151.0,101.0,388.0,963,1162.0,Clean APIs for data cleaning. Python implementation of R package Janitor.,104.0,27,2022-05-03 04:09:24,0.23.1,50.0,pyjanitor-devs/pyjanitor,pyjanitor,conda-forge/pyjanitor,,,,216.0,216.0,https://pypi.org/project/pyjanitor,28585.0,31084.0,https://anaconda.org/conda-forge/pyjanitor,2021-11-22 17:28:45.154,132489.0,,,,,2.0,,,,,,,,,,,,,,,, +220,patsy,True,pydata/patsy,,probabilistics,https://github.com/pydata/patsy,https://github.com/pydata/patsy,,2012-07-10 12:30:06.000,2022-08-16 17:32:35.000000,2022-08-16 04:02:22,88.0,61.0,71.0,847,541.0,Describing statistical models in Python using symbolic formulas.,17.0,27,2021-09-27 02:10:26,0.5.2,9.0,,patsy,conda-forge/patsy,,,,55903.0,55903.0,https://pypi.org/project/patsy,7483007.0,7559795.0,https://anaconda.org/conda-forge/patsy,2021-09-26 14:43:31.594,5528795.0,,,,,2.0,,,,,,,,,,,,,,,, +221,Hail,True,hail-is/hail,,medical-data,https://github.com/hail-is/hail,https://github.com/hail-is/hail,MIT,2015-10-27 20:55:42.000,2022-08-26 00:23:32.000000,2022-08-26 00:23:31,213.0,10.0,2004.0,818,7617.0,Scalable genomic data analysis.,81.0,27,2022-08-22 22:08:37,0.2.98,86.0,,hail,,,,['spark'],75.0,75.0,https://pypi.org/project/hail,241261.0,241261.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +222,geojson,True,jazzband/geojson,,geospatial-data,https://github.com/jazzband/geojson,https://github.com/jazzband/geojson,BSD-3-Clause,2011-07-01 20:39:48.000,2022-07-04 18:14:16.000000,2022-05-07 01:15:33,93.0,22.0,63.0,737,460.0,Python bindings and utilities for GeoJSON.,48.0,27,,,9.0,,geojson,conda-forge/geojson,,,,9954.0,9954.0,https://pypi.org/project/geojson,776558.0,783833.0,https://anaconda.org/conda-forge/geojson,2019-08-11 12:10:34.426,560230.0,,,,,3.0,,,,,,,,,,,,,,,, +223,data-validation,True,tensorflow/data-validation,,data-viz,https://github.com/tensorflow/data-validation,https://github.com/tensorflow/data-validation,Apache-2.0,2018-07-02 15:47:02.000,2022-08-24 17:41:44.000000,2022-08-24 17:41:44,129.0,25.0,124.0,661,809.0,Library for exploring and validating machine learning..,24.0,27,2022-06-29 17:34:01,1.9.0,38.0,,tensorflow-data-validation,,,,"['tensorflow', 'jupyter']",542.0,542.0,https://pypi.org/project/tensorflow-data-validation,1141254.0,1141261.0,,,,,,,,2.0,366.0,,,,,,,,,,,,,,, +224,hvPlot,True,holoviz/hvplot,,data-viz,https://github.com/holoviz/hvplot,https://github.com/holoviz/hvplot,BSD-3-Clause,2018-03-19 14:22:41.000,2022-08-26 03:51:37.000000,2022-08-25 12:48:57,73.0,181.0,299.0,618,507.0,"A high-level plotting API for pandas, dask, xarray, and networkx built on..",37.0,27,2022-05-09 22:03:14,0.8.0,12.0,,hvplot,conda-forge/hvplot,,,,1635.0,1635.0,https://pypi.org/project/hvplot,164086.0,168555.0,https://anaconda.org/conda-forge/hvplot,2022-05-09 16:16:22.098,214523.0,,,,,2.0,,,,,,,,,,,,,,,, +225,InsightFace,True,deepinsight/insightface,,image,https://github.com/deepinsight/insightface,https://github.com/deepinsight/insightface,MIT,2017-09-01 00:36:51.000,2022-08-19 11:49:29.000000,2022-08-19 11:49:09,3882.0,1091.0,873.0,12474,2086.0,Face Analysis Project on MXNet and PyTorch.,46.0,26,,,,,insightface,,,,['mxnet'],182.0,182.0,https://pypi.org/project/insightface,21199.0,21199.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +226,ParlAI,True,facebookresearch/ParlAI,,nlp,https://github.com/facebookresearch/ParlAI,https://github.com/facebookresearch/ParlAI,MIT,2017-04-24 17:10:44.000,2022-08-25 18:49:12.000000,2022-08-25 18:49:11,1843.0,83.0,1330.0,9399,,A framework for training and evaluating AI models on a variety of..,198.0,26,2022-08-23 22:36:35,1.7.0,21.0,,parlai,,,,['pytorch'],87.0,87.0,https://pypi.org/project/parlai,3375.0,3375.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +227,wordcloud,True,amueller/word_cloud,,data-viz,https://github.com/amueller/word_cloud,https://github.com/amueller/word_cloud,MIT,2012-11-04 22:57:59.000,2022-08-25 22:09:30.453000,2022-06-27 19:03:14,2181.0,98.0,372.0,8947,552.0,A little word cloud generator in Python.,65.0,26,2018-07-26 17:23:44,1.5.0,10.0,,wordcloud,conda-forge/wordcloud,,,,,,https://pypi.org/project/wordcloud,693220.0,697577.0,https://anaconda.org/conda-forge/wordcloud,2022-08-25 22:09:30.453,313768.0,,,,,2.0,,,,,,,,,,,,,,,, +228,PySyft,True,OpenMined/PySyft,,privacy-ml,https://github.com/OpenMined/PySyft,https://github.com/OpenMined/PySyft,Apache-2.0,2017-07-18 20:41:16.000,2022-08-26 02:10:56.000000,2022-08-25 04:57:36,1795.0,46.0,3067.0,8286,9339.0,A library for answering questions using data you cannot see.,449.0,26,2021-12-01 19:45:11,0.6.0,22.0,,syft,,,,['pytorch'],,,https://pypi.org/project/syft,3968.0,3968.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +229,Vaex,True,vaexio/vaex,,data-containers,https://github.com/vaexio/vaex,https://github.com/vaexio/vaex,MIT,2014-09-27 09:44:42.000,2022-08-25 15:04:54.000000,2022-08-25 15:04:45,551.0,327.0,724.0,7254,3548.0,"Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and..",70.0,26,2018-03-29 14:50:46,aexpaper_1,28.0,,vaex,conda-forge/vaex,,,,314.0,314.0,https://pypi.org/project/vaex,43608.0,45546.0,https://anaconda.org/conda-forge/vaex,2022-07-27 06:42:31.316,135525.0,,,,,3.0,244.0,,,,,,,,,,,,,,, +230,imageai,True,OlafenwaMoses/ImageAI,,image,https://github.com/OlafenwaMoses/ImageAI,https://github.com/OlafenwaMoses/ImageAI,MIT,2018-03-19 23:12:33.000,2022-08-16 01:05:57.000000,2021-05-08 20:05:36,1935.0,262.0,430.0,7186,292.0,A python library built to empower developers to build applications and..,15.0,26,2021-01-04 19:24:41,essentials-v5,10.0,,imageai,,,,,1150.0,1150.0,https://pypi.org/project/imageai,8947.0,23874.0,,,,,,,,2.0,776236.0,,,,,,,,,,,,,,, +231,PyMC3,True,pymc-devs/pymc3,,probabilistics,https://github.com/pymc-devs/pymc,https://github.com/pymc-devs/pymc,,2009-05-05 09:43:50.000,2022-08-26 02:43:43.000000,2022-08-25 19:03:14,1586.0,176.0,2600.0,6947,,Probabilistic Programming in Python: Bayesian Modeling and..,407.0,26,2022-08-25 10:36:57,4.1.6,44.0,pymc-devs/pymc,pymc3,conda-forge/pymc3,,,,692.0,692.0,https://pypi.org/project/pymc3,409443.0,415740.0,https://anaconda.org/conda-forge/pymc3,2022-05-20 12:40:09.903,439391.0,,,,,2.0,1904.0,,,,,,,,,,,,,,, +232,Tokenizers,True,huggingface/tokenizers,,nlp,https://github.com/huggingface/tokenizers,https://github.com/huggingface/tokenizers,Apache-2.0,2019-11-01 17:52:20.000,2022-08-25 14:47:22.000000,2022-08-25 12:50:06,481.0,196.0,457.0,5832,,Fast State-of-the-Art Tokenizers optimized for Research and..,59.0,26,2022-03-31 13:07:30,node-v0.12.0,58.0,,tokenizers,conda-forge/tokenizers,,,,51.0,51.0,https://pypi.org/project/tokenizers,5906927.0,5920092.0,https://anaconda.org/conda-forge/tokenizers,2022-05-21 19:32:48.700,329130.0,,,,,2.0,,,,,,,,,,,,,,,, +233,CleverHans,True,cleverhans-lab/cleverhans,,adversarial,https://github.com/cleverhans-lab/cleverhans,https://github.com/cleverhans-lab/cleverhans,MIT,2016-09-15 00:28:04.000,2022-01-23 02:08:30.000000,2021-09-23 22:14:27,1329.0,24.0,422.0,5567,3201.0,"An adversarial example library for constructing attacks,..",128.0,26,2021-07-24 08:48:41,4.0.0,8.0,,cleverhans,,,,['tensorflow'],350.0,350.0,https://pypi.org/project/cleverhans,1266.0,1266.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +234,PDFMiner,True,euske/pdfminer,,data-loading,https://github.com/euske/pdfminer,https://github.com/euske/pdfminer,MIT,2010-12-12 12:50:22.000,2021-02-16 14:43:27.000000,2020-01-18 07:00:32,984.0,197.0,43.0,4855,540.0,Python PDF Parser (Not actively maintained). Check out pdfminer.six.,28.0,26,,,2.0,,pdfminer,conda-forge/pdfminer,,,,3184.0,3184.0,https://pypi.org/project/pdfminer,122143.0,122472.0,https://anaconda.org/conda-forge/pdfminer,2021-02-15 15:07:18.804,23700.0,,,,,2.0,,,,,,,,,,,,,,,, +235,AutoGluon,True,awslabs/autogluon,,hyperopt,https://github.com/awslabs/autogluon,https://github.com/awslabs/autogluon,Apache-2.0,2019-07-29 18:51:24.000,2022-08-26 00:18:06.000000,2022-08-25 19:54:27,616.0,157.0,585.0,4743,1082.0,"AutoGluon: AutoML for Text, Image, and Tabular Data.",85.0,26,2022-07-29 00:05:50,0.5.2,21.0,,autogluon,,,,['mxnet'],159.0,159.0,https://pypi.org/project/autogluon,40267.0,40267.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +236,skorch,True,skorch-dev/skorch,,ml-frameworks,https://github.com/skorch-dev/skorch,https://github.com/skorch-dev/skorch,BSD-3-Clause,2017-07-18 00:13:54.000,2022-08-22 10:46:51.000000,2022-08-22 10:46:51,310.0,44.0,398.0,4649,1005.0,A scikit-learn compatible neural network library that wraps..,50.0,26,2021-10-31 15:54:20,0.11.0,10.0,,skorch,conda-forge/skorch,,,"['pytorch', 'sklearn']",551.0,551.0,https://pypi.org/project/skorch,30971.0,43860.0,https://anaconda.org/conda-forge/skorch,2021-11-30 10:48:50.965,605824.0,,,,,3.0,,,,,,,,,,,,,,,, +237,pyfolio,True,quantopian/pyfolio,,financial-data,https://github.com/quantopian/pyfolio,https://github.com/quantopian/pyfolio,Apache-2.0,2015-06-01 15:31:39.000,2021-12-26 17:08:51.000000,2020-07-15 13:46:58,1390.0,138.0,265.0,4548,1184.0,Portfolio and risk analytics in Python.,56.0,26,2019-04-15 11:38:22,0.9.2,8.0,,pyfolio,conda-forge/pyfolio,,,,448.0,448.0,https://pypi.org/project/pyfolio,6472.0,6644.0,https://anaconda.org/conda-forge/pyfolio,2020-05-16 14:11:57.267,9310.0,,,,,2.0,,,,,,,,,,,,,,,, +238,lightfm,True,lyst/lightfm,,recommender-systems,https://github.com/lyst/lightfm,https://github.com/lyst/lightfm,Apache-2.0,2015-07-30 08:34:00.000,2022-07-19 05:09:29.000000,2022-07-19 05:09:29,627.0,112.0,349.0,4112,463.0,"A Python implementation of LightFM, a hybrid recommendation algorithm.",44.0,26,2020-11-27 19:48:30,1.16,8.0,,lightfm,conda-forge/lightfm,,,,794.0,794.0,https://pypi.org/project/lightfm,355484.0,357793.0,https://anaconda.org/conda-forge/lightfm,2022-03-09 22:21:56.668,127046.0,,,,,1.0,,,,,,,,,,,,,,,, +239,Ignite,True,pytorch/ignite,,ml-frameworks,https://github.com/pytorch/ignite,https://github.com/pytorch/ignite,BSD-3-Clause,2017-11-23 17:31:21.000,2022-08-25 23:08:01.000000,2022-08-25 22:57:31,539.0,110.0,975.0,4029,1432.0,High-level library to help with training and evaluating neural..,178.0,26,2022-05-04 20:24:44,0.4.9,20.0,,pytorch-ignite,pytorch/ignite,,,['pytorch'],,,https://pypi.org/project/pytorch-ignite,149963.0,151943.0,https://anaconda.org/pytorch/ignite,2022-05-04 20:29:56.200,99011.0,,,,,3.0,,,,,,,,,,,,,,,, +240,BigDL,True,intel-analytics/BigDL,,distributed-ml,https://github.com/intel-analytics/BigDL,https://github.com/intel-analytics/BigDL,Apache-2.0,2016-08-29 07:59:50.000,2022-08-26 04:02:48.000000,2022-08-26 02:12:12,973.0,422.0,982.0,4004,2682.0,BigDL: Distributed Deep Learning Framework for Apache Spark.,168.0,26,2022-03-09 07:47:13,2.0.0,15.0,,bigdl,,,,,38.0,38.0,https://pypi.org/project/bigdl,4026.0,4026.0,,,,,,,,2.0,,,,,,,,,,,com.intel.analytics.bigdl:bigdl-SPARK_2.4,https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4,,,, +241,ta,True,bukosabino/ta,,financial-data,https://github.com/bukosabino/ta,https://github.com/bukosabino/ta,MIT,2018-01-02 18:08:48.000,2022-08-23 16:01:02.000000,2022-08-23 15:59:41,716.0,101.0,97.0,3195,615.0,Technical Analysis Library using Pandas and Numpy.,29.0,26,,,,,ta,,,,,1376.0,1376.0,https://pypi.org/project/ta,71042.0,71042.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +242,pomegranate,True,jmschrei/pomegranate,,probabilistics,https://github.com/jmschrei/pomegranate,https://github.com/jmschrei/pomegranate,MIT,2014-11-24 18:36:58.000,2022-07-04 02:48:18.000000,2022-07-04 02:48:18,530.0,59.0,614.0,2944,934.0,"Fast, flexible and easy to use probabilistic modelling in Python.",66.0,26,2016-03-30 20:01:37,0.4.0,7.0,,pomegranate,conda-forge/pomegranate,,,,743.0,743.0,https://pypi.org/project/pomegranate,52845.0,55413.0,https://anaconda.org/conda-forge/pomegranate,2021-11-16 01:22:35.020,95050.0,,,,,2.0,,,,,,,,,,,,,,,, +243,implicit,True,benfred/implicit,,recommender-systems,https://github.com/benfred/implicit,https://github.com/benfred/implicit,MIT,2016-04-17 03:45:23.000,2022-08-21 18:04:19.000000,2022-08-21 18:04:16,534.0,68.0,354.0,2925,,Fast Python Collaborative Filtering for Implicit Feedback Datasets.,32.0,26,2022-07-11 17:26:36,0.6.0,14.0,,implicit,conda-forge/implicit,,,,651.0,651.0,https://pypi.org/project/implicit,158897.0,165968.0,https://anaconda.org/conda-forge/implicit,2022-01-29 16:35:56.077,388230.0,,,,,1.0,95.0,,,,,,,,,,,,,,, +244,Sumy,True,miso-belica/sumy,,nlp,https://github.com/miso-belica/sumy,https://github.com/miso-belica/sumy,Apache-2.0,2013-02-20 12:56:48.000,2022-07-31 08:48:12.000000,2022-07-31 08:48:12,471.0,17.0,90.0,2891,,Module for automatic summarization of text documents and HTML pages.,23.0,26,2022-04-21 21:59:07,0.10.0,14.0,,sumy,,,,,1363.0,1363.0,https://pypi.org/project/sumy,20725.0,20725.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +245,aubio,True,aubio/aubio,,audio,https://github.com/aubio/aubio,https://github.com/aubio/aubio,GPL-3.0,2009-12-04 21:07:44.000,2022-08-25 08:05:34.000000,2022-01-25 17:32:20,339.0,131.0,183.0,2778,4123.0,a library for audio and music analysis.,24.0,26,2019-02-27 09:00:43,0.4.9,8.0,,aubio,conda-forge/aubio,,,,314.0,314.0,https://pypi.org/project/aubio,1516.0,9813.0,https://anaconda.org/conda-forge/aubio,2022-07-13 13:00:34.244,539317.0,,,,,2.0,,,,,,,,,,,,,,,, +246,Cufflinks,True,santosjorge/cufflinks,,data-viz,https://github.com/santosjorge/cufflinks,https://github.com/santosjorge/cufflinks,MIT,2014-11-19 20:59:33.000,2022-02-11 16:25:24.000000,2021-02-25 05:05:09,602.0,86.0,123.0,2644,452.0,Productivity Tools for Plotly + Pandas.,38.0,26,,,,,cufflinks,,,,['pandas'],6469.0,6469.0,https://pypi.org/project/cufflinks,308643.0,308643.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +247,hmmlearn,True,hmmlearn/hmmlearn,,probabilistics,https://github.com/hmmlearn/hmmlearn,https://github.com/hmmlearn/hmmlearn,BSD-3-Clause,2014-03-23 10:33:09.000,2022-07-31 02:44:55.000000,2022-07-04 21:48:21,663.0,53.0,335.0,2585,,"Hidden Markov Models in Python, with scikit-learn like API.",41.0,26,2021-02-03 14:33:20,0.2.5,8.0,,hmmlearn,conda-forge/hmmlearn,,,['sklearn'],1360.0,1360.0,https://pypi.org/project/hmmlearn,105629.0,108581.0,https://anaconda.org/conda-forge/hmmlearn,2022-02-12 03:10:38.209,132845.0,,,,,2.0,,,,,,,,,,,,,,,, +248,smart-open,True,RaRe-Technologies/smart_open,,data-loading,https://github.com/RaRe-Technologies/smart_open,https://github.com/RaRe-Technologies/smart_open,MIT,2015-01-02 13:05:52.000,2022-08-25 20:47:58.000000,2022-08-21 13:04:21,314.0,60.0,295.0,2573,983.0,"Utils for streaming large files (S3, HDFS, gzip, bz2...).",96.0,26,2022-08-21 12:49:45,6.1.0,43.0,,smart-open,,,,,,,https://pypi.org/project/smart-open,11015576.0,11015576.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +249,pytorch-optimizer,True,jettify/pytorch-optimizer,,pytorch-utils,https://github.com/jettify/pytorch-optimizer,https://github.com/jettify/pytorch-optimizer,Apache-2.0,2020-01-03 03:16:39.000,2022-08-15 10:07:52.000000,2021-11-11 16:56:57,241.0,21.0,29.0,2523,430.0,torch-optimizer -- collection of optimizers for..,25.0,26,2021-10-31 02:57:04,0.3.0,20.0,,torch_optimizer,,,,['pytorch'],670.0,670.0,https://pypi.org/project/torch_optimizer,48337.0,48337.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +250,STUMPY,True,TDAmeritrade/stumpy,,time-series-data,https://github.com/TDAmeritrade/stumpy,https://github.com/TDAmeritrade/stumpy,BSD-3-Clause,2019-05-03 19:23:44.000,2022-08-20 19:09:24.000000,2022-08-04 19:33:55,226.0,39.0,296.0,2357,,STUMPY is a powerful and scalable Python library for computing a Matrix..,31.0,26,2022-03-31 21:21:50,1.11.1,25.0,,stumpy,conda-forge/stumpy,,,,258.0,258.0,https://pypi.org/project/stumpy,171369.0,172597.0,https://anaconda.org/conda-forge/stumpy,2022-03-31 21:30:16.208,47928.0,,,,,2.0,,,,,,,,,,,,,,,, +251,BoTorch,True,pytorch/botorch,,hyperopt,https://github.com/pytorch/botorch,https://github.com/pytorch/botorch,MIT,2018-07-30 23:59:57.000,2022-08-25 19:23:32.000000,2022-08-25 19:21:46,258.0,46.0,246.0,2344,,Bayesian optimization in PyTorch.,80.0,26,2022-08-12 21:19:58,0.6.6,25.0,,botorch,,,,['pytorch'],300.0,300.0,https://pypi.org/project/botorch,206015.0,206015.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +252,HoloViews,True,holoviz/holoviews,,data-viz,https://github.com/holoviz/holoviews,https://github.com/holoviz/holoviews,BSD-3-Clause,2014-05-07 16:59:22.000,2022-08-23 09:32:00.000000,2022-08-22 09:17:01,349.0,883.0,1945.0,2254,10361.0,"With Holoviews, your data visualizes itself.",123.0,26,2022-07-11 12:41:38,1.15.0,66.0,,holoviews,conda-forge/holoviews,,,['jupyter'],,,https://pypi.org/project/holoviews,381400.0,393542.0,https://anaconda.org/conda-forge/holoviews,2022-07-07 21:07:13.582,847725.0,,,,,2.0,,,@pyviz/jupyterlab_pyviz,https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz,839.0,,,,,,,,,,, +253,scikit-plot,True,reiinakano/scikit-plot,,interpretability,https://github.com/reiinakano/scikit-plot,https://github.com/reiinakano/scikit-plot,MIT,2017-02-04 06:22:59.000,2021-08-11 23:58:11.000000,2018-08-19 12:37:47,259.0,19.0,39.0,2239,130.0,An intuitive library to add plotting functionality to..,13.0,26,2018-08-19 12:21:01,0.3.7,17.0,,scikit-plot,conda-forge/scikit-plot,,,['sklearn'],2274.0,2274.0,https://pypi.org/project/scikit-plot,650855.0,652846.0,https://anaconda.org/conda-forge/scikit-plot,2019-06-05 14:23:59.043,121469.0,,,,,2.0,,,,,,,,,,,,,,,, +254,TextAttack,True,QData/TextAttack,,adversarial,https://github.com/QData/TextAttack,https://github.com/QData/TextAttack,MIT,2019-10-15 00:51:44.000,2022-08-20 15:51:10.000000,2022-08-14 16:27:46,246.0,21.0,197.0,2062,2552.0,"TextAttack is a Python framework for adversarial attacks, data..",53.0,26,2022-08-14 16:26:58,0.3.7,13.0,,textattack,,,,,93.0,93.0,https://pypi.org/project/textattack,6641.0,6641.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +255,PyFunctional,True,EntilZha/PyFunctional,,data-pipelines,https://github.com/EntilZha/PyFunctional,https://github.com/EntilZha/PyFunctional,MIT,2015-02-05 17:17:51.000,2022-08-05 20:47:44.000000,2022-08-05 20:47:30,113.0,7.0,120.0,2061,522.0,Python library for creating data pipelines with chain functional..,26.0,26,2021-01-12 19:21:07,1.4.3,11.0,,pyfunctional,,,,,460.0,460.0,https://pypi.org/project/pyfunctional,230611.0,230611.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +256,Ax,True,facebook/Ax,,hyperopt,https://github.com/facebook/Ax,https://github.com/facebook/Ax,MIT,2019-02-09 15:23:44.000,2022-08-25 21:53:25.000000,2022-08-25 21:23:00,208.0,36.0,391.0,1869,,Adaptive Experimentation Platform.,120.0,26,2022-08-17 18:51:50,0.2.6,27.0,,ax-platform,,,,['pytorch'],308.0,308.0,https://pypi.org/project/ax-platform,162996.0,162996.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +257,FairScale,True,facebookresearch/fairscale,,distributed-ml,https://github.com/facebookresearch/fairscale,https://github.com/facebookresearch/fairscale,BSD-3-Clause,2020-07-07 19:02:01.000,2022-08-26 01:31:54.000000,2022-08-26 01:31:53,182.0,67.0,251.0,1849,,PyTorch extensions for high performance and large scale training.,63.0,26,2022-07-26 23:16:17,0.4.8,30.0,,fairscale,,,,['pytorch'],494.0,494.0,https://pypi.org/project/fairscale,227706.0,227706.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +258,Cartopy,True,mapbox/rasterio,,geospatial-data,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,,2013-11-04 16:36:27.000,2022-08-26 04:04:21.000000,2022-08-18 03:59:02,467.0,135.0,1431.0,1801,,Rasterio reads and writes geospatial raster datasets.,130.0,26,2022-08-19 18:48:01,1.3.2,21.0,rasterio/rasterio,Cartopy,conda-forge/cartopy,,,,5403.0,5403.0,https://pypi.org/project/Cartopy,119301.0,149154.0,https://anaconda.org/conda-forge/cartopy,2022-08-25 20:18:53.716,2298036.0,,,,,3.0,761.0,,,,,,,,,,,,,,, +259,jellyfish,True,jamesturk/jellyfish,,nlp,https://github.com/jamesturk/jellyfish,https://github.com/jamesturk/jellyfish,BSD-2-Clause,2010-07-09 20:41:11.000,2022-07-03 15:25:48.000000,2022-01-07 20:13:06,145.0,11.0,99.0,1708,,a python library for doing approximate and phonetic matching of..,25.0,26,,,10.0,,jellyfish,conda-forge/jellyfish,,,,4115.0,4115.0,https://pypi.org/project/jellyfish,2624519.0,2628748.0,https://anaconda.org/conda-forge/jellyfish,2022-04-08 08:13:55.565,300260.0,,,,,2.0,,,,,,,,,,,,,,,, +260,tesserocr,True,sirfz/tesserocr,,ocr,https://github.com/sirfz/tesserocr,https://github.com/sirfz/tesserocr,MIT,2015-12-17 23:29:36.000,2022-08-23 11:38:01.000000,2022-08-23 11:38:01,218.0,79.0,168.0,1684,181.0,A Python wrapper for the tesseract-ocr API.,26.0,26,2021-06-19 21:08:11,2.5.2,13.0,,tesserocr,conda-forge/tesserocr,,,,696.0,696.0,https://pypi.org/project/tesserocr,48583.0,50952.0,https://anaconda.org/conda-forge/tesserocr,2022-05-04 23:34:17.279,80567.0,,,,,2.0,,,,,,,,,,,,,,,, +261,Elephas,True,maxpumperla/elephas,,distributed-ml,https://github.com/maxpumperla/elephas,https://github.com/maxpumperla/elephas,MIT,2015-08-13 12:09:19.000,2022-08-10 22:19:39.000000,2022-03-30 23:22:31,294.0,20.0,138.0,1547,502.0,Distributed Deep learning with Keras & Spark.,27.0,26,2021-08-17 01:14:44,3.0.0,9.0,,elephas,,,,"['keras', 'spark']",56.0,56.0,https://pypi.org/project/elephas,116106.0,116106.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +262,PyVista,True,pyvista/pyvista,,data-viz,https://github.com/pyvista/pyvista,https://github.com/pyvista/pyvista,MIT,2017-05-31 18:01:42.000,2022-08-26 04:01:03.000000,2022-08-26 03:35:36,280.0,258.0,658.0,1413,,3D plotting and mesh analysis through a streamlined interface for the..,104.0,26,2022-08-01 19:01:23,0.36.1,47.0,,pyvista,conda-forge/pyvista,,,['jupyter'],901.0,901.0,https://pypi.org/project/pyvista,45906.0,51345.0,https://anaconda.org/conda-forge/pyvista,2022-08-01 19:06:21.044,211730.0,,,,,2.0,656.0,,,,,,,,,,,,,,, +263,TF Recommenders,True,tensorflow/recommenders,,recommender-systems,https://github.com/tensorflow/recommenders,https://github.com/tensorflow/recommenders,Apache-2.0,2020-06-26 21:38:01.000,2022-08-23 18:33:16.000000,2022-08-23 18:33:11,205.0,139.0,142.0,1413,,TensorFlow Recommenders is a library for building..,37.0,26,2022-07-12 23:32:26,0.7.1,14.0,,tensorflow-recommenders,,,,['tensorflow'],137.0,137.0,https://pypi.org/project/tensorflow-recommenders,560973.0,560973.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +264,Mesh,True,tensorflow/mesh,,distributed-ml,https://github.com/tensorflow/mesh,https://github.com/tensorflow/mesh,Apache-2.0,2018-09-20 20:23:34.000,2022-06-10 18:18:47.000000,2022-06-10 18:18:42,216.0,64.0,14.0,1299,653.0,Mesh TensorFlow: Model Parallelism Made Easier.,48.0,26,2018-12-11 00:09:43,0.0.5,4.0,,mesh-tensorflow,,,,['tensorflow'],710.0,710.0,https://pypi.org/project/mesh-tensorflow,20831.0,20831.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +265,explainerdashboard,True,oegedijk/explainerdashboard,,interpretability,https://github.com/oegedijk/explainerdashboard,https://github.com/oegedijk/explainerdashboard,MIT,2019-10-30 08:26:16.000,2022-06-16 19:38:58.000000,2022-06-16 19:38:52,165.0,15.0,168.0,1295,1284.0,Quickly build Explainable AI dashboards that show the inner..,15.0,26,2022-06-15 12:13:19,0.4.0,70.0,,explainerdashboard,,,,,157.0,157.0,https://pypi.org/project/explainerdashboard,58869.0,58869.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +266,metric-learn,True,scikit-learn-contrib/metric-learn,,others,https://github.com/scikit-learn-contrib/metric-learn,https://github.com/scikit-learn-contrib/metric-learn,MIT,2013-11-02 08:29:47.000,2022-08-19 13:16:19.000000,2022-06-21 11:53:05,221.0,43.0,119.0,1267,286.0,Metric learning algorithms in Python.,22.0,26,2020-07-02 12:55:51,0.6.2,10.0,,metric-learn,,,,['sklearn'],228.0,228.0,https://pypi.org/project/metric-learn,43566.0,43566.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +267,ffn,True,pmorissette/ffn,,financial-data,https://github.com/pmorissette/ffn,https://github.com/pmorissette/ffn,MIT,2014-06-19 15:54:09.000,2022-07-01 03:49:20.000000,2022-07-01 03:49:20,216.0,21.0,82.0,1266,393.0,ffn - a financial function library for Python.,28.0,26,2021-04-21 02:47:05,0.3.6,3.0,,ffn,,,,,222.0,222.0,https://pypi.org/project/ffn,37436.0,37436.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +268,Model Analysis,True,tensorflow/model-analysis,,interpretability,https://github.com/tensorflow/model-analysis,https://github.com/tensorflow/model-analysis,Apache-2.0,2018-03-23 19:08:49.000,2022-08-25 03:25:11.000000,2022-08-25 03:25:10,235.0,16.0,49.0,1166,1193.0,Model analysis tools for TensorFlow.,47.0,26,2022-07-01 08:38:27,0.40.0,50.0,,tensorflow-model-analysis,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/tensorflow-model-analysis,1026699.0,1026699.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +269,ktrain,True,amaiya/ktrain,,ml-frameworks,https://github.com/amaiya/ktrain,https://github.com/amaiya/ktrain,Apache-2.0,2019-02-06 17:01:39.000,2022-08-04 23:22:40.000000,2022-08-04 23:17:02,242.0,2.0,421.0,1041,2844.0,ktrain is a Python library that makes deep learning and AI more..,15.0,26,2022-08-04 23:22:40,0.31.7,100.0,,ktrain,,,,['tensorflow'],328.0,328.0,https://pypi.org/project/ktrain,20346.0,20346.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +270,zarr,True,zarr-developers/zarr-python,,data-containers,https://github.com/zarr-developers/zarr-python,https://github.com/zarr-developers/zarr-python,MIT,2015-12-15 14:49:40.000,2022-08-25 13:35:39.000000,2022-08-15 22:47:23,160.0,193.0,302.0,968,,"An implementation of chunked, compressed, N-dimensional arrays for Python.",65.0,26,2022-06-23 08:46:10,2.12.0,42.0,,zarr,conda-forge/zarr,,,,1425.0,1425.0,https://pypi.org/project/zarr,124244.0,144934.0,https://anaconda.org/conda-forge/zarr,2022-06-23 16:03:38.147,1551813.0,,,,,3.0,,,,,,,,,,,,,,,, +271,Neural Structured Learning,True,tensorflow/neural-structured-learning,,tensorflow-utils,https://github.com/tensorflow/neural-structured-learning,https://github.com/tensorflow/neural-structured-learning,Apache-2.0,2019-08-27 21:48:16.000,2022-08-19 16:37:00.000000,2022-08-19 16:36:58,173.0,2.0,63.0,930,533.0,Training neural models with structured signals.,34.0,26,2022-07-29 20:57:47,1.4.0,7.0,,neural-structured-learning,,,,['tensorflow'],255.0,255.0,https://pypi.org/project/neural-structured-learning,16447.0,16447.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +272,ml-metadata,True,google/ml-metadata,,ml-experiments,https://github.com/google/ml-metadata,https://github.com/google/ml-metadata,Apache-2.0,2019-01-15 21:02:09.000,2022-08-23 18:29:49.000000,2022-08-23 18:29:48,95.0,24.0,67.0,487,645.0,For recording and retrieving metadata associated with ML..,15.0,26,2022-08-23 00:58:31,1.10.0,32.0,,ml-metadata,,,,,242.0,242.0,https://pypi.org/project/ml-metadata,478734.0,478776.0,,,,,,,,2.0,1742.0,,,,,,,,,,,,,,, +273,Face Recognition,True,ageitgey/face_recognition,,image,https://github.com/ageitgey/face_recognition,https://github.com/ageitgey/face_recognition,MIT,2017-03-03 21:52:39.000,2022-07-28 23:17:04.000000,2022-06-10 09:12:18,12161.0,663.0,567.0,45625,238.0,The world's simplest facial recognition api for..,54.0,25,2018-04-02 17:18:43,1.2.2,2.0,,face_recognition,,,,['pytorch'],,,https://pypi.org/project/face_recognition,38641.0,38648.0,,,,,,,,2.0,466.0,,,,,,,,,,,,,,, +274,detectron2,True,facebookresearch/detectron2,,image,https://github.com/facebookresearch/detectron2,https://github.com/facebookresearch/detectron2,Apache-2.0,2019-09-05 21:30:20.000,2022-08-25 19:45:45.000000,2022-08-24 18:04:47,5661.0,231.0,2863.0,22026,,Detectron2 is FAIR's next-generation platform for object..,214.0,25,2021-11-15 22:08:26,0.6,10.0,,,conda-forge/detectron2,,,['pytorch'],712.0,712.0,,,2898.0,https://anaconda.org/conda-forge/detectron2,2022-04-25 07:03:51.961,78247.0,,,,,2.0,,,,,,,,,,,,,,,, +275,Prophet,True,facebook/prophet,,time-series-data,https://github.com/facebook/prophet,https://github.com/facebook/prophet,MIT,2016-11-16 01:50:08.000,2022-08-25 18:02:08.000000,2022-07-07 22:19:56,4195.0,251.0,1612.0,14835,,Tool for producing high quality forecasts for time series data that has..,152.0,25,2022-06-24 21:14:57,1.1,11.0,,fbprophet,,,,,,,https://pypi.org/project/fbprophet,1668667.0,1668679.0,,,,,,,,2.0,807.0,,,,,,,,,,,,,,, +276,Rasa,True,RasaHQ/rasa,,nlp,https://github.com/RasaHQ/rasa,https://github.com/RasaHQ/rasa,Apache-2.0,2016-10-14 12:27:49.000,2022-08-26 02:10:58.000000,2022-08-24 18:38:11,3950.0,810.0,5778.0,14737,,Open source machine learning framework to automate text- and voice-..,548.0,25,2022-08-12 11:15:43,3.2.6,100.0,,rasa,,,,['tensorflow'],,,https://pypi.org/project/rasa,170879.0,170879.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +277,vit-pytorch,True,lucidrains/vit-pytorch,,image,https://github.com/lucidrains/vit-pytorch,https://github.com/lucidrains/vit-pytorch,MIT,2020-10-03 22:47:24.000,2022-07-27 15:58:18.000000,2022-07-27 15:58:18,1825.0,91.0,102.0,11192,,"Implementation of Vision Transformer, a simple way to..",15.0,25,2022-07-16 23:22:50,0.35.8,100.0,,vit-pytorch,,,,['pytorch'],136.0,136.0,https://pypi.org/project/vit-pytorch,18517.0,18517.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +278,Turi Create,True,apple/turicreate,,ml-frameworks,https://github.com/apple/turicreate,https://github.com/apple/turicreate,BSD-3-Clause,2017-12-01 00:42:04.000,2021-11-29 19:55:31.000000,2021-11-29 19:55:31,1104.0,485.0,1288.0,10784,,Turi Create simplifies the development of custom machine learning..,85.0,25,2020-09-30 22:44:07,6.4.1,30.0,,turicreate,,,,,317.0,317.0,https://pypi.org/project/turicreate,20495.0,20615.0,,,,,,,,3.0,6772.0,,,,,,,,,,,,,,, +279,DVC,True,iterative/dvc,,ml-experiments,https://github.com/iterative/dvc,https://github.com/iterative/dvc,Apache-2.0,2017-03-04 08:16:33.000,2022-08-26 03:29:12.000000,2022-08-25 15:19:05,950.0,635.0,3205.0,10199,,Data Version Control | Git for Data & Models.,272.0,25,2022-08-25 19:08:50,2.21.1,194.0,,dvc,conda-forge/dvc,,,,,,https://pypi.org/project/dvc,534582.0,571420.0,https://anaconda.org/conda-forge/dvc,2022-08-25 19:51:58.501,1175928.0,,,,,2.0,116323.0,,,,,,,dvc,,,,,dvc,dvc,, +280,Trax,True,google/trax,,others,https://github.com/google/trax,https://github.com/google/trax,Apache-2.0,2019-10-05 15:09:14.000,2022-08-08 21:40:05.000000,2022-08-08 21:39:59,717.0,89.0,123.0,7075,1609.0,Trax Deep Learning with Clear Code and Speed.,78.0,25,2021-10-26 20:29:38,1.4.1,18.0,,trax,,,,,75.0,75.0,https://pypi.org/project/trax,3993.0,3993.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +281,Great Expectations,True,great-expectations/great_expectations,,data-pipelines,https://github.com/great-expectations/great_expectations,https://github.com/great-expectations/great_expectations,Apache-2.0,2017-09-11 00:18:46.000,2022-08-26 03:30:44.000000,2022-08-26 01:02:50,1042.0,170.0,1188.0,7058,,Always know what to expect from your data.,318.0,25,2022-08-25 17:12:08,0.15.20,100.0,,great_expectations,,,,,,,https://pypi.org/project/great_expectations,5306168.0,5306168.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +282,Facets Overview,True,pair-code/facets,,data-viz,https://github.com/PAIR-code/facets,https://github.com/PAIR-code/facets,Apache-2.0,2017-07-07 14:03:03.000,2021-11-29 10:48:23.000000,2021-05-06 12:01:05,853.0,76.0,76.0,6999,264.0,Visualizations for machine learning datasets.,28.0,25,2019-07-01 16:35:20,1.0.0,4.0,,facets-overview,,,,['jupyter'],129.0,129.0,https://pypi.org/project/facets-overview,298163.0,298163.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +283,faust,True,robinhood/faust,,data-pipelines,https://github.com/robinhood/faust,https://github.com/robinhood/faust,,2017-03-08 18:36:11.000,2022-07-23 14:20:04.000000,2020-10-09 12:59:42,528.0,226.0,239.0,6286,4137.0,Python Stream Processing.,94.0,25,2018-05-24 05:44:13,1.0.10d3,3.0,,faust,,,,,1112.0,1112.0,https://pypi.org/project/faust,31851.0,31851.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +284,stanza,True,stanfordnlp/stanza,,nlp,https://github.com/stanfordnlp/stanza,https://github.com/stanfordnlp/stanza,,2017-09-26 08:00:56.000,2022-08-26 02:02:21.000000,2022-04-23 04:36:46,786.0,85.0,631.0,6249,,Official Stanford NLP Python Library for Many Human Languages.,48.0,25,2022-04-23 06:01:01,1.4.0,13.0,,stanza,stanfordnlp/stanza,,,,1185.0,1185.0,https://pypi.org/project/stanza,333194.0,333386.0,https://anaconda.org/stanfordnlp/stanza,2022-04-23 06:42:39.551,5587.0,,,,,2.0,,,,,,,,,,,,,,,, +285,keras-rl,True,keras-rl/keras-rl,,reinforcement-learning,https://github.com/keras-rl/keras-rl,https://github.com/keras-rl/keras-rl,MIT,2016-07-02 15:53:12.000,2022-05-23 13:10:46.000000,2019-11-11 22:14:54,1297.0,7.0,227.0,5302,308.0,Deep Reinforcement Learning for Keras.,40.0,25,2018-05-01 14:27:32,0.4.2,8.0,,keras-rl,,,,['tensorflow'],606.0,606.0,https://pypi.org/project/keras-rl,1348.0,1348.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +286,snorkel,True,snorkel-team/snorkel,,data-loading,https://github.com/snorkel-team/snorkel,https://github.com/snorkel-team/snorkel,Apache-2.0,2016-02-26 05:52:45.000,2022-08-01 04:39:50.000000,2022-07-29 17:48:21,815.0,18.0,951.0,5234,,A system for quickly generating training data with weak supervision.,78.0,25,2022-07-29 04:06:03,0.9.9,15.0,,snorkel,conda-forge/snorkel,,,,190.0,190.0,https://pypi.org/project/snorkel,65353.0,66187.0,https://anaconda.org/conda-forge/snorkel,2022-07-29 17:25:18.088,30363.0,,,,,3.0,978.0,,,,,,,,,,,,,,, +287,Darts,True,unit8co/darts,,time-series-data,https://github.com/unit8co/darts,https://github.com/unit8co/darts,Apache-2.0,2018-09-13 15:17:28.000,2022-08-25 23:55:57.000000,2022-08-25 15:25:21,480.0,143.0,455.0,4553,831.0,A python library for easy manipulation and forecasting of time series.,61.0,25,2022-08-12 21:02:32,0.21.0,31.0,,u8darts,,unit8/darts,,,92.0,92.0,https://pypi.org/project/u8darts,6355.0,6362.0,,,,https://hub.docker.com/r/unit8/darts,2022-08-12 23:50:36.695341,,356.0,2.0,,,,,,,,,,,,,,,, +288,Tesseract,True,madmaze/pytesseract,,ocr,https://github.com/madmaze/pytesseract,https://github.com/madmaze/pytesseract,Apache-2.0,2010-10-27 23:02:49.000,2022-08-16 07:38:27.000000,2022-08-16 07:38:24,605.0,14.0,298.0,4379,497.0,Python-tesseract is an optical character recognition (OCR) tool for python.,41.0,25,2022-03-14 19:28:46,0.3.10,23.0,,pytesseract,conda-forge/pytesseract,,,,,,https://pypi.org/project/pytesseract,665752.0,679819.0,https://anaconda.org/conda-forge/pytesseract,2022-03-15 01:11:17.076,520494.0,,,,,2.0,,,,,,,,,,,,,,,, +289,ArrayFire,True,arrayfire/arrayfire,,gpu-utilities,https://github.com/arrayfire/arrayfire,https://github.com/arrayfire/arrayfire,BSD-3-Clause,2014-10-28 20:58:33.000,2022-08-25 19:58:39.000000,2022-07-09 02:02:37,492.0,247.0,1287.0,3886,5841.0,ArrayFire: a general purpose GPU library.,81.0,25,2022-05-19 15:14:26,3.8.2,32.0,,arrayfire,,,,,,,https://pypi.org/project/arrayfire,133727.0,133757.0,,,,,,,,2.0,2657.0,,,,,,,,,,,,,,, +290,pytorch-summary,True,sksq96/pytorch-summary,,pytorch-utils,https://github.com/sksq96/pytorch-summary,https://github.com/sksq96/pytorch-summary,MIT,2018-04-23 13:58:04.000,2022-08-05 09:55:03.000000,2021-05-10 18:34:53,402.0,94.0,42.0,3637,57.0,Model summary in PyTorch similar to `model.summary()`..,11.0,25,,,,,torchsummary,,,,['pytorch'],5744.0,5744.0,https://pypi.org/project/torchsummary,100691.0,100691.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +291,AzureML SDK,True,Azure/MachineLearningNotebooks,,ml-experiments,https://github.com/Azure/MachineLearningNotebooks,https://github.com/Azure/MachineLearningNotebooks,MIT,2018-08-17 17:29:14.000,2022-08-19 00:23:55.000000,2022-08-19 00:23:55,2143.0,278.0,1032.0,3368,1227.0,Python notebooks with ML and deep learning examples with Azure..,60.0,25,2019-08-29 17:25:28,80469,28.0,,azureml-sdk,,,,,,,https://pypi.org/project/azureml-sdk,1464770.0,1464780.0,,,,,,,,2.0,463.0,,,,,,,,,,,,,,, +292,MONAI,True,Project-MONAI/MONAI,,medical-data,https://github.com/Project-MONAI/MONAI,https://github.com/Project-MONAI/MONAI,Apache-2.0,2019-10-11 16:41:38.000,2022-08-26 03:04:06.000000,2022-08-25 20:54:13,641.0,218.0,1665.0,3286,,AI Toolkit for Healthcare Imaging.,114.0,25,2022-07-25 18:28:21,0.9.1,12.0,,monai,,,,['pytorch'],457.0,457.0,https://pypi.org/project/monai,48048.0,48048.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +293,ftfy,True,LuminosoInsight/python-ftfy,,nlp,https://github.com/rspeer/python-ftfy,https://github.com/rspeer/python-ftfy,MIT,2012-08-24 16:14:59.000,2022-05-07 09:43:39.000000,2022-02-09 19:43:12,109.0,12.0,118.0,3276,,"Fixes mojibake and other glitches in Unicode text, after the fact.",18.0,25,2021-08-23 21:02:05,6.0.3,11.0,rspeer/python-ftfy,ftfy,conda-forge/ftfy,,,,6574.0,6574.0,https://pypi.org/project/ftfy,2090291.0,2093158.0,https://anaconda.org/conda-forge/ftfy,2022-03-13 19:47:23.479,183549.0,,,,,2.0,,,,,,,,,,,,,,,, +294,Chartify,True,spotify/chartify,,data-viz,https://github.com/spotify/chartify,https://github.com/spotify/chartify,Apache-2.0,2018-09-17 14:12:05.000,2022-08-14 07:19:07.000000,2021-02-05 18:49:02,282.0,41.0,31.0,3201,195.0,Python library that makes it easy for data scientists to create..,21.0,25,2020-11-02 22:13:24,3.0.3,16.0,,chartify,conda-forge/chartify,,,,65.0,65.0,https://pypi.org/project/chartify,10044.0,10513.0,https://anaconda.org/conda-forge/chartify,2020-11-07 19:52:50.628,21106.0,,,,,3.0,,,,,,,,,,,,,,,, +295,facenet-pytorch,True,timesler/facenet-pytorch,,image,https://github.com/timesler/facenet-pytorch,https://github.com/timesler/facenet-pytorch,MIT,2019-05-25 01:29:24.000,2022-07-20 00:52:45.000000,2021-12-13 12:07:11,648.0,60.0,92.0,3044,235.0,Pretrained Pytorch face detection (MTCNN) and recognition..,14.0,25,2020-09-07 23:53:20,2.4.1,6.0,,facenet-pytorch,,,,['pytorch'],854.0,854.0,https://pypi.org/project/facenet-pytorch,18445.0,30314.0,,,,,,,,2.0,391692.0,,,,,,,,,,,,,,, +296,xLearn,True,aksnzhy/xlearn,,ml-frameworks,https://github.com/aksnzhy/xlearn,https://github.com/aksnzhy/xlearn,Apache-2.0,2017-06-10 08:09:31.000,2022-08-23 09:45:09.000000,2022-06-05 10:44:18,513.0,182.0,114.0,3010,1342.0,"High performance, easy-to-use, and scalable machine learning (ML)..",30.0,25,2019-04-25 02:10:05,0.4.4,15.0,,xlearn,,,,,93.0,93.0,https://pypi.org/project/xlearn,5207.0,5271.0,,,,,,,,3.0,3404.0,,,,,,,,,,,,,,, +297,opencv-python,True,skvark/opencv-python,,image,https://github.com/opencv/opencv-python,https://github.com/opencv/opencv-python,MIT,2016-04-08 13:36:40.000,2022-08-25 13:26:43.000000,2022-08-22 10:37:11,577.0,43.0,526.0,2941,860.0,"Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-..",39.0,25,2022-06-07 10:10:16,66,65.0,opencv/opencv-python,opencv-python,,,,,,,https://pypi.org/project/opencv-python,5645063.0,5645063.0,,,,,,,,2.0,,9.0,,,,,,,,,,,,,, +298,Core ML Tools,True,apple/coremltools,,model-serialisation,https://github.com/apple/coremltools,https://github.com/apple/coremltools,BSD-3-Clause,2017-06-30 07:39:02.000,2022-08-25 16:36:13.000000,2022-08-24 17:54:35,423.0,275.0,699.0,2828,,Core ML tools contain supporting tools for Core ML model..,127.0,25,2022-02-22 22:36:08,5.2,28.0,,coremltools,,,,,1009.0,1009.0,https://pypi.org/project/coremltools,92811.0,92885.0,,,,,,,,1.0,4403.0,,,,,,,,,,,,,,, +299,fastNLP,True,fastnlp/fastNLP,,nlp,https://github.com/fastnlp/fastNLP,https://github.com/fastnlp/fastNLP,Apache-2.0,2018-03-07 13:30:20.000,2022-08-23 03:35:06.000000,2022-08-23 02:43:43,420.0,44.0,150.0,2663,2439.0,fastNLP: A Modularized and Extensible NLP Framework. Currently still..,59.0,25,2020-11-06 15:31:29,0.6.0,7.0,,fastnlp,,,,,90.0,90.0,https://pypi.org/project/fastnlp,2464.0,2465.0,,,,,,,,2.0,66.0,,,,,,,,,,,,,,, +300,neuralcoref,True,huggingface/neuralcoref,,nlp,https://github.com/huggingface/neuralcoref,https://github.com/huggingface/neuralcoref,MIT,2017-07-03 13:04:16.000,2022-03-11 12:17:58.000000,2021-06-22 10:51:48,442.0,49.0,253.0,2580,116.0,Fast Coreference Resolution in spaCy with Neural Networks.,21.0,25,2019-04-08 11:28:27,4.0.0,5.0,,neuralcoref,conda-forge/neuralcoref,,,,523.0,523.0,https://pypi.org/project/neuralcoref,272728.0,273135.0,https://anaconda.org/conda-forge/neuralcoref,2020-02-21 22:10:40.453,12021.0,,,,,2.0,453.0,,,,,,,,,,,,,,, +301,StellarGraph,True,stellargraph/stellargraph,,graph,https://github.com/stellargraph/stellargraph,https://github.com/stellargraph/stellargraph,Apache-2.0,2018-04-13 07:35:51.000,2022-03-12 00:28:06.000000,2021-10-29 06:15:49,375.0,273.0,737.0,2477,2515.0,StellarGraph - Machine Learning on Graphs.,36.0,25,2020-06-30 05:15:21,1.2.1,25.0,,stellargraph,,,,['tensorflow'],158.0,158.0,https://pypi.org/project/stellargraph,21517.0,21517.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +302,Alphalens,True,quantopian/alphalens,,financial-data,https://github.com/quantopian/alphalens,https://github.com/quantopian/alphalens,Apache-2.0,2016-06-03 21:49:15.000,2021-12-05 06:35:06.000000,2020-04-27 18:40:41,883.0,38.0,145.0,2379,522.0,Performance analysis of predictive (alpha) stock factors.,25.0,25,2020-04-30 15:42:52,0.4.0,10.0,,alphalens,conda-forge/alphalens,,,,569.0,569.0,https://pypi.org/project/alphalens,12993.0,13287.0,https://anaconda.org/conda-forge/alphalens,2020-05-16 13:52:44.922,15897.0,,,,,2.0,,,,,,,,,,,,,,,, +303,tslearn,True,tslearn-team/tslearn,,time-series-data,https://github.com/tslearn-team/tslearn,https://github.com/tslearn-team/tslearn,BSD-2-Clause,2017-05-04 13:08:13.000,2022-08-25 22:45:20.000000,2022-06-17 20:29:08,284.0,89.0,186.0,2217,,A machine learning toolkit dedicated to time-series data.,39.0,25,2021-08-16 07:09:52,0.5.2,21.0,,tslearn,conda-forge/tslearn,,,['sklearn'],563.0,563.0,https://pypi.org/project/tslearn,100806.0,105985.0,https://anaconda.org/conda-forge/tslearn,2022-01-15 08:48:51.564,274538.0,,,,,2.0,,,,,,,,,,,,,,,, +304,pytorch-forecasting,True,jdb78/pytorch-forecasting,,time-series-data,https://github.com/jdb78/pytorch-forecasting,https://github.com/jdb78/pytorch-forecasting,MIT,2020-07-03 13:05:24.000,2022-08-22 19:48:54.000000,2022-08-22 19:48:42,354.0,252.0,254.0,2192,1493.0,Time series forecasting with PyTorch.,32.0,25,2022-05-23 11:53:09,0.10.2,29.0,,pytorch-forecasting,,,,,,,https://pypi.org/project/pytorch-forecasting,73948.0,73948.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +305,m2cgen,True,BayesWitnesses/m2cgen,,model-serialisation,https://github.com/BayesWitnesses/m2cgen,https://github.com/BayesWitnesses/m2cgen,MIT,2019-01-13 02:32:55.000,2022-08-23 02:01:29.000000,2022-08-14 19:22:19,197.0,24.0,68.0,2177,369.0,"Transform ML models into a native code (Java, C, Python, Go, JavaScript,..",13.0,25,2022-04-25 18:51:36,0.10.0,13.0,,m2cgen,,,,,59.0,59.0,https://pypi.org/project/m2cgen,44920.0,44920.0,,,,,,,,1.0,32.0,,,,,,,,,,,,,,, +306,Spektral,True,danielegrattarola/spektral,,graph,https://github.com/danielegrattarola/spektral,https://github.com/danielegrattarola/spektral,MIT,2019-01-17 11:19:10.000,2022-08-12 12:40:21.000000,2022-07-22 15:30:42,303.0,39.0,193.0,2144,1107.0,Graph Neural Networks with Keras and Tensorflow 2.,24.0,25,2022-07-22 15:16:38,1.2,3.0,,spektral,,,,"['tensorflow""']",144.0,144.0,https://pypi.org/project/spektral,6753.0,6753.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +307,pgmpy,True,pgmpy/pgmpy,,probabilistics,https://github.com/pgmpy/pgmpy,https://github.com/pgmpy/pgmpy,MIT,2013-09-20 08:18:58.000,2022-08-22 07:37:19.000000,2022-08-22 07:37:19,633.0,188.0,582.0,2136,6.0,Python Library for learning (Structure and Parameter) and inference..,110.0,25,2022-06-30 09:29:19,0.1.19,9.0,,pgmpy,,,,,400.0,400.0,https://pypi.org/project/pgmpy,57144.0,57150.0,,,,,,,,3.0,161.0,,,,,,,,,,,,,,, +308,PyTextRank,True,DerwenAI/pytextrank,,nlp,https://github.com/DerwenAI/pytextrank,https://github.com/DerwenAI/pytextrank,MIT,2016-10-02 18:39:12.000,2022-07-27 22:00:22.000000,2022-07-27 21:58:40,301.0,17.0,72.0,1877,,Python implementation of TextRank for phrase extraction and..,18.0,25,2022-07-27 22:00:22,3.2.4,20.0,,pytextrank,,,,,276.0,276.0,https://pypi.org/project/pytextrank,70092.0,70092.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +309,TFX,True,tensorflow/tfx,,data-pipelines,https://github.com/tensorflow/tfx,https://github.com/tensorflow/tfx,Apache-2.0,2019-02-04 17:14:36.000,2022-08-26 01:18:15.000000,2022-08-24 18:23:27,583.0,203.0,572.0,1808,4446.0,TFX is an end-to-end platform for deploying production ML pipelines.,148.0,25,2022-08-02 20:41:16,1.9.1,81.0,,tfx,,,,['tensorflow'],,,https://pypi.org/project/tfx,366771.0,366771.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +310,numexpr,True,pydata/numexpr,,data-containers,https://github.com/pydata/numexpr,https://github.com/pydata/numexpr,MIT,2013-11-30 22:33:48.000,2022-08-19 12:32:57.000000,2022-07-19 20:27:37,175.0,60.0,271.0,1800,751.0,"Fast numerical array expression evaluator for Python, NumPy, PyTables,..",63.0,25,2022-06-27 17:37:51,2.8.3,13.0,,numexpr,conda-forge/numexpr,,,,,,https://pypi.org/project/numexpr,2589940.0,2655380.0,https://anaconda.org/conda-forge/numexpr,2022-07-17 17:04:31.706,4711741.0,,,,,3.0,62.0,,,,,,,,,,,,,,, +311,Alibi,True,SeldonIO/alibi,,interpretability,https://github.com/SeldonIO/alibi,https://github.com/SeldonIO/alibi,Apache-2.0,2019-02-26 10:10:56.000,2022-08-25 16:20:08.000000,2022-08-24 11:06:34,194.0,109.0,190.0,1739,467.0,Algorithms for monitoring and explaining machine learning models.,18.0,25,2022-05-18 11:35:00,0.7.0,25.0,,alibi,,,,,189.0,189.0,https://pypi.org/project/alibi,15409.0,15409.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +312,chainercv,True,chainer/chainercv,,image,https://github.com/chainer/chainercv,https://github.com/chainer/chainercv,MIT,2017-02-13 04:15:10.000,2021-07-01 16:54:50.000000,2020-01-07 11:48:31,302.0,37.0,168.0,1475,4930.0,ChainerCV: a Library for Deep Learning in Computer Vision.,39.0,25,2019-06-12 11:55:02,0.13.1,13.0,,chainercv,,,,,303.0,303.0,https://pypi.org/project/chainercv,3204.0,3204.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +313,TabPy,True,tableau/TabPy,,others,https://github.com/tableau/TabPy,https://github.com/tableau/TabPy,MIT,2016-09-27 21:26:03.000,2022-06-10 20:11:23.000000,2022-06-10 20:11:23,483.0,5.0,288.0,1302,891.0,Execute Python code on the fly and display results in Tableau visualizations:.,47.0,25,2022-01-20 21:47:12,2.5.0,18.0,,tabpy,,,,,93.0,93.0,https://pypi.org/project/tabpy,19090.0,19090.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +314,SciSpacy,True,allenai/scispacy,,nlp,https://github.com/allenai/scispacy,https://github.com/allenai/scispacy,Apache-2.0,2018-09-24 21:45:52.000,2022-08-17 21:20:51.000000,2022-08-04 21:27:12,159.0,28.0,236.0,1210,,A full spaCy pipeline and models for scientific/biomedical..,24.0,25,2022-03-10 20:15:56,0.5.0,7.0,,scispacy,,,,,501.0,501.0,https://pypi.org/project/scispacy,21176.0,21176.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +315,PyTables,True,PyTables/PyTables,,data-containers,https://github.com/PyTables/PyTables,https://github.com/PyTables/PyTables,BSD-3-Clause,2011-06-03 19:44:46.000,2022-08-24 09:21:35.000000,2022-08-24 07:58:56,209.0,145.0,504.0,1142,4127.0,A Python package to manage extremely large amounts of data.,106.0,25,2021-12-28 21:59:09,3.7.0,12.0,,tables,conda-forge/pytables,,,,,,https://pypi.org/project/tables,997064.0,1060830.0,https://anaconda.org/conda-forge/pytables,2022-08-13 08:42:22.555,4591033.0,,,,,3.0,170.0,,,,,,,,,,,,,,, +316,fancyimpute,True,iskandr/fancyimpute,,sklearn-utils,https://github.com/iskandr/fancyimpute,https://github.com/iskandr/fancyimpute,Apache-2.0,2015-11-05 23:39:34.000,2021-10-21 17:45:20.000000,2021-10-21 17:45:17,164.0,2.0,111.0,1098,202.0,Multivariate imputation and matrix completion algorithms..,12.0,25,2021-03-30 16:22:41,0.5.5,5.0,,fancyimpute,,,,['sklearn'],1221.0,1221.0,https://pypi.org/project/fancyimpute,16025.0,16025.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +317,empyrical,True,quantopian/empyrical,,financial-data,https://github.com/quantopian/empyrical,https://github.com/quantopian/empyrical,Apache-2.0,2016-03-18 10:22:52.000,2020-10-14 13:28:13.625000,2020-10-14 13:22:39,299.0,23.0,26.0,966,167.0,Common financial risk and performance metrics. Used by zipline and..,22.0,25,2020-10-13 21:28:25,0.5.5,9.0,,empyrical,conda-forge/empyrical,,,,937.0,937.0,https://pypi.org/project/empyrical,28491.0,28819.0,https://anaconda.org/conda-forge/empyrical,2020-10-14 13:28:13.625,17742.0,,,,,2.0,,,,,,,,,,,,,,,, +318,GPUtil,True,anderskm/gputil,,gpu-utilities,https://github.com/anderskm/gputil,https://github.com/anderskm/gputil,MIT,2017-01-16 11:57:43.000,2022-07-28 04:39:33.000000,2019-08-16 09:00:15,98.0,12.0,14.0,898,140.0,A Python module for getting the GPU status from NVIDA GPUs using..,13.0,25,2018-12-18 08:58:49,1.4.0,8.0,,gputil,,,,,2299.0,2299.0,https://pypi.org/project/gputil,478882.0,478882.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +319,dask-ml,True,dask/dask-ml,,distributed-ml,https://github.com/dask/dask-ml,https://github.com/dask/dask-ml,BSD-3-Clause,2017-06-15 15:56:06.000,2022-07-28 15:53:17.000000,2022-06-19 13:42:12,226.0,201.0,244.0,819,,Scalable Machine Learning with Dask.,76.0,25,2022-05-27 14:17:08,2022.5.27,27.0,,dask-ml,conda-forge/dask-ml,,,,657.0,657.0,https://pypi.org/project/dask-ml,70204.0,77113.0,https://anaconda.org/conda-forge/dask-ml,2022-05-27 20:11:18.984,400743.0,,,,,3.0,,,,,,,,,,,,,,,, +320,mahotas,True,luispedro/mahotas,,image,https://github.com/luispedro/mahotas,https://github.com/luispedro/mahotas,,2010-01-31 00:13:06.000,2022-07-28 01:17:04.704000,2022-06-28 07:53:54,142.0,16.0,63.0,772,1293.0,Computer Vision in Python.,32.0,25,2022-06-28 14:25:55,1.4.13,10.0,,mahotas,conda-forge/mahotas,,,,866.0,866.0,https://pypi.org/project/mahotas,10709.0,15005.0,https://anaconda.org/conda-forge/mahotas,2022-07-28 01:17:04.704,330803.0,,,,,2.0,,,,,,,,,,,,,,,, +321,pyahocorasick,True,WojciechMula/pyahocorasick,,nlp,https://github.com/WojciechMula/pyahocorasick,https://github.com/WojciechMula/pyahocorasick,BSD-3-Clause,2013-05-30 19:55:46.000,2022-08-21 02:47:35.000000,2022-05-04 14:09:22,108.0,24.0,94.0,739,502.0,Python module (C extension and plain python) implementing Aho-..,24.0,25,,,6.0,,pyahocorasick,conda-forge/pyahocorasick,,,,1172.0,1172.0,https://pypi.org/project/pyahocorasick,396783.0,399536.0,https://anaconda.org/conda-forge/pyahocorasick,2022-04-15 10:03:58.690,154178.0,,,,,2.0,,,,,,,,,,,,,,,, +322,TensorFlow I/O,True,tensorflow/io,,tensorflow-utils,https://github.com/tensorflow/io,https://github.com/tensorflow/io,Apache-2.0,2018-11-09 22:44:05.000,2022-08-18 12:26:00.000000,2022-08-18 12:20:51,214.0,196.0,336.0,573,1574.0,"Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO.",94.0,25,2022-05-18 01:03:25,0.26.0,33.0,,tensorflow-io,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-io,443822.0,443822.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +323,GeoViews,True,holoviz/geoviews,,geospatial-data,https://github.com/holoviz/geoviews,https://github.com/holoviz/geoviews,BSD-3-Clause,2016-04-19 16:27:01.000,2022-08-24 06:50:21.000000,2022-08-24 06:50:20,66.0,103.0,196.0,427,706.0,"Simple, concise geographical visualization in Python.",28.0,25,2022-03-08 14:53:17,1.9.5,27.0,,geoviews,conda-forge/geoviews,,,,469.0,469.0,https://pypi.org/project/geoviews,7708.0,9972.0,https://anaconda.org/conda-forge/geoviews,2022-03-08 21:16:14.407,119993.0,,,,,3.0,,,,,,,,,,,,,,,, +324,spleeter,True,deezer/spleeter,,audio,https://github.com/deezer/spleeter,https://github.com/deezer/spleeter,MIT,2019-09-26 15:40:46.000,2022-08-25 16:19:17.000000,2022-06-10 09:22:51,2236.0,144.0,538.0,20334,484.0,Deezer source separation library including pretrained models.,19.0,24,2021-09-03 09:59:00,2.3.0,10.0,,spleeter,conda-forge/spleeter,,,['tensorflow'],,,https://pypi.org/project/spleeter,10451.0,65465.0,https://anaconda.org/conda-forge/spleeter,2020-06-30 14:33:43.220,67522.0,,,,,2.0,1800931.0,,,,,,,,,,,,,,, +325,baselines,True,openai/baselines,,reinforcement-learning,https://github.com/openai/baselines,https://github.com/openai/baselines,MIT,2017-05-24 01:58:13.000,2022-06-16 12:24:07.000000,2020-01-31 13:06:18,3454.0,397.0,432.0,12873,347.0,OpenAI Baselines: high-quality implementations of reinforcement..,114.0,24,,,,,baselines,,,,,408.0,408.0,https://pypi.org/project/baselines,938.0,938.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +326,Ciphey,True,Ciphey/Ciphey,,nlp,https://github.com/Ciphey/Ciphey,https://github.com/Ciphey/Ciphey,MIT,2019-07-16 20:20:39.000,2022-08-19 03:15:49.000000,2022-06-28 14:27:10,652.0,46.0,242.0,10560,1885.0,"Automatically decrypt encryptions without knowing the key or cipher,..",46.0,24,2021-06-06 17:14:16,5.14.0,29.0,,ciphey,,remnux/ciphey,,,,,https://pypi.org/project/ciphey,22681.0,23117.0,,,,https://hub.docker.com/r/remnux/ciphey,2022-05-27 10:54:13.897087,8.0,16134.0,2.0,,,,,,,,,,,,,,,, +327,Qlib,True,microsoft/qlib,,financial-data,https://github.com/microsoft/qlib,https://github.com/microsoft/qlib,MIT,2020-08-14 06:46:00.000,2022-08-25 16:12:23.000000,2022-08-24 06:09:45,1666.0,163.0,437.0,9468,,"Qlib is an AI-oriented quantitative investment platform, which aims to..",105.0,24,2022-06-15 06:53:00,0.8.6,15.0,,pyqlib,,,,['pytorch'],27.0,27.0,https://pypi.org/project/pyqlib,2442.0,2456.0,,,,,,,,2.0,333.0,,,,,,,,,,,,,,, +328,Apex,True,NVIDIA/apex,,gpu-utilities,https://github.com/NVIDIA/apex,https://github.com/NVIDIA/apex,BSD-3-Clause,2018-04-23 16:28:52.000,2022-08-25 21:22:28.000000,2022-08-25 21:22:25,1002.0,530.0,469.0,6574,1035.0,A PyTorch Extension: Tools for easy mixed precision and distributed..,100.0,24,,,1.0,,,conda-forge/nvidia-apex,,,['pytorch'],1164.0,1164.0,,,2985.0,https://anaconda.org/conda-forge/nvidia-apex,2022-04-06 03:11:02.383,101496.0,,,,,2.0,,,,,,,,,,,,,,,, +329,SpeechRecognition,True,Uberi/speech_recognition,,audio,https://github.com/Uberi/speech_recognition,https://github.com/Uberi/speech_recognition,BSD-3-Clause,2014-04-23 04:53:54.000,2022-08-02 12:38:33.000000,2022-08-02 12:38:27,2040.0,229.0,284.0,6455,400.0,"Speech recognition module for Python, supporting..",47.0,24,2017-12-05 14:05:14,3.8.1,23.0,,SpeechRecognition,conda-forge/speechrecognition,,,,,,https://pypi.org/project/SpeechRecognition,333346.0,335343.0,https://anaconda.org/conda-forge/speechrecognition,2021-12-13 09:59:53.408,143791.0,,,,,2.0,,,,,,,,,,,,,,,, +330,NuPIC,True,numenta/nupic,,ml-frameworks,https://github.com/numenta/nupic,https://github.com/numenta/nupic,AGPL-3.0,2013-04-05 23:14:27.000,2021-03-25 21:39:47.000000,2019-10-23 20:45:07,1550.0,452.0,1338.0,6295,6625.0,Numenta Platform for Intelligent Computing is an implementation..,121.0,24,2018-06-01 15:12:12,1.0.5,47.0,,nupic,,,,,111.0,111.0,https://pypi.org/project/nupic,1410.0,1410.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +331,pyAudioAnalysis,True,tyiannak/pyAudioAnalysis,,audio,https://github.com/tyiannak/pyAudioAnalysis,https://github.com/tyiannak/pyAudioAnalysis,Apache-2.0,2014-08-27 12:43:13.000,2022-07-14 21:54:26.000000,2022-04-19 21:26:51,1070.0,171.0,118.0,4944,771.0,"Python Audio Analysis Library: Feature Extraction,..",26.0,24,,,,,pyAudioAnalysis,,,,,293.0,293.0,https://pypi.org/project/pyAudioAnalysis,21357.0,21357.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +332,Lucid,True,tensorflow/lucid,,interpretability,https://github.com/tensorflow/lucid,https://github.com/tensorflow/lucid,Apache-2.0,2018-01-25 17:41:44.000,2022-04-18 14:51:39.000000,2021-03-19 15:48:33,598.0,74.0,100.0,4431,667.0,A collection of infrastructure and tools for research in neural..,40.0,24,2021-03-19 15:59:35,0.3.10,15.0,,lucid,,,,['tensorflow'],651.0,651.0,https://pypi.org/project/lucid,1969.0,1969.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +333,torchdiffeq,True,rtqichen/torchdiffeq,,pytorch-utils,https://github.com/rtqichen/torchdiffeq,https://github.com/rtqichen/torchdiffeq,MIT,2018-11-14 17:51:25.000,2022-08-10 14:37:11.000000,2022-08-10 14:37:11,725.0,38.0,137.0,4196,240.0,Differentiable ODE solvers with full GPU support and..,21.0,24,,,,,torchdiffeq,,,,['pytorch'],295.0,295.0,https://pypi.org/project/torchdiffeq,24533.0,24533.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +334,tensorflow-probability,True,tensorflow/probability,,probabilistics,https://github.com/tensorflow/probability,https://github.com/tensorflow/probability,Apache-2.0,2017-10-23 23:50:54.000,2022-08-26 01:02:06.000000,2022-08-26 01:02:04,963.0,506.0,687.0,3757,,Probabilistic reasoning and statistical analysis in..,458.0,24,2022-06-07 18:01:34,0.17.0,43.0,,tensorflow-probability,conda-forge/tensorflow-probability,,,['tensorflow'],,,https://pypi.org/project/tensorflow-probability,905728.0,907388.0,https://anaconda.org/conda-forge/tensorflow-probability,2022-08-08 13:42:52.189,69729.0,,,,,3.0,,,,,,,,,,,,,,,, +335,vaderSentiment,True,cjhutto/vaderSentiment,,nlp,https://github.com/cjhutto/vaderSentiment,https://github.com/cjhutto/vaderSentiment,MIT,2014-11-17 16:31:45.000,2022-04-01 13:57:36.000000,2022-04-01 13:57:36,882.0,35.0,77.0,3688,131.0,VADER Sentiment Analysis. VADER (Valence Aware Dictionary and..,11.0,24,2014-11-17 16:34:37,0.5,1.0,,vadersentiment,,,,,4132.0,4132.0,https://pypi.org/project/vadersentiment,189061.0,189061.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +336,causalml,True,uber/causalml,,others,https://github.com/uber/causalml,https://github.com/uber/causalml,,2019-07-09 02:08:58.000,2022-08-24 13:09:26.000000,2022-08-22 19:19:51,515.0,59.0,219.0,3242,478.0,Uplift modeling and causal inference with machine learning..,44.0,24,2022-03-14 23:35:04,0.12.3,9.0,,causalml,,,,,52.0,52.0,https://pypi.org/project/causalml,48209.0,48209.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +337,ART,True,Trusted-AI/adversarial-robustness-toolbox,,adversarial,https://github.com/Trusted-AI/adversarial-robustness-toolbox,https://github.com/Trusted-AI/adversarial-robustness-toolbox,MIT,2018-03-15 14:40:43.000,2022-08-25 20:06:36.000000,2022-08-25 20:05:57,849.0,89.0,621.0,3172,,Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning..,108.0,24,2022-07-01 15:43:19,1.11.0,42.0,,adversarial-robustness-toolbox,,,,,248.0,248.0,https://pypi.org/project/adversarial-robustness-toolbox,5559.0,5559.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +338,torchtext,True,pytorch/text,,nlp,https://github.com/pytorch/text,https://github.com/pytorch/text,BSD-3-Clause,2016-12-12 00:56:03.000,2022-08-25 11:33:57.000000,2022-08-19 15:54:10,703.0,225.0,449.0,3073,847.0,Data loaders and abstractions for text and NLP.,135.0,24,2022-08-05 22:18:59,0.13.1,20.0,,torchtext,,,,['pytorch'],,,https://pypi.org/project/torchtext,268588.0,268588.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +339,VisPy,True,vispy/vispy,,data-viz,https://github.com/vispy/vispy,https://github.com/vispy/vispy,,2013-03-21 18:43:22.000,2022-08-24 14:25:50.000000,2022-08-24 14:25:50,582.0,266.0,1048.0,2919,,High-performance interactive 2D/3D data visualization library.,175.0,24,2022-07-04 15:33:11,0.11.0,29.0,,vispy,conda-forge/vispy,,,['jupyter'],821.0,821.0,https://pypi.org/project/vispy,50728.0,55378.0,https://anaconda.org/conda-forge/vispy,2022-07-05 16:41:32.117,269147.0,,,,,3.0,,,vispy,https://www.npmjs.com/package/vispy,10.0,,,,,,,,,,, +340,TorchServe,True,pytorch/serve,,model-serialisation,https://github.com/pytorch/serve,https://github.com/pytorch/serve,Apache-2.0,2019-10-03 03:17:43.000,2022-08-25 22:11:01.000000,2022-08-25 16:44:55,573.0,144.0,829.0,2817,3215.0,Model Serving on PyTorch.,125.0,24,2022-05-16 20:02:45,0.6.0,14.0,,torchserve,pytorch/torchserve,pytorch/torchserve,,['pytorch'],,,https://pypi.org/project/torchserve,17114.0,48756.0,https://anaconda.org/pytorch/torchserve,2022-05-13 21:22:14.370,33186.0,https://hub.docker.com/r/pytorch/torchserve,2022-07-19 22:07:31.666907,15.0,1033073.0,2.0,2048.0,,,,,,,,,,,,,,, +341,Arctic,True,man-group/arctic,,data-containers,https://github.com/man-group/arctic,https://github.com/man-group/arctic,LGPL-2.1,2015-05-29 13:37:30.000,2022-08-25 19:47:42.000000,2022-03-02 16:04:05,527.0,77.0,455.0,2769,1111.0,Arctic is a high performance datastore for numeric data.,76.0,24,2022-01-26 14:04:58,1.80.4,8.0,,arctic,conda-forge/arctic,,,,175.0,175.0,https://pypi.org/project/arctic,6417.0,6954.0,https://anaconda.org/conda-forge/arctic,2022-05-11 01:49:53.570,20900.0,,,,,3.0,192.0,,,,,,,,,,,,,,, +342,Acme,True,deepmind/acme,,reinforcement-learning,https://github.com/deepmind/acme,https://github.com/deepmind/acme,Apache-2.0,2020-05-01 09:18:12.000,2022-08-25 14:46:09.000000,2022-08-25 14:45:41,339.0,31.0,183.0,2739,1059.0,A library of reinforcement learning components and agents.,75.0,24,2022-02-10 06:52:01,0.4.0,12.0,,dm-acme,,,,['tensorflow'],99.0,99.0,https://pypi.org/project/dm-acme,5014.0,5014.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +343,aim,True,aimhubio/aim,,ml-experiments,https://github.com/aimhubio/aim,https://github.com/aimhubio/aim,Apache-2.0,2019-05-31 18:25:07.000,2022-08-26 00:06:09.000000,2022-08-25 18:10:40,163.0,132.0,494.0,2702,,"Aim a super-easy way to record, search and compare 1000s of ML training..",42.0,24,2022-08-21 08:49:28,3.13.0,34.0,,aim,,,,,102.0,102.0,https://pypi.org/project/aim,33876.0,33876.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +344,ploomber,True,ploomber/ploomber,,data-pipelines,https://github.com/ploomber/ploomber,https://github.com/ploomber/ploomber,Apache-2.0,2020-01-20 20:13:06.000,2022-08-26 03:05:11.000000,2022-08-26 03:05:11,176.0,201.0,590.0,2635,2872.0,Lean Data Science workflows: develop and test locally. Deploy to..,59.0,24,,,,,ploomber,,,,,51.0,51.0,https://pypi.org/project/ploomber,15266.0,15266.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +345,Pandaral·lel,True,nalepae/pandarallel,,data-containers,https://github.com/nalepae/pandarallel,https://github.com/nalepae/pandarallel,BSD-3-Clause,2019-03-10 11:58:29.000,2022-08-24 21:49:06.000000,2022-08-24 21:49:06,151.0,77.0,90.0,2374,171.0,A simple and efficient tool to parallelize Pandas operations on all availableCPUs.,20.0,24,2022-08-09 09:59:20,1.6.3,39.0,,pandarallel,,,,"['pandas', 'jupyter']",,,https://pypi.org/project/pandarallel,515542.0,515542.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +346,vidgear,True,abhiTronix/vidgear,,image,https://github.com/abhiTronix/vidgear,https://github.com/abhiTronix/vidgear,Apache-2.0,2019-03-17 02:42:42.000,2022-08-25 13:01:31.000000,2022-07-06 02:29:40,189.0,4.0,230.0,2374,915.0,High-performance cross-platform Video Processing Python framework..,13.0,24,2022-07-05 15:51:13,idgear-0.2.6,18.0,,vidgear,,,,,230.0,230.0,https://pypi.org/project/vidgear,6542.0,6557.0,,,,,,,,3.0,645.0,,,,,,,,,,,,,,, +347,Essentia,True,MTG/essentia,,audio,https://github.com/MTG/essentia,https://github.com/MTG/essentia,AGPL-3.0,2013-06-03 14:53:47.000,2022-08-23 11:19:48.000000,2022-08-23 11:19:09,456.0,342.0,607.0,2170,3181.0,"C++ library for audio and music analysis, description and..",74.0,24,2015-03-31 16:33:30,2.0,6.0,,essentia,,,,,319.0,319.0,https://pypi.org/project/essentia,3859.0,3859.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +348,Hyperas,True,maxpumperla/hyperas,,hyperopt,https://github.com/maxpumperla/hyperas,https://github.com/maxpumperla/hyperas,MIT,2016-02-19 14:45:10.000,2022-06-27 15:05:42.000000,2021-11-19 13:23:56,305.0,95.0,158.0,2137,211.0,Keras + Hyperopt: A very simple wrapper for convenient..,21.0,24,,,,,hyperas,,,,['tensorflow'],248.0,248.0,https://pypi.org/project/hyperas,18224.0,18224.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +349,pytorch-nlp,True,PetrochukM/PyTorch-NLP,,nlp,https://github.com/PetrochukM/PyTorch-NLP,https://github.com/PetrochukM/PyTorch-NLP,BSD-3-Clause,2018-02-25 05:00:36.000,2022-07-16 23:44:23.000000,2021-07-10 15:56:42,250.0,18.0,49.0,2104,447.0,Basic Utilities for PyTorch Natural Language Processing (NLP).,18.0,24,2019-11-04 05:16:00,0.5.0,5.0,,pytorch-nlp,,,,['pytorch'],408.0,408.0,https://pypi.org/project/pytorch-nlp,5976.0,5976.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +350,swifter,True,jmcarpenter2/swifter,,data-containers,https://github.com/jmcarpenter2/swifter,https://github.com/jmcarpenter2/swifter,MIT,2018-04-07 21:37:19.000,2022-08-17 15:26:16.515000,2022-08-16 23:30:01,97.0,9.0,113.0,2064,472.0,A package which efficiently applies any function to a pandas..,17.0,24,,,26.0,,swifter,conda-forge/swifter,,,['pandas'],663.0,663.0,https://pypi.org/project/swifter,269021.0,272804.0,https://anaconda.org/conda-forge/swifter,2022-08-17 15:26:16.515,151348.0,,,,,3.0,,,,,,,,,,,,,,,, +351,mljar-supervised,True,mljar/mljar-supervised,,hyperopt,https://github.com/mljar/mljar-supervised,https://github.com/mljar/mljar-supervised,MIT,2018-11-05 12:58:04.000,2022-08-16 08:57:03.000000,2022-08-16 08:55:34,284.0,95.0,399.0,2030,1010.0,Automated Machine Learning Pipeline with Feature Engineering..,19.0,24,2022-08-16 08:57:03,0.11.3,48.0,,mljar-supervised,,,,,50.0,50.0,https://pypi.org/project/mljar-supervised,7400.0,7400.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +352,efficientnet,True,qubvel/efficientnet,,tensorflow-utils,https://github.com/qubvel/efficientnet,https://github.com/qubvel/efficientnet,Apache-2.0,2019-05-30 20:21:09.000,2021-08-16 07:14:52.000000,2021-07-16 09:03:20,453.0,54.0,58.0,1987,66.0,Implementation of EfficientNet model. Keras and..,10.0,24,2020-09-15 16:22:45,1.1.1,8.0,,efficientnet,,,,['tensorflow'],1108.0,1108.0,https://pypi.org/project/efficientnet,53122.0,59265.0,,,,,,,,3.0,239593.0,,,,,,,,,,,,,,, +353,Fairness 360,True,Trusted-AI/AIF360,,interpretability,https://github.com/Trusted-AI/AIF360,https://github.com/Trusted-AI/AIF360,Apache-2.0,2018-08-22 20:47:15.000,2022-08-25 23:58:31.000000,2022-08-25 21:52:30,575.0,79.0,65.0,1806,382.0,A comprehensive set of fairness metrics for datasets and..,52.0,24,2021-03-04 18:01:29,0.4.0,9.0,,aif360,,,,,172.0,172.0,https://pypi.org/project/aif360,7329.0,7329.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +354,HyperTools,True,ContextLab/hypertools,,data-viz,https://github.com/ContextLab/hypertools,https://github.com/ContextLab/hypertools,MIT,2016-09-27 21:31:25.000,2022-02-12 03:29:55.000000,2022-02-12 02:32:06,153.0,68.0,125.0,1736,1636.0,A Python toolbox for gaining geometric insights into high-dimensional..,21.0,24,2022-02-12 03:29:55,0.8.0,21.0,,hypertools,,,,,208.0,208.0,https://pypi.org/project/hypertools,553.0,553.0,,,,,,,,3.0,20.0,,,,,,,,,,,,,,, +355,CausalNex,True,quantumblacklabs/causalnex,,interpretability,https://github.com/quantumblacklabs/causalnex,https://github.com/quantumblacklabs/causalnex,Apache-2.0,2019-12-12 15:26:09.000,2022-08-25 09:36:48.000000,2022-07-06 00:54:07,183.0,19.0,92.0,1614,155.0,A Python library that helps data scientists to infer..,22.0,24,2021-11-11 15:15:24,0.11.0,15.0,,causalnex,,,,"['pytorch', 'sklearn']",53.0,53.0,https://pypi.org/project/causalnex,1273.0,1273.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +356,bt,True,pmorissette/bt,,financial-data,https://github.com/pmorissette/bt,https://github.com/pmorissette/bt,MIT,2014-06-19 16:06:28.000,2022-08-24 17:52:30.000000,2022-08-24 17:52:29,322.0,60.0,237.0,1477,487.0,bt - flexible backtesting for Python.,27.0,24,2021-04-21 02:49:56,0.2.9,2.0,,bt,,,,,132.0,132.0,https://pypi.org/project/bt,5478.0,5478.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +357,streamparse,True,Parsely/streamparse,,data-pipelines,https://github.com/Parsely/streamparse,https://github.com/Parsely/streamparse,Apache-2.0,2014-05-02 20:33:50.000,2022-07-18 20:04:25.000000,2022-07-18 20:04:25,213.0,63.0,263.0,1462,1071.0,"Run Python in Apache Storm topologies. Pythonic API, CLI..",43.0,24,2022-01-10 21:46:17,4.1.2,44.0,,streamparse,,,,,55.0,55.0,https://pypi.org/project/streamparse,2178.0,2178.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +358,fklearn,True,nubank/fklearn,,ml-frameworks,https://github.com/nubank/fklearn,https://github.com/nubank/fklearn,Apache-2.0,2019-02-27 14:32:57.000,2022-08-25 21:07:56.000000,2022-08-25 21:05:27,161.0,26.0,22.0,1410,143.0,fklearn: Functional Machine Learning.,47.0,24,2022-07-27 13:37:41,2.1.0,23.0,,fklearn,,,,,13.0,13.0,https://pypi.org/project/fklearn,11938.0,11938.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +359,ArcGIS API,True,Esri/arcgis-python-api,,geospatial-data,https://github.com/Esri/arcgis-python-api,https://github.com/Esri/arcgis-python-api,Apache-2.0,2016-03-16 01:09:14.000,2022-08-22 07:19:06.000000,2022-08-17 17:30:57,913.0,38.0,434.0,1391,3566.0,Documentation and samples for ArcGIS API for Python.,81.0,24,2022-06-01 17:24:30,2.0.1,31.0,,arcgis,,esridocker/arcgis-api-python-notebook,,,,,https://pypi.org/project/arcgis,45394.0,45559.0,,,,https://hub.docker.com/r/esridocker/arcgis-api-python-notebook,2022-06-17 15:56:10.986929,35.0,7218.0,3.0,5162.0,,,,,,,,,,,,,,, +360,Opacus,True,pytorch/opacus,,privacy-ml,https://github.com/pytorch/opacus,https://github.com/pytorch/opacus,Apache-2.0,2019-12-07 01:58:09.000,2022-08-25 20:38:42.000000,2022-08-25 15:59:50,218.0,42.0,155.0,1216,,Training PyTorch models with differential privacy.,55.0,24,2022-07-13 13:36:07,1.1.3,17.0,,opacus,,,,['pytorch'],131.0,131.0,https://pypi.org/project/opacus,14711.0,14712.0,,,,,,,,2.0,51.0,,,,,,,,,,,,,,, +361,Explainability 360,True,Trusted-AI/AIX360,,interpretability,https://github.com/Trusted-AI/AIX360,https://github.com/Trusted-AI/AIX360,Apache-2.0,2019-07-11 07:17:48.000,2022-07-26 11:58:47.000000,2022-07-26 11:58:46,237.0,37.0,28.0,1145,360.0,Interpretability and explainability of data and machine..,31.0,24,2020-10-28 09:32:21,0.2.1,2.0,,aix360,,,,,55.0,55.0,https://pypi.org/project/aix360,1228.0,1228.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +362,pandasql,True,yhat/pandasql,,data-containers,https://github.com/yhat/pandasql,https://github.com/yhat/pandasql,MIT,2013-02-18 01:53:56.000,2020-08-14 13:00:13.000000,2017-02-01 15:40:30,153.0,46.0,24.0,1144,127.0,sqldf for pandas.,15.0,24,,,,,pandasql,,,,['pandas'],1454.0,1454.0,https://pypi.org/project/pandasql,1625378.0,1625378.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +363,pyclustering,True,annoviko/pyclustering,,others,https://github.com/annoviko/pyclustering,https://github.com/annoviko/pyclustering,BSD-3-Clause,2014-02-25 18:59:03.000,2022-04-08 00:39:29.000000,2021-02-12 19:04:59,225.0,62.0,589.0,986,2079.0,"pyclustring is a Python, C++ data mining library.",26.0,24,2020-11-25 22:33:07,0.10.1.2,18.0,,pyclustering,conda-forge/pyclustering,,,,350.0,350.0,https://pypi.org/project/pyclustering,49561.0,50850.0,https://anaconda.org/conda-forge/pyclustering,2021-09-13 14:29:08.300,41103.0,,,,,3.0,409.0,,,,,,,,,,,,,,, +364,bcolz,True,Blosc/bcolz,,data-containers,https://github.com/Blosc/bcolz,https://github.com/Blosc/bcolz,,2010-08-18 15:27:02.000,2022-06-20 11:21:54.775000,2020-09-10 12:12:45,126.0,122.0,122.0,943,1280.0,A columnar data container that can be compressed.,33.0,24,2018-04-13 07:34:26,1.2.1,3.0,,bcolz,conda-forge/bcolz,,,,1778.0,1778.0,https://pypi.org/project/bcolz,13912.0,18591.0,https://anaconda.org/conda-forge/bcolz,2022-06-20 11:21:54.775,308850.0,,,,,3.0,,,,,,,,,,,,,,,, +365,Nilearn,True,nilearn/nilearn,,medical-data,https://github.com/nilearn/nilearn,https://github.com/nilearn/nilearn,,2011-01-09 19:02:23.000,2022-08-25 13:57:26.000000,2022-08-25 13:57:26,449.0,228.0,1380.0,881,,Machine learning for NeuroImaging in Python.,193.0,24,2022-08-24 11:32:03,0.9.2,19.0,,nilearn,conda-forge/nilearn,,,['sklearn'],1697.0,1697.0,https://pypi.org/project/nilearn,37512.0,39856.0,https://anaconda.org/conda-forge/nilearn,2022-08-24 15:52:48.090,175529.0,,,,,2.0,64.0,,,,,,,,,,,,,,, +366,pythreejs,True,jupyter-widgets/pythreejs,,data-viz,https://github.com/jupyter-widgets/pythreejs,https://github.com/jupyter-widgets/pythreejs,,2013-12-23 17:02:11.000,2022-08-25 13:38:05.000000,2022-08-25 13:37:51,172.0,51.0,165.0,829,1715.0,A Jupyter - Three.js bridge.,30.0,24,2022-08-24 09:43:58,2.3.0,16.0,,pythreejs,conda-forge/pythreejs,,,['jupyter'],21.0,21.0,https://pypi.org/project/pythreejs,63787.0,73862.0,https://anaconda.org/conda-forge/pythreejs,2022-08-25 09:57:28.021,408504.0,,,,,3.0,,,jupyter-threejs,https://www.npmjs.com/package/jupyter-threejs,4629.0,,,,,,,,,,, +367,Intake,True,intake/intake,,data-loading,https://github.com/intake/intake,https://github.com/intake/intake,BSD-2-Clause,2017-08-14 20:44:22.000,2022-08-22 19:29:32.000000,2022-08-22 19:29:31,122.0,84.0,225.0,799,1825.0,"Intake is a lightweight package for finding, investigating, loading and..",78.0,24,,,18.0,,intake,conda-forge/intake,,,,485.0,485.0,https://pypi.org/project/intake,20804.0,25616.0,https://anaconda.org/conda-forge/intake,2022-01-10 03:38:28.358,216543.0,,,,,3.0,,,,,,,,,,,,,,,, +368,scikit-multilearn,True,scikit-multilearn/scikit-multilearn,,sklearn-utils,https://github.com/scikit-multilearn/scikit-multilearn,https://github.com/scikit-multilearn/scikit-multilearn,BSD-2-Clause,2014-04-30 13:05:44.000,2022-07-09 14:15:15.000000,2022-07-09 14:15:15,141.0,82.0,95.0,772,490.0,A scikit-learn based module for multi-label et. al...,17.0,24,2018-12-10 10:51:36,0.2.0,4.0,,scikit-multilearn,,,,['sklearn'],819.0,819.0,https://pypi.org/project/scikit-multilearn,87354.0,87354.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +369,CLTK,True,cltk/cltk,,nlp,https://github.com/cltk/cltk,https://github.com/cltk/cltk,MIT,2014-01-11 23:59:47.000,2022-08-20 03:18:10.000000,2022-07-20 18:52:17,308.0,27.0,499.0,738,3628.0,The Classical Language Toolkit.,116.0,24,2021-06-10 16:34:40,1.0.15,66.0,,cltk,,,,,208.0,208.0,https://pypi.org/project/cltk,482.0,482.0,,,,,,,,2.0,25.0,,,,,,,,,,,,,,, +370,tensorflow-upstream,True,ROCmSoftwarePlatform/tensorflow-upstream,,ml-frameworks,https://github.com/ROCmSoftwarePlatform/tensorflow-upstream,https://github.com/ROCmSoftwarePlatform/tensorflow-upstream,Apache-2.0,2018-04-09 21:24:50.000,2022-08-25 22:40:45.000000,2022-08-23 17:03:25,71.0,54.0,272.0,606,79524.0,TensorFlow ROCm port.,4119.0,24,2019-10-11 17:16:09,2.0.0-rocm,2.0,,tensorflow-rocm,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-rocm,1745.0,1745.0,,,,,,,,3.0,20.0,,,,,,,,,,,,,,, +371,DIPY,True,dipy/dipy,,medical-data,https://github.com/dipy/dipy,https://github.com/dipy/dipy,,2010-02-06 11:43:08.000,2022-08-25 17:19:47.000000,2022-08-25 17:19:47,344.0,113.0,667.0,537,12295.0,DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic..,134.0,24,,,13.0,,dipy,conda-forge/dipy,,,,602.0,602.0,https://pypi.org/project/dipy,13020.0,17336.0,https://anaconda.org/conda-forge/dipy,2022-03-15 06:15:21.138,323772.0,,,,,2.0,,,,,,,,,,,,,,,, +372,tsfresh,True,blue-yonder/tsfresh,,time-series-data,https://github.com/blue-yonder/tsfresh,https://github.com/blue-yonder/tsfresh,MIT,2016-10-26 11:29:17.000,2022-08-09 13:09:18.000000,2021-12-21 03:31:43,1009.0,50.0,440.0,6594,398.0,Automatic extraction of relevant features from time series:.,82.0,23,2021-12-21 03:36:40,0.19.0,11.0,,tsfresh,conda-forge/tsfresh,,,['sklearn'],,,https://pypi.org/project/tsfresh,421385.0,425223.0,https://anaconda.org/conda-forge/tsfresh,2021-12-21 18:56:28.651,218817.0,,,,,2.0,,,,,,,,,,,,,,,, +373,PyTorch3D,True,facebookresearch/pytorch3d,,image,https://github.com/facebookresearch/pytorch3d,https://github.com/facebookresearch/pytorch3d,,2019-10-25 02:23:45.000,2022-08-25 16:42:29.000000,2022-08-25 16:40:43,940.0,88.0,1025.0,6445,,PyTorch3D is FAIR's library of reusable components for deep..,96.0,23,2022-08-10 11:16:16,0.7.0,12.0,,pytorch3d,pytorch3d/pytorch3d,,,['pytorch'],268.0,268.0,https://pypi.org/project/pytorch3d,13868.0,15676.0,https://anaconda.org/pytorch3d/pytorch3d,2022-08-14 22:28:03.284,59676.0,,,,,3.0,,,,,,,,,,,,,,,, +374,Face Alignment,True,1adrianb/face-alignment,,image,https://github.com/1adrianb/face-alignment,https://github.com/1adrianb/face-alignment,BSD-3-Clause,2017-09-15 20:32:44.000,2022-06-21 07:33:21.000000,2021-08-04 06:54:21,1198.0,60.0,220.0,5848,205.0,2D and 3D Face alignment library build using pytorch.,23.0,23,2021-04-28 22:15:40,1.3.4,10.0,,face-alignment,,,,['pytorch'],,,https://pypi.org/project/face-alignment,9624.0,9624.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +375,mmdnn,True,Microsoft/MMdnn,,model-serialisation,https://github.com/microsoft/MMdnn,https://github.com/microsoft/MMdnn,MIT,2017-08-16 08:03:52.000,2022-08-17 14:53:46.000000,2020-08-14 02:32:30,954.0,323.0,287.0,5616,1083.0,MMdnn is a set of tools to help users inter-operate among different deep..,85.0,23,2020-07-24 06:14:52,0.3.1,12.0,,mmdnn,,,,,85.0,85.0,https://pypi.org/project/mmdnn,585.0,647.0,,,,,,,,2.0,3582.0,,,,,,,,,,,,,,, +376,librosa,True,librosa/librosa,,audio,https://github.com/librosa/librosa,https://github.com/librosa/librosa,ISC,2012-10-20 14:21:01.000,2022-08-25 11:15:43.000000,2022-08-25 11:14:00,811.0,45.0,967.0,5358,,Python library for audio and music analysis.,106.0,23,2022-06-27 11:24:38,0.9.2,35.0,,librosa,conda-forge/librosa,,,,,,https://pypi.org/project/librosa,1208202.0,1215143.0,https://anaconda.org/conda-forge/librosa,2022-06-27 13:25:19.354,506701.0,,,,,3.0,,,,,,,,,,,,,,,, +377,TinyDB,True,msiemens/tinydb,,data-containers,https://github.com/msiemens/tinydb,https://github.com/msiemens/tinydb,MIT,2013-07-12 23:31:13.000,2022-07-31 03:30:54.000000,2022-07-23 19:52:28,447.0,11.0,274.0,5269,674.0,TinyDB is a lightweight document oriented database optimized for your..,78.0,23,2022-02-19 16:17:59,4.7.0,59.0,,tinydb,conda-forge/tinydb,,,,,,https://pypi.org/project/tinydb,386740.0,389411.0,https://anaconda.org/conda-forge/tinydb,2022-02-19 18:47:02.852,197715.0,,,,,3.0,,,,,,,,,,,,,,,, +378,flashtext,True,vi3k6i5/flashtext,,nlp,https://github.com/vi3k6i5/flashtext,https://github.com/vi3k6i5/flashtext,MIT,2017-08-15 18:03:01.000,2021-07-26 20:38:52.000000,2020-05-03 07:13:22,572.0,51.0,52.0,5247,108.0,Extract Keywords from sentence or Replace keywords in sentences.,7.0,23,,,,,flashtext,,,,,848.0,848.0,https://pypi.org/project/flashtext,734758.0,734758.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +379,Augmentor,True,mdbloice/Augmentor,,image,https://github.com/mdbloice/Augmentor,https://github.com/mdbloice/Augmentor,MIT,2016-03-01 18:29:55.000,2022-05-24 12:15:11.000000,2022-05-24 12:15:11,823.0,116.0,72.0,4778,544.0,Image augmentation library in Python for machine learning.,22.0,23,,,,,Augmentor,,,,,484.0,484.0,https://pypi.org/project/Augmentor,16065.0,16065.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +380,Hub,True,activeloopai/Hub,,data-pipelines,https://github.com/activeloopai/Hub,https://github.com/activeloopai/Hub,MPL-2.0,2019-08-09 06:17:59.000,2022-08-26 02:01:06.000000,2022-08-26 02:01:05,387.0,43.0,333.0,4752,2203.0,Fastest unstructured dataset management for TensorFlow/PyTorch...,99.0,23,2022-08-24 15:15:52,2.7.5,53.0,,hub,,,,"['tensorflow', 'pytorch']",,,https://pypi.org/project/hub,3664.0,3664.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +381,Edward,True,blei-lab/edward,,probabilistics,https://github.com/blei-lab/edward,https://github.com/blei-lab/edward,,2016-02-10 20:06:05.000,2019-10-22 20:30:48.000000,2018-07-25 01:28:08,754.0,185.0,328.0,4729,1796.0,A probabilistic programming language in TensorFlow. Deep..,87.0,23,2018-01-22 06:03:37,1.3.5,28.0,,edward,,,,['tensorflow'],274.0,274.0,https://pypi.org/project/edward,1277.0,1277.0,,,,,,,,3.0,15.0,,,,,,,,,,,,,,, +382,mlpack,True,mlpack/mlpack,,ml-frameworks,https://github.com/mlpack/mlpack,https://github.com/mlpack/mlpack,,2014-12-17 18:16:59.000,2022-08-23 03:56:39.000000,2022-08-18 13:54:06,1412.0,32.0,1418.0,4060,28222.0,mlpack: a scalable C++ machine learning library --.,289.0,23,2020-10-28 16:27:07,3.4.2,40.0,,mlpack,conda-forge/mlpack,,,,,,https://pypi.org/project/mlpack,631.0,2885.0,https://anaconda.org/conda-forge/mlpack,2021-11-09 18:05:21.719,110466.0,,,,,3.0,,,,,,,,,,,,,,,, +383,TensorFlowOnSpark,True,yahoo/TensorFlowOnSpark,,distributed-ml,https://github.com/yahoo/TensorFlowOnSpark,https://github.com/yahoo/TensorFlowOnSpark,Apache-2.0,2017-01-20 18:15:57.000,2022-04-21 20:08:19.000000,2022-04-21 18:24:14,922.0,10.0,355.0,3806,631.0,TensorFlowOnSpark brings TensorFlow programs to..,34.0,23,2022-04-21 20:41:22,2.2.5,23.0,,tensorflowonspark,,,,"['tensorflow', 'spark']",,,https://pypi.org/project/tensorflowonspark,270522.0,270522.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +384,Dedupe,True,dedupeio/dedupe,,nlp,https://github.com/dedupeio/dedupe,https://github.com/dedupeio/dedupe,MIT,2012-04-20 14:57:36.000,2022-08-17 18:48:43.000000,2022-08-17 17:20:53,460.0,54.0,705.0,3487,,"A python library for accurate and scalable fuzzy matching, record..",64.0,23,,,,,dedupe,,,,,234.0,234.0,https://pypi.org/project/dedupe,326451.0,326451.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +385,scikit-opt,True,guofei9987/scikit-opt,,sklearn-utils,https://github.com/guofei9987/scikit-opt,https://github.com/guofei9987/scikit-opt,MIT,2017-12-05 10:20:41.000,2022-07-15 16:49:30.000000,2022-07-15 16:49:30,796.0,47.0,107.0,3457,323.0,"Genetic Algorithm, Particle Swarm Optimization, Simulated..",16.0,23,2021-06-28 12:45:52,0.6.5,20.0,,scikit-opt,,,,['sklearn'],83.0,83.0,https://pypi.org/project/scikit-opt,1558.0,1558.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +386,nevergrad,True,facebookresearch/nevergrad,,hyperopt,https://github.com/facebookresearch/nevergrad,https://github.com/facebookresearch/nevergrad,MIT,2018-11-21 00:33:17.000,2022-08-25 09:28:03.000000,2022-08-10 10:13:11,312.0,67.0,156.0,3342,,A Python toolbox for performing gradient-free optimization.,50.0,23,,,18.0,,nevergrad,conda-forge/nevergrad,,,,368.0,368.0,https://pypi.org/project/nevergrad,32967.0,34069.0,https://anaconda.org/conda-forge/nevergrad,2021-06-14 12:44:22.518,30869.0,,,,,2.0,,,,,,,,,,,,,,,, +387,textract,True,deanmalmgren/textract,,data-loading,https://github.com/deanmalmgren/textract,https://github.com/deanmalmgren/textract,MIT,2014-07-03 20:36:59.000,2022-08-18 16:25:40.000000,2022-03-10 10:33:50,470.0,82.0,127.0,3286,585.0,extract text from any document. no muss. no fuss.,40.0,23,2021-08-21 17:09:22,1.6.4,16.0,,textract,conda-forge/textract,,,,,,https://pypi.org/project/textract,119948.0,120171.0,https://anaconda.org/conda-forge/textract,2022-03-10 14:00:02.289,15849.0,,,,,3.0,,,,,,,,,,,,,,,, +388,keras-vis,True,raghakot/keras-vis,,interpretability,https://github.com/raghakot/keras-vis,https://github.com/raghakot/keras-vis,MIT,2016-11-11 23:27:34.000,2022-02-07 16:06:07.000000,2020-04-20 01:03:12,634.0,113.0,101.0,2940,195.0,Neural network visualization toolkit for keras.,10.0,23,,,8.0,,keras-vis,,,,['tensorflow'],2063.0,2063.0,https://pypi.org/project/keras-vis,3276.0,3276.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +389,PyQtGraph,True,pyqtgraph/pyqtgraph,,data-viz,https://github.com/pyqtgraph/pyqtgraph,https://github.com/pyqtgraph/pyqtgraph,,2013-09-12 07:18:21.000,2022-08-25 13:10:24.000000,2022-08-24 17:07:22,927.0,325.0,718.0,2904,3322.0,Fast data visualization and GUI tools for scientific / engineering..,232.0,23,2022-03-04 18:36:49,pyqtgraph-0.12.4,9.0,,pyqtgraph,conda-forge/pyqtgraph,,,,,,https://pypi.org/project/pyqtgraph,103293.0,107469.0,https://anaconda.org/conda-forge/pyqtgraph,2022-03-05 00:25:53.937,279804.0,,,,,3.0,,,,,,,,,,,,,,,, +390,Neural Network Libraries,True,sony/nnabla,,ml-frameworks,https://github.com/sony/nnabla,https://github.com/sony/nnabla,Apache-2.0,2017-06-26 01:07:10.000,2022-08-25 07:38:08.000000,2022-08-25 07:38:05,310.0,23.0,49.0,2554,3118.0,Neural Network Libraries.,67.0,23,2022-06-20 00:38:12,1.29.0,61.0,,nnabla,,,,,,,https://pypi.org/project/nnabla,2786.0,2794.0,,,,,,,,3.0,535.0,,,,,,,,,,,,,,, +391,TF Ranking,True,tensorflow/ranking,,recommender-systems,https://github.com/tensorflow/ranking,https://github.com/tensorflow/ranking,Apache-2.0,2018-12-03 20:48:57.000,2022-06-29 05:18:35.000000,2022-04-26 21:33:51,434.0,57.0,236.0,2535,470.0,Learning to Rank in TensorFlow.,28.0,23,2021-11-16 23:49:54,0.5.0,15.0,,tensorflow_ranking,,,,['tensorflow'],,,https://pypi.org/project/tensorflow_ranking,107380.0,107380.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +392,analytics-zoo,True,intel-analytics/analytics-zoo,,distributed-ml,https://github.com/intel-analytics/analytics-zoo,https://github.com/intel-analytics/analytics-zoo,Apache-2.0,2017-05-05 02:27:30.000,2022-06-22 04:30:29.000000,2022-06-01 01:54:06,703.0,409.0,846.0,2526,3427.0,"Distributed Tensorflow, Keras and PyTorch on Apache..",105.0,23,2022-01-24 01:44:53,0.11.2,15.0,,analytics-zoo,,,,['spark'],3.0,3.0,https://pypi.org/project/analytics-zoo,2196.0,2196.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +393,mtcnn,True,ipazc/mtcnn,,image,https://github.com/ipazc/mtcnn,https://github.com/ipazc/mtcnn,MIT,2018-01-05 04:08:32.000,2022-06-07 08:07:35.000000,2021-07-09 11:06:18,458.0,62.0,38.0,1845,56.0,"MTCNN face detection implementation for TensorFlow, as a PIP package.",15.0,23,,,,,mtcnn,,,,['tensorflow'],2573.0,2573.0,https://pypi.org/project/mtcnn,23156.0,23156.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +394,FiftyOne,True,voxel51/fiftyone,,data-viz,https://github.com/voxel51/fiftyone,https://github.com/voxel51/fiftyone,Apache-2.0,2020-04-22 13:43:28.000,2022-08-26 01:47:39.000000,2022-08-25 23:40:14,216.0,281.0,610.0,1837,,"Visualize, create, and debug image and video datasets and model predictions.",46.0,23,2022-08-25 22:22:49,desktop-v0.22.2,48.0,,fiftyone,,,,"['tensorflow', 'pytorch', 'jupyter']",163.0,163.0,https://pypi.org/project/fiftyone,20895.0,20895.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +395,Neural Tangents,True,google/neural-tangents,,ml-frameworks,https://github.com/google/neural-tangents,https://github.com/google/neural-tangents,Apache-2.0,2019-04-08 16:48:48.000,2022-08-19 21:27:02.000000,2022-08-19 21:26:56,204.0,41.0,79.0,1826,,Fast and Easy Infinite Neural Networks in Python.,23.0,23,2022-07-18 19:09:09,0.6.0,13.0,,neural-tangents,,,,,47.0,47.0,https://pypi.org/project/neural-tangents,1499.0,1508.0,,,,,,,,3.0,243.0,,,,,,,,,,,,,,, +396,lightly,True,lightly-ai/lightly,,image,https://github.com/lightly-ai/lightly,https://github.com/lightly-ai/lightly,MIT,2020-10-13 13:02:56.000,2022-08-25 15:22:29.000000,2022-08-25 15:22:28,142.0,66.0,260.0,1746,792.0,A python library for self-supervised learning on images.,19.0,23,2022-08-17 14:50:28,1.2.27,61.0,,lightly,,,,['pytorch'],46.0,46.0,https://pypi.org/project/lightly,3341.0,3341.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +397,FinTA,True,peerchemist/finta,,financial-data,https://github.com/peerchemist/finta,https://github.com/peerchemist/finta,LGPL-3.0,2016-09-01 21:02:46.000,2022-07-24 08:40:51.000000,2022-07-24 08:40:51,547.0,21.0,64.0,1715,394.0,Common financial technical indicators implemented in Pandas.,28.0,23,2021-04-03 08:51:49,1.3,18.0,,finta,,,,,256.0,256.0,https://pypi.org/project/finta,7722.0,7722.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +398,Karate Club,True,benedekrozemberczki/karateclub,,graph,https://github.com/benedekrozemberczki/karateclub,https://github.com/benedekrozemberczki/karateclub,GPL-3.0,2019-12-05 17:35:56.000,2022-08-21 20:58:21.000000,2022-08-20 12:30:34,212.0,,87.0,1709,2250.0,Karate Club: An API Oriented Open-source Python Framework for..,15.0,23,2022-08-13 14:08:23,_10301,100.0,,karateclub,,,,,100.0,100.0,https://pypi.org/project/karateclub,2753.0,2753.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +399,pytorch_geometric_temporal,True,benedekrozemberczki/pytorch_geometric_temporal,,graph,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,https://github.com/benedekrozemberczki/pytorch_geometric_temporal,MIT,2020-06-27 01:11:33.000,2022-08-02 20:19:08.000000,2022-08-02 20:19:08,248.0,7.0,113.0,1690,1891.0,PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021).,23.0,23,2022-07-12 16:35:40,0.53.0,41.0,,torch-geometric-temporal,,,,['pytorch'],,,https://pypi.org/project/torch-geometric-temporal,1806.0,1806.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +400,TensorFlow Privacy,True,tensorflow/privacy,,privacy-ml,https://github.com/tensorflow/privacy,https://github.com/tensorflow/privacy,Apache-2.0,2018-12-21 18:46:46.000,2022-08-25 23:54:20.000000,2022-08-22 23:16:46,353.0,67.0,87.0,1639,725.0,Library for training machine learning models with..,49.0,23,2022-07-27 21:35:20,0.8.2,12.0,,tensorflow-privacy,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-privacy,32253.0,32255.0,,,,,,,,2.0,80.0,,,,,,,,,,,,,,, +401,garage,True,rlworkgroup/garage,,reinforcement-learning,https://github.com/rlworkgroup/garage,https://github.com/rlworkgroup/garage,MIT,2018-06-10 21:31:23.000,2022-08-10 22:51:20.000000,2022-05-20 06:22:46,264.0,195.0,805.0,1498,1220.0,A toolkit for reproducible reinforcement learning research.,78.0,23,2020-09-14 22:30:57,2020.06.3,21.0,,garage,,,,['tensorflow'],51.0,51.0,https://pypi.org/project/garage,460.0,460.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +402,ViZDoom,True,mwydmuch/ViZDoom,,reinforcement-learning,https://github.com/mwydmuch/ViZDoom,https://github.com/mwydmuch/ViZDoom,,2015-06-26 18:38:23.000,2022-06-26 18:35:34.000000,2022-06-26 18:35:34,329.0,87.0,349.0,1405,1552.0,Doom-based AI Research Platform for Reinforcement Learning from Raw..,49.0,23,2022-04-18 01:40:02,1.1.13,24.0,,vizdoom,,,,,148.0,148.0,https://pypi.org/project/vizdoom,627.0,777.0,,,,,,,,2.0,11551.0,,,,,,,,,,,,,,, +403,pyts,True,johannfaouzi/pyts,,time-series-data,https://github.com/johannfaouzi/pyts,https://github.com/johannfaouzi/pyts,BSD-3-Clause,2017-07-31 09:23:16.000,2022-06-16 08:52:20.000000,2022-06-16 08:52:20,137.0,38.0,26.0,1319,,A Python package for time series classification.,11.0,23,2021-10-31 13:50:40,0.12.0,7.0,,pyts,conda-forge/pyts,,,,240.0,240.0,https://pypi.org/project/pyts,144029.0,144396.0,https://anaconda.org/conda-forge/pyts,2021-10-31 15:13:32.850,13228.0,,,,,2.0,,,,,,,,,,,,,,,, +404,livelossplot,True,stared/livelossplot,,ml-experiments,https://github.com/stared/livelossplot,https://github.com/stared/livelossplot,MIT,2018-03-10 17:51:43.000,2022-07-15 12:45:07.000000,2022-04-04 16:13:36,140.0,5.0,70.0,1198,330.0,"Live training loss plot in Jupyter Notebook for Keras,..",17.0,23,,,,,livelossplot,,,,['jupyter'],841.0,841.0,https://pypi.org/project/livelossplot,63440.0,63440.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +405,Labml,True,lab-ml/labml,,ml-experiments,https://github.com/labmlai/labml,https://github.com/labmlai/labml,MIT,2018-11-16 09:34:48.000,2022-08-15 10:19:08.000000,2022-08-15 04:25:24,78.0,13.0,16.0,1162,1278.0,Monitor deep learning model training and hardware usage from your mobile..,7.0,23,2021-08-27 10:19:56,0.4.132,3.0,labmlai/labml,labml,,,,,54.0,54.0,https://pypi.org/project/labml,3202.0,3202.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +406,Hivemind,True,learning-at-home/hivemind,,distributed-ml,https://github.com/learning-at-home/hivemind,https://github.com/learning-at-home/hivemind,MIT,2020-02-27 13:50:19.000,2022-08-24 15:01:35.000000,2022-08-23 11:30:28,67.0,36.0,89.0,1102,515.0,Decentralized deep learning in PyTorch. Built to train models on..,23.0,23,2022-06-20 19:02:33,1.1.0,15.0,,hivemind,,,,,10.0,10.0,https://pypi.org/project/hivemind,5212.0,5212.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +407,Streamz,True,python-streamz/streamz,,time-series-data,https://github.com/python-streamz/streamz,https://github.com/python-streamz/streamz,BSD-3-Clause,2017-04-04 21:45:49.000,2022-07-28 13:12:55.935000,2022-07-27 18:06:48,135.0,97.0,146.0,1084,782.0,Real-time stream processing for python.,45.0,23,,,16.0,,streamz,conda-forge/streamz,,,,312.0,312.0,https://pypi.org/project/streamz,11537.0,17968.0,https://anaconda.org/conda-forge/streamz,2022-07-28 13:12:55.935,379484.0,,,,,2.0,,,,,,,,,,,,,,,, +408,PySAL,True,pysal/pysal,,geospatial-data,https://github.com/pysal/pysal,https://github.com/pysal/pysal,BSD-3-Clause,2013-02-19 17:27:42.000,2022-08-01 15:32:54.853000,2022-07-23 22:25:53,259.0,9.0,600.0,1055,4188.0,PySAL: Python Spatial Analysis Library Meta-Package.,77.0,23,2022-07-31 21:00:14,2.7.0,25.0,,pysal,conda-forge/pysal,,,,,,https://pypi.org/project/pysal,30160.0,36310.0,https://anaconda.org/conda-forge/pysal,2022-08-01 15:32:54.853,449017.0,,,,,3.0,,,,,,,,,,,,,,,, +409,openTSNE,True,pavlin-policar/openTSNE,,data-viz,https://github.com/pavlin-policar/openTSNE,https://github.com/pavlin-policar/openTSNE,BSD-3-Clause,2018-06-08 18:42:09.000,2022-05-27 21:10:04.647000,2022-03-18 13:03:22,121.0,6.0,100.0,1045,603.0,"Extensible, parallel implementations of t-SNE.",10.0,23,2022-03-18 13:55:30,0.6.2,17.0,,opentsne,conda-forge/opentsne,,,,379.0,379.0,https://pypi.org/project/opentsne,21412.0,24912.0,https://anaconda.org/conda-forge/opentsne,2022-05-27 21:10:04.647,154011.0,,,,,3.0,,,,,,,,,,,,,,,, +410,SDV,True,sdv-dev/SDV,,data-loading,https://github.com/sdv-dev/SDV,https://github.com/sdv-dev/SDV,,2018-05-11 15:56:50.000,2022-08-26 02:08:06.000000,2022-08-19 22:18:40,159.0,119.0,459.0,980,1080.0,"Synthetic Data Generation for tabular, relational and time series data.",41.0,23,2022-07-22 03:02:41,0.16.0,37.0,,sdv,,,,,81.0,81.0,https://pypi.org/project/sdv,32608.0,32608.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +411,arch,True,bashtage/arch,,financial-data,https://github.com/bashtage/arch,https://github.com/bashtage/arch,,2014-08-29 15:41:28.000,2022-08-17 08:33:52.000000,2022-08-17 08:29:56,214.0,15.0,162.0,972,,ARCH models in Python.,31.0,23,2022-06-22 10:43:23,5.3.1,38.0,,arch,,,,,624.0,624.0,https://pypi.org/project/arch,321869.0,321869.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +412,PySwarms,True,ljvmiranda921/pyswarms,,others,https://github.com/ljvmiranda921/pyswarms,https://github.com/ljvmiranda921/pyswarms,MIT,2017-07-12 12:04:45.000,2022-08-11 11:20:29.000000,2022-07-03 12:07:58,302.0,8.0,198.0,958,412.0,A research toolkit for particle swarm optimization in Python.,44.0,23,2020-11-14 05:18:38,.1.2.0,15.0,,pyswarms,,,,,180.0,180.0,https://pypi.org/project/pyswarms,17776.0,17776.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +413,GPyOpt,True,SheffieldML/GPyOpt,,hyperopt,https://github.com/SheffieldML/GPyOpt,https://github.com/SheffieldML/GPyOpt,BSD-3-Clause,2014-08-13 09:58:25.000,2020-11-17 10:32:02.000000,2020-11-05 15:16:04,251.0,101.0,186.0,828,514.0,Gaussian Process Optimization using GPy.,49.0,23,2020-03-19 21:21:18,1.2.6,1.0,,gpyopt,,,,,307.0,307.0,https://pypi.org/project/gpyopt,11649.0,11649.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +414,Cornac,True,PreferredAI/cornac,,recommender-systems,https://github.com/PreferredAI/cornac,https://github.com/PreferredAI/cornac,Apache-2.0,2018-07-17 06:31:35.000,2022-08-16 09:46:15.000000,2022-07-22 01:10:13,104.0,9.0,92.0,626,1235.0,A Comparative Framework for Multimodal Recommender Systems.,15.0,23,2022-02-19 03:37:13,1.14.2,41.0,,cornac,conda-forge/cornac,,,,118.0,118.0,https://pypi.org/project/cornac,40195.0,46280.0,https://anaconda.org/conda-forge/cornac,2022-02-19 07:51:09.542,237323.0,,,,,2.0,,,,,,,,,,,,,,,, +415,python-ternary,True,marcharper/python-ternary,,data-viz,https://github.com/marcharper/python-ternary,https://github.com/marcharper/python-ternary,MIT,2012-08-07 23:48:55.000,2022-08-24 19:20:08.000000,2022-02-27 03:35:23,139.0,32.0,95.0,583,394.0,Ternary plotting library for python with matplotlib.,27.0,23,2021-02-17 18:23:31,1.0.8,8.0,,python-ternary,conda-forge/python-ternary,,,,101.0,101.0,https://pypi.org/project/python-ternary,27139.0,28001.0,https://anaconda.org/conda-forge/python-ternary,2021-02-17 22:38:55.625,65533.0,,,,,3.0,18.0,,,,,,,,,,,,,,, +416,snowballstemmer,True,snowballstem/snowball,,nlp,https://github.com/snowballstem/snowball,https://github.com/snowballstem/snowball,BSD-3-Clause,2013-02-23 07:17:42.000,2022-03-28 04:36:11.000000,2021-12-17 04:08:52,155.0,16.0,44.0,581,919.0,Snowball compiler and stemming algorithms.,28.0,23,,,6.0,,snowballstemmer,conda-forge/snowballstemmer,,,,4.0,4.0,https://pypi.org/project/snowballstemmer,7580190.0,7648573.0,https://anaconda.org/conda-forge/snowballstemmer,2021-11-17 09:59:16.947,4923641.0,,,,,3.0,,,,,,,,,,,,,,,, +417,tinytag,True,devsnd/tinytag,,audio,https://github.com/devsnd/tinytag,https://github.com/devsnd/tinytag,MIT,2014-01-27 15:27:01.000,2022-08-13 15:26:44.000000,2022-08-13 15:26:44,88.0,12.0,81.0,555,397.0,"Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and..",22.0,23,,,,,tinytag,,,,,576.0,576.0,https://pypi.org/project/tinytag,84739.0,84739.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +418,pySBD,True,nipunsadvilkar/pySBD,,nlp,https://github.com/nipunsadvilkar/pySBD,https://github.com/nipunsadvilkar/pySBD,MIT,2017-06-11 06:15:20.000,2022-07-22 20:34:33.000000,2021-02-11 16:40:18,58.0,14.0,51.0,472,279.0,pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence..,6.0,23,2021-02-11 16:42:37,0.3.4,15.0,,pysbd,,,,,394.0,394.0,https://pypi.org/project/pysbd,51680.0,51680.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +419,TensorFlow Cloud,True,tensorflow/cloud,,tensorflow-utils,https://github.com/tensorflow/cloud,https://github.com/tensorflow/cloud,Apache-2.0,2020-02-10 18:51:59.000,2022-03-24 17:54:54.000000,2022-03-24 17:54:49,71.0,56.0,26.0,328,569.0,The TensorFlow Cloud repository provides APIs that..,27.0,23,2021-06-16 20:29:30,0.1.16,17.0,,tensorflow-cloud,,,,['tensorflow'],170.0,170.0,https://pypi.org/project/tensorflow-cloud,152027.0,152027.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +420,py3nvml,True,fbcotter/py3nvml,,gpu-utilities,https://github.com/fbcotter/py3nvml,https://github.com/fbcotter/py3nvml,BSD-3-Clause,2016-11-21 01:07:37.000,2022-06-20 06:00:11.237000,2022-04-14 09:41:50,30.0,1.0,12.0,213,86.0,Python 3 Bindings for NVML library. Get NVIDIA GPU status inside..,9.0,23,2019-10-11 13:39:49,0.2.4,6.0,,py3nvml,conda-forge/py3nvml,,,,506.0,506.0,https://pypi.org/project/py3nvml,105826.0,106826.0,https://anaconda.org/conda-forge/py3nvml,2022-06-20 06:00:11.237,31014.0,,,,,2.0,,,,,,,,,,,,,,,, +421,stop-words,True,Alir3z4/python-stop-words,,nlp,https://github.com/Alir3z4/python-stop-words,https://github.com/Alir3z4/python-stop-words,BSD-3-Clause,2014-05-26 06:44:03.000,2021-12-28 13:59:30.000000,2018-07-23 21:04:09,26.0,3.0,9.0,140,90.0,Get list of common stop words in various languages in Python.,8.0,23,2018-07-23 20:58:34,2018.7.23,7.0,,stop-words,,,,,1589.0,1589.0,https://pypi.org/project/stop-words,549333.0,549333.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +422,CNTK,True,microsoft/CNTK,,ml-frameworks,https://github.com/microsoft/CNTK,https://github.com/microsoft/CNTK,,2015-11-26 09:52:06.000,2022-08-17 14:57:15.000000,2020-03-31 15:55:14,4257.0,753.0,2533.0,17207,16116.0,"Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.",271.0,22,2019-04-26 14:13:32,2.7,32.0,,cntk,,,,,,,https://pypi.org/project/cntk,726.0,903.0,,,,,,,,3.0,13984.0,,,,,,,,,,,,,,, +423,Dopamine,True,google/dopamine,,reinforcement-learning,https://github.com/google/dopamine,https://github.com/google/dopamine,Apache-2.0,2018-07-26 09:58:36.000,2022-06-13 19:24:53.000000,2022-06-13 19:24:52,1288.0,65.0,85.0,9876,299.0,Dopamine is a research framework for fast prototyping of..,15.0,22,2019-09-26 14:58:33,2,2.0,,dopamine-rl,,,,['tensorflow'],,,https://pypi.org/project/dopamine-rl,49248.0,49248.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +424,cortex,True,cortexlabs/cortex,,model-serialisation,https://github.com/cortexlabs/cortex,https://github.com/cortexlabs/cortex,Apache-2.0,2019-01-24 04:43:14.000,2022-08-22 22:24:15.000000,2022-04-23 04:02:53,583.0,110.0,983.0,7787,2321.0,Cost-effective serverless computing at scale.,24.0,22,2022-01-10 17:48:15,0.42.0,62.0,,cortex,,,,,,,https://pypi.org/project/cortex,1713.0,1713.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +425,OCRmyPDF,True,jbarlow83/OCRmyPDF,,ocr,https://github.com/ocrmypdf/OCRmyPDF,https://github.com/ocrmypdf/OCRmyPDF,MPL-2.0,2013-12-20 08:26:28.000,2022-08-15 00:01:19.000000,2022-08-15 00:01:10,592.0,86.0,797.0,7010,3304.0,"OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them..",74.0,22,2016-02-17 09:22:48,4.0,5.0,ocrmypdf/OCRmyPDF,ocrmypdf,,,,,,,https://pypi.org/project/ocrmypdf,24989.0,24989.0,,,,,,,,2.0,,,,,,,,ocrmypdf,,,,,ocrmypdf,,, +426,featuretools,True,alteryx/featuretools,,hyperopt,https://github.com/alteryx/featuretools,https://github.com/alteryx/featuretools,BSD-3-Clause,2017-09-08 22:15:17.000,2022-08-25 19:40:51.000000,2022-08-24 20:48:13,803.0,156.0,694.0,6310,,An open source python library for automated feature engineering.,67.0,22,2022-08-18 18:44:10,1.13.0,100.0,,featuretools,conda-forge/featuretools,,,,,,https://pypi.org/project/featuretools,163556.0,165893.0,https://anaconda.org/conda-forge/featuretools,2022-08-18 19:57:05.971,102840.0,,,,,2.0,,,,,,,,,,,,,,,, +427,snownlp,True,isnowfy/snownlp,,chinese-nlp,https://github.com/isnowfy/snownlp,https://github.com/isnowfy/snownlp,MIT,2013-11-26 11:46:56.000,2020-01-19 02:39:05.000000,2020-01-19 02:39:03,1324.0,40.0,65.0,5897,57.0,Python library for processing Chinese text.,8.0,22,,,,,snownlp,,,,,930.0,930.0,https://pypi.org/project/snownlp,3618.0,3618.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +428,scikit-surprise,True,NicolasHug/Surprise,,recommender-systems,https://github.com/NicolasHug/Surprise,https://github.com/NicolasHug/Surprise,BSD-3-Clause,2016-10-23 14:59:38.000,2022-08-22 18:58:36.000000,2022-08-21 17:35:43,920.0,53.0,295.0,5491,643.0,A Python scikit for building and analyzing recommender..,43.0,22,,,6.0,,scikit-surprise,conda-forge/scikit-surprise,,,,,,https://pypi.org/project/scikit-surprise,119935.0,124394.0,https://anaconda.org/conda-forge/scikit-surprise,2021-11-18 20:15:44.176,245249.0,,,,,3.0,,,,,,,,,,,,,,,, +429,textgenrnn,True,minimaxir/textgenrnn,,nlp,https://github.com/minimaxir/textgenrnn,https://github.com/minimaxir/textgenrnn,,2017-08-07 02:13:37.000,2022-07-17 19:07:49.000000,2020-07-14 02:41:10,719.0,127.0,93.0,4745,174.0,Easily train your own text-generating neural network of any..,19.0,22,2020-02-03 01:07:00,2.0.0,12.0,,textgenrnn,,,,['tensorflow'],1017.0,1017.0,https://pypi.org/project/textgenrnn,462.0,476.0,,,,,,,,3.0,735.0,,,,,,,,,,,,,,, +430,NeMo,True,NVIDIA/NeMo,,nlp,https://github.com/NVIDIA/NeMo,https://github.com/NVIDIA/NeMo,Apache-2.0,2019-08-05 20:16:42.000,2022-08-26 03:02:28.000000,2022-08-25 21:17:30,1094.0,38.0,1177.0,4615,,NeMo: a toolkit for conversational AI.,170.0,22,2022-07-01 22:14:42,1.10.0,32.0,,nemo-toolkit,,,,['pytorch'],,,https://pypi.org/project/nemo-toolkit,17830.0,18272.0,,,,,,,,3.0,15495.0,,,,,,,,,,,,,,, +431,FATE,True,FederatedAI/FATE,,privacy-ml,https://github.com/FederatedAI/FATE,https://github.com/FederatedAI/FATE,Apache-2.0,2019-01-24 10:32:43.000,2022-08-26 03:30:35.000000,2022-04-15 10:35:39,1325.0,479.0,844.0,4441,10410.0,An Industrial Grade Federated Learning Framework.,74.0,22,2022-04-18 14:23:38,1.8.0,34.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +432,T5,True,google-research/text-to-text-transfer-transformer,,nlp,https://github.com/google-research/text-to-text-transfer-transformer,https://github.com/google-research/text-to-text-transfer-transformer,Apache-2.0,2019-10-17 21:45:14.000,2022-08-18 22:59:32.000000,2022-08-10 08:17:55,589.0,48.0,341.0,4368,,Code for the paper Exploring the Limits of Transfer Learning with a..,50.0,22,2020-04-03 19:06:25,0.4.0,1.0,,t5,,,,['tensorflow'],114.0,114.0,https://pypi.org/project/t5,10802.0,10802.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +433,Image Deduplicator,True,idealo/imagededup,,image,https://github.com/idealo/imagededup,https://github.com/idealo/imagededup,Apache-2.0,2019-04-05 12:10:54.000,2022-08-18 04:29:45.000000,2020-11-23 17:40:40,373.0,34.0,59.0,4141,460.0,Finding duplicate images made easy!.,10.0,22,2020-11-23 17:55:24,0.2.4,5.0,,imagededup,,,,['tensorflow'],26.0,26.0,https://pypi.org/project/imagededup,1308.0,1308.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +434,TensorTrade,True,tensortrade-org/tensortrade,,financial-data,https://github.com/tensortrade-org/tensortrade,https://github.com/tensortrade-org/tensortrade,Apache-2.0,2019-07-30 21:28:32.000,2022-08-23 22:54:25.000000,2022-08-23 22:54:23,890.0,39.0,194.0,3933,1046.0,"An open source reinforcement learning framework for training,..",61.0,22,2021-05-10 18:04:30,1.0.3,6.0,,tensortrade,,,,,36.0,36.0,https://pypi.org/project/tensortrade,487.0,487.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +435,Lasagne,True,Lasagne/Lasagne,,ml-frameworks,https://github.com/Lasagne/Lasagne,https://github.com/Lasagne/Lasagne,,2014-09-11 15:31:41.000,2022-03-26 02:58:32.000000,2019-11-20 20:28:30,933.0,115.0,402.0,3816,1161.0,Lightweight library to build and train neural networks in Theano.,72.0,22,2015-08-13 21:00:09,0.1,1.0,,lasagne,,,,,925.0,925.0,https://pypi.org/project/lasagne,1356.0,1356.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +436,PyAlgoTrade,True,gbeced/pyalgotrade,,financial-data,https://github.com/gbeced/pyalgotrade,https://github.com/gbeced/pyalgotrade,Apache-2.0,2012-03-07 01:09:54.000,2022-07-13 19:50:51.000000,2018-08-21 02:42:52,1236.0,39.0,84.0,3745,1156.0,Python Algorithmic Trading Library.,11.0,22,,,,,pyalgotrade,,,,,114.0,114.0,https://pypi.org/project/pyalgotrade,480.0,480.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +437,yellowbrick,True,DistrictDataLabs/yellowbrick,,interpretability,https://github.com/DistrictDataLabs/yellowbrick,https://github.com/DistrictDataLabs/yellowbrick,Apache-2.0,2016-05-18 14:12:17.000,2022-08-21 12:54:41.000000,2022-08-21 12:54:36,507.0,79.0,591.0,3713,,Visual analysis and diagnostic tools to facilitate machine..,109.0,22,2022-08-21 12:49:43,1.5,24.0,,yellowbrick,,,,['sklearn'],,,https://pypi.org/project/yellowbrick,580163.0,580163.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +438,AdaNet,True,tensorflow/adanet,,hyperopt,https://github.com/tensorflow/adanet,https://github.com/tensorflow/adanet,Apache-2.0,2018-06-28 20:20:24.000,2021-08-30 19:33:24.000000,2021-08-30 19:33:24,523.0,63.0,49.0,3416,440.0,Fast and flexible AutoML with learning guarantees.,27.0,22,2020-07-09 20:53:28,0.9.0,11.0,,adanet,,,,['tensorflow'],44.0,44.0,https://pypi.org/project/adanet,487.0,487.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +439,TensorForce,True,tensorforce/tensorforce,,reinforcement-learning,https://github.com/tensorforce/tensorforce,https://github.com/tensorforce/tensorforce,Apache-2.0,2017-03-19 16:24:22.000,2022-07-29 23:31:11.000000,2022-02-10 08:43:04,512.0,25.0,626.0,3161,2099.0,Tensorforce: a TensorFlow library for applied..,82.0,22,2021-08-30 20:20:58,0.6.5,14.0,,tensorforce,,,,['tensorflow'],,,https://pypi.org/project/tensorforce,1165.0,1165.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +440,phonenumbers,True,daviddrysdale/python-phonenumbers,,nlp,https://github.com/daviddrysdale/python-phonenumbers,https://github.com/daviddrysdale/python-phonenumbers,Apache-2.0,2011-04-21 03:06:38.000,2022-08-19 21:24:21.176000,2022-08-19 17:21:51,366.0,4.0,144.0,3071,,Python port of Google's libphonenumber.,26.0,22,,,64.0,,phonenumbers,conda-forge/phonenumbers,,,,,,https://pypi.org/project/phonenumbers,4582513.0,4590699.0,https://anaconda.org/conda-forge/phonenumbers,2022-08-19 21:24:21.176,605769.0,,,,,3.0,,,,,,,,,,,,,,,, +441,Hummingbird,True,microsoft/hummingbird,,model-serialisation,https://github.com/microsoft/hummingbird,https://github.com/microsoft/hummingbird,MIT,2020-03-12 20:27:03.000,2022-08-22 16:54:51.000000,2022-08-17 08:07:37,240.0,40.0,207.0,2993,,Hummingbird compiles trained ML models into tensor computation for..,31.0,22,2022-08-05 20:36:45,0.4.5,18.0,,hummingbird-ml,,,,,39.0,39.0,https://pypi.org/project/hummingbird-ml,3911.0,3917.0,,,,,,,,3.0,181.0,,,,,,,,,,,,,,, +442,GluonTS,True,awslabs/gluon-ts,,time-series-data,https://github.com/awslabs/gluon-ts,https://github.com/awslabs/gluon-ts,Apache-2.0,2019-05-15 17:17:29.000,2022-08-25 19:30:04.000000,2022-08-25 19:30:04,583.0,235.0,504.0,2919,,Probabilistic time series modeling in Python.,93.0,22,2022-08-14 16:56:10,0.10.4,55.0,,gluonts,,,,['mxnet'],,,https://pypi.org/project/gluonts,135315.0,135315.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +443,SHOGUN,True,shogun-toolbox/shogun,,ml-frameworks,https://github.com/shogun-toolbox/shogun,https://github.com/shogun-toolbox/shogun,BSD-3-Clause,2011-04-01 10:44:32.000,2022-01-18 22:03:55.000000,2020-12-08 16:56:38,1028.0,414.0,1106.0,2901,16205.0,Unified and efficient Machine Learning.,248.0,22,2019-07-05 10:23:31,shogun_6.1.4,10.0,,,conda-forge/shogun,shogun/shogun,,,,,,,1914.0,https://anaconda.org/conda-forge/shogun,2018-06-25 20:49:17.070,116165.0,https://hub.docker.com/r/shogun/shogun,2019-01-31 13:45:10.435327,1.0,1489.0,3.0,,,,,,,,shogun,,,,,,,, +444,eli5,True,TeamHG-Memex/eli5,,interpretability,https://github.com/TeamHG-Memex/eli5,https://github.com/TeamHG-Memex/eli5,MIT,2016-09-15 01:04:57.000,2022-05-14 05:59:23.776000,2020-01-22 07:39:36,310.0,140.0,112.0,2576,1198.0,A library for debugging/inspecting machine learning classifiers and..,14.0,22,,,11.0,,eli5,conda-forge/eli5,,,,,,https://pypi.org/project/eli5,481411.0,483311.0,https://anaconda.org/conda-forge/eli5,2022-05-14 05:59:23.776,119711.0,,,,,2.0,,,,,,,,,,,,,,,, +445,DeepVariant,True,google/deepvariant,,medical-data,https://github.com/google/deepvariant,https://github.com/google/deepvariant,BSD-3-Clause,2017-11-23 01:56:22.000,2022-06-13 17:38:49.000000,2022-06-02 05:29:11,617.0,6.0,497.0,2560,1945.0,DeepVariant is an analysis pipeline that uses a deep neural..,24.0,22,2022-06-02 18:41:21,1.4.0,18.0,,,bioconda/deepvariant,,,['tensorflow'],,,,,869.0,https://anaconda.org/bioconda/deepvariant,2022-06-05 19:39:33.507,43734.0,,,,,3.0,4145.0,,,,,,,,,,,,,,, +446,knockknock,True,huggingface/knockknock,,ml-experiments,https://github.com/huggingface/knockknock,https://github.com/huggingface/knockknock,MIT,2019-03-20 13:08:55.000,2022-05-26 16:35:40.000000,2020-03-16 04:26:47,209.0,16.0,23.0,2492,75.0,Knock Knock: Get notified when your training ends with only two..,18.0,22,,,5.0,,knockknock,conda-forge/knockknock,,,,378.0,378.0,https://pypi.org/project/knockknock,59145.0,59439.0,https://anaconda.org/conda-forge/knockknock,2020-03-17 01:52:16.317,9996.0,,,,,3.0,,,,,,,,,,,,,,,, +447,Sweetviz,True,fbdesignpro/sweetviz,,data-viz,https://github.com/fbdesignpro/sweetviz,https://github.com/fbdesignpro/sweetviz,MIT,2020-05-09 15:25:47.000,2022-06-14 21:52:54.000000,2022-06-08 12:10:12,209.0,28.0,72.0,2139,103.0,"Visualize and compare datasets, target values and associations, with one..",6.0,22,2022-06-14 21:52:54,2.1.4,6.0,,sweetviz,,,,,,,https://pypi.org/project/sweetviz,64276.0,64276.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +448,SRU,True,asappresearch/sru,,pytorch-utils,https://github.com/asappresearch/sru,https://github.com/asappresearch/sru,MIT,2017-08-28 20:37:41.000,2022-01-04 21:17:53.000000,2021-05-19 15:52:48,304.0,59.0,68.0,2060,400.0,Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755).,21.0,22,2021-05-18 16:12:33,2.6.0,30.0,,sru,,,,['pytorch'],18.0,18.0,https://pypi.org/project/sru,2695.0,2695.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +449,RecBole,True,RUCAIBox/RecBole,,recommender-systems,https://github.com/RUCAIBox/RecBole,https://github.com/RUCAIBox/RecBole,MIT,2020-06-11 15:18:11.000,2022-08-26 04:09:54.000000,2022-08-26 04:09:54,384.0,63.0,400.0,2035,3557.0,"A unified, comprehensive and efficient recommendation library.",47.0,22,2022-02-25 13:56:32,1.0.1,7.0,,recbole,aibox/recbole,,,['pytorch'],,,https://pypi.org/project/recbole,6675.0,6766.0,https://anaconda.org/aibox/recbole,2022-02-25 14:10:37.696,1931.0,,,,,3.0,,,,,,,,,,,,,,,, +450,langid,True,saffsd/langid.py,,nlp,https://github.com/saffsd/langid.py,https://github.com/saffsd/langid.py,,2011-04-29 00:16:56.000,2020-01-01 10:49:30.000000,2017-07-15 02:49:17,282.0,25.0,46.0,1992,242.0,Stand-alone language identification system.,9.0,22,,,,,langid,,,,,1086.0,1086.0,https://pypi.org/project/langid,384138.0,384138.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +451,PyFlux,True,RJT1990/pyflux,,time-series-data,https://github.com/RJT1990/pyflux,https://github.com/RJT1990/pyflux,BSD-3-Clause,2016-02-16 20:12:02.000,2019-03-19 10:45:02.000000,2018-12-16 15:30:13,225.0,85.0,66.0,1987,118.0,Open source time series library for Python.,6.0,22,,,,,pyflux,,,,,220.0,220.0,https://pypi.org/project/pyflux,147259.0,147259.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +452,scattertext,True,JasonKessler/scattertext,,nlp,https://github.com/JasonKessler/scattertext,https://github.com/JasonKessler/scattertext,Apache-2.0,2016-07-21 01:47:12.000,2022-03-26 17:35:11.489000,2022-03-26 09:22:25,251.0,16.0,73.0,1869,357.0,Beautiful visualizations of how language differs among document..,12.0,22,2017-03-13 05:31:21,0.0.2.4.4,14.0,,scattertext,conda-forge/scattertext,,,,307.0,307.0,https://pypi.org/project/scattertext,2360.0,3456.0,https://anaconda.org/conda-forge/scattertext,2022-03-26 17:35:11.489,65816.0,,,,,3.0,,,,,,,,,,,,,,,, +453,AmpliGraph,True,Accenture/AmpliGraph,,graph,https://github.com/Accenture/AmpliGraph,https://github.com/Accenture/AmpliGraph,Apache-2.0,2019-01-09 14:52:05.000,2022-06-23 08:04:00.000000,2021-05-25 16:49:48,210.0,26.0,182.0,1804,947.0,Python library for Representation Learning on Knowledge..,19.0,22,2021-05-25 16:57:42,1.4.0,11.0,,ampligraph,,,,['tensorflow'],25.0,25.0,https://pypi.org/project/ampligraph,1199.0,1199.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +454,Talos,True,autonomio/talos,,hyperopt,https://github.com/autonomio/talos,https://github.com/autonomio/talos,MIT,2018-05-04 20:36:41.000,2022-05-28 10:07:13.000000,2022-04-23 16:54:30,255.0,24.0,372.0,1544,635.0,"Hyperparameter Optimization for TensorFlow, Keras and PyTorch.",22.0,22,2022-05-28 10:07:13,1.3,15.0,,talos,,,,['tensorflow'],148.0,148.0,https://pypi.org/project/talos,748.0,748.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +455,Magnitude,True,plasticityai/magnitude,,nn-search,https://github.com/plasticityai/magnitude,https://github.com/plasticityai/magnitude,MIT,2018-02-24 07:28:16.000,2021-02-23 18:10:43.000000,2020-07-17 20:19:46,106.0,32.0,51.0,1532,350.0,"A fast, efficient universal vector embedding utility package.",4.0,22,2020-05-25 11:26:09,0.1.143,100.0,,pymagnitude,,,,,243.0,243.0,https://pypi.org/project/pymagnitude,3080.0,3080.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +456,anaGo,True,Hironsan/anago,,nlp,https://github.com/Hironsan/anago,https://github.com/Hironsan/anago,MIT,2017-06-26 21:28:36.000,2022-07-06 20:05:03.000000,2021-04-01 12:34:50,362.0,37.0,72.0,1460,298.0,"Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-..",11.0,22,2018-06-03 13:51:56,1.0.0,5.0,,anago,,,,['tensorflow'],30.0,30.0,https://pypi.org/project/anago,1175.0,1175.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +457,sense2vec,True,explosion/sense2vec,,nlp,https://github.com/explosion/sense2vec,https://github.com/explosion/sense2vec,MIT,2016-01-23 22:15:49.000,2021-08-16 11:44:51.000000,2021-08-16 11:44:51,223.0,20.0,88.0,1401,454.0,Contextually-keyed word vectors.,17.0,22,2021-02-07 06:11:17,2.0.0,16.0,,sense2vec,conda-forge/sense2vec,,,,170.0,170.0,https://pypi.org/project/sense2vec,3546.0,5024.0,https://anaconda.org/conda-forge/sense2vec,2021-07-14 13:20:19.752,27338.0,,,,,3.0,36249.0,,,,,,,,,,,,,,, +458,Paddle Graph Learning,True,PaddlePaddle/PGL,,graph,https://github.com/PaddlePaddle/PGL,https://github.com/PaddlePaddle/PGL,Apache-2.0,2019-06-11 03:23:28.000,2022-08-22 02:57:01.000000,2022-08-22 02:57:01,269.0,52.0,94.0,1386,,Paddle Graph Learning (PGL) is an efficient and..,28.0,22,2022-08-10 06:23:44,2.2.4,8.0,,pgl,,,,['paddle'],33.0,33.0,https://pypi.org/project/pgl,1840.0,1840.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +459,PyCUDA,True,inducer/pycuda,,gpu-utilities,https://github.com/inducer/pycuda,https://github.com/inducer/pycuda,,2011-04-06 02:53:31.000,2022-08-16 20:24:28.000000,2022-08-16 20:08:00,254.0,61.0,161.0,1367,,"CUDA integration for Python, plus shiny features.",76.0,22,2022-06-24 23:18:35,2022.1,1.0,,pycuda,,,,,1459.0,1459.0,https://pypi.org/project/pycuda,34825.0,34825.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +460,NiftyNet,True,NifTK/NiftyNet,,medical-data,https://github.com/NifTK/NiftyNet,https://github.com/NifTK/NiftyNet,Apache-2.0,2017-08-30 07:55:43.000,2020-04-21 19:54:52.000000,2020-04-21 19:54:51,392.0,100.0,224.0,1314,2848.0,[unmaintained] An open-source convolutional neural..,59.0,22,2019-10-09 19:33:30,0.6.0,8.0,,niftynet,,,,['tensorflow'],38.0,38.0,https://pypi.org/project/niftynet,264.0,264.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +461,gplearn,True,trevorstephens/gplearn,,others,https://github.com/trevorstephens/gplearn,https://github.com/trevorstephens/gplearn,BSD-3-Clause,2015-03-26 01:01:14.000,2022-08-04 10:28:06.000000,2022-08-04 10:15:01,202.0,15.0,177.0,1182,,"Genetic Programming in Python, with a scikit-learn inspired API.",10.0,22,2022-05-03 10:56:08,0.4.2,1.0,,gplearn,,,,['sklearn'],275.0,275.0,https://pypi.org/project/gplearn,5340.0,5340.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +462,ChainerRL,True,chainer/chainerrl,,reinforcement-learning,https://github.com/chainer/chainerrl,https://github.com/chainer/chainerrl,MIT,2017-01-30 04:58:15.000,2021-08-10 18:25:48.000000,2021-04-17 06:02:30,219.0,51.0,147.0,1070,3471.0,ChainerRL is a deep reinforcement learning library built on top of..,29.0,22,2020-02-14 05:32:03,0.8.0,8.0,,chainerrl,,,,,127.0,127.0,https://pypi.org/project/chainerrl,515.0,515.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +463,pyopencl,True,inducer/pyopencl,,others,https://github.com/inducer/pyopencl,https://github.com/inducer/pyopencl,,2011-04-06 02:51:33.000,2022-08-23 03:49:08.000000,2022-08-23 03:49:08,220.0,62.0,241.0,909,,"OpenCL integration for Python, plus shiny features.",92.0,22,2022-06-22 06:21:51,2022.1.6,45.0,,pyopencl,conda-forge/pyopencl,,,,804.0,804.0,https://pypi.org/project/pyopencl,33922.0,43470.0,https://anaconda.org/conda-forge/pyopencl,2022-06-22 15:05:40.972,668390.0,,,,,3.0,,,,,,,,,,,,,,,, +464,RLax,True,deepmind/rlax,,reinforcement-learning,https://github.com/deepmind/rlax,https://github.com/deepmind/rlax,Apache-2.0,2020-02-18 07:14:59.000,2022-08-24 10:22:08.000000,2022-08-24 10:22:02,66.0,4.0,15.0,891,183.0,A library of reinforcement learning building blocks in JAX.,19.0,22,2022-08-15 07:29:33,0.1.4,5.0,,rlax,,,,['jax'],75.0,75.0,https://pypi.org/project/rlax,5305.0,5305.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +465,imodels,True,csinva/imodels,,interpretability,https://github.com/csinva/imodels,https://github.com/csinva/imodels,MIT,2019-07-04 15:38:48.000,2022-08-25 14:15:06.000000,2022-08-25 05:00:45,83.0,14.0,26.0,888,665.0,"Interpretable ML package for concise, transparent, and accurate predictive..",13.0,22,2022-08-25 05:01:42,1.3.4,22.0,,imodels,,,,,20.0,20.0,https://pypi.org/project/imodels,18827.0,18827.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +466,scikit-lego,True,koaning/scikit-lego,,sklearn-utils,https://github.com/koaning/scikit-lego,https://github.com/koaning/scikit-lego,MIT,2019-01-21 15:30:15.000,2022-08-18 11:03:02.000000,2022-08-18 11:03:02,90.0,23.0,222.0,876,,Extra blocks for scikit-learn pipelines.,52.0,22,2022-06-05 14:36:08,0.6.12,30.0,,scikit-lego,conda-forge/scikit-lego,,,['sklearn'],59.0,59.0,https://pypi.org/project/scikit-lego,22588.0,23276.0,https://anaconda.org/conda-forge/scikit-lego,2022-06-06 08:45:38.549,23414.0,,,,,2.0,,,,,,,,,,,,,,,, +467,kapre,True,keunwoochoi/kapre,,audio,https://github.com/keunwoochoi/kapre,https://github.com/keunwoochoi/kapre,MIT,2016-12-14 18:36:36.000,2022-07-04 00:10:02.000000,2022-07-04 00:10:02,139.0,12.0,82.0,853,195.0,kapre: Keras Audio Preprocessors.,13.0,22,2022-01-21 20:10:47,Kapre-0.3.7,10.0,,kapre,,,,['tensorflow'],1767.0,1767.0,https://pypi.org/project/kapre,3611.0,3611.0,,,,,,,,3.0,22.0,,,,,,,,,,,,,,, +468,Prince,True,MaxHalford/prince,,others,https://github.com/MaxHalford/prince,https://github.com/MaxHalford/prince,MIT,2016-10-22 12:36:06.000,2022-06-24 13:33:50.000000,2021-12-28 17:01:09,150.0,39.0,70.0,847,209.0,"Python factor analysis library (PCA, CA, MCA, MFA, FAMD).",12.0,22,,,,,prince,,,,['sklearn'],235.0,235.0,https://pypi.org/project/prince,45144.0,45144.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +469,Sentinelsat,True,sentinelsat/sentinelsat,,geospatial-data,https://github.com/sentinelsat/sentinelsat,https://github.com/sentinelsat/sentinelsat,GPL-3.0,2015-05-22 20:32:26.000,2022-08-01 09:43:24.000000,2022-08-01 09:43:24,195.0,8.0,322.0,794,,Search and download Copernicus Sentinel satellite images.,42.0,22,2022-01-05 19:57:25,1.1.1,12.0,,sentinelsat,,,,,350.0,350.0,https://pypi.org/project/sentinelsat,13298.0,13301.0,,,,,,,,3.0,232.0,,,,,,,,,,,,,,, +470,lets-plot,True,JetBrains/lets-plot,,data-viz,https://github.com/JetBrains/lets-plot,https://github.com/JetBrains/lets-plot,MIT,2019-03-20 16:13:03.000,2022-08-26 00:11:59.000000,2022-08-23 14:10:55,34.0,72.0,194.0,780,2675.0,An open-source plotting library for statistical data.,17.0,22,2022-06-20 17:10:47,2.4.0,50.0,,lets-plot,,,,,17.0,17.0,https://pypi.org/project/lets-plot,1768.0,1777.0,,,,,,,,3.0,302.0,,,,,,,,,,,,,,, +471,NeuPy,True,itdxer/neupy,,ml-frameworks,https://github.com/itdxer/neupy,https://github.com/itdxer/neupy,MIT,2015-08-24 19:45:11.000,2022-03-11 23:25:33.000000,2019-09-02 19:02:38,152.0,32.0,234.0,714,1145.0,NeuPy is a Tensorflow based python library for prototyping and building..,7.0,22,2019-04-04 19:44:59,0.8.2,29.0,,neupy,,,,,134.0,134.0,https://pypi.org/project/neupy,3486.0,3486.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +472,iterative-stratification,True,trent-b/iterative-stratification,,sklearn-utils,https://github.com/trent-b/iterative-stratification,https://github.com/trent-b/iterative-stratification,BSD-3-Clause,2018-02-04 00:32:10.000,2022-06-06 22:38:33.000000,2022-06-06 22:38:33,64.0,1.0,19.0,709,57.0,scikit-learn cross validators for iterative..,7.0,22,2021-10-03 18:24:15,0.1.7,3.0,,iterative-stratification,,,,['sklearn'],221.0,221.0,https://pypi.org/project/iterative-stratification,35109.0,35109.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +473,PDPbox,True,SauceCat/PDPbox,,data-viz,https://github.com/SauceCat/PDPbox,https://github.com/SauceCat/PDPbox,MIT,2017-06-26 08:01:54.000,2021-06-24 15:32:01.000000,2021-03-14 16:01:01,114.0,22.0,38.0,702,227.0,python partial dependence plot toolbox.,7.0,22,2021-03-14 16:07:34,0.2.1,2.0,,pdpbox,conda-forge/pdpbox,,,,511.0,511.0,https://pypi.org/project/pdpbox,34397.0,34744.0,https://anaconda.org/conda-forge/pdpbox,2021-03-14 19:37:51.465,12866.0,,,,,3.0,,,,,,,,,,,,,,,, +474,Mapbox GL,True,mapbox/mapboxgl-jupyter,,geospatial-data,https://github.com/mapbox/mapboxgl-jupyter,https://github.com/mapbox/mapboxgl-jupyter,MIT,2017-08-08 15:10:51.000,2022-01-11 05:18:07.000000,2021-04-19 05:00:36,129.0,32.0,67.0,615,221.0,Use Mapbox GL JS to visualize data in a Python Jupyter notebook.,21.0,22,2019-06-03 21:24:10,0.10.2,14.0,,mapboxgl,,,,['jupyter'],140.0,140.0,https://pypi.org/project/mapboxgl,11474.0,11474.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +475,mpi4py,True,mpi4py/mpi4py,,distributed-ml,https://github.com/mpi4py/mpi4py,https://github.com/mpi4py/mpi4py,BSD-2-Clause,2013-09-05 14:44:25.000,2022-08-25 22:33:15.000000,2022-08-21 14:26:39,78.0,10.0,74.0,570,2618.0,Python bindings for MPI.,21.0,22,2021-11-25 21:00:09,3.1.3,10.0,,mpi4py,conda-forge/mpi4py,,,,,,https://pypi.org/project/mpi4py,290694.0,309202.0,https://anaconda.org/conda-forge/mpi4py,2022-08-12 18:28:22.542,1296541.0,,,,,3.0,6182.0,,,,,,,,,,,,,,, +476,findspark,True,minrk/findspark,,others,https://github.com/minrk/findspark,https://github.com/minrk/findspark,BSD-3-Clause,2015-06-12 21:34:06.000,2022-02-11 17:17:32.393000,2022-02-11 07:59:35,68.0,11.0,11.0,444,,Find pyspark to make it importable.,15.0,22,,,6.0,,findspark,conda-forge/findspark,,,['spark'],2674.0,2674.0,https://pypi.org/project/findspark,2117252.0,2126589.0,https://anaconda.org/conda-forge/findspark,2022-02-11 17:17:32.393,691007.0,,,,,3.0,,,,,,,,,,,,,,,, +477,pyvips,True,libvips/pyvips,,image,https://github.com/libvips/pyvips,https://github.com/libvips/pyvips,MIT,2017-07-28 16:39:43.000,2022-08-13 07:13:51.000000,2022-08-13 07:13:51,40.0,109.0,192.0,435,437.0,python binding for libvips using cffi.,14.0,22,,,5.0,,pyvips,conda-forge/pyvips,,,,351.0,351.0,https://pypi.org/project/pyvips,19119.0,19922.0,https://anaconda.org/conda-forge/pyvips,2022-07-24 14:46:32.955,28940.0,,,,,3.0,,,,,,,,,,,,,,,, +478,MedPy,True,loli/medpy,,medical-data,https://github.com/loli/medpy,https://github.com/loli/medpy,GPL-3.0,2012-05-11 10:57:34.000,2022-07-15 00:18:39.000000,2020-05-01 15:25:38,118.0,12.0,68.0,430,324.0,Medical image processing in Python.,14.0,22,2019-02-14 17:09:49,0.4.0,5.0,,MedPy,,,,,699.0,699.0,https://pypi.org/project/MedPy,12834.0,12834.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +479,sklearn-crfsuite,True,TeamHG-Memex/sklearn-crfsuite,,sklearn-utils,https://github.com/TeamHG-Memex/sklearn-crfsuite,https://github.com/TeamHG-Memex/sklearn-crfsuite,,2015-11-26 21:15:41.000,2022-06-30 18:26:21.000000,2019-12-05 08:17:22,190.0,33.0,23.0,408,46.0,scikit-learn inspired API for CRFsuite.,6.0,22,,,,,sklearn-crfsuite,,,,['sklearn'],3991.0,3991.0,https://pypi.org/project/sklearn-crfsuite,195075.0,195075.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +480,StaticFrame,True,InvestmentSystems/static-frame,,data-containers,https://github.com/InvestmentSystems/static-frame,https://github.com/InvestmentSystems/static-frame,MIT,2018-01-03 15:07:52.000,2022-08-25 07:34:29.000000,2022-08-23 15:41:40,26.0,43.0,407.0,314,4586.0,Immutable and grow-only Pandas-like DataFrames with a more explicit..,20.0,22,2022-08-14 14:43:07,0.9.11,133.0,,static-frame,conda-forge/static-frame,,,,11.0,11.0,https://pypi.org/project/static-frame,1553.0,5851.0,https://anaconda.org/conda-forge/static-frame,2022-08-14 23:42:32.968,180535.0,,,,,3.0,,,,,,,,,,,,,,,, +481,Orion,True,Epistimio/orion,,hyperopt,https://github.com/Epistimio/orion,https://github.com/Epistimio/orion,,2017-09-07 06:05:21.000,2022-08-25 18:17:37.000000,2022-08-19 16:56:19,43.0,187.0,166.0,238,3708.0,Asynchronous Distributed Hyperparameter Optimization.,27.0,22,2022-08-22 15:02:45,0.2.6,25.0,,orion,,,,,73.0,73.0,https://pypi.org/project/orion,4359.0,4359.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +482,tabulator-py,True,frictionlessdata/tabulator-py,,data-loading,https://github.com/frictionlessdata/tabulator-py,https://github.com/frictionlessdata/tabulator-py,MIT,2015-08-24 05:34:38.000,2021-06-01 12:40:01.000000,2021-03-22 13:33:48,42.0,,178.0,228,,Python library for reading and writing tabular data via streams.,27.0,22,2021-03-21 07:42:12,1.53.5,100.0,,tabulator,conda-forge/tabulator-py,,,,826.0,826.0,https://pypi.org/project/tabulator,209891.0,210670.0,https://anaconda.org/conda-forge/tabulator-py,2018-07-24 12:57:07.018,48311.0,,,,,3.0,,,,,,,,,,,,,,,, +483,Glow,True,projectglow/glow,,medical-data,https://github.com/projectglow/glow,https://github.com/projectglow/glow,Apache-2.0,2019-10-04 21:26:47.000,2022-07-29 19:25:23.000000,2022-05-09 15:19:36,78.0,54.0,80.0,211,394.0,An open-source toolkit for large-scale genomic analysis.,21.0,22,2022-04-21 00:32:28,1.2.1,15.0,,glow.py,,,,,,,https://pypi.org/project/glow.py,138248.0,138248.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +484,pyexcel-xlsx,True,pyexcel/pyexcel-xlsx,,data-loading,https://github.com/pyexcel/pyexcel-xlsx,https://github.com/pyexcel/pyexcel-xlsx,,2014-12-02 00:03:24.000,2022-08-18 09:18:39.000000,2020-11-28 22:30:53,23.0,9.0,25.0,109,267.0,"A wrapper library to read, manipulate and write data in xlsx and..",4.0,22,2020-10-10 13:13:09,0.6.0,30.0,,pyexcel-xlsx,conda-forge/pyexcel-xlsx,,,,1728.0,1728.0,https://pypi.org/project/pyexcel-xlsx,87884.0,88243.0,https://anaconda.org/conda-forge/pyexcel-xlsx,2020-10-10 15:53:49.660,20836.0,,,,,3.0,51.0,,,,,,,,,,,,,,, +485,Recommenders,True,microsoft/recommenders,,recommender-systems,https://github.com/microsoft/recommenders,https://github.com/microsoft/recommenders,MIT,2018-09-19 10:06:07.000,2022-08-18 23:30:55.000000,2022-07-20 02:31:54,2394.0,143.0,568.0,13896,,Best Practices on Recommendation Systems.,119.0,21,2022-07-20 05:58:55,1.1.1,12.0,,,,,,,33.0,33.0,,,5.0,,,,,,,,3.0,234.0,,,,,,,,,,,,,,, +486,PaddleDetection,True,PaddlePaddle/PaddleDetection,,image,https://github.com/PaddlePaddle/PaddleDetection,https://github.com/PaddlePaddle/PaddleDetection,Apache-2.0,2019-10-25 07:21:14.000,2022-08-26 03:53:01.000000,2022-08-16 11:03:14,2117.0,790.0,3034.0,8322,,Object detection and instance segmentation toolkit..,104.0,21,2022-04-24 03:51:25,2.4.0,6.0,,,,,,['paddle'],30.0,30.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +487,EfficientNet-PyTorch,True,lukemelas/EfficientNet-PyTorch,,pytorch-utils,https://github.com/lukemelas/EfficientNet-PyTorch,https://github.com/lukemelas/EfficientNet-PyTorch,Apache-2.0,2019-05-30 05:24:11.000,2022-04-08 12:30:25.000000,2021-04-15 15:16:36,1410.0,142.0,140.0,7106,162.0,A PyTorch implementation of EfficientNet and..,24.0,21,2020-03-01 03:29:43,1.0,1.0,,efficientnet-pytorch,,,,['pytorch'],,,https://pypi.org/project/efficientnet-pytorch,102624.0,168221.0,,,,,,,,2.0,1902316.0,,,,,,,,,,,,,,, +488,TensorLayer,True,tensorlayer/tensorlayer,,reinforcement-learning,https://github.com/tensorlayer/TensorLayer,https://github.com/tensorlayer/TensorLayer,,2016-06-07 15:55:16.000,2022-07-20 21:04:11.000000,2022-04-23 17:46:37,1559.0,20.0,441.0,7053,3352.0,Deep Learning and Reinforcement Learning Library for..,132.0,21,2021-01-06 07:16:21,2.2.4,76.0,,tensorlayer,,,,['tensorflow'],,,https://pypi.org/project/tensorlayer,1528.0,1547.0,,,,,,,,3.0,1397.0,,,,,,,,,,,,,,, +489,DoWhy,True,Microsoft/dowhy,,interpretability,https://github.com/py-why/dowhy,https://github.com/py-why/dowhy,MIT,2018-05-31 13:07:04.000,2022-08-26 00:32:15.000000,2022-08-23 11:27:05,695.0,80.0,174.0,5148,,DoWhy is a Python library for causal inference that supports explicit..,60.0,21,2022-07-18 18:24:37,0.8,9.0,py-why/dowhy,dowhy,conda-forge/dowhy,,,,,,https://pypi.org/project/dowhy,181380.0,181682.0,https://anaconda.org/conda-forge/dowhy,2022-07-19 11:17:50.796,8160.0,,,,,3.0,31.0,,,,,,,,,,,,,,, +490,kaggle,True,Kaggle/kaggle-api,,ml-experiments,https://github.com/Kaggle/kaggle-api,https://github.com/Kaggle/kaggle-api,Apache-2.0,2018-01-25 03:02:39.000,2022-07-22 15:58:54.000000,2021-03-15 15:49:05,938.0,204.0,149.0,4916,145.0,Official Kaggle API.,36.0,21,,,8.0,,kaggle,conda-forge/kaggle,,,,,,https://pypi.org/project/kaggle,124138.0,126571.0,https://anaconda.org/conda-forge/kaggle,2021-12-17 19:19:11.878,94891.0,,,,,3.0,,,,,,,,,,,,,,,, +491,Perspective,True,finos/perspective,,data-viz,https://github.com/finos/perspective,https://github.com/finos/perspective,Apache-2.0,2017-11-02 16:27:54.000,2022-08-25 15:12:02.000000,2022-08-25 15:12:01,493.0,78.0,467.0,4812,5333.0,Streaming pivot visualization via WebAssembly.,72.0,21,,,,,perspective-python,,,,['jupyter'],4.0,4.0,https://pypi.org/project/perspective-python,3011.0,4453.0,,,,,,,,3.0,,,@finos/perspective-jupyterlab,https://www.npmjs.com/package/@finos/perspective-jupyterlab,1442.0,,,,,,,,,,, +492,segmentation_models,True,qubvel/segmentation_models,,image,https://github.com/qubvel/segmentation_models,https://github.com/qubvel/segmentation_models,MIT,2018-06-05 13:27:56.000,2022-07-29 10:37:24.000000,2022-07-29 10:37:24,914.0,221.0,259.0,4010,205.0,Segmentation models with pretrained backbones. Keras and TensorFlow Keras.,14.0,21,2020-01-10 11:28:38,1.0.1,4.0,,segmentation_models,,,,['tensorflow'],,,https://pypi.org/project/segmentation_models,25880.0,25880.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +493,Image Super-Resolution,True,idealo/image-super-resolution,,image,https://github.com/idealo/image-super-resolution,https://github.com/idealo/image-super-resolution,Apache-2.0,2018-11-26 13:41:13.000,2022-01-23 11:27:35.000000,2021-06-02 09:45:13,627.0,90.0,109.0,3762,150.0,Super-scale your images and run experiments with..,10.0,21,2020-01-08 15:35:45,2.2.0,1.0,,ISR,,idealo/image-super-resolution-gpu,,['tensorflow'],97.0,97.0,https://pypi.org/project/ISR,4468.0,4472.0,,,,https://hub.docker.com/r/idealo/image-super-resolution-gpu,2019-04-01 13:48:45.697251,,217.0,3.0,,,,,,,,,,,,,,,, +494,Alpha Vantage,True,RomelTorres/alpha_vantage,,financial-data,https://github.com/RomelTorres/alpha_vantage,https://github.com/RomelTorres/alpha_vantage,MIT,2017-04-29 17:23:00.000,2022-01-04 14:23:20.000000,2021-06-14 05:10:42,643.0,6.0,249.0,3712,497.0,A python wrapper for Alpha Vantage API for financial data.,39.0,21,2020-12-21 02:37:29,2.3.1,5.0,,alpha_vantage,,,,,,,https://pypi.org/project/alpha_vantage,16891.0,16891.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +495,Snips NLU,True,snipsco/snips-nlu,,nlp,https://github.com/snipsco/snips-nlu,https://github.com/snipsco/snips-nlu,Apache-2.0,2017-02-08 16:16:36.000,2021-11-17 15:23:01.000000,2021-05-03 12:18:31,489.0,61.0,197.0,3691,2154.0,Snips Python library to extract meaning from text.,22.0,21,2020-01-15 09:51:41,0.20.2,58.0,,snips-nlu,,,,,,,https://pypi.org/project/snips-nlu,2254.0,2254.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +496,plotnine,True,has2k1/plotnine,,data-viz,https://github.com/has2k1/plotnine,https://github.com/has2k1/plotnine,MIT,2017-04-24 19:00:44.000,2022-07-24 12:06:01.000000,2022-07-01 19:35:08,169.0,69.0,435.0,3163,,A grammar of graphics for Python.,96.0,21,2021-03-25 12:57:10,0.8.0,11.0,,plotnine,conda-forge/plotnine,,,,,,https://pypi.org/project/plotnine,346309.0,349335.0,https://anaconda.org/conda-forge/plotnine,2022-07-02 08:55:06.336,190700.0,,,,,3.0,,,,,,,,,,,,,,,, +497,Porcupine,True,Picovoice/Porcupine,,audio,https://github.com/Picovoice/porcupine,https://github.com/Picovoice/porcupine,Apache-2.0,2018-03-08 01:55:25.000,2022-08-26 02:26:30.000000,2022-08-26 00:08:24,379.0,2.0,387.0,2752,779.0,On-device wake word detection powered by deep learning.,31.0,21,2022-01-21 17:58:25,2.1,12.0,,pvporcupine,,,,,9.0,9.0,https://pypi.org/project/pvporcupine,1203.0,1203.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +498,Texthero,True,jbesomi/texthero,,nlp,https://github.com/jbesomi/texthero,https://github.com/jbesomi/texthero,MIT,2020-04-06 15:16:05.000,2022-07-19 11:51:36.000000,2022-07-19 11:51:36,215.0,52.0,62.0,2545,270.0,"Text preprocessing, representation and visualization from zero to hero.",19.0,21,2021-07-01 16:53:52,1.1.0,4.0,,texthero,,,,,,,https://pypi.org/project/texthero,22690.0,22693.0,,,,,,,,3.0,92.0,,,,,,,,,,,,,,, +499,pygal,True,Kozea/pygal,,graph,https://github.com/Kozea/pygal,https://github.com/Kozea/pygal,LGPL-3.0,2011-09-23 10:17:50.000,2022-03-03 16:14:41.000000,2021-11-24 21:04:02,392.0,159.0,244.0,2482,1018.0,PYthon svg GrAph plotting Library.,71.0,21,2015-02-16 16:54:22,1.7.0,2.0,,pygal,conda-forge/pygal,,,,,,https://pypi.org/project/pygal,122471.0,122995.0,https://anaconda.org/conda-forge/pygal,2019-06-04 02:55:56.728,19925.0,,,,,2.0,,,,,,,,,,,,,,,, +500,Enigma Catalyst,True,enigmampc/catalyst,,financial-data,https://github.com/scrtlabs/catalyst,https://github.com/scrtlabs/catalyst,Apache-2.0,2017-06-13 22:31:34.000,2021-09-22 15:32:01.000000,2021-09-22 15:31:55,697.0,124.0,358.0,2360,6364.0,An Algorithmic Trading Library for Crypto-Assets in Python.,149.0,21,,,,scrtlabs/catalyst,enigma-catalyst,,,,,25.0,25.0,https://pypi.org/project/enigma-catalyst,428.0,428.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +501,Texar,True,asyml/texar,,nlp,https://github.com/asyml/texar,https://github.com/asyml/texar,Apache-2.0,2017-07-22 19:02:05.000,2021-08-26 09:49:50.000000,2020-07-29 00:38:30,365.0,31.0,126.0,2300,1719.0,"Toolkit for Machine Learning, Natural Language Processing, and..",43.0,21,2019-11-19 03:54:40,0.2.4,6.0,,texar,,,,['tensorflow'],26.0,26.0,https://pypi.org/project/texar,65.0,65.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +502,DDSP,True,magenta/ddsp,,audio,https://github.com/magenta/ddsp,https://github.com/magenta/ddsp,Apache-2.0,2020-01-14 18:38:27.000,2022-08-25 01:55:59.000000,2022-05-16 16:44:22,251.0,26.0,113.0,2241,,DDSP: Differentiable Digital Signal Processing.,31.0,21,2022-02-10 03:10:14,3.1.0,22.0,,ddsp,,,,['tensorflow'],28.0,28.0,https://pypi.org/project/ddsp,3048.0,3048.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +503,Haiku,True,deepmind/dm-haiku,,ml-frameworks,https://github.com/deepmind/dm-haiku,https://github.com/deepmind/dm-haiku,Apache-2.0,2020-02-18 07:14:02.000,2022-08-25 15:39:54.000000,2022-08-25 15:39:46,166.0,48.0,135.0,2117,,JAX-based neural network library.,63.0,21,2022-07-04 18:49:07,0.0.7,9.0,,,,,,,542.0,542.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +504,polyglot,True,aboSamoor/polyglot,,nlp,https://github.com/aboSamoor/polyglot,https://github.com/aboSamoor/polyglot,,2014-06-30 02:07:45.000,2022-05-18 09:36:53.000000,2020-09-22 22:35:28,308.0,146.0,67.0,2038,271.0,Multilingual text (NLP) processing toolkit.,26.0,21,,,,,polyglot,,,,,749.0,749.0,https://pypi.org/project/polyglot,52794.0,52794.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +505,TabNet,True,dreamquark-ai/tabnet,,pytorch-utils,https://github.com/dreamquark-ai/tabnet,https://github.com/dreamquark-ai/tabnet,MIT,2019-10-17 11:17:32.000,2022-08-24 12:52:10.000000,2022-06-27 10:04:15,374.0,17.0,217.0,1835,193.0,PyTorch implementation of TabNet paper :..,19.0,21,2021-02-02 08:05:08,3.1.1,15.0,,pytorch-tabnet,,,,['pytorch'],,,https://pypi.org/project/pytorch-tabnet,20298.0,20298.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +506,Multicore-TSNE,True,DmitryUlyanov/Multicore-TSNE,,data-viz,https://github.com/DmitryUlyanov/Multicore-TSNE,https://github.com/DmitryUlyanov/Multicore-TSNE,BSD-3-Clause,2016-10-19 05:46:52.000,2022-04-29 15:26:19.000000,2020-08-19 14:58:00,195.0,37.0,21.0,1735,113.0,Parallel t-SNE implementation with Python and Torch..,15.0,21,,,1.0,,MulticoreTSNE,conda-forge/multicore-tsne,,,['pytorch'],314.0,314.0,https://pypi.org/project/MulticoreTSNE,18980.0,19370.0,https://anaconda.org/conda-forge/multicore-tsne,2021-11-09 17:22:51.512,17553.0,,,,,3.0,,,,,,,,,,,,,,,, +507,checklist,True,marcotcr/checklist,,interpretability,https://github.com/marcotcr/checklist,https://github.com/marcotcr/checklist,MIT,2020-03-09 17:18:49.000,2022-08-12 15:43:09.000000,2022-08-12 15:43:09,166.0,2.0,81.0,1732,249.0,Beyond Accuracy: Behavioral Testing of NLP models with CheckList.,13.0,21,,,,,checklist,,,,['jupyter'],153.0,153.0,https://pypi.org/project/checklist,7829.0,7829.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +508,Norfair,True,tryolabs/norfair,,image,https://github.com/tryolabs/norfair,https://github.com/tryolabs/norfair,BSD-3-Clause,2020-07-01 20:15:44.000,2022-08-24 21:08:46.000000,2022-08-24 12:27:58,151.0,12.0,63.0,1558,395.0,Lightweight Python library for adding real-time 2D object tracking to..,18.0,21,2022-05-30 20:55:38,1.0.0,9.0,,norfair,,,,,,,https://pypi.org/project/norfair,7337.0,7345.0,,,,,,,,3.0,197.0,,,,,,,,,,,,,,, +509,bonobo,True,python-bonobo/bonobo,,data-pipelines,https://github.com/python-bonobo/bonobo,https://github.com/python-bonobo/bonobo,Apache-2.0,2016-12-09 04:03:23.000,2022-08-23 17:12:54.000000,2021-03-10 15:44:00,127.0,71.0,108.0,1524,978.0,Extract Transform Load for Python 3.5+.,37.0,21,,,,,bonobo,,,http://docs.bonobo-project.org/en/master/,,135.0,135.0,https://pypi.org/project/bonobo,7321.0,7321.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +510,EfficientNets,True,rwightman/gen-efficientnet-pytorch,,pytorch-utils,https://github.com/rwightman/gen-efficientnet-pytorch,https://github.com/rwightman/gen-efficientnet-pytorch,Apache-2.0,2019-05-11 19:35:56.000,2022-07-01 09:55:35.000000,2021-07-08 19:03:55,196.0,3.0,51.0,1489,108.0,"Pretrained EfficientNet, EfficientNet-Lite, MixNet,..",5.0,21,,,,,geffnet,,,,['pytorch'],125.0,125.0,https://pypi.org/project/geffnet,15000.0,15000.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +511,Orbit,True,uber/orbit,,probabilistics,https://github.com/uber/orbit,https://github.com/uber/orbit,,2020-01-07 18:20:37.000,2022-08-17 19:39:55.000000,2022-08-17 19:39:54,108.0,47.0,322.0,1453,826.0,A Python package for Bayesian forecasting with object-oriented design..,18.0,21,2022-04-28 21:45:14,1.1.2,19.0,,orbit-ml,,,,,9.0,9.0,https://pypi.org/project/orbit-ml,304893.0,304893.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +512,fairlearn,True,fairlearn/fairlearn,,interpretability,https://github.com/fairlearn/fairlearn,https://github.com/fairlearn/fairlearn,MIT,2018-05-15 01:51:35.000,2022-08-24 15:29:27.000000,2022-08-24 15:28:07,313.0,142.0,220.0,1356,,A Python package to assess and improve fairness of machine..,68.0,21,2021-07-07 08:16:09,0.7.0,11.0,,fairlearn,conda-forge/fairlearn,,,['sklearn'],,,https://pypi.org/project/fairlearn,228022.0,228696.0,https://anaconda.org/conda-forge/fairlearn,2021-07-07 15:56:16.605,20231.0,,,,,3.0,,,,,,,,,,,,,,,, +513,MLBox,True,AxeldeRomblay/MLBox,,hyperopt,https://github.com/AxeldeRomblay/MLBox,https://github.com/AxeldeRomblay/MLBox,,2017-06-01 16:59:24.000,2022-06-21 22:13:03.000000,2020-08-25 09:26:27,266.0,18.0,74.0,1346,1121.0,MLBox is a powerful Automated Machine Learning python library.,9.0,21,2019-08-25 22:46:42,0.8.1,7.0,,mlbox,,,,,28.0,28.0,https://pypi.org/project/mlbox,2898.0,2898.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +514,Pytorch Toolbelt,True,BloodAxe/pytorch-toolbelt,,pytorch-utils,https://github.com/BloodAxe/pytorch-toolbelt,https://github.com/BloodAxe/pytorch-toolbelt,MIT,2019-03-15 16:02:49.000,2022-08-20 19:23:10.000000,2022-08-20 19:23:03,104.0,2.0,22.0,1287,852.0,PyTorch extensions for fast R&D prototyping and Kaggle..,7.0,21,2022-06-27 19:58:11,0.5.1,23.0,,pytorch_toolbelt,,,,['pytorch'],,,https://pypi.org/project/pytorch_toolbelt,14854.0,14854.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +515,TaskTiger,True,closeio/tasktiger,,data-pipelines,https://github.com/closeio/tasktiger,https://github.com/closeio/tasktiger,MIT,2015-05-14 00:26:32.000,2022-07-25 10:01:08.000000,2022-04-25 12:38:59,64.0,22.0,36.0,1187,286.0,Python task queue using Redis.,24.0,21,2021-12-02 17:42:13,0.16,7.0,,tasktiger,,,,,23.0,23.0,https://pypi.org/project/tasktiger,1478.0,1478.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +516,DALEX,True,ModelOriented/DALEX,,interpretability,https://github.com/ModelOriented/DALEX,https://github.com/ModelOriented/DALEX,GPL-3.0,2018-02-18 03:24:12.000,2022-08-06 08:39:57.000000,2022-08-03 10:48:07,137.0,20.0,350.0,1095,634.0,moDel Agnostic Language for Exploration and eXplanation.,20.0,21,2021-01-04 17:21:32,1.0.0,3.0,,dalex,,,,,57.0,57.0,https://pypi.org/project/dalex,9549.0,9549.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +517,keract,True,philipperemy/keract,,interpretability,https://github.com/philipperemy/keract,https://github.com/philipperemy/keract,MIT,2017-05-17 04:50:57.000,2022-07-23 14:22:41.000000,2022-07-23 14:22:41,184.0,5.0,82.0,990,396.0,Layers Outputs and Gradients in Keras. Made easy.,16.0,21,2021-06-19 16:14:57,4.5.0,10.0,,keract,,,,['tensorflow'],145.0,145.0,https://pypi.org/project/keract,897.0,897.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +518,PyKEEN,True,pykeen/pykeen,,graph,https://github.com/pykeen/pykeen,https://github.com/pykeen/pykeen,MIT,2020-02-24 07:26:03.000,2022-08-25 20:40:51.000000,2022-08-25 14:29:52,130.0,56.0,369.0,955,2744.0,A Python library for learning and evaluating knowledge graph embeddings.,31.0,21,2022-08-04 15:51:28,1.9.0,17.0,,pykeen,,,,,,,https://pypi.org/project/pykeen,1386.0,1391.0,,,,,,,,2.0,144.0,,,,,,,,,,,,,,, +519,Node2Vec,True,eliorc/node2vec,,graph,https://github.com/eliorc/node2vec,https://github.com/eliorc/node2vec,MIT,2017-12-08 13:30:06.000,2022-08-01 11:34:35.000000,2022-08-01 11:33:22,201.0,,77.0,953,71.0,Implementation of the node2vec algorithm.,11.0,21,2022-08-01 11:34:27,0.4.6,9.0,,node2vec,conda-forge/node2vec,,,,,,https://pypi.org/project/node2vec,77897.0,78325.0,https://anaconda.org/conda-forge/node2vec,2020-04-25 22:41:13.714,21831.0,,,,,2.0,,,,,,,,,,,,,,,, +520,tf-explain,True,sicara/tf-explain,,interpretability,https://github.com/sicara/tf-explain,https://github.com/sicara/tf-explain,MIT,2019-07-15 08:26:24.000,2022-06-30 08:14:18.000000,2022-06-30 08:14:18,101.0,37.0,51.0,941,208.0,Interpretability Methods for tf.keras models with Tensorflow 2.x.,18.0,21,2021-11-18 20:27:53,0.3.1,7.0,,tf-explain,,,,['tensorflow'],130.0,130.0,https://pypi.org/project/tf-explain,1134.0,1134.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +521,Satpy,True,pytroll/satpy,,geospatial-data,https://github.com/pytroll/satpy,https://github.com/pytroll/satpy,GPL-3.0,2016-02-09 20:29:43.000,2022-08-25 13:31:01.000000,2022-08-25 13:31:00,240.0,306.0,484.0,846,,Python package for earth-observing satellite data processing.,128.0,21,2022-08-15 08:08:33,0.37.1,48.0,,satpy,conda-forge/satpy,,,,72.0,72.0,https://pypi.org/project/satpy,1148.0,3261.0,https://anaconda.org/conda-forge/satpy,2022-08-15 14:27:55.969,103583.0,,,,,3.0,,,,,,,,,,,,,,,, +522,YouTokenToMe,True,vkcom/youtokentome,,nlp,https://github.com/VKCOM/YouTokenToMe,https://github.com/VKCOM/YouTokenToMe,MIT,2019-06-06 11:38:28.000,2021-01-28 23:05:01.000000,2021-01-28 19:04:09,61.0,30.0,24.0,823,79.0,Unsupervised text tokenizer focused on computational efficiency.,6.0,21,2020-02-13 09:57:47,1.0.6,4.0,,youtokentome,,,,,287.0,287.0,https://pypi.org/project/youtokentome,30097.0,30097.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +523,Guild AI,True,guildai/guildai,,ml-experiments,https://github.com/guildai/guildai,https://github.com/guildai/guildai,Apache-2.0,2017-09-27 18:57:50.000,2022-08-24 19:50:06.000000,2022-08-24 17:50:25,66.0,169.0,206.0,730,,"Experiment tracking, ML developer tools.",21.0,21,2022-05-11 01:13:36,0.8.1,2.0,,guildai,,,,,58.0,58.0,https://pypi.org/project/guildai,3097.0,3098.0,,,,,,,,3.0,6.0,,,,,,,,,,,,,,, +524,PyTorch Sparse,True,rusty1s/pytorch_sparse,,pytorch-utils,https://github.com/rusty1s/pytorch_sparse,https://github.com/rusty1s/pytorch_sparse,MIT,2018-07-28 18:46:53.000,2022-08-22 14:39:48.000000,2022-08-22 14:39:46,104.0,27.0,174.0,708,696.0,PyTorch Extension Library of Optimized Autograd Sparse..,32.0,21,2022-08-17 10:46:06,0.6.15,25.0,,torch-sparse,,,,['pytorch'],,,https://pypi.org/project/torch-sparse,26536.0,26536.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +525,CellProfiler,True,CellProfiler/CellProfiler,,image,https://github.com/CellProfiler/CellProfiler,https://github.com/CellProfiler/CellProfiler,,2011-04-05 12:10:12.000,2022-08-25 15:43:38.000000,2022-08-17 19:31:04,323.0,177.0,2918.0,695,15507.0,An open-source application for biological image analysis.,131.0,21,2022-08-15 20:12:40,4.2.4,46.0,,cellprofiler,,,,,9.0,9.0,https://pypi.org/project/cellprofiler,904.0,936.0,,,,,,,,3.0,3363.0,,,,,,,,,,,,,,, +526,inflect,True,jaraco/inflect,,nlp,https://github.com/jaraco/inflect,https://github.com/jaraco/inflect,MIT,2010-06-20 13:43:13.000,2022-08-26 00:15:20.000000,2022-08-26 00:15:18,74.0,17.0,74.0,687,,"Correctly generate plurals, ordinals, indefinite articles; convert numbers..",45.0,21,2022-07-30 19:31:36,6.0.0,18.0,,inflect,conda-forge/inflect,,,,,,https://pypi.org/project/inflect,2534832.0,2538653.0,https://anaconda.org/conda-forge/inflect,2022-07-31 08:58:36.228,244576.0,,,,,3.0,,,,,,,,,,,,,,,, +527,pdpipe,True,pdpipe/pdpipe,,data-pipelines,https://github.com/pdpipe/pdpipe,https://github.com/pdpipe/pdpipe,MIT,2017-01-24 20:37:22.000,2022-08-19 12:40:11.000000,2022-08-09 09:30:14,42.0,16.0,35.0,678,435.0,Easy pipelines for pandas DataFrames.,10.0,21,2022-08-09 09:38:12,0.3.1,46.0,,pdpipe,,,,['pandas'],41.0,41.0,https://pypi.org/project/pdpipe,1746.0,1746.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +528,torch-cluster,True,rusty1s/pytorch_cluster,,graph,https://github.com/rusty1s/pytorch_cluster,https://github.com/rusty1s/pytorch_cluster,MIT,2018-01-12 20:56:06.000,2022-08-22 07:25:16.000000,2022-08-22 07:25:16,102.0,19.0,89.0,558,578.0,PyTorch Extension Library of Optimized Graph Cluster..,25.0,21,2022-03-11 11:56:16,1.6.0,29.0,,torch-cluster,,,,['pytorch'],,,https://pypi.org/project/torch-cluster,26877.0,26877.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +529,Neuraxle,True,Neuraxio/Neuraxle,,hyperopt,https://github.com/Neuraxio/Neuraxle,https://github.com/Neuraxio/Neuraxle,Apache-2.0,2019-03-26 21:01:54.000,2022-08-16 18:12:08.000000,2022-08-16 17:43:49,52.0,62.0,253.0,535,1877.0,A Sklearn-like Framework for Hyperparameter Tuning and AutoML in..,7.0,21,2022-08-16 19:54:29,0.8.1,27.0,,neuraxle,,,,,34.0,34.0,https://pypi.org/project/neuraxle,486.0,486.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +530,random-forest-importances,True,parrt/random-forest-importances,,interpretability,https://github.com/parrt/random-forest-importances,https://github.com/parrt/random-forest-importances,MIT,2018-03-22 19:20:13.000,2021-01-30 21:50:08.000000,2021-01-30 21:50:02,118.0,5.0,29.0,513,249.0,Code to compute permutation and drop-column..,14.0,21,2021-01-28 23:23:17,1.3.7,5.0,,rfpimp,,,,['sklearn'],102.0,102.0,https://pypi.org/project/rfpimp,30203.0,30203.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +531,python-soundfile,True,bastibe/python-soundfile,,audio,https://github.com/bastibe/python-soundfile,https://github.com/bastibe/python-soundfile,BSD-3-Clause,2013-08-27 13:36:52.000,2022-08-21 23:27:49.000000,2022-02-23 08:02:30,75.0,68.0,104.0,473,505.0,"SoundFile is an audio library based on libsndfile, CFFI, and..",24.0,21,2019-12-04 10:03:39,0.10.3post1,12.0,,soundfile,,,,,,,https://pypi.org/project/soundfile,1082081.0,1082119.0,,,,,,,,3.0,3953.0,,,,,,,,,,,,,,, +532,optunity,True,claesenm/optunity,,hyperopt,https://github.com/claesenm/optunity,https://github.com/claesenm/optunity,BSD-3-Clause,2014-05-28 17:29:11.000,2020-05-11 14:32:39.000000,2020-05-11 14:32:38,75.0,49.0,48.0,393,782.0,optimization routines for hyperparameter tuning.,9.0,21,2015-09-30 04:59:38,1.1.1,3.0,,optunity,,,,,81.0,81.0,https://pypi.org/project/optunity,10851.0,10851.0,,,,,,,,3.0,67.0,,,,,,,,,,,,,,, +533,EarthPy,True,earthlab/earthpy,,geospatial-data,https://github.com/earthlab/earthpy,https://github.com/earthlab/earthpy,BSD-3-Clause,2018-02-20 03:02:42.000,2022-07-27 02:32:14.000000,2021-12-20 23:24:01,139.0,19.0,207.0,385,,A package built to support working with spatial data using open source..,40.0,21,2021-10-01 22:50:41,0.9.4,14.0,,earthpy,conda-forge/earthpy,,,,155.0,155.0,https://pypi.org/project/earthpy,8445.0,9672.0,https://anaconda.org/conda-forge/earthpy,2021-10-04 19:35:49.510,49116.0,,,,,3.0,,,,,,,,,,,,,,,, +534,messytables,True,okfn/messytables,,data-loading,https://github.com/okfn/messytables,https://github.com/okfn/messytables,,2011-07-27 18:08:21.000,2022-07-06 19:45:09.000000,2019-11-13 07:35:33,103.0,30.0,55.0,384,601.0,Tools for parsing messy tabular data. This is now superseded by..,44.0,21,2016-09-29 14:15:14,0.15.1,1.0,,messytables,,,,,246.0,246.0,https://pypi.org/project/messytables,10310.0,10310.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +535,sklearn-evaluation,True,edublancas/sklearn-evaluation,,interpretability,https://github.com/ploomber/sklearn-evaluation,https://github.com/ploomber/sklearn-evaluation,MIT,2015-09-04 16:33:42.000,2022-08-22 21:50:00.000000,2022-08-22 21:49:58,28.0,8.0,31.0,335,576.0,"Machine learning model evaluation made easy: plots,..",8.0,21,2021-06-26 14:03:00,0.5.6,8.0,ploomber/sklearn-evaluation,sklearn-evaluation,,,,['sklearn'],49.0,49.0,https://pypi.org/project/sklearn-evaluation,1692.0,1692.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +536,PyText,True,facebookresearch/pytext,,nlp,https://github.com/facebookresearch/pytext,https://github.com/facebookresearch/pytext,,2018-07-31 23:40:46.000,2022-08-11 21:12:39.000000,2022-08-11 21:07:04,791.0,61.0,74.0,6350,,A natural language modeling framework based on PyTorch.,230.0,20,2020-06-08 23:30:58,0.3.3,9.0,,pytext-nlp,,,,['pytorch'],109.0,109.0,https://pypi.org/project/pytext-nlp,182.0,188.0,,,,,,,,3.0,301.0,,,,,,,,,,,,,,, +537,MMF,True,facebookresearch/mmf,,image,https://github.com/facebookresearch/mmf,https://github.com/facebookresearch/mmf,BSD-3-Clause,2018-06-27 04:52:40.000,2022-08-11 00:18:21.000000,2022-08-11 00:14:13,838.0,192.0,432.0,4994,,A modular framework for vision & language multimodal research from..,104.0,20,2019-08-26 19:04:21,0.3.1,2.0,,mmf,,,,['pytorch'],12.0,12.0,https://pypi.org/project/mmf,235.0,235.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +538,cuDF,True,rapidsai/cudf,,gpu-utilities,https://github.com/rapidsai/cudf,https://github.com/rapidsai/cudf,Apache-2.0,2017-05-07 03:43:37.000,2022-08-26 03:12:12.000000,2022-08-26 03:04:45,627.0,605.0,4156.0,4934,,cuDF - GPU DataFrame Library.,250.0,20,2022-08-17 15:15:31,22.08.00,26.0,,cudf,,,,,,,https://pypi.org/project/cudf,1801.0,1801.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +539,mace,True,XiaoMi/mace,,ml-frameworks,https://github.com/XiaoMi/mace,https://github.com/XiaoMi/mace,Apache-2.0,2018-06-27 03:50:12.000,2022-07-13 06:56:31.000000,2022-05-30 07:32:06,793.0,48.0,617.0,4672,3344.0,MACE is a deep learning inference framework optimized for mobile..,64.0,20,2022-01-13 09:55:14,1.1.1,12.0,,,,,,,,,,,29.0,,,,,,,,3.0,1425.0,,,,,,,,,,,,,,, +540,MatchZoo,True,NTMC-Community/MatchZoo,,nlp,https://github.com/NTMC-Community/MatchZoo,https://github.com/NTMC-Community/MatchZoo,Apache-2.0,2017-06-08 08:55:22.000,2021-06-03 02:58:49.000000,2021-06-02 17:38:16,897.0,33.0,429.0,3696,1810.0,"Facilitating the design, comparison and sharing of deep..",36.0,20,2019-10-09 19:24:22,2.2,2.0,,matchzoo,,,,['tensorflow'],11.0,11.0,https://pypi.org/project/matchzoo,63.0,63.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +541,Stable Baselines,True,hill-a/stable-baselines,,reinforcement-learning,https://github.com/hill-a/stable-baselines,https://github.com/hill-a/stable-baselines,MIT,2018-07-02 14:28:59.000,2021-08-25 09:25:32.000000,2021-08-25 09:25:32,690.0,105.0,817.0,3605,838.0,"A fork of OpenAI Baselines, implementations of reinforcement..",112.0,20,2020-08-05 19:45:11,2.10.1,21.0,,stable-baselines,,,,,,,https://pypi.org/project/stable-baselines,7893.0,7893.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +542,River,True,online-ml/river,,others,https://github.com/online-ml/river,https://github.com/online-ml/river,BSD-3-Clause,2019-01-24 15:18:26.000,2022-08-24 12:56:26.000000,2022-08-24 12:52:43,382.0,4.0,370.0,3552,,Online machine learning in Python.,81.0,20,2022-06-06 21:34:22,0.11.1,4.0,,,,,,,158.0,158.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +543,MMLSpark,True,Azure/mmlspark,,distributed-ml,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000,2022-08-26 03:49:47.000000,2022-08-26 02:22:40,670.0,224.0,348.0,3499,1207.0,Microsoft Machine Learning for Apache Spark.,97.0,20,2022-08-23 03:41:02,0.10.1,25.0,microsoft/SynapseML,mmlspark,,,,['spark'],,,https://pypi.org/project/mmlspark,4.0,4.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +544,tf-quant-finance,True,google/tf-quant-finance,,financial-data,https://github.com/google/tf-quant-finance,https://github.com/google/tf-quant-finance,Apache-2.0,2019-07-24 16:09:50.000,2022-08-19 12:06:36.000000,2022-08-19 12:06:31,425.0,15.0,25.0,3243,900.0,High-performance TensorFlow library for quantitative..,41.0,20,,,4.0,,tf-quant-finance,,,,['tensorflow'],,,https://pypi.org/project/tf-quant-finance,4758.0,4758.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +545,NLP Architect,True,IntelLabs/nlp-architect,,nlp,https://github.com/IntelLabs/nlp-architect,https://github.com/IntelLabs/nlp-architect,Apache-2.0,2018-05-17 21:00:13.000,2022-06-29 05:50:24.000000,2022-06-29 05:46:04,433.0,14.0,112.0,2858,955.0,A model library for exploring state-of-the-art deep learning..,37.0,20,2020-11-17 12:32:37,0.5.5.1,13.0,,nlp-architect,,,,,8.0,8.0,https://pypi.org/project/nlp-architect,168.0,168.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +546,PARL,True,PaddlePaddle/PARL,,reinforcement-learning,https://github.com/PaddlePaddle/PARL,https://github.com/PaddlePaddle/PARL,Apache-2.0,2018-04-25 17:54:22.000,2022-08-26 02:29:19.000000,2022-08-25 11:11:45,731.0,62.0,346.0,2707,1.0,A high-performance distributed training framework for Reinforcement..,31.0,20,2021-06-03 09:31:59,2.0.0,7.0,,parl,,,,['paddle'],94.0,94.0,https://pypi.org/project/parl,503.0,503.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +547,dpark,True,douban/dpark,,data-pipelines,https://github.com/douban/dpark,https://github.com/douban/dpark,BSD-3-Clause,2012-04-11 08:35:06.000,2020-12-25 10:36:06.000000,2020-12-25 10:36:05,538.0,1.0,60.0,2685,1467.0,"Python clone of Spark, a MapReduce alike framework in Python.",35.0,20,2018-07-27 04:05:25,0.5.0,4.0,,dpark,,,,['spark'],5.0,5.0,https://pypi.org/project/dpark,32.0,32.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +548,tensorflow-graphics,True,tensorflow/graphics,,image,https://github.com/tensorflow/graphics,https://github.com/tensorflow/graphics,Apache-2.0,2019-01-08 10:39:44.000,2022-07-31 05:47:39.000000,2022-04-04 20:19:03,337.0,75.0,90.0,2654,753.0,TensorFlow Graphics: Differentiable Graphics Layers..,36.0,20,2019-05-09 10:06:22,1.0.0,1.0,,tensorflow-graphics,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-graphics,2681.0,2681.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +549,zenml,True,maiot-io/zenml,,data-pipelines,https://github.com/zenml-io/zenml,https://github.com/zenml-io/zenml,Apache-2.0,2020-11-19 09:25:46.000,2022-08-25 15:44:41.000000,2022-08-25 12:14:41,191.0,24.0,82.0,2322,,ZenML : MLOps framework to create reproducible ML pipelines for..,46.0,20,2022-08-17 15:06:17,0.13.0,36.0,zenml-io/zenml,zenml,,,,,,,https://pypi.org/project/zenml,2529.0,2529.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +550,python_speech_features,True,jameslyons/python_speech_features,,audio,https://github.com/jameslyons/python_speech_features,https://github.com/jameslyons/python_speech_features,MIT,2013-10-31 02:42:08.000,2021-10-20 10:08:48.000000,2020-12-31 13:27:01,594.0,20.0,51.0,2125,120.0,This library provides common speech features for ASR including MFCCs and filterbank energies.,19.0,20,2020-01-14 14:12:10,0.6.1,3.0,,python_speech_features,,,,,,,https://pypi.org/project/python_speech_features,149374.0,149374.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +551,IB-insync,True,erdewit/ib_insync,,financial-data,https://github.com/erdewit/ib_insync,https://github.com/erdewit/ib_insync,BSD-2-Clause,2017-07-12 12:09:24.000,2022-08-23 12:02:51.000000,2022-08-23 12:02:40,487.0,5.0,416.0,1883,651.0,Python sync/async framework for Interactive Brokers API.,31.0,20,,,15.0,,ib_insync,conda-forge/ib-insync,,,,,,https://pypi.org/project/ib_insync,7433.0,7967.0,https://anaconda.org/conda-forge/ib-insync,2021-11-29 01:17:29.243,19788.0,,,,,3.0,,,,,,,,,,,,,,,, +552,reformer-pytorch,True,lucidrains/reformer-pytorch,,pytorch-utils,https://github.com/lucidrains/reformer-pytorch,https://github.com/lucidrains/reformer-pytorch,MIT,2020-01-09 20:42:37.000,2022-06-24 01:30:44.000000,2022-06-24 01:30:35,240.0,13.0,104.0,1782,247.0,"Reformer, the efficient Transformer, in Pytorch.",11.0,20,2021-11-06 23:08:36,1.4.4,21.0,,reformer-pytorch,,,,['pytorch'],,,https://pypi.org/project/reformer-pytorch,1940.0,1940.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +553,Torchmeta,True,tristandeleu/pytorch-meta,,pytorch-utils,https://github.com/tristandeleu/pytorch-meta,https://github.com/tristandeleu/pytorch-meta,MIT,2018-12-04 23:36:45.000,2022-01-10 12:07:24.000000,2021-09-20 16:03:46,215.0,42.0,89.0,1675,382.0,A collection of extensions and data-loaders for few-shot learning..,12.0,20,,,,,torchmeta,,,,['pytorch'],97.0,97.0,https://pypi.org/project/torchmeta,1383.0,1383.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +554,hiddenlayer,True,waleedka/hiddenlayer,,ml-experiments,https://github.com/waleedka/hiddenlayer,https://github.com/waleedka/hiddenlayer,MIT,2018-05-18 22:34:51.000,2022-06-23 20:25:11.000000,2020-04-24 06:58:09,233.0,50.0,35.0,1632,58.0,Neural network graphs and training metrics for..,6.0,20,2018-12-03 04:33:29,0.2,1.0,,hiddenlayer,,,,"['pytorch', 'tensorflow', 'jupyter']",127.0,127.0,https://pypi.org/project/hiddenlayer,1704.0,1704.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +555,datatable,True,h2oai/datatable,,data-containers,https://github.com/h2oai/datatable,https://github.com/h2oai/datatable,MPL-2.0,2017-03-03 02:32:59.000,2022-08-24 23:57:09.000000,2022-08-12 05:33:20,138.0,146.0,1289.0,1585,,A Python package for manipulating 2-dimensional tabular data..,33.0,20,2021-07-02 00:15:35,1.0.0,16.0,,datatable,,,,,,,https://pypi.org/project/datatable,67476.0,67504.0,,,,,,,,3.0,1698.0,,,,,,,,,,,,,,, +556,FARM,True,deepset-ai/FARM,,nlp,https://github.com/deepset-ai/FARM,https://github.com/deepset-ai/FARM,Apache-2.0,2019-07-17 14:51:12.000,2022-04-25 08:34:07.000000,2022-04-25 08:32:55,219.0,3.0,398.0,1568,593.0,Fast & easy transfer learning for NLP. Harvesting language models..,37.0,20,2021-06-10 09:45:12,0.8.0,22.0,,farm,,,,['pytorch'],,,https://pypi.org/project/farm,4410.0,4410.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +557,DELTA,True,Delta-ML/delta,,nlp,https://github.com/Delta-ML/delta,https://github.com/Delta-ML/delta,Apache-2.0,2019-05-29 08:33:57.000,2022-08-10 01:35:09.000000,2020-12-17 06:57:15,293.0,1.0,74.0,1525,932.0,DELTA is a deep learning based natural language and speech..,41.0,20,2020-07-16 09:31:45,0.3.3,4.0,,delta-nlp,,zh794390558/delta,,['tensorflow'],,,https://pypi.org/project/delta-nlp,14.0,349.0,,,,https://hub.docker.com/r/zh794390558/delta,2021-08-03 14:50:00.516864,,13091.0,3.0,,,,,,,,,,,,,,,, +558,TNT,True,pytorch/tnt,,ml-experiments,https://github.com/pytorch/tnt,https://github.com/pytorch/tnt,BSD-3-Clause,2016-12-10 11:49:58.000,2022-08-18 22:58:42.000000,2022-08-18 22:57:08,197.0,,59.0,1409,237.0,"Simple tools for logging and visualizing, loading and training.",53.0,20,,,,,torchnet,,,,['pytorch'],,,https://pypi.org/project/torchnet,8784.0,8784.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +559,Pypeline,True,cgarciae/pypeln,,data-pipelines,https://github.com/cgarciae/pypeln,https://github.com/cgarciae/pypeln,MIT,2018-09-01 13:43:31.000,2022-06-23 00:13:44.000000,2022-06-23 00:13:44,80.0,15.0,44.0,1355,239.0,Concurrent data pipelines in Python .,13.0,20,2022-01-06 15:32:49,0.4.9,14.0,,pypeln,,,,,,,https://pypi.org/project/pypeln,8297.0,8297.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +560,sklearn-porter,True,nok/sklearn-porter,,model-serialisation,https://github.com/nok/sklearn-porter,https://github.com/nok/sklearn-porter,BSD-3-Clause,2016-06-22 22:21:34.000,2022-07-25 15:59:11.000000,2022-05-22 23:59:48,158.0,34.0,34.0,1177,,"Transpile trained scikit-learn estimators to C, Java,..",12.0,20,2019-01-20 13:14:03,0.7.2,15.0,,sklearn-porter,,,,['sklearn'],44.0,44.0,https://pypi.org/project/sklearn-porter,335.0,335.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +561,torch-scatter,True,rusty1s/pytorch_scatter,,pytorch-utils,https://github.com/rusty1s/pytorch_scatter,https://github.com/rusty1s/pytorch_scatter,MIT,2017-12-16 16:34:23.000,2022-08-18 07:52:12.000000,2022-08-18 07:52:12,125.0,18.0,253.0,1069,1011.0,PyTorch Extension Library of Optimized Scatter Operations.,22.0,20,2021-10-22 09:39:51,2.0.9,20.0,,torch-scatter,,,,['pytorch'],,,https://pypi.org/project/torch-scatter,29555.0,29555.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +562,luminol,True,linkedin/luminol,,time-series-data,https://github.com/linkedin/luminol,https://github.com/linkedin/luminol,Apache-2.0,2015-11-18 23:16:33.000,2022-08-24 16:16:11.000000,2018-01-09 07:46:55,205.0,24.0,12.0,1043,69.0,Anomaly Detection and Correlation library.,8.0,20,,,,,luminol,,,,,66.0,66.0,https://pypi.org/project/luminol,31741.0,31741.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +563,TFEncrypted,True,tf-encrypted/tf-encrypted,,privacy-ml,https://github.com/tf-encrypted/tf-encrypted,https://github.com/tf-encrypted/tf-encrypted,Apache-2.0,2018-03-21 18:22:13.000,2022-08-26 01:45:16.000000,2022-08-26 01:45:16,180.0,156.0,260.0,1030,600.0,A Framework for Encrypted Machine Learning in TensorFlow.,28.0,20,,,,,tf-encrypted,,,,['tensorflow'],62.0,62.0,https://pypi.org/project/tf-encrypted,443.0,443.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +564,TensorNets,True,taehoonlee/tensornets,,tensorflow-utils,https://github.com/taehoonlee/tensornets,https://github.com/taehoonlee/tensornets,MIT,2017-09-19 05:19:01.000,2021-01-02 06:28:10.000000,2021-01-02 06:26:24,184.0,16.0,42.0,1008,284.0,High level network definitions with pre-trained weights in..,6.0,20,2020-03-31 04:38:27,0.4.6,12.0,,tensornets,,,,['tensorflow'],52.0,52.0,https://pypi.org/project/tensornets,150.0,150.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +565,scikit-cuda,True,lebedov/scikit-cuda,,gpu-utilities,https://github.com/lebedov/scikit-cuda,https://github.com/lebedov/scikit-cuda,,2010-09-27 02:02:07.000,2022-03-31 14:08:20.000000,2022-03-31 14:08:20,171.0,50.0,170.0,911,1034.0,Python interface to GPU-powered libraries.,46.0,20,2015-12-29 15:56:39,0.5.1,7.0,,scikit-cuda,,,,,199.0,199.0,https://pypi.org/project/scikit-cuda,487.0,487.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +566,PFRL,True,pfnet/pfrl,,reinforcement-learning,https://github.com/pfnet/pfrl,https://github.com/pfnet/pfrl,MIT,2020-06-24 09:31:50.000,2022-06-20 14:44:53.000000,2022-03-14 08:29:44,116.0,24.0,39.0,893,406.0,PFRL: a PyTorch-based deep reinforcement learning library.,16.0,20,2021-07-07 02:43:23,0.3.0,4.0,,pfrl,,,,,54.0,54.0,https://pypi.org/project/pfrl,409.0,409.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +567,DiCE,True,interpretml/DiCE,,interpretability,https://github.com/interpretml/DiCE,https://github.com/interpretml/DiCE,MIT,2019-05-02 09:51:02.000,2022-07-11 11:27:10.000000,2022-07-06 16:45:45,125.0,56.0,70.0,888,561.0,Generate Diverse Counterfactual Explanations for any machine..,14.0,20,2022-06-02 13:39:31,0.8,9.0,,dice-ml,,,,"['tensorflow', 'pytorch']",,,https://pypi.org/project/dice-ml,140712.0,140712.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +568,AutoViz,True,AutoViML/AutoViz,,data-viz,https://github.com/AutoViML/AutoViz,https://github.com/AutoViML/AutoViz,Apache-2.0,2019-07-17 17:14:06.000,2022-08-10 12:51:03.000000,2022-08-10 12:50:31,120.0,3.0,56.0,887,135.0,"Automatically Visualize any dataset, any size with a single line of..",12.0,20,,,,,autoviz,,,,,242.0,242.0,https://pypi.org/project/autoviz,51682.0,51682.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +569,nude.py,True,hhatto/nude.py,,image,https://github.com/hhatto/nude.py,https://github.com/hhatto/nude.py,MIT,2013-06-09 06:55:55.000,2020-11-23 13:49:32.000000,2020-11-23 13:49:02,130.0,7.0,3.0,859,79.0,Nudity detection with Python.,12.0,20,,,,,nudepy,,,,,2609.0,2609.0,https://pypi.org/project/nudepy,9533.0,9533.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +570,Performer Pytorch,True,lucidrains/performer-pytorch,,pytorch-utils,https://github.com/lucidrains/performer-pytorch,https://github.com/lucidrains/performer-pytorch,MIT,2020-10-03 03:41:36.000,2022-02-02 20:33:32.000000,2022-02-02 20:33:18,121.0,35.0,43.0,856,,"An implementation of Performer, a linear attention-..",6.0,20,2022-02-02 20:33:33,1.1.4,80.0,,performer-pytorch,,,,['pytorch'],49.0,49.0,https://pypi.org/project/performer-pytorch,74781.0,74781.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +571,bambi,True,bambinos/bambi,,probabilistics,https://github.com/bambinos/bambi,https://github.com/bambinos/bambi,MIT,2016-05-16 03:21:00.000,2022-08-25 15:38:15.000000,2022-08-21 21:14:51,89.0,51.0,221.0,822,,BAyesian Model-Building Interface (Bambi) in Python.,26.0,20,2022-06-06 17:17:14,0.9.0,16.0,,bambi,,,,,32.0,32.0,https://pypi.org/project/bambi,6743.0,6743.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +572,rows,True,turicas/rows,,data-loading,https://github.com/turicas/rows,https://github.com/turicas/rows,LGPL-3.0,2014-05-07 05:43:11.000,2022-08-18 22:27:24.000000,2022-08-18 22:27:13,135.0,144.0,149.0,808,738.0,"A common, beautiful interface to tabular data, no matter the format.",31.0,20,2019-02-14 21:20:15,0.4.1,7.0,,rows,,,,,144.0,144.0,https://pypi.org/project/rows,881.0,881.0,,,,,,,,3.0,38.0,,,,,,,,,,,,,,, +573,Objax,True,google/objax,,ml-frameworks,https://github.com/google/objax,https://github.com/google/objax,Apache-2.0,2020-08-20 06:20:40.000,2022-08-24 18:59:01.000000,2022-07-12 21:58:34,60.0,38.0,60.0,716,432.0,Objax is a machine learning framework that provides an Object..,23.0,20,2022-02-01 00:17:20,1.6.0,7.0,,objax,,,,['jax'],25.0,25.0,https://pypi.org/project/objax,438.0,438.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +574,TreeInterpreter,True,andosa/treeinterpreter,,interpretability,https://github.com/andosa/treeinterpreter,https://github.com/andosa/treeinterpreter,BSD-3-Clause,2015-08-02 20:26:21.000,2021-02-28 18:33:06.000000,2021-02-28 18:33:06,135.0,19.0,4.0,716,37.0,Package for interpreting scikit-learn's decision tree..,11.0,20,,,,,treeinterpreter,,,,['sklearn'],281.0,281.0,https://pypi.org/project/treeinterpreter,145793.0,145793.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +575,pickleDB,True,patx/pickledb,,data-containers,https://github.com/patx/pickledb,https://github.com/patx/pickledb,BSD-3-Clause,2011-10-28 00:04:40.000,2022-02-10 09:36:27.000000,2019-11-15 03:38:30,111.0,16.0,41.0,696,105.0,pickleDB is an open source key-value store using Python's json..,12.0,20,,,,,pickledb,,,,,941.0,941.0,https://pypi.org/project/pickledb,38378.0,38378.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +576,SALib,True,SALib/SALib,,probabilistics,https://github.com/SALib/SALib,https://github.com/SALib/SALib,MIT,2013-05-30 13:38:10.000,2022-08-25 09:02:50.000000,2022-08-21 04:35:28,188.0,44.0,234.0,623,,"Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,..",37.0,20,2021-09-04 09:49:51,1.4.5,29.0,,salib,conda-forge/salib,,,,,,https://pypi.org/project/salib,155311.0,156618.0,https://anaconda.org/conda-forge/salib,2021-09-04 07:03:28.179,90192.0,,,,,3.0,,,,,,,,,,,,,,,, +577,combo,True,yzhao062/combo,,sklearn-utils,https://github.com/yzhao062/combo,https://github.com/yzhao062/combo,BSD-2-Clause,2019-07-14 01:13:36.000,2022-07-07 13:25:34.000000,2022-07-07 13:25:27,100.0,10.0,3.0,591,208.0,(AAAI' 20) A Python Toolbox for Machine Learning Model..,2.0,20,2020-02-19 02:11:55,V0.1.0,1.0,,combo,,,,"['sklearn', 'xgboost']",477.0,477.0,https://pypi.org/project/combo,34662.0,34662.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +578,HpBandSter,True,automl/HpBandSter,,hyperopt,https://github.com/automl/HpBandSter,https://github.com/automl/HpBandSter,BSD-3-Clause,2017-12-17 20:28:20.000,2022-04-22 06:33:34.000000,2022-04-22 06:33:31,111.0,54.0,35.0,545,188.0,a distributed Hyperband implementation on Steroids.,11.0,20,2019-07-30 12:47:43,1.0,1.0,,hpbandster,,,,,239.0,239.0,https://pypi.org/project/hpbandster,21874.0,21874.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +579,Poutyne,True,GRAAL-Research/poutyne,,pytorch-utils,https://github.com/GRAAL-Research/poutyne,https://github.com/GRAAL-Research/poutyne,LGPL-3.0,2017-12-07 18:30:17.000,2022-08-21 19:31:38.000000,2022-07-16 21:38:46,62.0,8.0,45.0,529,719.0,A simplified framework and utilities for PyTorch.,18.0,20,2022-07-16 21:48:35,1.12,30.0,,poutyne,,,,['pytorch'],91.0,91.0,https://pypi.org/project/poutyne,5311.0,5311.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +580,PyWaffle,True,gyli/PyWaffle,,data-viz,https://github.com/gyli/PyWaffle,https://github.com/gyli/PyWaffle,MIT,2017-11-14 20:03:47.000,2022-06-08 03:46:06.000000,2022-06-08 03:46:02,92.0,4.0,14.0,505,305.0,Make Waffle Charts in Python.,6.0,20,,,,,pywaffle,,,,,148.0,148.0,https://pypi.org/project/pywaffle,8334.0,8334.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +581,BioPandas,True,rasbt/biopandas,,others,https://github.com/rasbt/biopandas,https://github.com/rasbt/biopandas,BSD-3-Clause,2015-11-21 00:00:14.000,2022-08-08 12:28:34.000000,2022-08-06 14:43:01,101.0,20.0,27.0,504,,Working with molecular structures in pandas DataFrames.,10.0,20,2022-05-13 14:31:23,0.4.1,15.0,,biopandas,conda-forge/biopandas,,,['pandas'],120.0,120.0,https://pypi.org/project/biopandas,5327.0,7034.0,https://anaconda.org/conda-forge/biopandas,2022-05-13 17:21:19.313,116083.0,,,,,3.0,,,,,,,,,,,,,,,, +582,skope-rules,True,scikit-learn-contrib/skope-rules,,sklearn-utils,https://github.com/scikit-learn-contrib/skope-rules,https://github.com/scikit-learn-contrib/skope-rules,,2018-02-18 13:42:47.000,2022-07-24 13:44:59.000000,2020-10-23 14:31:57,79.0,25.0,6.0,481,247.0,machine learning with logical rules in Python.,18.0,20,2020-12-11 09:37:02,1.0.1,1.0,,skope-rules,,,,['sklearn'],129.0,129.0,https://pypi.org/project/skope-rules,96337.0,96337.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +583,pysparkling,True,svenkreiss/pysparkling,,data-pipelines,https://github.com/svenkreiss/pysparkling,https://github.com/svenkreiss/pysparkling,,2015-05-09 19:23:20.000,2021-10-31 16:40:25.000000,2021-02-22 17:29:11,42.0,6.0,21.0,250,1527.0,A pure Python implementation of Apache Spark's RDD and DStream..,10.0,20,2021-01-10 21:14:23,0.6.1,26.0,,pysparkling,,,,,124.0,124.0,https://pypi.org/project/pysparkling,13250.0,13250.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +584,scikit-posthocs,True,maximtrp/scikit-posthocs,,probabilistics,https://github.com/maximtrp/scikit-posthocs,https://github.com/maximtrp/scikit-posthocs,MIT,2017-06-22 19:41:37.000,2022-08-21 20:24:17.000000,2022-08-21 20:24:17,28.0,6.0,41.0,250,487.0,Multiple Pairwise Comparisons (Post Hoc) Tests in Python.,10.0,20,2022-05-07 07:57:06,0.7.0,6.0,,scikit-posthocs,,,,['sklearn'],,,https://pypi.org/project/scikit-posthocs,40332.0,40332.0,,,,,,,,3.0,25.0,,,,,,,,,,,,,,, +585,pyfasttext,True,vrasneur/pyfasttext,,nlp,https://github.com/vrasneur/pyfasttext,https://github.com/vrasneur/pyfasttext,GPL-3.0,2017-06-30 18:44:42.000,2018-12-08 15:02:54.000000,2018-12-08 15:02:12,30.0,21.0,28.0,230,153.0,Yet another Python binding for fastText.,4.0,20,2018-12-08 15:02:54,0.4.6,12.0,,pyfasttext,,,,,244.0,244.0,https://pypi.org/project/pyfasttext,3362.0,3367.0,,,,,,,,3.0,348.0,,,,,,,,,,,,,,, +586,MindsDB,True,mindsdb/mindsdb,,ml-frameworks,https://github.com/mindsdb/mindsdb,https://github.com/mindsdb/mindsdb,GPL-3.0,2018-08-02 17:56:45.000,2022-08-25 23:05:15.000000,2022-08-25 14:51:43,1020.0,144.0,1063.0,9708,,Predictive AI layer for existing databases.,131.0,19,2022-08-24 14:39:28,22.8.4.1,100.0,,mindsdb,,,,['pytorch'],,,https://pypi.org/project/mindsdb,2854.0,2854.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +587,TTS,True,mozilla/TTS,,audio,https://github.com/mozilla/TTS,https://github.com/mozilla/TTS,MPL-2.0,2018-01-23 14:22:06.000,2022-08-24 14:08:31.000000,2021-02-12 10:36:31,931.0,3.0,532.0,6165,2184.0,Deep learning for Text to Speech (Discussion forum:..,56.0,19,2021-01-29 00:03:56,0.0.9,1.0,,,,,,,,,,,137.0,,,,,,,,3.0,2617.0,,,,,,,,,,,,,,, +588,Dejavu,True,worldveil/dejavu,,audio,https://github.com/worldveil/dejavu,https://github.com/worldveil/dejavu,MIT,2013-11-19 02:50:35.000,2022-07-02 09:54:39.000000,2020-06-03 05:58:03,1283.0,84.0,128.0,5822,146.0,Audio fingerprinting and recognition in Python.,22.0,19,,,,,PyDejavu,,,,,23.0,23.0,https://pypi.org/project/PyDejavu,67.0,67.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +589,haystack,True,deepset-ai/haystack,,nlp,https://github.com/deepset-ai/haystack,https://github.com/deepset-ai/haystack,Apache-2.0,2019-11-14 09:05:28.000,2022-08-26 00:23:42.000000,2022-08-25 15:50:57,827.0,228.0,1302.0,5237,,End-to-end Python framework for building natural language search..,136.0,19,2022-08-25 12:29:52,1.7.2,20.0,,haystack,,,,,,,https://pypi.org/project/haystack,870.0,870.0,,,,,,,,3.0,15.0,,,,,,,,,,,,,,, +590,Crypto Signals,True,CryptoSignal/crypto-signal,,financial-data,https://github.com/CryptoSignal/Crypto-Signal,https://github.com/CryptoSignal/Crypto-Signal,MIT,2017-09-16 23:49:24.000,2022-08-09 13:26:32.000000,2022-08-09 13:26:32,1057.0,52.0,205.0,4122,565.0,Github.com/CryptoSignal - #1 Quant Trading & Technical..,28.0,19,,,,,,,shadowreaver/crypto-signal,,,,,,,2410.0,,,,https://hub.docker.com/r/shadowreaver/crypto-signal,2020-09-03 13:00:35.801133,7.0,142245.0,3.0,,,,,,,,,,,,,,,, +591,neon,True,NervanaSystems/neon,,ml-frameworks,https://github.com/NervanaSystems/neon,https://github.com/NervanaSystems/neon,Apache-2.0,2014-10-16 01:00:17.000,2020-12-23 01:21:42.000000,2019-05-22 18:27:54,805.0,83.0,306.0,3858,1118.0,Intel Nervana reference deep learning framework committed to best..,108.0,19,2018-01-05 21:36:23,2.6.0,32.0,,nervananeon,,,,,,,https://pypi.org/project/nervananeon,32.0,35.0,,,,,,,,3.0,335.0,,,,,,,,,,,,,,, +592,Camelot,True,atlanhq/camelot,,data-loading,https://github.com/atlanhq/camelot,https://github.com/atlanhq/camelot,,2016-06-18 11:48:49.000,2021-11-24 11:40:44.000000,2019-10-15 05:25:40,329.0,86.0,278.0,3256,446.0,Camelot: PDF Table Extraction for Humans.,23.0,19,2019-01-17 04:21:43,0.7.2,1.0,,camelot-py,,,,,,,https://pypi.org/project/camelot-py,78771.0,78771.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +593,TensorWatch,True,microsoft/tensorwatch,,ml-experiments,https://github.com/microsoft/tensorwatch,https://github.com/microsoft/tensorwatch,MIT,2019-05-15 08:29:34.000,2021-04-13 09:44:02.000000,2021-01-15 19:46:05,345.0,52.0,15.0,3239,112.0,"Debugging, monitoring and visualization for Python Machine Learning..",13.0,19,,,,,tensorwatch,,,,,86.0,86.0,https://pypi.org/project/tensorwatch,5251.0,5251.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +594,TRFL,True,deepmind/trfl,,reinforcement-learning,https://github.com/deepmind/trfl,https://github.com/deepmind/trfl,Apache-2.0,2018-08-08 14:44:11.000,2021-08-16 11:47:43.000000,2021-08-16 11:45:18,375.0,4.0,16.0,3124,123.0,TensorFlow Reinforcement Learning.,13.0,19,,,,,trfl,,,,['tensorflow'],89.0,89.0,https://pypi.org/project/trfl,4202.0,4202.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +595,PyTorch-BigGraph,True,facebookresearch/PyTorch-BigGraph,,graph,https://github.com/facebookresearch/PyTorch-BigGraph,https://github.com/facebookresearch/PyTorch-BigGraph,,2018-10-01 20:41:16.000,2022-07-05 15:22:12.000000,2022-07-05 15:19:13,414.0,50.0,137.0,3109,,Generate embeddings from large-scale graph-structured..,27.0,19,2019-10-14 16:45:11,1.0.0,3.0,,torchbiggraph,,,,['pytorch'],,,https://pypi.org/project/torchbiggraph,323913.0,323916.0,,,,,,,,3.0,135.0,,,,,,,,,,,,,,, +596,LIT,True,PAIR-code/lit,,interpretability,https://github.com/PAIR-code/lit,https://github.com/PAIR-code/lit,Apache-2.0,2020-07-28 13:07:26.000,2022-08-25 20:27:41.000000,2022-03-15 12:13:11,311.0,41.0,69.0,2975,,The Language Interpretability Tool: Interactively analyze NLP models for..,18.0,19,2021-12-21 14:29:03,0.4.1,6.0,,lit-nlp,,,,,11.0,11.0,https://pypi.org/project/lit-nlp,818.0,818.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +597,AdaBound,True,Luolc/AdaBound,,pytorch-utils,https://github.com/Luolc/AdaBound,https://github.com/Luolc/AdaBound,Apache-2.0,2019-02-15 18:05:20.000,2019-03-06 17:01:52.000000,2019-03-06 17:01:45,322.0,18.0,7.0,2894,27.0,An optimizer that trains as fast as Adam and as good as SGD.,2.0,19,2019-03-06 16:44:42,0.0.5,1.0,,adabound,,,,['pytorch'],143.0,143.0,https://pypi.org/project/adabound,1368.0,1368.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +598,cuML,True,rapidsai/cuml,,gpu-utilities,https://github.com/rapidsai/cuml,https://github.com/rapidsai/cuml,Apache-2.0,2018-10-11 15:45:35.000,2022-08-25 23:02:53.000000,2022-08-25 22:13:04,415.0,675.0,1381.0,2892,,cuML - RAPIDS Machine Learning Library.,157.0,19,2022-08-17 22:20:06,22.08.00,24.0,,cuml,,,,,,,https://pypi.org/project/cuml,936.0,936.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +599,PandasGUI,True,adamerose/pandasgui,,data-viz,https://github.com/adamerose/PandasGUI,https://github.com/adamerose/PandasGUI,MIT-0,2019-06-12 02:19:42.000,2022-03-16 17:52:29.000000,2022-03-16 17:52:29,180.0,45.0,117.0,2725,715.0,A GUI for Pandas DataFrames.,13.0,19,,,,,pandasgui,,,,['pandas'],173.0,173.0,https://pypi.org/project/pandasgui,3666.0,3666.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +600,StreamAlert,True,airbnb/streamalert,,others,https://github.com/airbnb/streamalert,https://github.com/airbnb/streamalert,Apache-2.0,2017-01-22 01:10:56.000,2022-08-03 09:39:58.000000,2022-07-20 20:54:36,321.0,83.0,259.0,2713,1904.0,"StreamAlert is a serverless, realtime data analysis framework..",33.0,19,2021-11-04 19:07:51,3.5.0,28.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +601,Apache Singa,True,apache/singa,,distributed-ml,https://github.com/apache/singa,https://github.com/apache/singa,Apache-2.0,2015-04-02 07:00:05.000,2022-08-25 09:20:24.000000,2022-06-01 08:52:55,781.0,17.0,62.0,2657,2472.0,a distributed deep learning platform.,79.0,19,2020-04-21 08:01:08,3.0.0,16.0,,,nusdbsystem/singa,apache/singa,,,1.0,1.0,,,14.0,https://anaconda.org/nusdbsystem/singa,2021-08-09 13:10:26.397,508.0,https://hub.docker.com/r/apache/singa,2022-05-31 15:24:19.649658,4.0,692.0,3.0,,,,,,,,,,,,,,,, +602,DeepWalk,True,phanein/deepwalk,,graph,https://github.com/phanein/deepwalk,https://github.com/phanein/deepwalk,,2014-08-23 03:38:20.000,2022-06-28 14:03:23.000000,2020-04-02 01:05:35,808.0,26.0,80.0,2474,46.0,DeepWalk - Deep Learning for Graphs.,10.0,19,2014-11-19 19:20:33,1.0.2,1.0,,deepwalk,,,,,56.0,56.0,https://pypi.org/project/deepwalk,3072.0,3072.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +603,pandas-datareader,True,pydata/pandas-datareader,,data-loading,https://github.com/pydata/pandas-datareader,https://github.com/pydata/pandas-datareader,,2015-01-15 00:34:19.000,2022-08-01 07:46:46.000000,2022-03-16 23:35:07,592.0,101.0,395.0,2412,,Extract data from a wide range of Internet sources into..,85.0,19,2021-07-13 12:27:15,0.10.0,19.0,,pandas-datareader,conda-forge/pandas-datareader,,,['pandas'],,,https://pypi.org/project/pandas-datareader,324377.0,327313.0,https://anaconda.org/conda-forge/pandas-datareader,2021-07-14 09:19:08.289,187942.0,,,,,3.0,,,,,,,,,,,,,,,, +604,Luminoth,True,tryolabs/luminoth,,image,https://github.com/tryolabs/luminoth,https://github.com/tryolabs/luminoth,BSD-3-Clause,2017-02-16 15:07:46.000,2022-05-26 20:44:42.000000,2020-01-07 20:53:25,403.0,52.0,128.0,2387,838.0,Deep Learning toolkit for Computer Vision.,15.0,19,,,10.0,,luminoth,,,,['tensorflow'],41.0,41.0,https://pypi.org/project/luminoth,614.0,830.0,,,,,,,,3.0,12536.0,,,,,,,,,,,,,,, +605,HiPlot,True,facebookresearch/hiplot,,data-viz,https://github.com/facebookresearch/hiplot,https://github.com/facebookresearch/hiplot,MIT,2019-11-08 13:06:41.000,2022-07-21 03:45:18.000000,2022-07-05 08:38:04,115.0,12.0,68.0,2338,,HiPlot makes understanding high dimensional data easy.,8.0,19,2021-11-04 14:24:43,0.1.32,35.0,,hiplot,conda-forge/hiplot,,,,5.0,5.0,https://pypi.org/project/hiplot,27386.0,30667.0,https://anaconda.org/conda-forge/hiplot,2022-05-31 21:21:53.546,98443.0,,,,,3.0,,,,,,,,,,,,,,,, +606,Kashgari,True,BrikerMan/Kashgari,,nlp,https://github.com/BrikerMan/Kashgari,https://github.com/BrikerMan/Kashgari,Apache-2.0,2019-01-19 01:53:28.000,2021-07-09 03:57:16.000000,2021-07-09 03:57:16,435.0,44.0,330.0,2317,,Kashgari is a production-level NLP Transfer learning framework..,21.0,19,2021-07-04 10:44:36,2.0.2,24.0,,kashgari-tf,,,,['tensorflow'],54.0,54.0,https://pypi.org/project/kashgari-tf,44.0,44.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +607,pdftabextract,True,WZBSocialScienceCenter/pdftabextract,,ocr,https://github.com/WZBSocialScienceCenter/pdftabextract,https://github.com/WZBSocialScienceCenter/pdftabextract,Apache-2.0,2016-07-08 11:44:46.000,2022-06-24 09:51:22.000000,2022-06-24 09:51:22,347.0,3.0,18.0,1999,171.0,A set of tools for extracting tables from PDF files..,3.0,19,,,,,pdftabextract,,,,,42.0,42.0,https://pypi.org/project/pdftabextract,664.0,664.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +608,fast-bert,True,kaushaltrivedi/fast-bert,,nlp,https://github.com/utterworks/fast-bert,https://github.com/utterworks/fast-bert,Apache-2.0,2019-04-18 22:01:20.000,2022-08-25 20:49:07.000000,2022-08-25 20:49:07,329.0,153.0,94.0,1758,,Super easy library for BERT based NLP models.,36.0,19,2020-07-09 12:05:40,1.8.0,5.0,utterworks/fast-bert,fast-bert,,,,,,,https://pypi.org/project/fast-bert,1372.0,1372.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +609,sklearn-contrib-lightning,True,scikit-learn-contrib/lightning,,sklearn-utils,https://github.com/scikit-learn-contrib/lightning,https://github.com/scikit-learn-contrib/lightning,,2012-01-11 13:53:52.000,2022-01-30 01:28:10.000000,2022-01-30 01:22:30,185.0,46.0,42.0,1584,743.0,"Large-scale linear classification, regression and..",17.0,19,2022-01-30 01:10:13,0.6.2.post0,4.0,,sklearn-contrib-lightning,conda-forge/sklearn-contrib-lightning,,,['sklearn'],104.0,104.0,https://pypi.org/project/sklearn-contrib-lightning,1737.0,4110.0,https://anaconda.org/conda-forge/sklearn-contrib-lightning,2021-11-13 15:37:21.493,172083.0,,,,,3.0,232.0,,,,,,,,,,,,,,, +610,auto_ml,True,ClimbsRocks/auto_ml,,hyperopt,https://github.com/ClimbsRocks/auto_ml,https://github.com/ClimbsRocks/auto_ml,MIT,2016-08-07 21:35:08.000,2021-02-10 07:52:35.000000,2018-03-25 19:46:25,304.0,179.0,216.0,1578,1149.0,[UNMAINTAINED] Automated machine learning for analytics & production.,13.0,19,2017-09-12 03:01:00,2.7.0,12.0,,auto_ml,,,,,,,https://pypi.org/project/auto_ml,842.0,842.0,,,,,,,,3.0,42.0,,,,,,,,,,,,,,, +611,Antialiased CNNs,True,adobe/antialiased-cnns,,pytorch-utils,https://github.com/adobe/antialiased-cnns,https://github.com/adobe/antialiased-cnns,CC BY-NC-SA 4.0,2019-05-14 20:51:25.000,2021-09-29 18:48:52.000000,2021-09-29 18:48:52,196.0,13.0,31.0,1550,239.0,pip install antialiased-cnns to improve stability and..,6.0,19,2020-10-23 22:45:52,0.3,4.0,,antialiased-cnns,,,,['pytorch'],29.0,29.0,https://pypi.org/project/antialiased-cnns,1529.0,1529.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +612,lore,True,instacart/lore,,ml-experiments,https://github.com/instacart/lore,https://github.com/instacart/lore,MIT,2017-10-19 21:51:45.000,2022-04-11 17:21:50.000000,2022-04-11 17:21:50,124.0,16.0,19.0,1538,273.0,Lore makes machine learning approachable for Software Engineers and..,26.0,19,2020-05-05 20:16:54,0.8.3,1.0,,lore,,,,,20.0,20.0,https://pypi.org/project/lore,532.0,532.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +613,Classy Vision,True,facebookresearch/ClassyVision,,image,https://github.com/facebookresearch/ClassyVision,https://github.com/facebookresearch/ClassyVision,MIT,2019-09-13 22:54:44.000,2022-08-12 14:26:48.000000,2022-08-03 14:42:01,258.0,13.0,63.0,1488,,An end-to-end PyTorch framework for image and video..,76.0,19,2021-07-19 20:08:51,0.6.0,6.0,,classy_vision,conda-forge/classy_vision,,,['pytorch'],,,https://pypi.org/project/classy_vision,2044.0,2497.0,https://anaconda.org/conda-forge/classy_vision,2022-03-22 13:12:30.498,14052.0,,,,,3.0,,,,,,,,,,,,,,,, +614,Higher,True,facebookresearch/higher,,pytorch-utils,https://github.com/facebookresearch/higher,https://github.com/facebookresearch/higher,Apache-2.0,2019-09-06 18:58:36.000,2022-03-25 15:56:51.000000,2021-10-26 07:08:33,105.0,51.0,50.0,1430,,higher is a pytorch library allowing users to obtain higher..,9.0,19,,,,,higher,,,,['pytorch'],162.0,162.0,https://pypi.org/project/higher,107143.0,107143.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +615,ThunderSVM,True,Xtra-Computing/thundersvm,,ml-frameworks,https://github.com/Xtra-Computing/thundersvm,https://github.com/Xtra-Computing/thundersvm,Apache-2.0,2014-12-11 04:24:04.000,2022-04-09 02:38:13.000000,2022-04-09 02:38:13,194.0,61.0,148.0,1418,904.0,ThunderSVM: A Fast SVM Library on GPUs and CPUs.,34.0,19,2019-11-17 09:36:51,0.3.4,5.0,,thundersvm,,,,,,,https://pypi.org/project/thundersvm,350.0,386.0,,,,,,,,3.0,2499.0,,,,,,,,,,,,,,, +616,Optimus,True,ironmussa/Optimus,,data-pipelines,https://github.com/hi-primus/optimus,https://github.com/hi-primus/optimus,Apache-2.0,2017-07-13 02:31:18.000,2022-08-23 07:09:25.000000,2022-06-21 18:44:25,214.0,32.0,196.0,1249,1.0,"Agile Data Preparation Workflows madeeasy with pandas, dask,..",23.0,19,2020-07-19 03:05:40,2.2.32,83.0,hi-primus/optimus,optimuspyspark,,,,['spark'],,,https://pypi.org/project/optimuspyspark,52334.0,52334.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +617,Sockeye,True,awslabs/sockeye,,nlp,https://github.com/awslabs/sockeye,https://github.com/awslabs/sockeye,Apache-2.0,2017-06-08 07:44:30.000,2022-08-25 14:46:45.000000,2022-08-25 14:04:31,295.0,7.0,276.0,1113,,Sequence-to-sequence framework with a focus on Neural Machine..,57.0,19,2022-05-05 08:42:03,3.1.14,71.0,,sockeye,,,,['mxnet'],,,https://pypi.org/project/sockeye,374.0,374.0,,,,,,,,3.0,15.0,,,,,,,,,,,,,,, +618,stockstats,True,jealous/stockstats,,financial-data,https://github.com/jealous/stockstats,https://github.com/jealous/stockstats,,2016-06-05 15:21:22.000,2022-01-07 14:52:00.000000,2022-01-07 14:51:56,262.0,10.0,77.0,1036,41.0,Supply a wrapper ``StockDataFrame`` based on the..,8.0,19,2022-01-07 11:42:21,0.4.1,2.0,,stockstats,,,,,530.0,530.0,https://pypi.org/project/stockstats,6206.0,6206.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +619,fastFM,True,ibayer/fastFM,,recommender-systems,https://github.com/ibayer/fastFM,https://github.com/ibayer/fastFM,,2014-10-27 12:25:51.000,2022-07-17 13:12:39.000000,2021-03-24 12:22:31,196.0,47.0,60.0,996,297.0,fastFM: A Library for Factorization Machines.,20.0,19,2017-11-22 16:13:16,0.2.11,10.0,,fastfm,,,,,97.0,97.0,https://pypi.org/project/fastfm,366.0,370.0,,,,,,,,3.0,448.0,,,,,,,,,,,,,,, +620,geoplotlib,True,andrea-cuttone/geoplotlib,,geospatial-data,https://github.com/andrea-cuttone/geoplotlib,https://github.com/andrea-cuttone/geoplotlib,MIT,2015-02-24 13:13:07.000,2022-06-13 13:53:07.000000,2019-05-06 07:06:50,159.0,25.0,19.0,972,159.0,python toolbox for visualizing geographical data and making maps.,8.0,19,,,,,geoplotlib,,,,,146.0,146.0,https://pypi.org/project/geoplotlib,885.0,885.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +621,Madmom,True,CPJKU/madmom,,audio,https://github.com/CPJKU/madmom,https://github.com/CPJKU/madmom,,2015-09-08 08:19:06.000,2022-06-18 17:26:43.000000,2022-01-06 15:08:19,154.0,41.0,201.0,950,,Python audio and music signal processing library.,20.0,19,2018-11-14 14:57:41,0.16.1,10.0,,madmom,,,,,210.0,210.0,https://pypi.org/project/madmom,1703.0,1703.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +622,calamari,True,Calamari-OCR/calamari,,ocr,https://github.com/Calamari-OCR/calamari,https://github.com/Calamari-OCR/calamari,Apache-2.0,2018-03-20 15:22:29.000,2022-07-05 18:12:32.000000,2022-06-10 10:36:12,194.0,50.0,202.0,935,439.0,Line based ATR Engine based on OCRopy.,19.0,19,2022-03-21 11:52:48,2.2.2,34.0,,calamari_ocr,,,,,,,https://pypi.org/project/calamari_ocr,426.0,426.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +623,NGT,True,yahoojapan/NGT,,nn-search,https://github.com/yahoojapan/NGT,https://github.com/yahoojapan/NGT,Apache-2.0,2016-09-01 07:36:57.000,2022-08-15 23:17:34.000000,2022-08-15 23:13:15,94.0,12.0,89.0,930,145.0,Nearest Neighbor Search with Neighborhood Graph and Tree for High-..,14.0,19,2022-06-03 01:55:11,1.14.6,56.0,,ngt,,,,,,,https://pypi.org/project/ngt,16423.0,16423.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +624,attention-ocr,True,emedvedev/attention-ocr,,ocr,https://github.com/emedvedev/attention-ocr,https://github.com/emedvedev/attention-ocr,MIT,2017-07-21 18:35:19.000,2021-10-29 14:44:11.000000,2021-10-29 14:44:08,243.0,23.0,127.0,918,205.0,A Tensorflow model for text recognition (CNN + seq2seq with..,27.0,19,2020-10-12 06:56:40,0.7.6,2.0,,aocr,,,,['tensorflow'],20.0,20.0,https://pypi.org/project/aocr,96.0,96.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +625,mrq,True,pricingassistant/mrq,,data-pipelines,https://github.com/pricingassistant/mrq,https://github.com/pricingassistant/mrq,MIT,2014-02-13 09:32:40.000,2022-07-23 21:52:33.000000,2020-12-13 18:58:15,112.0,52.0,119.0,872,709.0,Mr. Queue - A distributed worker task queue in Python using Redis & gevent.,40.0,19,2018-08-31 13:59:56,0.9.10,5.0,,mrq,,,,,29.0,29.0,https://pypi.org/project/mrq,132.0,132.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +626,TensorFrames,True,databricks/tensorframes,,distributed-ml,https://github.com/databricks/tensorframes,https://github.com/databricks/tensorframes,Apache-2.0,2016-03-04 19:25:19.000,2022-05-26 20:14:58.000000,2019-11-15 21:43:53,157.0,49.0,43.0,757,221.0,[DEPRECATED] Tensorflow wrapper for DataFrames on..,16.0,19,2018-11-16 20:50:02,0.6.0,6.0,,tensorframes,,,,"['tensorflow', 'spark']",,,https://pypi.org/project/tensorframes,39733.0,39733.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +627,What-If Tool,True,PAIR-code/what-if-tool,,interpretability,https://github.com/PAIR-code/what-if-tool,https://github.com/PAIR-code/what-if-tool,Apache-2.0,2018-09-07 20:26:10.000,2022-06-03 01:25:04.000000,2022-01-05 20:19:46,140.0,58.0,52.0,739,328.0,Source code/webpage/demos for the What-If Tool.,20.0,19,2021-10-12 17:36:36,1.8.1,3.0,,witwidget,,,,,,,https://pypi.org/project/witwidget,10727.0,16620.0,,,,,,,,3.0,,,wit-widget,https://www.npmjs.com/package/wit-widget,5893.0,,,,,,,,,,, +628,NearPy,True,pixelogik/NearPy,,nn-search,https://github.com/pixelogik/NearPy,https://github.com/pixelogik/NearPy,MIT,2013-04-25 09:10:26.000,2021-09-26 01:44:54.000000,2018-10-21 17:54:28,143.0,24.0,38.0,713,159.0,Python framework for fast (approximated) nearest neighbour search in..,18.0,19,2016-09-27 13:04:44,1.0.0,1.0,,NearPy,,,,,70.0,70.0,https://pypi.org/project/NearPy,1345.0,1345.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +629,deeplift,True,kundajelab/deeplift,,interpretability,https://github.com/kundajelab/deeplift,https://github.com/kundajelab/deeplift,MIT,2016-06-01 02:18:06.000,2022-04-28 10:04:52.000000,2021-11-11 17:50:26,151.0,37.0,48.0,654,553.0,Public facing deeplift repo.,11.0,19,,,21.0,,deeplift,,,,,62.0,62.0,https://pypi.org/project/deeplift,534.0,534.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +630,TF Compression,True,tensorflow/compression,,tensorflow-utils,https://github.com/tensorflow/compression,https://github.com/tensorflow/compression,Apache-2.0,2018-05-15 23:32:19.000,2022-08-25 20:50:20.000000,2022-08-25 20:49:46,214.0,2.0,85.0,644,241.0,Data compression in TensorFlow.,16.0,19,2022-08-13 06:18:43,2.9.2,17.0,,tensorflow-compression,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-compression,1027.0,1027.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +631,Torchbearer,True,pytorchbearer/torchbearer,,ml-frameworks,https://github.com/pytorchbearer/torchbearer,https://github.com/pytorchbearer/torchbearer,MIT,2018-03-12 16:30:42.000,2021-03-26 19:56:57.000000,2021-03-26 19:56:57,66.0,10.0,237.0,631,430.0,torchbearer: A model fitting library for PyTorch.,13.0,19,2020-01-31 14:07:22,0.5.3,24.0,,torchbearer,,,,['pytorch'],64.0,64.0,https://pypi.org/project/torchbearer,699.0,699.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +632,aequitas,True,dssg/aequitas,,interpretability,https://github.com/dssg/aequitas,https://github.com/dssg/aequitas,MIT,2018-02-13 19:40:30.000,2022-08-16 15:32:58.000000,2021-05-27 09:45:10,90.0,40.0,21.0,489,857.0,Bias and Fairness Audit Toolkit.,16.0,19,,,,,aequitas,,,,,106.0,106.0,https://pypi.org/project/aequitas,2022.0,2022.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +633,pivottablejs,True,nicolaskruchten/jupyter_pivottablejs,,data-viz,https://github.com/nicolaskruchten/jupyter_pivottablejs,https://github.com/nicolaskruchten/jupyter_pivottablejs,,2015-09-09 13:39:18.000,2018-12-04 14:43:26.000000,2018-12-04 14:43:25,62.0,17.0,41.0,470,32.0,Dragndrop Pivot Tables and Charts for Jupyter/IPython..,3.0,19,2018-01-15 18:11:51,0.9.0,8.0,,pivottablejs,,,,['jupyter'],257.0,257.0,https://pypi.org/project/pivottablejs,14346.0,14346.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +634,joypy,True,sbebo/joypy,,data-viz,https://github.com/leotac/joypy,https://github.com/leotac/joypy,MIT,2017-07-30 17:18:50.000,2021-12-21 20:58:11.000000,2021-12-19 09:41:43,47.0,10.0,37.0,437,133.0,Joyplots in Python with matplotlib & pandas.,6.0,19,,,5.0,leotac/joypy,joypy,conda-forge/joypy,,,,186.0,186.0,https://pypi.org/project/joypy,13494.0,13870.0,https://anaconda.org/conda-forge/joypy,2020-12-28 14:07:53.760,15446.0,,,,,3.0,,,,,,,,,,,,,,,, +635,recmetrics,True,statisticianinstilettos/recmetrics,,recommender-systems,https://github.com/statisticianinstilettos/recmetrics,https://github.com/statisticianinstilettos/recmetrics,MIT,2018-10-15 15:29:49.000,2022-04-26 18:03:18.000000,2022-04-17 14:49:12,85.0,8.0,12.0,422,264.0,A library of metrics for evaluating recommender systems.,16.0,19,2022-04-26 18:03:18,0.1.5,1.0,,recmetrics,,,,,29.0,29.0,https://pypi.org/project/recmetrics,3276.0,3276.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +636,audioread,True,beetbox/audioread,,audio,https://github.com/beetbox/audioread,https://github.com/beetbox/audioread,MIT,2011-11-08 19:53:18.000,2022-08-14 17:30:18.405000,2022-08-12 21:06:37,94.0,31.0,49.0,409,,cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding..,22.0,19,,,6.0,,audioread,conda-forge/audioread,,,,,,https://pypi.org/project/audioread,1189691.0,1196282.0,https://anaconda.org/conda-forge/audioread,2022-08-14 17:30:18.405,481212.0,,,,,3.0,,-8.0,,,,,,,,,,,,,, +637,lazypredict,True,shankarpandala/lazypredict,,hyperopt,https://github.com/shankarpandala/lazypredict,https://github.com/shankarpandala/lazypredict,MIT,2019-11-16 09:56:35.000,2022-05-27 05:51:07.000000,2022-05-25 05:43:59,67.0,32.0,34.0,382,195.0,Lazy Predict help build a lot of basic models without much code..,17.0,19,,,,,lazypredict,,,,['sklearn'],322.0,322.0,https://pypi.org/project/lazypredict,5074.0,5074.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +638,SUOD,True,yzhao062/SUOD,,others,https://github.com/yzhao062/SUOD,https://github.com/yzhao062/SUOD,BSD-2-Clause,2019-11-20 00:23:54.000,2022-07-07 13:45:09.000000,2022-07-07 13:45:02,41.0,6.0,3.0,333,146.0,(MLSys' 21) An Acceleration System for Large-scare Unsupervised..,2.0,19,,,,,suod,,,,,434.0,434.0,https://pypi.org/project/suod,29484.0,29484.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +639,impyute,True,eltonlaw/impyute,,others,https://github.com/eltonlaw/impyute,https://github.com/eltonlaw/impyute,MIT,2017-01-21 09:16:27.000,2021-11-06 21:15:04.000000,2021-11-06 21:15:04,46.0,27.0,37.0,325,292.0,Data imputations library to preprocess datasets with missing data.,11.0,19,,,,,impyute,,,,,143.0,143.0,https://pypi.org/project/impyute,8168.0,8168.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +640,Sherpa,True,sherpa-ai/sherpa,,hyperopt,https://github.com/sherpa-ai/sherpa,https://github.com/sherpa-ai/sherpa,GPL-3.0,2018-05-16 21:41:54.000,2020-10-18 07:57:50.000000,2020-10-18 07:57:48,48.0,16.0,41.0,311,823.0,"Hyperparameter optimization that enables researchers to experiment,..",43.0,19,2020-07-31 05:29:09,1.0.7,4.0,,parameter-sherpa,,,,,23.0,23.0,https://pypi.org/project/parameter-sherpa,1147.0,1147.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +641,model-card-toolkit,True,tensorflow/model-card-toolkit,,interpretability,https://github.com/tensorflow/model-card-toolkit,https://github.com/tensorflow/model-card-toolkit,Apache-2.0,2020-07-24 16:48:58.000,2022-08-17 17:26:25.000000,2022-04-28 23:30:20,60.0,12.0,2.0,302,217.0,a tool that leverages rich metadata and lineage..,13.0,19,2022-02-24 21:00:01,1.3.0,6.0,,model-card-toolkit,,,,,10.0,10.0,https://pypi.org/project/model-card-toolkit,853.0,853.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +642,ivis,True,beringresearch/ivis,,data-viz,https://github.com/beringresearch/ivis,https://github.com/beringresearch/ivis,Apache-2.0,2018-08-13 08:31:01.000,2022-07-29 16:39:36.000000,2022-07-29 16:39:02,35.0,3.0,54.0,275,619.0,Dimensionality reduction in very large datasets using Siamese..,10.0,19,2022-03-10 14:58:28,2.07,33.0,,ivis,,,,['tensorflow'],26.0,26.0,https://pypi.org/project/ivis,330.0,330.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +643,fairness-indicators,True,tensorflow/fairness-indicators,,interpretability,https://github.com/tensorflow/fairness-indicators,https://github.com/tensorflow/fairness-indicators,Apache-2.0,2019-09-30 22:56:45.000,2022-08-23 13:51:40.000000,2022-07-26 20:55:28,68.0,3.0,8.0,272,300.0,Tensorflow's Fairness Evaluation and Visualization..,33.0,19,2022-07-20 07:04:00,0.40.0,19.0,,fairness-indicators,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/fairness-indicators,624.0,624.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +644,gokart,True,m3dev/gokart,,ml-experiments,https://github.com/m3dev/gokart,https://github.com/m3dev/gokart,MIT,2018-12-23 07:40:27.000,2022-08-03 06:46:44.000000,2022-08-02 20:35:09,45.0,14.0,59.0,261,484.0,A wrapper of the data pipeline library luigi.,34.0,19,2022-08-03 06:46:44,1.2.0,47.0,,gokart,,,,,,,https://pypi.org/project/gokart,1036.0,1036.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +645,datatest,True,shawnbrown/datatest,,data-loading,https://github.com/shawnbrown/datatest,https://github.com/shawnbrown/datatest,,2016-05-12 13:16:27.000,2021-12-05 17:44:33.000000,2021-12-05 17:44:33,13.0,12.0,43.0,260,2173.0,Tools for test driven data-wrangling and data validation.,7.0,19,2021-01-04 03:43:58,0.11.1,16.0,,datatest,,,,,74.0,74.0,https://pypi.org/project/datatest,8267.0,8267.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +646,fletcher,True,xhochy/fletcher,,data-containers,https://github.com/xhochy/fletcher,https://github.com/xhochy/fletcher,MIT,2018-03-04 16:44:22.000,2021-11-04 09:30:27.570000,2021-02-18 14:46:18,33.0,34.0,40.0,223,520.0,Pandas ExtensionDType/Array backed by Apache Arrow.,24.0,19,2021-01-17 20:04:41,0.7.2,14.0,,fletcher,conda-forge/fletcher,,,['pandas'],4.0,4.0,https://pypi.org/project/fletcher,617.0,1549.0,https://anaconda.org/conda-forge/fletcher,2021-11-04 09:30:27.570,45687.0,,,,,3.0,13.0,,,,,,,,,,,,,,, +647,Funsor,True,pyro-ppl/funsor,,probabilistics,https://github.com/pyro-ppl/funsor,https://github.com/pyro-ppl/funsor,Apache-2.0,2019-01-30 23:13:39.000,2022-05-05 21:21:02.000000,2022-04-08 17:51:44,17.0,67.0,75.0,196,568.0,Functional tensors for probabilistic programming.,10.0,19,2022-03-21 15:23:15,0.4.3,9.0,,funsor,,,,['pytorch'],32.0,32.0,https://pypi.org/project/funsor,1218.0,1218.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +648,BatchFlow,True,analysiscenter/batchflow,,data-pipelines,https://github.com/analysiscenter/batchflow,https://github.com/analysiscenter/batchflow,Apache-2.0,2017-03-13 14:22:53.000,2022-08-25 13:53:56.000000,2022-08-03 13:02:49,40.0,29.0,72.0,181,5166.0,BatchFlow helps you conveniently work with random or sequential..,32.0,19,2022-07-07 14:27:34,0.7.5,10.0,,batchflow,,,,,2.0,2.0,https://pypi.org/project/batchflow,135.0,135.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +649,gpt-2-simple,True,minimaxir/gpt-2-simple,,nlp,https://github.com/minimaxir/gpt-2-simple,https://github.com/minimaxir/gpt-2-simple,,2019-04-13 20:00:52.000,2022-05-22 02:02:04.000000,2022-05-22 02:02:04,597.0,153.0,96.0,3012,149.0,Python package to easily retrain OpenAI's GPT-2 text-..,21.0,18,2021-10-18 02:38:39,0.8.1,17.0,,gpt-2-simple,,,,['tensorflow'],,,https://pypi.org/project/gpt-2-simple,3815.0,3823.0,,,,,,,,3.0,343.0,,,,,,,,,,,,,,, +650,finmarketpy,True,cuemacro/finmarketpy,,financial-data,https://github.com/cuemacro/finmarketpy,https://github.com/cuemacro/finmarketpy,Apache-2.0,2015-02-19 23:32:03.000,2022-04-05 16:57:55.000000,2022-04-05 16:57:43,437.0,23.0,3.0,2956,679.0,Python library for backtesting trading strategies & analyzing..,14.0,18,2021-10-07 14:56:30,0.11.11,12.0,,finmarketpy,,,,,5.0,5.0,https://pypi.org/project/finmarketpy,103.0,103.0,,,,,,,,3.0,40.0,,,,,,,,,,,,,,, +651,Spotlight,True,maciejkula/spotlight,,recommender-systems,https://github.com/maciejkula/spotlight,https://github.com/maciejkula/spotlight,MIT,2017-06-25 18:52:19.000,2022-07-18 20:48:20.000000,2020-02-09 21:03:48,401.0,62.0,48.0,2771,299.0,Deep recommender models using PyTorch.,11.0,18,2019-09-08 10:19:53,0.1.6,7.0,,,maciejkula/spotlight,,,['pytorch'],,,,,122.0,https://anaconda.org/maciejkula/spotlight,2018-05-27 18:32:12.235,7602.0,,,,,3.0,,,,,,,,,,,,,,,, +652,ipyparallel,True,ipython/ipyparallel,,distributed-ml,https://github.com/ipython/ipyparallel,https://github.com/ipython/ipyparallel,,2015-04-09 07:43:55.000,2022-08-22 22:30:27.000000,2022-08-16 11:53:24,871.0,53.0,279.0,2254,,Interactive Parallel Computing in Python.,111.0,18,,,24.0,,ipyparallel,conda-forge/ipyparallel,,,['jupyter'],,,https://pypi.org/project/ipyparallel,115677.0,124430.0,https://anaconda.org/conda-forge/ipyparallel,2022-06-21 14:24:53.709,665234.0,,,,,3.0,,,,,,,,,,,,,,,, +653,Coach,True,IntelLabs/coach,,reinforcement-learning,https://github.com/IntelLabs/coach,https://github.com/IntelLabs/coach,Apache-2.0,2017-10-01 19:27:43.000,2021-12-27 09:52:12.000000,2021-06-28 07:40:53,428.0,81.0,183.0,2176,521.0,Reinforcement Learning Coach by Intel AI Lab enables easy..,35.0,18,2019-07-24 13:14:28,1.0.0,9.0,,rl_coach,,,,,,,https://pypi.org/project/rl_coach,117.0,117.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +654,textacy,True,chartbeat-labs/textacy,,nlp,https://github.com/chartbeat-labs/textacy,https://github.com/chartbeat-labs/textacy,,2016-02-03 16:52:45.000,2022-07-25 01:15:10.000000,2022-03-06 19:51:43,233.0,29.0,224.0,1965,,"NLP, before and after spaCy.",32.0,18,2021-12-06 14:59:26,0.12.0,28.0,,textacy,conda-forge/textacy,,,,,,https://pypi.org/project/textacy,38229.0,40017.0,https://anaconda.org/conda-forge/textacy,2022-02-06 16:50:51.205,112684.0,,,,,3.0,,,,,,,,,,,,,,,, +655,DLTK,True,DLTK/DLTK,,medical-data,https://github.com/DLTK/DLTK,https://github.com/DLTK/DLTK,Apache-2.0,2017-05-02 15:40:36.000,2022-06-21 21:11:42.000000,2019-01-21 14:01:28,391.0,7.0,24.0,1321,379.0,Deep Learning Toolkit for Medical Image Analysis.,9.0,18,,,,,dltk,,,,['tensorflow'],23.0,23.0,https://pypi.org/project/dltk,100.0,100.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +656,doc2text,True,jlsutherland/doc2text,,ocr,https://github.com/jlsutherland/doc2text,https://github.com/jlsutherland/doc2text,MIT,2016-08-28 19:30:02.000,2020-12-01 22:56:27.000000,2020-12-01 22:56:26,95.0,12.0,9.0,1256,62.0,Detect text blocks and OCR poorly scanned PDFs in bulk. Python module..,5.0,18,,,,,doc2text,,,,,60.0,60.0,https://pypi.org/project/doc2text,1831.0,1831.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +657,tensorrec,True,jfkirk/tensorrec,,recommender-systems,https://github.com/jfkirk/tensorrec,https://github.com/jfkirk/tensorrec,Apache-2.0,2017-02-28 18:51:11.000,2022-03-11 23:26:22.000000,2020-02-04 21:10:25,223.0,36.0,90.0,1200,334.0,A TensorFlow recommendation algorithm and framework in..,9.0,18,,,,,tensorrec,,,,['tensorflow'],27.0,27.0,https://pypi.org/project/tensorrec,468.0,468.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +658,CrypTen,True,facebookresearch/CrypTen,,privacy-ml,https://github.com/facebookresearch/CrypTen,https://github.com/facebookresearch/CrypTen,MIT,2019-08-15 00:00:31.000,2022-08-26 00:15:50.000000,2022-06-10 23:04:56,179.0,20.0,136.0,1114,,A framework for Privacy Preserving Machine Learning.,29.0,18,2020-04-21 13:59:37,0.1,1.0,,crypten,,,,['pytorch'],21.0,21.0,https://pypi.org/project/crypten,231.0,231.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +659,advertorch,True,BorealisAI/advertorch,,adversarial,https://github.com/BorealisAI/advertorch,https://github.com/BorealisAI/advertorch,GPL-3.0,2018-11-29 22:17:33.000,2022-05-29 19:09:18.000000,2022-05-29 19:09:18,168.0,18.0,34.0,1085,309.0,A Toolbox for Adversarial Robustness Research.,21.0,18,,,,,advertorch,,,,['pytorch'],85.0,85.0,https://pypi.org/project/advertorch,342.0,342.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +660,keras-ocr,True,faustomorales/keras-ocr,,ocr,https://github.com/faustomorales/keras-ocr,https://github.com/faustomorales/keras-ocr,MIT,2019-09-20 23:08:50.000,2022-05-19 13:11:19.000000,2022-05-19 13:10:12,272.0,69.0,108.0,1075,200.0,A packaged and flexible version of the CRAFT text detector and..,15.0,18,2020-09-13 21:05:45,0.8.4,1.0,,keras-ocr,,,,['tensorflow'],,,https://pypi.org/project/keras-ocr,5797.0,18678.0,,,,,,,,3.0,296263.0,,,,,,,,,,,,,,, +661,iNNvestigate,True,albermax/innvestigate,,interpretability,https://github.com/albermax/innvestigate,https://github.com/albermax/innvestigate,BSD-2-Clause,2017-12-13 18:11:20.000,2022-08-01 16:01:28.000000,2022-08-01 16:00:28,222.0,46.0,187.0,1018,1068.0,A toolbox to iNNvestigate neural networks' predictions!.,19.0,18,2022-08-01 16:11:33,2.0.0,1.0,,innvestigate,,,,['tensorflow'],,,https://pypi.org/project/innvestigate,444.0,460.0,,,,,,,,3.0,16.0,,,,,,,,,,,,,,, +662,Bounter,True,RaRe-Technologies/bounter,,data-containers,https://github.com/RaRe-Technologies/bounter,https://github.com/RaRe-Technologies/bounter,MIT,2017-07-18 07:24:15.000,2021-09-19 00:43:46.000000,2021-05-24 07:29:54,44.0,16.0,9.0,939,156.0,Efficient Counter that uses a limited (bounded) amount of memory..,8.0,18,2022-02-18 13:23:55,1.1.1,4.0,,bounter,,,,,26.0,26.0,https://pypi.org/project/bounter,173.0,173.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +663,Vulkan Kompute,True,EthicalML/vulkan-kompute,,gpu-utilities,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000,2022-08-01 07:14:34.000000,2022-06-21 07:15:10,64.0,59.0,120.0,920,1030.0,General purpose GPU compute framework for cross vendor..,19.0,18,2022-04-13 10:24:33,0.8.1,13.0,KomputeProject/kompute,kp,,,,,4.0,4.0,https://pypi.org/project/kp,87.0,94.0,,,,,,,,3.0,169.0,,,,,,,,,,,,,,, +664,ADTK,True,arundo/adtk,,time-series-data,https://github.com/arundo/adtk,https://github.com/arundo/adtk,MPL-2.0,2019-09-27 00:34:22.000,2021-07-18 06:52:12.000000,2020-04-17 02:27:44,105.0,31.0,36.0,850,78.0,A Python toolkit for rule-based/unsupervised anomaly detection in time..,11.0,18,2020-04-17 02:17:35,0.6.2,12.0,,adtk,,,,,,,https://pypi.org/project/adtk,280489.0,280489.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +665,pytorch2keras,True,nerox8664/pytorch2keras,,model-serialisation,https://github.com/gmalivenko/pytorch2keras,https://github.com/gmalivenko/pytorch2keras,MIT,2017-11-16 20:21:43.000,2022-06-11 07:21:47.000000,2021-08-06 08:18:46,136.0,54.0,68.0,811,282.0,PyTorch to Keras model convertor.,13.0,18,,,1.0,gmalivenko/pytorch2keras,pytorch2keras,,,,,51.0,51.0,https://pypi.org/project/pytorch2keras,478.0,478.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +666,Pandas-Bokeh,True,PatrikHlobil/Pandas-Bokeh,,data-viz,https://github.com/PatrikHlobil/Pandas-Bokeh,https://github.com/PatrikHlobil/Pandas-Bokeh,MIT,2018-11-23 20:49:14.000,2022-03-25 13:49:39.000000,2022-03-25 13:48:28,100.0,31.0,67.0,795,300.0,Bokeh Plotting Backend for Pandas and GeoPandas.,14.0,18,2021-04-11 17:42:31,0.5.5,5.0,,pandas-bokeh,,,,['pandas'],,,https://pypi.org/project/pandas-bokeh,14360.0,14360.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +667,gmaps,True,pbugnion/gmaps,,geospatial-data,https://github.com/pbugnion/gmaps,https://github.com/pbugnion/gmaps,BSD-3-Clause,2014-12-01 09:12:06.000,2022-04-15 13:31:22.000000,2019-07-22 06:22:45,145.0,67.0,137.0,744,1380.0,Google maps for Jupyter notebooks.,16.0,18,2016-01-02 19:06:03,0.2,20.0,,gmaps,conda-forge/gmaps,,,['jupyter'],1.0,1.0,https://pypi.org/project/gmaps,8966.0,15044.0,https://anaconda.org/conda-forge/gmaps,2019-08-02 11:56:50.940,270834.0,,,,,3.0,,,jupyter-gmaps,https://www.npmjs.com/package/jupyter-gmaps,1780.0,,,,,,,,,,, +668,SMAC3,True,automl/SMAC3,,hyperopt,https://github.com/automl/SMAC3,https://github.com/automl/SMAC3,,2016-08-17 10:58:05.000,2022-08-25 15:04:46.000000,2022-07-14 08:00:56,174.0,75.0,320.0,728,,Sequential Model-based Algorithm Configuration.,38.0,18,2022-07-14 08:05:24,1.4.0,36.0,,smac,,,,,,,https://pypi.org/project/smac,50297.0,50297.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +669,Test Tube,True,williamFalcon/test-tube,,hyperopt,https://github.com/williamFalcon/test-tube,https://github.com/williamFalcon/test-tube,MIT,2017-09-06 02:14:57.000,2022-07-22 06:10:37.000000,2020-03-17 22:44:47,67.0,23.0,21.0,721,642.0,Python library to easily log experiments and parallelize..,16.0,18,2019-06-29 19:21:43,0.64,3.0,,test_tube,,,,,,,https://pypi.org/project/test_tube,50649.0,50649.0,,,,,,,,3.0,12.0,,,,,,,,,,,,,,, +670,sklearn-deap,True,rsteca/sklearn-deap,,hyperopt,https://github.com/rsteca/sklearn-deap,https://github.com/rsteca/sklearn-deap,MIT,2015-10-28 22:52:34.000,2021-07-30 15:07:28.000000,2021-07-30 15:06:27,116.0,16.0,34.0,703,104.0,Use evolutionary algorithms instead of gridsearch in..,22.0,18,2021-07-30 15:07:28,0.3.0,14.0,,sklearn-deap,,,,['sklearn'],35.0,35.0,https://pypi.org/project/sklearn-deap,673.0,673.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +671,Submit it,True,facebookincubator/submitit,,distributed-ml,https://github.com/facebookincubator/submitit,https://github.com/facebookincubator/submitit,MIT,2020-04-24 07:41:09.000,2022-08-23 15:21:37.000000,2022-08-23 15:21:37,74.0,23.0,48.0,682,,Python 3.6+ toolbox for submitting jobs to Slurm.,23.0,18,2021-02-01 10:18:48,1.2.0,6.0,,submitit,conda-forge/submitit,,,,,,https://pypi.org/project/submitit,36701.0,37039.0,https://anaconda.org/conda-forge/submitit,2021-02-10 12:48:57.745,8115.0,,,,,3.0,,,,,,,,,,,,,,,, +672,Dragonfly,True,dragonfly/dragonfly,,hyperopt,https://github.com/dragonfly/dragonfly,https://github.com/dragonfly/dragonfly,MIT,2018-04-20 22:19:50.000,2022-07-14 06:00:29.000000,2022-07-14 06:00:28,206.0,36.0,20.0,672,399.0,An open source python library for scalable Bayesian optimisation.,13.0,18,,,,,dragonfly-opt,,,,,,,https://pypi.org/project/dragonfly-opt,35162.0,35162.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +673,finetune,True,IndicoDataSolutions/finetune,,nlp,https://github.com/IndicoDataSolutions/finetune,https://github.com/IndicoDataSolutions/finetune,MPL-2.0,2018-06-12 17:02:16.000,2022-08-15 23:06:49.000000,2022-06-16 10:06:33,71.0,22.0,117.0,658,1201.0,Scikit-learn style model finetuning for NLP.,19.0,18,2019-01-18 20:10:51,0.5.14,14.0,,finetune,,,,"['tensorflow', 'sklearn']",9.0,9.0,https://pypi.org/project/finetune,96.0,96.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +674,Caer,True,jasmcaus/caer,,image,https://github.com/jasmcaus/caer,https://github.com/jasmcaus/caer,MIT,2020-08-06 18:36:14.000,2021-10-13 21:04:50.000000,2021-10-13 21:05:33,74.0,2.0,13.0,630,5078.0,"A lightweight Computer Vision library. Scale your models, not boilerplate.",8.0,18,2021-10-06 07:29:20,2.0.3,13.0,,caer,,,https://caer.rtfd.io,,,,https://pypi.org/project/caer,2978.0,2978.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,, +675,Baal,True,ElementAI/baal,,probabilistics,https://github.com/baal-org/baal,https://github.com/baal-org/baal,Apache-2.0,2019-09-30 20:16:26.000,2022-08-25 17:58:45.000000,2022-08-22 14:00:27,60.0,23.0,61.0,626,180.0,Using approximate bayesian posteriors in deep nets for active learning.,16.0,18,2022-05-03 12:50:35,1.6.0,10.0,baal-org/baal,baal,,,,,,,https://pypi.org/project/baal,743.0,743.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +676,N2,True,kakao/n2,,nn-search,https://github.com/kakao/n2,https://github.com/kakao/n2,Apache-2.0,2017-11-23 02:27:59.000,2021-05-20 05:41:36.000000,2021-05-20 05:39:44,64.0,11.0,22.0,522,242.0,TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast..,18.0,18,2020-10-16 03:43:47,0.1.7,4.0,,n2,,,,,23.0,23.0,https://pypi.org/project/n2,860.0,860.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +677,pydlm,True,wwrechard/pydlm,,time-series-data,https://github.com/wwrechard/pydlm,https://github.com/wwrechard/pydlm,BSD-3-Clause,2016-06-29 07:58:53.000,2021-02-24 14:21:28.000000,2019-10-22 07:18:40,91.0,35.0,8.0,425,362.0,A python library for Bayesian time series modeling.,6.0,18,,,,,pydlm,,,,,27.0,27.0,https://pypi.org/project/pydlm,27399.0,27399.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +678,elegy,True,poets-ai/elegy,,ml-frameworks,https://github.com/poets-ai/elegy,https://github.com/poets-ai/elegy,MIT,2020-06-30 14:00:37.000,2022-07-20 05:28:42.000000,2022-05-23 17:26:29,26.0,34.0,66.0,404,339.0,Elegy is a framework-agnostic Trainer interface for the Jax..,17.0,18,2022-03-23 21:47:54,0.8.6,21.0,,elegy,,,,"['tensorflow', 'jax']",,,https://pypi.org/project/elegy,1042.0,1042.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +679,tick,True,X-DataInitiative/tick,,time-series-data,https://github.com/X-DataInitiative/tick,https://github.com/X-DataInitiative/tick,BSD-3-Clause,2016-12-01 10:59:08.000,2022-01-30 17:29:29.000000,2020-06-15 12:01:36,84.0,57.0,167.0,397,413.0,"Module for statistical learning, with a particular emphasis on time-..",16.0,18,2019-09-11 11:25:15,0.6,5.0,,tick,,,,,66.0,66.0,https://pypi.org/project/tick,976.0,979.0,,,,,,,,3.0,198.0,,,,,,,,,,,,,,, +680,animatplot,True,t-makaro/animatplot,,data-viz,https://github.com/t-makaro/animatplot,https://github.com/t-makaro/animatplot,MIT,2017-04-03 00:54:04.000,2021-04-07 10:46:25.000000,2020-10-05 06:14:18,34.0,13.0,17.0,395,178.0,A python package for animating plots build on matplotlib.,7.0,18,2019-03-05 21:32:47,0.4.1,7.0,,animatplot,conda-forge/animatplot,,,,35.0,35.0,https://pypi.org/project/animatplot,259.0,472.0,https://anaconda.org/conda-forge/animatplot,2020-10-06 02:02:00.460,8958.0,,,,,3.0,,,,,,,,,,,,,,,, +681,Studio.ml,True,studioml/studio,,ml-experiments,https://github.com/studioml/studio,https://github.com/studioml/studio,Apache-2.0,2017-05-15 01:49:28.000,2021-09-14 22:54:36.000000,2021-09-14 22:26:21,51.0,57.0,195.0,376,2409.0,Studio: Simplify and expedite model building process.,21.0,18,2020-02-19 22:50:45,0.0.15,4.0,,studioml,,,,,5.0,5.0,https://pypi.org/project/studioml,35.0,35.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +682,vega,True,vega/ipyvega,,data-viz,https://github.com/vega/ipyvega,https://github.com/vega/ipyvega,BSD-3-Clause,2015-08-04 03:22:47.000,2022-08-01 02:43:25.000000,2022-08-01 02:43:25,55.0,13.0,82.0,332,593.0,IPython/Jupyter notebook module for Vega and Vega-Lite.,11.0,18,,,27.0,,vega,conda-forge/vega,,,['jupyter'],,,https://pypi.org/project/vega,7282.0,14033.0,https://anaconda.org/conda-forge/vega,2022-02-10 13:26:24.004,499616.0,,,,,3.0,,,,,,,,,,,,,,,, +683,MXBoard,True,awslabs/mxboard,,ml-experiments,https://github.com/awslabs/mxboard,https://github.com/awslabs/mxboard,Apache-2.0,2018-02-06 23:03:51.000,2021-11-30 10:46:24.000000,2020-01-24 23:21:55,46.0,16.0,15.0,328,42.0,Logging MXNet data for visualization in TensorBoard.,9.0,18,2018-05-22 20:20:50,0.1.0,1.0,,mxboard,,,,['mxnet'],157.0,157.0,https://pypi.org/project/mxboard,7680.0,7680.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +684,NIPY,True,nipy/nipy,,medical-data,https://github.com/nipy/nipy,https://github.com/nipy/nipy,BSD-3-Clause,2010-05-02 10:00:33.000,2021-12-05 02:53:17.000000,2021-03-29 16:56:48,126.0,40.0,111.0,323,6427.0,Neuroimaging in Python FMRI analysis package.,63.0,18,,,2.0,,nipy,conda-forge/nipy,,,,,,https://pypi.org/project/nipy,1510.0,3065.0,https://anaconda.org/conda-forge/nipy,2020-05-04 19:38:04.112,94909.0,,,,,3.0,,,,,,,,,,,,,,,, +685,sk-dist,True,Ibotta/sk-dist,,distributed-ml,https://github.com/Ibotta/sk-dist,https://github.com/Ibotta/sk-dist,Apache-2.0,2019-08-14 21:07:17.000,2021-07-07 00:44:10.000000,2021-07-07 00:44:07,49.0,7.0,10.0,282,58.0,Distributed scikit-learn meta-estimators in PySpark.,7.0,18,,,,,sk-dist,,,,"['sklearn', 'spark']",10.0,10.0,https://pypi.org/project/sk-dist,170811.0,170811.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +686,Brainiak,True,brainiak/brainiak,,medical-data,https://github.com/brainiak/brainiak,https://github.com/brainiak/brainiak,Apache-2.0,2016-02-08 23:19:27.000,2022-08-10 20:44:02.000000,2021-05-28 01:21:58,126.0,74.0,124.0,281,393.0,Brain Imaging Analysis Kit.,34.0,18,,,,,brainiak,,brainiak/brainiak,,,16.0,16.0,https://pypi.org/project/brainiak,175.0,184.0,,,,https://hub.docker.com/r/brainiak/brainiak,2020-10-15 21:11:03.379549,1.0,762.0,3.0,,,,,,,,,,,,,,,, +687,pymap3d,True,geospace-code/pymap3d,,geospatial-data,https://github.com/geospace-code/pymap3d,https://github.com/geospace-code/pymap3d,BSD-2-Clause,2014-08-03 04:28:03.000,2022-08-02 20:47:15.000000,2022-07-03 21:12:17,68.0,1.0,37.0,270,,pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef..,11.0,18,2022-07-03 21:21:01,2.9.1,54.0,,pymap3d,conda-forge/pymap3d,,,,,,https://pypi.org/project/pymap3d,50394.0,51405.0,https://anaconda.org/conda-forge/pymap3d,2022-07-04 06:23:12.422,29324.0,,,,,3.0,,,,,,,,,,,,,,,, +688,skift,True,shaypal5/skift,,nlp,https://github.com/shaypal5/skift,https://github.com/shaypal5/skift,MIT,2018-02-03 11:37:21.000,2022-06-07 15:07:07.000000,2022-06-07 15:07:04,23.0,1.0,10.0,234,141.0,scikit-learn wrappers for Python fastText.,9.0,18,2022-02-14 13:45:54,0.0.23,3.0,,skift,,,,['sklearn'],12.0,12.0,https://pypi.org/project/skift,1055.0,1055.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +689,PyStan,True,stan-dev/pystan,,probabilistics,https://github.com/stan-dev/pystan,https://github.com/stan-dev/pystan,ISC,2017-03-06 19:56:42.094,2022-08-16 10:48:36.000000,2022-07-07 17:37:23,39.0,4.0,171.0,203,,"PyStan, a Python interface to Stan, a platform for statistical modeling...",10.0,18,,,10.0,,pystan,conda-forge/pystan,,,,,,https://pypi.org/project/pystan,2844257.0,2868860.0,https://anaconda.org/conda-forge/pystan,2022-07-25 04:58:28.171,1599226.0,,,,,3.0,,,,,,,,,,,,,,,, +690,DE⫶TR,True,facebookresearch/detr,,image,https://github.com/facebookresearch/detr,https://github.com/facebookresearch/detr,Apache-2.0,2020-05-26 23:54:52.000,2022-08-12 03:57:58.000000,2022-03-07 12:59:53,1653.0,170.0,274.0,9594,42.0,End-to-End Object Detection with Transformers.,25.0,17,2020-06-29 16:41:01,0.2,1.0,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +691,tinygrad,True,geohot/tinygrad,,pytorch-utils,https://github.com/geohot/tinygrad,https://github.com/geohot/tinygrad,MIT,2020-10-18 16:23:12.000,2022-08-25 04:50:31.000000,2022-08-23 00:13:08,646.0,15.0,92.0,6531,1050.0,You like pytorch? You like micrograd? You love tinygrad!.,62.0,17,,,,,,,,,['pytorch'],3.0,3.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +692,DALI,True,NVIDIA/DALI,,gpu-utilities,https://github.com/NVIDIA/DALI,https://github.com/NVIDIA/DALI,Apache-2.0,2018-06-01 22:18:01.000,2022-08-25 20:28:51.000000,2022-08-25 20:28:51,505.0,186.0,1041.0,3998,,A GPU-accelerated library containing highly optimized building blocks..,77.0,17,2022-07-25 12:38:50,1.16.0,55.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +693,ReAgent,True,facebookresearch/ReAgent,,reinforcement-learning,https://github.com/facebookresearch/ReAgent,https://github.com/facebookresearch/ReAgent,BSD-3-Clause,2017-07-27 17:53:21.000,2022-08-25 22:14:36.000000,2022-08-25 22:12:06,460.0,26.0,75.0,3237,1339.0,"A platform for Reasoning systems (Reinforcement Learning,..",140.0,17,,,,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +694,Backtesting.py,True,kernc/backtesting.py,,financial-data,https://github.com/kernc/backtesting.py,https://github.com/kernc/backtesting.py,AGPL-3.0,2019-01-02 03:11:32.000,2022-08-17 21:12:58.000000,2022-03-27 23:39:16,546.0,58.0,270.0,2752,252.0,Backtest trading strategies in Python.,15.0,17,,,,,backtesting,,,,,,,https://pypi.org/project/backtesting,7396.0,7396.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +695,spark-deep-learning,True,databricks/spark-deep-learning,,data-pipelines,https://github.com/databricks/spark-deep-learning,https://github.com/databricks/spark-deep-learning,Apache-2.0,2017-05-31 17:30:28.000,2022-03-21 17:15:55.000000,2022-03-21 17:12:16,463.0,78.0,27.0,1940,138.0,Deep Learning Pipelines for Apache Spark.,17.0,17,2020-01-08 19:50:31,1.6.0,9.0,,,,,,['spark'],24.0,24.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +696,Mara Pipelines,True,mara/mara-pipelines,,data-pipelines,https://github.com/mara/mara-pipelines,https://github.com/mara/mara-pipelines,MIT,2018-03-31 20:37:22.000,2022-07-18 06:41:40.000000,2022-07-18 05:57:57,89.0,16.0,14.0,1935,142.0,"A lightweight opinionated ETL framework, halfway between plain..",17.0,17,2020-07-31 19:31:29,3.1.1,7.0,,mara-pipelines,,,,,,,https://pypi.org/project/mara-pipelines,356.0,356.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +697,Pillow-SIMD,True,uploadcare/pillow-simd,,image,https://github.com/uploadcare/pillow-simd,https://github.com/uploadcare/pillow-simd,PIL,2014-11-12 15:33:02.000,2022-08-25 12:14:23.000000,2022-01-17 10:12:52,74.0,11.0,66.0,1855,,The friendly PIL fork.,384.0,17,,,,,pillow-simd,,,,,,,https://pypi.org/project/pillow-simd,50926.0,50926.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +698,Skater,True,oracle/Skater,,interpretability,https://github.com/oracle/Skater,https://github.com/oracle/Skater,UPL-1.0,2017-01-26 05:45:42.000,2022-08-09 20:28:48.000000,2022-02-11 18:01:55,168.0,67.0,97.0,1030,,Python Library for Model Interpretation/Explanations.,36.0,17,2018-09-21 06:46:11,1.1.2,15.0,,skater,conda-forge/skater,,,,,,https://pypi.org/project/skater,3004.0,3822.0,https://anaconda.org/conda-forge/skater,2021-11-15 19:51:51.883,50758.0,,,,,3.0,,,,,,,,,,,,,,,, +699,Singer,True,singer-io/getting-started,,data-loading,https://github.com/singer-io/getting-started,https://github.com/singer-io/getting-started,AGPL-3.0,2016-10-31 16:53:56.000,2022-03-16 19:49:58.000000,2021-04-29 14:20:17,136.0,20.0,18.0,1020,188.0,"Standard for moving data between databases, web APIs, files, queues, and just about anything else you can think of.",26.0,17,,,,,singer-python,,,,,,,https://pypi.org/project/singer-python,272605.0,272605.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +700,AstroML,True,astroML/astroML,,others,https://github.com/astroML/astroML,https://github.com/astroML/astroML,BSD-2-Clause,2012-10-17 22:33:50.000,2022-08-17 06:28:19.000000,2022-08-17 06:28:18,270.0,56.0,92.0,843,,"Machine learning, statistics, and data mining for astronomy and..",30.0,17,,,6.0,,astroML,conda-forge/astroml,,,['sklearn'],,,https://pypi.org/project/astroML,1255.0,1779.0,https://anaconda.org/conda-forge/astroml,2022-03-02 04:14:21.434,31466.0,,,,,3.0,,,,,,,,,,,,,,,, +701,Saliency,True,PAIR-code/saliency,,tensorflow-utils,https://github.com/PAIR-code/saliency,https://github.com/PAIR-code/saliency,Apache-2.0,2017-06-09 22:07:35.000,2022-05-13 18:48:13.000000,2022-05-13 18:48:12,168.0,,26.0,813,83.0,Framework-agnostic implementation for state-of-the-art saliency..,15.0,17,,,,,saliency,,,,['tensorflow'],41.0,41.0,https://pypi.org/project/saliency,1281.0,1281.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +702,AlphaPy,True,ScottfreeLLC/AlphaPy,,hyperopt,https://github.com/ScottfreeLLC/AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,Apache-2.0,2016-02-14 00:47:32.000,2022-05-12 09:12:38.000000,2022-04-23 13:47:59,161.0,12.0,29.0,798,417.0,"Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,..",3.0,17,2020-08-29 18:48:20,2.5.0,11.0,,alphapy,,,,,3.0,3.0,https://pypi.org/project/alphapy,59.0,59.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +703,tffm,True,geffy/tffm,,tensorflow-utils,https://github.com/geffy/tffm,https://github.com/geffy/tffm,MIT,2016-05-02 17:06:07.000,2022-01-17 20:39:04.000000,2022-01-17 20:38:58,177.0,18.0,22.0,783,107.0,TensorFlow implementation of an arbitrary order Factorization Machine.,10.0,17,,,,,tffm,,,,['tensorflow'],11.0,11.0,https://pypi.org/project/tffm,1508.0,1508.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +704,robustness,True,MadryLab/robustness,,adversarial,https://github.com/MadryLab/robustness,https://github.com/MadryLab/robustness,MIT,2019-08-21 09:26:33.000,2022-04-20 20:42:41.000000,2022-02-14 20:43:06,143.0,19.0,56.0,722,145.0,"A library for experimenting with, training and evaluating neural..",13.0,17,2020-12-01 06:11:12,1.2.1.post2,7.0,,robustness,,,,,81.0,81.0,https://pypi.org/project/robustness,641.0,641.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +705,matrixprofile-ts,True,target/matrixprofile-ts,,time-series-data,https://github.com/target/matrixprofile-ts,https://github.com/target/matrixprofile-ts,Apache-2.0,2018-09-10 19:03:34.000,2022-06-21 21:35:50.000000,2020-04-25 18:37:42,97.0,19.0,34.0,686,198.0,A Python library for detecting patterns and anomalies..,15.0,17,,,,,matrixprofile-ts,,,,,19.0,19.0,https://pypi.org/project/matrixprofile-ts,519.0,519.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +706,FlashTorch,True,MisaOgura/flashtorch,,interpretability,https://github.com/MisaOgura/flashtorch,https://github.com/MisaOgura/flashtorch,MIT,2019-03-22 13:00:57.000,2022-06-20 04:19:57.000000,2021-04-27 11:10:20,84.0,9.0,22.0,683,127.0,Visualization toolkit for neural networks in PyTorch! Demo --.,2.0,17,2020-05-29 14:39:38,0.1.3,5.0,,flashtorch,,,,['pytorch'],10.0,10.0,https://pypi.org/project/flashtorch,159.0,159.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +707,Tensor Sensor,True,parrt/tensor-sensor,,pytorch-utils,https://github.com/parrt/tensor-sensor,https://github.com/parrt/tensor-sensor,MIT,2020-08-28 22:54:04.000,2022-04-07 20:52:55.000000,2022-04-07 20:49:56,34.0,8.0,15.0,649,235.0,The goal of this library is to generate more helpful..,4.0,17,2021-12-11 21:24:11,1.0,15.0,,tensor-sensor,,,,['pytorch'],7.0,7.0,https://pypi.org/project/tensor-sensor,1789.0,1789.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +708,ThunderGBM,True,Xtra-Computing/thundergbm,,ml-frameworks,https://github.com/Xtra-Computing/thundergbm,https://github.com/Xtra-Computing/thundergbm,Apache-2.0,2016-11-11 09:58:08.000,2022-08-09 02:39:04.000000,2022-08-09 02:35:41,82.0,37.0,37.0,637,607.0,ThunderGBM: Fast GBDTs and Random Forests on GPUs.,10.0,17,2019-05-07 08:47:56,0.3.2,3.0,,thundergbm,,,,,,,https://pypi.org/project/thundergbm,239.0,239.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +709,tcav,True,tensorflow/tcav,,interpretability,https://github.com/tensorflow/tcav,https://github.com/tensorflow/tcav,Apache-2.0,2018-07-03 17:45:35.000,2022-06-21 23:29:45.000000,2021-09-16 17:56:31,131.0,7.0,54.0,534,171.0,Code for the TCAV ML interpretability project.,19.0,17,2018-11-21 15:34:40,0.2,2.0,,tcav,,,,['tensorflow'],14.0,14.0,https://pypi.org/project/tcav,48.0,48.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +710,seglearn,True,dmbee/seglearn,,time-series-data,https://github.com/dmbee/seglearn,https://github.com/dmbee/seglearn,BSD-3-Clause,2018-03-05 20:53:59.000,2022-06-16 18:12:39.000000,2022-06-16 18:12:39,61.0,6.0,23.0,522,270.0,Python module for machine learning time series:.,14.0,17,,,,,seglearn,,,,,11.0,11.0,https://pypi.org/project/seglearn,967.0,967.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +711,kglib,True,graknlabs/kglib,,graph,https://github.com/vaticle/typedb-ml,https://github.com/vaticle/typedb-ml,Apache-2.0,2018-09-16 16:46:48.000,2022-08-01 10:00:41.000000,2022-08-01 10:00:40,88.0,10.0,50.0,522,501.0,Grakn Knowledge Graph Library (ML R&D).,9.0,17,2022-07-29 11:37:34,0.3.0,8.0,vaticle/typedb-ml,grakn-kglib,,,,,,,https://pypi.org/project/grakn-kglib,26.0,30.0,,,,,,,,3.0,211.0,,,,,,,,,,,,,,, +712,Auto Tune Models,True,HDI-Project/ATM,,hyperopt,https://github.com/HDI-Project/ATM,https://github.com/HDI-Project/ATM,MIT,2016-10-14 18:03:00.000,2020-02-21 17:44:07.000000,2020-02-21 17:40:58,131.0,18.0,71.0,521,775.0,"Auto Tune Models - A multi-tenant, multi-data system for..",16.0,17,2019-07-30 09:28:26,0.2.2,6.0,,atm,,,,,12.0,12.0,https://pypi.org/project/atm,67.0,67.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +713,pyhsmm,True,mattjj/pyhsmm,,probabilistics,https://github.com/mattjj/pyhsmm,https://github.com/mattjj/pyhsmm,MIT,2012-03-18 17:40:13.000,2022-04-10 20:18:08.000000,2020-08-24 17:03:59,161.0,36.0,60.0,517,1426.0,Bayesian inference in HSMMs and HMMs.,13.0,17,,,,,pyhsmm,,,,,25.0,25.0,https://pypi.org/project/pyhsmm,85.0,85.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +714,Auto TS,True,AutoViML/Auto_TS,,time-series-data,https://github.com/AutoViML/Auto_TS,https://github.com/AutoViML/Auto_TS,Apache-2.0,2020-02-15 15:23:32.000,2022-08-16 12:42:19.000000,2022-08-16 12:41:57,86.0,6.0,69.0,471,256.0,"Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost..",6.0,17,,,2.0,,auto-ts,,,,,,,https://pypi.org/project/auto-ts,4380.0,4380.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +715,DeepMatcher,True,anhaidgroup/deepmatcher,,nlp,https://github.com/anhaidgroup/deepmatcher,https://github.com/anhaidgroup/deepmatcher,BSD-3-Clause,2017-12-01 19:01:11.000,2021-06-13 01:13:43.000000,2021-06-13 00:22:13,98.0,62.0,24.0,439,176.0,Python package for performing Entity and Text Matching using..,7.0,17,,,,,deepmatcher,,,,,21.0,21.0,https://pypi.org/project/deepmatcher,1136.0,1136.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +716,Case Recommender,True,caserec/CaseRecommender,,recommender-systems,https://github.com/caserec/CaseRecommender,https://github.com/caserec/CaseRecommender,MIT,2015-11-12 18:25:39.000,2021-11-25 23:08:48.000000,2021-11-25 23:08:43,79.0,5.0,20.0,417,204.0,Case Recommender: A Flexible and Extensible Python..,11.0,17,2021-11-25 23:10:34,1.1.1,2.0,,caserecommender,,,,['sklearn'],10.0,10.0,https://pypi.org/project/caserecommender,128.0,128.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +717,DESlib,True,scikit-learn-contrib/DESlib,,sklearn-utils,https://github.com/scikit-learn-contrib/DESlib,https://github.com/scikit-learn-contrib/DESlib,BSD-3-Clause,2017-12-08 22:49:49.000,2022-06-07 04:47:17.000000,2022-06-07 04:47:12,63.0,15.0,131.0,416,275.0,A Python library for dynamic classifier and ensemble selection.,14.0,17,,,,,deslib,,,,['sklearn'],29.0,29.0,https://pypi.org/project/deslib,341.0,341.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +718,Auto ViML,True,AutoViML/Auto_ViML,,hyperopt,https://github.com/AutoViML/Auto_ViML,https://github.com/AutoViML/Auto_ViML,Apache-2.0,2019-06-10 13:09:15.000,2022-08-16 11:44:37.000000,2022-08-16 11:44:18,81.0,4.0,17.0,362,301.0,Automatically Build Multiple ML Models with a Single Line of Code...,6.0,17,,,,,autoviml,,,,,17.0,17.0,https://pypi.org/project/autoviml,456.0,456.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +719,quinn,True,MrPowers/quinn,,ml-experiments,https://github.com/MrPowers/quinn,https://github.com/MrPowers/quinn,,2017-09-15 13:02:42.000,2022-08-22 17:10:41.000000,2021-02-09 04:48:07,47.0,14.0,10.0,352,110.0,pyspark methods to enhance developer productivity.,6.0,17,2017-10-17 03:04:48,0.2.0,1.0,,quinn,,,,['spark'],,,https://pypi.org/project/quinn,770317.0,770317.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +720,ExplainX.ai,True,explainX/explainx,,interpretability,https://github.com/explainX/explainx,https://github.com/explainX/explainx,MIT,2020-06-16 14:27:15.000,2022-06-22 02:41:47.000000,2021-02-02 09:03:57,42.0,9.0,17.0,317,184.0,Explainable AI framework for data scientists. Explain & debug any..,4.0,17,2021-02-07 11:06:21,2.407,21.0,,explainx,,,,,,,https://pypi.org/project/explainx,1949.0,1949.0,,,,,,,,3.0,4.0,,,,,,,,,,,,,,, +721,somoclu,True,peterwittek/somoclu,,distributed-ml,https://github.com/peterwittek/somoclu,https://github.com/peterwittek/somoclu,MIT,2013-01-16 06:33:16.000,2021-11-15 19:51:57.895000,2021-10-31 08:28:12,62.0,25.0,108.0,239,619.0,Massively parallel self-organizing maps: accelerate training on..,19.0,17,2021-10-31 08:33:47,1.7.6,13.0,,somoclu,conda-forge/somoclu,,,,,,https://pypi.org/project/somoclu,978.0,2055.0,https://anaconda.org/conda-forge/somoclu,2021-11-15 19:51:57.895,63650.0,,,,,3.0,1612.0,,,,,,,,,,,,,,, +722,Muda,True,bmcfee/muda,,audio,https://github.com/bmcfee/muda,https://github.com/bmcfee/muda,ISC,2014-11-07 21:21:22.000,2021-05-03 14:04:37.000000,2021-05-03 14:04:36,32.0,6.0,44.0,209,293.0,A library for augmenting annotated audio data.,7.0,17,2019-11-15 15:46:12,0.4.1,11.0,,muda,,,,,15.0,15.0,https://pypi.org/project/muda,107.0,107.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +723,Larq Compute Engine,True,larq/compute-engine,,model-serialisation,https://github.com/larq/compute-engine,https://github.com/larq/compute-engine,Apache-2.0,2019-08-29 15:02:43.000,2022-08-25 08:32:24.000000,2022-08-25 07:58:30,32.0,13.0,124.0,206,,Highly optimized inference engine for Binarized..,18.0,17,2022-08-25 08:27:32,0.8.0,17.0,,larq-compute-engine,,,,,6.0,6.0,https://pypi.org/project/larq-compute-engine,870.0,894.0,,,,,,,,3.0,728.0,,,,,,,,,,,,,,, +724,Parfit,True,jmcarpenter2/parfit,,hyperopt,https://github.com/jmcarpenter2/parfit,https://github.com/jmcarpenter2/parfit,MIT,2017-11-22 20:17:51.000,2020-04-04 19:26:44.000000,2020-04-04 19:26:37,25.0,6.0,5.0,200,127.0,A package for parallelizing the fit and flexibly scoring of..,4.0,17,,,,,parfit,,,,['sklearn'],16.0,16.0,https://pypi.org/project/parfit,9747.0,9747.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +725,celer,True,mathurinm/celer,,sklearn-utils,https://github.com/mathurinm/celer,https://github.com/mathurinm/celer,BSD-3-Clause,2018-02-20 19:37:31.000,2022-08-23 08:19:52.000000,2022-08-23 08:07:43,25.0,18.0,72.0,162,,"Fast solver for L1-type problems: Lasso, sparse Logisitic regression,..",11.0,17,2020-10-12 12:26:09,0.5.1,3.0,,celer,,,,['sklearn'],13.0,13.0,https://pypi.org/project/celer,615.0,615.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +726,nvidia-ml-py3,True,nicolargo/nvidia-ml-py3,,gpu-utilities,https://github.com/nicolargo/nvidia-ml-py3,https://github.com/nicolargo/nvidia-ml-py3,,2017-06-03 07:47:03.000,2019-03-06 20:41:10.000000,2019-03-06 20:41:09,18.0,2.0,,86,5.0,Python 3 Bindings for the NVIDIA Management Library.,2.0,17,,,,,nvidia-ml-py3,,,,,6174.0,6174.0,https://pypi.org/project/nvidia-ml-py3,966475.0,966475.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +727,PySlowFast,True,facebookresearch/SlowFast,,image,https://github.com/facebookresearch/SlowFast,https://github.com/facebookresearch/SlowFast,Apache-2.0,2019-08-20 22:47:26.000,2022-08-25 02:23:36.000000,2022-08-25 02:22:15,959.0,287.0,261.0,5037,,PySlowFast: video understanding codebase from FAIR for..,28.0,16,,,,,,,,,['pytorch'],10.0,10.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +728,BytePS,True,bytedance/byteps,,distributed-ml,https://github.com/bytedance/byteps,https://github.com/bytedance/byteps,Apache-2.0,2019-06-25 07:00:13.000,2022-08-19 00:53:25.000000,2022-02-10 07:36:23,453.0,99.0,160.0,3259,432.0,A high performance and generic framework for distributed DNN training.,19.0,16,2020-02-19 23:44:20,0.2,1.0,,byteps,,bytepsimage/tensorflow,,,,,https://pypi.org/project/byteps,19.0,52.0,,,,https://hub.docker.com/r/bytepsimage/tensorflow,2020-03-03 02:33:23.358610,,1268.0,3.0,,,,,,,,,,,,,,,, +729,GraphEmbedding,True,shenweichen/GraphEmbedding,,graph,https://github.com/shenweichen/GraphEmbedding,https://github.com/shenweichen/GraphEmbedding,MIT,2019-02-11 16:27:20.000,2022-06-22 11:47:45.000000,2022-06-21 18:24:09,865.0,34.0,23.0,2965,30.0,Implementation and experiments of graph embedding algorithms.,9.0,16,,,,,,,,,['sklearn'],21.0,21.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +730,image-match,True,EdjoLabs/image-match,,image,https://github.com/ProvenanceLabs/image-match,https://github.com/ProvenanceLabs/image-match,,2016-03-08 18:16:45.000,2022-05-14 16:58:36.000000,2021-09-21 13:07:59,383.0,55.0,48.0,2785,405.0,Quickly search over billions of images.,19.0,16,2017-02-06 08:12:01,1.1.2,10.0,ProvenanceLabs/image-match,image_match,,,,,,,https://pypi.org/project/image_match,594.0,594.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +731,micrograd,True,karpathy/micrograd,,pytorch-utils,https://github.com/karpathy/micrograd,https://github.com/karpathy/micrograd,MIT,2020-04-13 04:31:18.000,2022-08-24 20:12:47.000000,2020-04-18 19:15:25,211.0,2.0,3.0,2431,24.0,A tiny scalar-valued autograd engine and a neural net library..,2.0,16,,,,,micrograd,,,,['pytorch'],7.0,7.0,https://pypi.org/project/micrograd,363.0,363.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +732,automl-gs,True,minimaxir/automl-gs,,hyperopt,https://github.com/minimaxir/automl-gs,https://github.com/minimaxir/automl-gs,MIT,2019-01-13 18:57:44.000,2019-10-22 11:20:40.000000,2019-04-05 06:48:14,162.0,24.0,6.0,1788,102.0,"Provide an input CSV and a target field to predict, generate a..",7.0,16,2019-04-05 06:51:04,0.2.1,2.0,,automl_gs,,,,,,,https://pypi.org/project/automl_gs,22.0,22.0,,,,,,,,3.0,32.0,,,,,,,,,,,,,,, +733,Lambda Networks,True,lucidrains/lambda-networks,,pytorch-utils,https://github.com/lucidrains/lambda-networks,https://github.com/lucidrains/lambda-networks,MIT,2020-10-08 19:01:15.000,2020-11-18 19:54:34.000000,2020-11-18 19:54:30,157.0,13.0,15.0,1504,,"Implementation of LambdaNetworks, a new approach to..",3.0,16,2020-11-18 08:18:54,0.4.0,11.0,,lambda-networks,,,,['pytorch'],6.0,6.0,https://pypi.org/project/lambda-networks,45.0,45.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +734,Tez,True,abhishekkrthakur/tez,,pytorch-utils,https://github.com/abhishekkrthakur/tez,https://github.com/abhishekkrthakur/tez,Apache-2.0,2020-11-13 10:19:22.000,2022-08-10 15:58:46.000000,2022-08-10 15:58:42,136.0,20.0,17.0,1092,,Tez is a super-simple and lightweight Trainer for PyTorch. It..,2.0,16,2021-08-16 18:42:17,0.1.8,1.0,,tez,,,,['pytorch'],33.0,33.0,https://pypi.org/project/tez,1760.0,1760.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +735,cuGraph,True,rapidsai/cugraph,,gpu-utilities,https://github.com/rapidsai/cugraph,https://github.com/rapidsai/cugraph,Apache-2.0,2018-11-15 18:07:11.000,2022-08-25 23:34:48.000000,2022-08-25 15:55:00,210.0,198.0,790.0,1075,,cuGraph - RAPIDS Graph Analytics Library.,90.0,16,2022-08-18 00:25:04,22.08.00,21.0,,cugraph,,,,,,,https://pypi.org/project/cugraph,105.0,105.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +736,torchsde,True,google-research/torchsde,,pytorch-utils,https://github.com/google-research/torchsde,https://github.com/google-research/torchsde,Apache-2.0,2020-07-06 23:13:11.000,2021-07-26 13:59:41.000000,2021-07-26 13:59:38,110.0,9.0,41.0,1033,157.0,Differentiable SDE solvers with GPU support and efficient..,5.0,16,2021-01-05 18:31:38,0.2.4,4.0,,,,,,['pytorch'],19.0,19.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +737,Fiber,True,uber/fiber,,distributed-ml,https://github.com/uber/fiber,https://github.com/uber/fiber,Apache-2.0,2020-01-07 18:16:24.000,2022-06-22 04:12:10.000000,2021-03-15 07:00:08,107.0,17.0,8.0,981,66.0,Distributed Computing for AI Made Simple.,5.0,16,,,,,fiber,,,,,43.0,43.0,https://pypi.org/project/fiber,60.0,60.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +738,Pandas Summary,True,mouradmourafiq/pandas-summary,,data-containers,https://github.com/polyaxon/datatile,https://github.com/polyaxon/datatile,Apache-2.0,2016-03-25 21:59:32.000,2022-08-14 15:22:37.000000,2022-08-14 15:22:30,39.0,6.0,7.0,433,46.0,An extension to pandas dataframes describe function.,8.0,16,,,,polyaxon/datatile,pandas-summary,,,,['pandas'],,,https://pypi.org/project/pandas-summary,45927.0,45927.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +739,scikit-tda,True,scikit-tda/scikit-tda,,sklearn-utils,https://github.com/scikit-tda/scikit-tda,https://github.com/scikit-tda/scikit-tda,,2018-04-13 21:00:31.000,2022-03-13 16:33:15.000000,2022-03-13 16:33:15,44.0,15.0,4.0,361,64.0,Topological Data Analysis for Python.,4.0,16,2021-08-03 00:22:58,1.0.0,4.0,,scikit-tda,,,,['sklearn'],33.0,33.0,https://pypi.org/project/scikit-tda,1606.0,1606.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +740,Camphr,True,PKSHATechnology-Research/camphr,,nlp,https://github.com/PKSHATechnology-Research/camphr,https://github.com/PKSHATechnology-Research/camphr,Apache-2.0,2020-02-10 03:39:58.000,2022-06-22 04:45:05.000000,2021-08-18 06:06:51,16.0,2.0,26.0,344,1404.0,"spaCy plugin for Transformers , Udify, ELmo, etc.",7.0,16,2020-08-21 04:45:06,0.7.0,21.0,,camphr,,,,['spacy'],,,https://pypi.org/project/camphr,75.0,75.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +741,pdvega,True,altair-viz/pdvega,,data-viz,https://github.com/altair-viz/pdvega,https://github.com/altair-viz/pdvega,MIT,2018-01-11 21:30:27.000,2019-03-29 16:09:14.000000,2019-03-29 16:09:13,31.0,16.0,10.0,340,177.0,Interactive plotting for Pandas using Vega-Lite.,9.0,16,,,,,pdvega,,,,,67.0,67.0,https://pypi.org/project/pdvega,56.0,56.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +742,textpipe,True,textpipe/textpipe,,nlp,https://github.com/textpipe/textpipe,https://github.com/textpipe/textpipe,MIT,2018-06-21 16:23:32.000,2021-06-09 11:55:53.000000,2021-06-09 11:55:53,23.0,15.0,25.0,297,371.0,Textpipe: clean and extract metadata from text.,28.0,16,,,,,textpipe,,,,,8.0,8.0,https://pypi.org/project/textpipe,151.0,151.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +743,featurewiz,True,AutoViML/featurewiz,,hyperopt,https://github.com/AutoViML/featurewiz,https://github.com/AutoViML/featurewiz,Apache-2.0,2020-11-29 16:46:16.000,2022-08-21 13:42:07.000000,2022-08-21 13:41:34,57.0,,44.0,272,,Use advanced feature engineering strategies and select the..,4.0,16,,,,,featurewiz,,,,,14.0,14.0,https://pypi.org/project/featurewiz,6493.0,6493.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +744,skggm,True,skggm/skggm,,sklearn-utils,https://github.com/skggm/skggm,https://github.com/skggm/skggm,MIT,2016-06-11 18:35:56.000,2022-03-11 01:14:19.000000,2022-03-11 01:14:19,36.0,28.0,47.0,206,691.0,Scikit-learn compatible estimation of general graphical models.,6.0,16,2018-09-12 01:11:31,0.2.8,6.0,,skggm,,,,['sklearn'],8.0,8.0,https://pypi.org/project/skggm,61.0,61.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +745,openpyxl,True,,,data-loading,,https://foss.heptapod.net/openpyxl/openpyxl,MIT,2015-11-03 00:22:17.154,2022-07-07 13:17:59.209000,,0.0,228.0,1643.0,45,,A Python library to read/write Excel 2010 xlsx/xlsm files.,,16,,,42.0,,openpyxl,openpyxl,openpyxl/openpyxl-ci,https://openpyxl.readthedocs.io/en/stable/,,,,https://pypi.org/project/openpyxl,35457042.0,35458269.0,https://anaconda.org/anaconda/openpyxl,2022-07-07 13:17:59.209,98279.0,https://hub.docker.com/r/openpyxl/openpyxl-ci,2018-09-13 18:04:17.646261,,1202.0,3.0,,,,,,,,,,,,,,,https://foss.heptapod.net/api/graphql::openpyxl/openpyxl,https://foss.heptapod.net/openpyxl/openpyxl +746,Feature Engine,True,solegalli/feature_engine,,others,https://github.com/solegalli/feature_engine,https://github.com/solegalli/feature_engine,BSD-3-Clause,2020-08-06 19:43:35.639,2022-08-01 09:50:21.000000,2022-07-05 18:46:07,8.0,,,22,,Feature engineering package with sklearn like functionality.,36.0,16,,,13.0,,feature_engine,conda-forge/feature_engine,,,,,,https://pypi.org/project/feature_engine,93280.0,93882.0,https://anaconda.org/conda-forge/feature_engine,2022-06-14 07:05:45.491,14467.0,,,,,3.0,,,,,,,,,,,,,,,, +747,DeepMind Lab,True,deepmind/lab,,reinforcement-learning,https://github.com/deepmind/lab,https://github.com/deepmind/lab,,2016-11-30 13:41:26.000,2022-06-09 15:33:29.000000,2022-06-09 15:33:29,1330.0,56.0,163.0,6734,494.0,A customisable 3D platform for agent-based AI research.,8.0,15,2020-12-07 11:26:33,release-2020-12-07,8.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +748,graph-nets,True,deepmind/graph_nets,,graph,https://github.com/deepmind/graph_nets,https://github.com/deepmind/graph_nets,Apache-2.0,2018-08-31 08:19:28.000,2020-12-04 17:43:48.000000,2020-12-04 17:43:47,769.0,3.0,120.0,5155,47.0,Build Graph Nets in Tensorflow.,10.0,15,,,,,graph-nets,,,,['tensorflow'],,,https://pypi.org/project/graph-nets,1001.0,1001.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +749,Euler,True,alibaba/euler,,graph,https://github.com/alibaba/euler,https://github.com/alibaba/euler,Apache-2.0,2019-01-10 06:32:32.000,2022-06-26 20:58:20.000000,2020-07-29 05:53:01,549.0,214.0,102.0,2789,8.0,A distributed graph deep learning framework.,3.0,15,2020-07-07 02:24:18,2.0.0,2.0,,euler-gl,,,,['tensorflow'],,,https://pypi.org/project/euler-gl,15.0,15.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +750,pycls,True,facebookresearch/pycls,,image,https://github.com/facebookresearch/pycls,https://github.com/facebookresearch/pycls,MIT,2019-06-10 22:47:17.000,2022-07-12 01:15:33.000000,2022-07-12 01:13:05,228.0,22.0,56.0,1984,,"Codebase for Image Classification Research, written in PyTorch.",17.0,15,2021-05-21 00:29:47,0.2,2.0,,,,,,['pytorch'],6.0,6.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +751,BlazingSQL,True,BlazingDB/blazingsql,,gpu-utilities,https://github.com/BlazingDB/blazingsql,https://github.com/BlazingDB/blazingsql,Apache-2.0,2018-09-24 18:25:45.000,2022-03-08 21:17:32.000000,2021-09-30 21:51:09,169.0,127.0,586.0,1766,,"BlazingSQL is a lightweight, GPU accelerated, SQL engine for..",49.0,15,2021-08-16 15:40:43,21.08.00,19.0,,,blazingsql/blazingsql-protocol,,,,,,,,27.0,https://anaconda.org/blazingsql/blazingsql-protocol,2019-11-11 19:54:17.621,953.0,,,,,3.0,,,,,,,,,,,,,,,, +752,NeuroNER,True,Franck-Dernoncourt/NeuroNER,,nlp,https://github.com/Franck-Dernoncourt/NeuroNER,https://github.com/Franck-Dernoncourt/NeuroNER,MIT,2017-03-07 01:24:15.000,2022-06-21 21:47:21.000000,2019-10-02 23:26:11,456.0,82.0,67.0,1623,132.0,Named-entity recognition using neural networks. Easy-to-use and..,7.0,15,2019-03-13 20:28:15,1.0-dev2,1.0,,pyneuroner,,,,,,,https://pypi.org/project/pyneuroner,102.0,102.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +753,riko,True,nerevu/riko,,data-pipelines,https://github.com/nerevu/riko,https://github.com/nerevu/riko,MIT,2016-06-02 12:22:51.000,2021-12-28 23:01:39.000000,2021-12-28 23:01:31,68.0,21.0,8.0,1586,1269.0,A Python stream processing engine modeled after Yahoo! Pipes.,18.0,15,,,,,riko,,,,,,,https://pypi.org/project/riko,30.0,30.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +754,Advisor,True,tobegit3hub/advisor,,hyperopt,https://github.com/tobegit3hub/advisor,https://github.com/tobegit3hub/advisor,Apache-2.0,2017-09-14 03:50:33.000,2019-11-11 07:09:57.869705,2019-11-11 06:59:31,260.0,19.0,13.0,1476,165.0,Open-source implementation of Google Vizier for hyper parameters..,11.0,15,,,,,advisor,,tobegit3hub/advisor,,,,,https://pypi.org/project/advisor,34.0,62.0,,,,https://hub.docker.com/r/tobegit3hub/advisor,2019-11-11 07:09:57.869705,,1669.0,3.0,,,,,,,,,,,,,,,, +755,Xcessiv,True,reiinakano/xcessiv,,hyperopt,https://github.com/reiinakano/xcessiv,https://github.com/reiinakano/xcessiv,Apache-2.0,2017-03-07 18:18:25.000,2018-06-06 22:23:37.000000,2017-08-21 00:51:15,106.0,21.0,13.0,1264,316.0,"A web-based application for quick, scalable, and automated..",6.0,15,2017-08-21 00:53:25,0.5.1,20.0,,xcessiv,,,,,1.0,1.0,https://pypi.org/project/xcessiv,10.0,10.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +756,AdvBox,True,advboxes/AdvBox,,adversarial,https://github.com/advboxes/AdvBox,https://github.com/advboxes/AdvBox,Apache-2.0,2018-08-08 08:55:41.000,2022-08-08 02:56:23.000000,2022-08-08 02:56:23,245.0,8.0,30.0,1249,378.0,Advbox is a toolbox to generate adversarial examples that fool..,19.0,15,,,,,advbox,,,,,,,https://pypi.org/project/advbox,17.0,17.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +757,Databolt Flow,True,d6t/d6tflow,,data-pipelines,https://github.com/d6t/d6tflow,https://github.com/d6t/d6tflow,MIT,2019-02-03 01:51:22.000,2021-10-06 00:53:28.000000,2021-09-28 02:59:00,71.0,10.0,13.0,943,266.0,Python library for building highly effective data science workflows.,12.0,15,,,,,d6tflow,,,,,20.0,20.0,https://pypi.org/project/d6tflow,117.0,117.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +758,XAI,True,EthicalML/xai,,interpretability,https://github.com/EthicalML/xai,https://github.com/EthicalML/xai,MIT,2019-01-11 20:00:09.000,2021-10-30 06:35:19.000000,2021-10-30 06:30:12,123.0,2.0,7.0,837,91.0,XAI - An eXplainability toolbox for machine learning.,3.0,15,2021-10-30 06:35:19,0.1.0,1.0,,xai,,,,,19.0,19.0,https://pypi.org/project/xai,123.0,123.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +759,MedicalTorch,True,perone/medicaltorch,,medical-data,https://github.com/perone/medicaltorch,https://github.com/perone/medicaltorch,Apache-2.0,2018-02-27 02:50:07.000,2022-04-01 08:52:48.000000,2021-04-16 18:50:54,114.0,13.0,9.0,788,57.0,A medical imaging framework for Pytorch.,8.0,15,2018-11-24 00:33:11,0.2,1.0,,medicaltorch,,,,['pytorch'],12.0,12.0,https://pypi.org/project/medicaltorch,211.0,211.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +760,Translate,True,pytorch/translate,,nlp,https://github.com/pytorch/translate,https://github.com/pytorch/translate,BSD-3-Clause,2018-04-24 16:44:04.000,2022-06-10 23:07:53.000000,2022-06-10 23:04:56,176.0,11.0,27.0,756,813.0,Translate - a PyTorch Language Library.,87.0,15,,,,,pytorch-translate,,,,['pytorch'],,,https://pypi.org/project/pytorch-translate,10.0,10.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +761,Anchor,True,marcotcr/anchor,,interpretability,https://github.com/marcotcr/anchor,https://github.com/marcotcr/anchor,BSD-2-Clause,2018-02-02 23:38:50.000,2022-07-19 18:09:12.000000,2022-07-19 18:08:39,99.0,19.0,51.0,717,47.0,Code for High-Precision Model-Agnostic Explanations paper.,10.0,15,,,,,anchor_exp,,,,,,,https://pypi.org/project/anchor_exp,1158.0,1158.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +762,HyperparameterHunter,True,HunterMcGushion/hyperparameter_hunter,,hyperopt,https://github.com/HunterMcGushion/hyperparameter_hunter,https://github.com/HunterMcGushion/hyperparameter_hunter,MIT,2018-06-01 23:17:00.000,2021-01-20 03:52:41.000000,2021-01-20 03:52:40,88.0,32.0,84.0,692,1096.0,Easy hyperparameter optimization and automatic result..,4.0,15,2019-08-06 09:09:45,3.0.0,16.0,,hyperparameter-hunter,,,,,,,https://pypi.org/project/hyperparameter-hunter,61.0,68.0,,,,,,,,3.0,332.0,,,,,,,,,,,,,,, +763,NeoML,True,neoml-lib/neoml,,ml-frameworks,https://github.com/neoml-lib/neoml,https://github.com/neoml-lib/neoml,Apache-2.0,2020-06-14 17:37:36.000,2022-08-24 16:29:18.000000,2022-08-24 16:29:17,110.0,14.0,48.0,691,778.0,Machine learning framework for both deep learning and traditional..,32.0,15,2021-06-22 05:25:53,NeoML-master_2.0.5.0,2.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +764,TensorBoard Logger,True,TeamHG-Memex/tensorboard_logger,,ml-experiments,https://github.com/TeamHG-Memex/tensorboard_logger,https://github.com/TeamHG-Memex/tensorboard_logger,MIT,2016-10-27 14:02:25.000,2021-11-15 17:46:29.000000,2019-10-21 07:52:07,49.0,9.0,15.0,623,46.0,Log TensorBoard events without touching TensorFlow.,5.0,15,,,,,tensorboard_logger,,,,,,,https://pypi.org/project/tensorboard_logger,55740.0,55740.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +765,LOFO,True,aerdem4/lofo-importance,,interpretability,https://github.com/aerdem4/lofo-importance,https://github.com/aerdem4/lofo-importance,MIT,2019-01-14 10:46:46.000,2022-04-27 12:35:27.000000,2022-04-27 12:35:27,56.0,2.0,16.0,483,27.0,Leave One Feature Out Importance.,3.0,15,,,,,lofo-importance,,,,,19.0,19.0,https://pypi.org/project/lofo-importance,308.0,308.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +766,datmo,True,datmo/datmo,,ml-experiments,https://github.com/datmo/datmo,https://github.com/datmo/datmo,MIT,2017-11-03 05:46:43.000,2022-06-21 21:41:58.000000,2019-11-29 00:48:44,28.0,27.0,150.0,341,1051.0,Open source production model management tool for data scientists.,6.0,15,,,,,datmo,,,,,5.0,5.0,https://pypi.org/project/datmo,28.0,28.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +767,Julius,True,adefossez/julius,,audio,https://github.com/adefossez/julius,https://github.com/adefossez/julius,MIT,2020-10-26 10:54:21.000,2022-01-28 09:28:20.000000,2022-01-28 09:27:02,18.0,,9.0,279,,Fast PyTorch based DSP for audio and 1D signals.,2.0,15,,,,,julius,,,,['pytorch'],120.0,120.0,https://pypi.org/project/julius,23995.0,23995.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +768,DeepGraph,True,deepgraph/deepgraph,,graph,https://github.com/deepgraph/deepgraph,https://github.com/deepgraph/deepgraph,,2015-10-27 12:28:45.000,2022-04-19 08:20:13.909000,2021-06-14 10:58:10,38.0,9.0,5.0,262,162.0,Analyze Data with Pandas-based Networks. Documentation:.,2.0,15,2020-10-01 13:20:38,0.2.3,12.0,,deepgraph,conda-forge/deepgraph,,,['pandas'],5.0,5.0,https://pypi.org/project/deepgraph,294.0,2493.0,https://anaconda.org/conda-forge/deepgraph,2022-04-19 08:20:13.909,131966.0,,,,,3.0,,,,,,,,,,,,,,,, +769,NeuralQA,True,victordibia/neuralqa,,nlp,https://github.com/victordibia/neuralqa,https://github.com/victordibia/neuralqa,MIT,2020-05-19 03:55:56.000,2022-07-21 06:56:01.000000,2020-12-16 17:41:37,30.0,20.0,8.0,218,312.0,NeuralQA: A Usable Library for Question Answering on Large Datasets with..,3.0,15,,,,,neuralqa,,,,,4.0,4.0,https://pypi.org/project/neuralqa,68.0,68.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +770,pyRDF2Vec,True,IBCNServices/pyRDF2Vec,,graph,https://github.com/IBCNServices/pyRDF2Vec,https://github.com/IBCNServices/pyRDF2Vec,MIT,2019-06-13 11:36:12.000,2022-08-02 16:54:15.000000,2022-05-06 06:37:14,32.0,9.0,52.0,164,,Python Implementation and Extension of RDF2Vec.,6.0,15,2021-06-09 10:55:19,0.2.3,6.0,,pyrdf2vec,,,,,,,https://pypi.org/project/pyrdf2vec,297.0,297.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +771,steppy,True,minerva-ml/steppy,,ml-experiments,https://github.com/minerva-ml/steppy,https://github.com/minerva-ml/steppy,MIT,2018-01-15 09:40:49.000,2018-11-23 09:48:51.000000,2018-11-23 09:47:34,33.0,13.0,50.0,134,69.0,"Lightweight, Python library for fast and reproducible experimentation.",5.0,15,2018-11-23 09:48:51,0.1.16,16.0,,steppy,,,,,46.0,46.0,https://pypi.org/project/steppy,9.0,9.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +772,OpenNRE,True,thunlp/OpenNRE,,nlp,https://github.com/thunlp/OpenNRE,https://github.com/thunlp/OpenNRE,MIT,2017-02-26 07:37:12.000,2022-04-06 12:13:02.000000,2022-04-06 12:13:01,946.0,9.0,340.0,3755,162.0,An Open-Source Package for Neural Relation Extraction (NRE).,10.0,14,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +773,GraphSAGE,True,williamleif/GraphSAGE,,graph,https://github.com/williamleif/GraphSAGE,https://github.com/williamleif/GraphSAGE,MIT,2017-05-29 15:36:22.000,2022-07-06 20:09:56.000000,2018-09-19 19:27:00,773.0,98.0,59.0,2814,59.0,Representation learning on large graphs using stochastic..,9.0,14,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +774,ZhuSuan,True,thu-ml/zhusuan,,probabilistics,https://github.com/thu-ml/zhusuan,https://github.com/thu-ml/zhusuan,MIT,2016-07-18 13:31:38.000,2020-01-09 14:51:27.000000,2019-08-05 10:00:04,403.0,7.0,53.0,2136,439.0,"A probabilistic programming library for Bayesian deep learning,..",20.0,14,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +775,OpenNE,True,thunlp/OpenNE,,graph,https://github.com/thunlp/OpenNE,https://github.com/thunlp/OpenNE,MIT,2017-10-08 04:58:20.000,2022-06-21 21:24:15.000000,2019-08-12 10:56:27,475.0,1.0,96.0,1593,98.0,An Open-Source Package for Network Embedding (NE).,10.0,14,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +776,MedicalNet,True,Tencent/MedicalNet,,medical-data,https://github.com/Tencent/MedicalNet,https://github.com/Tencent/MedicalNet,MIT,2019-07-17 09:53:10.000,2022-06-21 22:20:52.000000,2020-08-27 13:37:26,369.0,55.0,15.0,1448,26.0,Many studies have shown that the performance on deep learning is..,,14,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +777,Medical Detection Toolkit,True,MIC-DKFZ/medicaldetectiontoolkit,,medical-data,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,https://github.com/MIC-DKFZ/medicaldetectiontoolkit,Apache-2.0,2018-10-12 12:34:57.000,2022-06-22 00:01:41.000000,2022-04-04 08:29:54,284.0,37.0,85.0,1149,41.0,The Medical Detection Toolkit contains 2D + 3D..,3.0,14,,,,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +778,AutoGL,True,THUMNLab/AutoGL,,graph,https://github.com/THUMNLab/AutoGL,https://github.com/THUMNLab/AutoGL,Apache-2.0,2020-11-30 14:26:22.000,2022-08-20 12:20:38.000000,2022-04-19 03:40:55,98.0,8.0,15.0,840,,An autoML framework & toolkit for machine learning on graphs.,13.0,14,2022-04-22 06:08:57,0.3.1,3.0,,auto-graph-learning,,,,['pytorch'],,,https://pypi.org/project/auto-graph-learning,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +779,SpeedTorch,True,Santosh-Gupta/SpeedTorch,,gpu-utilities,https://github.com/Santosh-Gupta/SpeedTorch,https://github.com/Santosh-Gupta/SpeedTorch,MIT,2019-09-07 18:57:52.000,2020-02-21 23:13:29.000000,2020-02-21 23:13:28,39.0,4.0,2.0,657,170.0,Library for faster pinned CPU - GPU transfer in Pytorch.,3.0,14,,,,,SpeedTorch,,,,['pytorch'],4.0,4.0,https://pypi.org/project/SpeedTorch,22.0,22.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +780,cuSignal,True,rapidsai/cusignal,,gpu-utilities,https://github.com/rapidsai/cusignal,https://github.com/rapidsai/cusignal,Apache-2.0,2019-08-22 14:27:27.000,2022-08-17 14:43:24.000000,2022-08-10 19:08:31,96.0,16.0,120.0,610,,GPU accelerated signal processing.,39.0,14,2022-08-17 14:43:25,22.08.00,14.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +781,SKLL,True,EducationalTestingService/skll,,ml-experiments,https://github.com/EducationalTestingService/skll,https://github.com/EducationalTestingService/skll,,2013-08-02 14:31:46.000,2022-07-29 18:16:12.000000,2021-12-21 20:03:06,65.0,31.0,365.0,526,,SciKit-Learn Laboratory (SKLL) makes it easy to run machine..,37.0,14,2021-12-21 20:12:29,3.0,65.0,,skll,,,,['sklearn'],38.0,38.0,https://pypi.org/project/skll,136.0,136.0,,,,,,,,3.0,11.0,,,,,,,,,,,,,,, +782,Sematch,True,gsi-upm/sematch,,graph,https://github.com/gsi-upm/sematch,https://github.com/gsi-upm/sematch,Apache-2.0,2012-11-30 11:11:53.000,2020-11-05 21:20:52.000000,2019-03-27 03:17:24,104.0,14.0,19.0,395,122.0,semantic similarity framework for knowledge graph.,5.0,14,,,,,sematch,,,,,34.0,34.0,https://pypi.org/project/sematch,128.0,128.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +783,Pywick,True,achaiah/pywick,,pytorch-utils,https://github.com/achaiah/pywick,https://github.com/achaiah/pywick,,2019-03-25 15:42:47.000,2022-02-04 15:57:11.000000,2021-10-22 03:09:17,39.0,1.0,13.0,374,149.0,High-level batteries-included neural network training library for..,4.0,14,2021-10-22 03:16:49,0.6.5,8.0,,pywick,,,,['pytorch'],7.0,7.0,https://pypi.org/project/pywick,36.0,36.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +784,tfdeploy,True,riga/tfdeploy,,model-serialisation,https://github.com/riga/tfdeploy,https://github.com/riga/tfdeploy,BSD-3-Clause,2016-03-07 13:08:21.000,2021-01-08 09:52:54.000000,2021-01-08 09:52:49,36.0,11.0,23.0,349,170.0,Deploy tensorflow graphs for fast evaluation and export to..,4.0,14,2016-12-23 10:46:31,0.3.3,10.0,,tfdeploy,,,,['tensorflow'],,,https://pypi.org/project/tfdeploy,9.0,9.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +785,data-describe,True,data-describe/data-describe,,data-viz,https://github.com/data-describe/data-describe,https://github.com/data-describe/data-describe,,2020-05-04 17:58:14.000,2022-08-23 05:04:25.000000,2021-11-19 06:05:15,18.0,70.0,175.0,292,700.0,datadescribe: Pythonic EDA Accelerator for Data Science.,14.0,14,,,5.0,,data-describe,,,,,,,https://pypi.org/project/data-describe,2576.0,2576.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +786,TransferNLP,True,feedly/transfer-nlp,,nlp,https://github.com/feedly/transfer-nlp,https://github.com/feedly/transfer-nlp,MIT,2019-03-12 20:00:31.000,2020-05-28 17:32:42.000000,2020-05-28 17:31:53,17.0,3.0,20.0,288,465.0,NLP library designed for reproducible experimentation..,7.0,14,2020-05-28 17:32:42,0.1.6,8.0,,transfer-nlp,,,,['pytorch'],,,https://pypi.org/project/transfer-nlp,100.0,100.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +787,ONNX-T5,True,abelriboulot/onnxt5,,nlp,https://github.com/abelriboulot/onnxt5,https://github.com/abelriboulot/onnxt5,Apache-2.0,2020-08-01 09:38:35.000,2021-01-28 09:24:53.000000,2021-01-28 09:24:52,23.0,7.0,8.0,204,74.0,"Summarization, translation, sentiment-analysis, text-generation and..",3.0,14,2021-01-28 09:24:24,0.1.9,9.0,,onnxt5,,,,,1.0,1.0,https://pypi.org/project/onnxt5,57.0,57.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +788,nx-altair,True,Zsailer/nx_altair,,data-viz,https://github.com/Zsailer/nx_altair,https://github.com/Zsailer/nx_altair,MIT,2018-05-13 00:10:12.000,2022-01-08 12:10:11.000000,2020-06-02 21:10:26,23.0,6.0,4.0,199,51.0,Draw interactive NetworkX graphs with Altair.,3.0,14,,,,,nx-altair,,,,['jupyter'],,,https://pypi.org/project/nx-altair,1477.0,1477.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +789,textvec,True,textvec/textvec,,nlp,https://github.com/textvec/textvec,https://github.com/textvec/textvec,MIT,2018-04-12 14:03:53.000,2022-07-05 09:43:14.000000,2022-07-05 09:43:05,23.0,3.0,6.0,185,72.0,Text vectorization tool to outperform TFIDF for classification tasks.,10.0,14,2019-09-12 07:41:04,2.0,1.0,,textvec,,,,['sklearn'],4.0,4.0,https://pypi.org/project/textvec,26.0,26.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +790,flupy,True,olirice/flupy,,data-pipelines,https://github.com/olirice/flupy,https://github.com/olirice/flupy,,2018-01-06 16:46:04.000,2022-02-18 14:51:19.000000,2022-02-17 15:29:05,12.0,,9.0,171,197.0,Fluent data pipelines for python and your shell.,6.0,14,,,,,flupy,,,,,,,https://pypi.org/project/flupy,73434.0,73434.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +791,ModelChimp,True,ModelChimp/modelchimp,,ml-experiments,https://github.com/ModelChimp/modelchimp,https://github.com/ModelChimp/modelchimp,BSD-2-Clause,2018-11-05 08:39:03.000,2022-08-26 01:03:25.000000,2021-08-01 07:11:57,12.0,4.0,10.0,124,363.0,Experiment tracking for machine and deep learning projects.,3.0,14,2019-04-09 10:43:15,0.4.0,3.0,,modelchimp,,modelchimp/modelchimp-server,,,,,https://pypi.org/project/modelchimp,43.0,57.0,,,,https://hub.docker.com/r/modelchimp/modelchimp-server,2019-04-09 10:15:09.532793,,657.0,3.0,,,,,,,,,,,,,,,, +792,Torch Points 3D,True,nicolas-chaulet/torch-points3d,,image,https://github.com/nicolas-chaulet/torch-points3d,https://github.com/nicolas-chaulet/torch-points3d,BSD-3-Clause,2022-01-09 14:41:37.000,2021-12-10 20:17:18.000000,2021-12-10 20:17:18,19.0,,,93,1788.0,Pytorch framework for doing deep learning on point clouds.,29.0,14,,,,,torch-points3d,,,,['pytorch'],,,https://pypi.org/project/torch-points3d,572.0,572.0,,,,,,,,3.0,,-8.0,,,,,,,,,,,,,, +793,ENAS,True,carpedm20/ENAS-pytorch,,hyperopt,https://github.com/carpedm20/ENAS-pytorch,https://github.com/carpedm20/ENAS-pytorch,Apache-2.0,2018-02-15 04:54:37.000,2020-12-09 18:13:03.000000,2020-06-16 07:23:32,469.0,37.0,7.0,2574,53.0,PyTorch implementation of Efficient Neural Architecture Search via..,6.0,13,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +794,Torch-Struct,True,harvardnlp/pytorch-struct,,pytorch-utils,https://github.com/harvardnlp/pytorch-struct,https://github.com/harvardnlp/pytorch-struct,MIT,2019-08-26 19:34:30.000,2022-04-20 08:21:20.000000,2022-01-30 19:49:08,83.0,24.0,30.0,1037,271.0,"Fast, general, and tested differentiable structured prediction..",16.0,13,2021-02-15 20:20:59,0.5,2.0,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +795,atspy,True,firmai/atspy,,time-series-data,https://github.com/firmai/atspy,https://github.com/firmai/atspy,,2020-01-28 05:00:10.000,2022-06-22 01:00:06.000000,2021-12-18 09:26:18,85.0,19.0,2.0,451,99.0,AtsPy: Automated Time Series Models in Python (by @firmai).,5.0,13,2020-11-12 16:10:48,zen,1.0,,atspy,,,,,6.0,6.0,https://pypi.org/project/atspy,350.0,350.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +796,VizSeq,True,facebookresearch/vizseq,,nlp,https://github.com/facebookresearch/vizseq,https://github.com/facebookresearch/vizseq,MIT,2019-08-26 13:19:38.000,2022-07-20 17:22:13.000000,2022-07-20 17:22:09,49.0,6.0,9.0,403,,"An Analysis Toolkit for Natural Language Generation (Translation,..",3.0,13,,,,,vizseq,,,,,6.0,6.0,https://pypi.org/project/vizseq,59.0,59.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +797,bodywork-core,True,bodywork-ml/bodywork-core,,data-pipelines,https://github.com/bodywork-ml/bodywork-core,https://github.com/bodywork-ml/bodywork-core,AGPL-3.0,2020-11-17 11:38:17.000,2022-07-05 23:22:23.000000,2022-07-04 09:38:06,18.0,20.0,57.0,399,946.0,MLOps tool for deploying machine learning projects to..,4.0,13,,,,,bodywork-core,,,,,10.0,10.0,https://pypi.org/project/bodywork-core,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +798,Auptimizer,True,LGE-ARC-AdvancedAI/auptimizer,,hyperopt,https://github.com/LGE-ARC-AdvancedAI/auptimizer,https://github.com/LGE-ARC-AdvancedAI/auptimizer,GPL-3.0,2019-09-12 01:08:37.000,2022-07-20 12:30:28.000000,2021-03-03 01:30:06,22.0,1.0,5.0,187,79.0,An automatic ML model optimization tool.,11.0,13,2021-03-03 02:00:23,2.0,3.0,,auptimizer,,,,,,,https://pypi.org/project/auptimizer,25.0,25.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +799,dabl,True,amueller/dabl,,sklearn-utils,https://github.com/amueller/dabl,https://github.com/amueller/dabl,BSD-3-Clause,2020-01-30 18:26:49.000,2022-08-06 00:11:41.000000,2021-07-09 18:47:52,10.0,,,117,,Data Analysis Baseline Library.,21.0,13,,,,,dabl,,,,['sklearn'],,,https://pypi.org/project/dabl,2074.0,2074.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +800,contextual-ai,True,SAP/contextual-ai,,interpretability,https://github.com/SAP/contextual-ai,https://github.com/SAP/contextual-ai,Apache-2.0,2020-05-12 07:15:56.000,2022-06-22 02:09:01.000000,2021-11-11 10:53:33,10.0,1.0,11.0,81,630.0,Contextual AI adds explainability to different stages of..,12.0,13,,,2.0,,contextual-ai,,,,,,,https://pypi.org/project/contextual-ai,65.0,65.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +801,cleanlab,True,cgnorthcutt/cleanlab,,others,https://github.com/cgnorthcutt/cleanlab,https://github.com/cgnorthcutt/cleanlab,AGPL-3.0,2022-02-17 20:36:34.000,2022-08-21 23:21:43.000000,2022-08-21 23:21:43,9.0,,,49,921.0,The standard package for machine learning with noisy labels and..,10.0,13,,,,,cleanlab,,,,,,,https://pypi.org/project/cleanlab,7248.0,7248.0,,,,,,,,3.0,,-7.0,,,,,,,,,,,,,, +802,LazyCluster,True,ml-tooling/lazycluster,,distributed-ml,https://github.com/ml-tooling/lazycluster,https://github.com/ml-tooling/lazycluster,Apache-2.0,2019-08-07 08:05:13.000,2022-06-22 04:08:37.000000,2021-08-19 13:59:11,9.0,,,43,,Distributed machine learning made simple.,2.0,13,2020-12-14 15:25:59,0.2.4,2.0,,lazycluster,,,,,17.0,17.0,https://pypi.org/project/lazycluster,42.0,42.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +803,StarSpace,True,facebookresearch/StarSpace,,ml-frameworks,https://github.com/facebookresearch/StarSpace,https://github.com/facebookresearch/StarSpace,MIT,2017-06-28 17:50:18.000,2021-11-03 16:23:46.000000,2019-12-13 19:03:25,509.0,48.0,149.0,3778,,"Learning embeddings for classification, retrieval and ranking.",17.0,12,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +804,surpriver,True,tradytics/surpriver,,financial-data,https://github.com/tradytics/surpriver,https://github.com/tradytics/surpriver,GPL-3.0,2020-08-30 07:56:22.000,2021-08-13 08:02:31.000000,2020-09-21 04:32:05,275.0,9.0,6.0,1489,64.0,Find big moving stocks before they move using machine..,6.0,12,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +805,Botflow,True,kkyon/botflow,,data-pipelines,https://github.com/kkyon/botflow,https://github.com/kkyon/botflow,,2018-08-20 03:13:31.000,2020-12-31 09:03:22.000000,2019-05-23 14:40:50,102.0,3.0,2.0,1183,192.0,Python Fast Dataflow programming framework for Data pipeline work(..,11.0,12,,,,,botflow,,,,,1.0,1.0,https://pypi.org/project/botflow,23.0,23.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +806,GraphVite,True,DeepGraphLearning/graphvite,,graph,https://github.com/DeepGraphLearning/graphvite,https://github.com/DeepGraphLearning/graphvite,Apache-2.0,2019-07-16 15:48:20.000,2021-01-14 02:19:03.000000,2021-01-14 02:18:46,138.0,43.0,58.0,1074,15.0,GraphVite: A General and High-performance Graph Embedding System.,,12,,,4.0,,,milagraph/graphvite,,,,,,,,122.0,https://anaconda.org/milagraph/graphvite,2020-03-19 18:21:30.972,4404.0,,,,,3.0,,,,,,,,,,,,,,,, +807,Hypermax,True,electricbrainio/hypermax,,hyperopt,https://github.com/electricbrainio/hypermax,https://github.com/electricbrainio/hypermax,BSD-3-Clause,2018-07-27 18:43:01.000,2020-08-02 18:08:50.000000,2020-08-02 18:08:46,13.0,3.0,2.0,103,207.0,"Better, faster hyper-parameter optimization.",9.0,12,,,,,hypermax,,,,,4.0,4.0,https://pypi.org/project/hypermax,30.0,30.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +808,OpenKE,True,thunlp/OpenKE,,graph,https://github.com/thunlp/OpenKE,https://github.com/thunlp/OpenKE,,2017-10-08 11:20:23.000,2021-09-29 09:46:39.000000,2021-04-06 08:24:50,896.0,5.0,348.0,3151,97.0,An Open-Source Package for Knowledge Embedding (KE).,10.0,11,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +809,Devol,True,joeddav/devol,,hyperopt,https://github.com/joeddav/devol,https://github.com/joeddav/devol,MIT,2017-02-10 03:07:54.000,2020-07-05 21:56:59.000000,2020-07-05 21:56:58,110.0,7.0,20.0,940,116.0,Genetic neural architecture search with Keras.,18.0,11,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +810,PySparNN,True,facebookresearch/pysparnn,,nn-search,https://github.com/facebookresearch/pysparnn,https://github.com/facebookresearch/pysparnn,BSD-3-Clause,2016-03-28 20:43:42.000,2020-10-02 06:01:01.000000,2018-01-31 16:50:23,142.0,15.0,14.0,902,147.0,Approximate Nearest Neighbor Search for Sparse Data in Python!.,5.0,11,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +811,Mozart,True,aashrafh/Mozart,,ocr,https://github.com/aashrafh/Mozart,https://github.com/aashrafh/Mozart,Apache-2.0,2020-12-14 11:49:14.000,2022-08-24 18:18:43.000000,2022-08-24 18:18:43,58.0,3.0,9.0,400,,An optical music recognition (OMR) system. Converts sheet..,5.0,11,,,,,,,,,['sklearn'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +812,Headliner,True,as-ideas/headliner,,nlp,https://github.com/as-ideas/headliner,https://github.com/as-ideas/headliner,,2019-09-30 11:33:28.000,2021-03-26 07:19:57.000000,2020-02-14 09:03:27,41.0,1.0,13.0,231,276.0,Easy training and deployment of seq2seq models.,2.0,11,,,,,headliner,,,,,3.0,3.0,https://pypi.org/project/headliner,117.0,117.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +813,ipyexperiments,True,stas00/ipyexperiments,,gpu-utilities,https://github.com/stas00/ipyexperiments,https://github.com/stas00/ipyexperiments,,2018-11-15 01:19:40.000,2021-12-07 18:50:39.000000,2021-12-07 18:50:38,11.0,,5.0,151,203.0,jupyter/ipython experiment containers for GPU and..,3.0,11,,,,,ipyexperiments,,,,['jupyter'],6.0,6.0,https://pypi.org/project/ipyexperiments,104.0,104.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +814,DeepNeuro,True,QTIM-Lab/DeepNeuro,,medical-data,https://github.com/QTIM-Lab/DeepNeuro,https://github.com/QTIM-Lab/DeepNeuro,MIT,2017-06-01 19:36:34.000,2020-06-24 13:00:15.000000,2020-06-24 13:00:14,34.0,25.0,16.0,111,285.0,A deep learning python package for neuroimaging data. Made by:.,6.0,11,,,,,deepneuro,,,,,1.0,1.0,https://pypi.org/project/deepneuro,20.0,20.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +815,Attribution Priors,True,suinleelab/attributionpriors,,interpretability,https://github.com/suinleelab/attributionpriors,https://github.com/suinleelab/attributionpriors,MIT,2019-06-24 23:54:24.000,2021-03-19 19:43:58.000000,2021-03-19 19:43:51,10.0,2.0,3.0,102,72.0,Tools for training explainable models using..,6.0,11,2021-03-16 17:47:18,1.0.0,1.0,,attributionpriors,,,,"['tensorflow', 'pytorch']",3.0,3.0,https://pypi.org/project/attributionpriors,18.0,18.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +816,bias-detector,True,intuit/bias-detector,,interpretability,https://github.com/intuit/bias-detector,https://github.com/intuit/bias-detector,MIT,2021-02-02 16:58:52.000,2021-12-20 16:28:25.000000,2021-12-20 16:28:25,11.0,,,40,,Bias Detector is a python package for detecting bias in machine..,4.0,11,2021-04-22 15:15:27,0.0.12,10.0,,bias-detector,,,,,,,https://pypi.org/project/bias-detector,48.0,48.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +817,nptsne,True,biovault/nptsne,,data-viz,https://github.com/biovault/nptsne,https://github.com/biovault/nptsne,Apache-2.0,2019-06-28 08:40:25.000,2022-03-16 13:45:37.000000,2021-02-03 08:52:27,2.0,7.0,6.0,29,857.0,nptsne is a numpy compatible python binary package that offers a number..,3.0,11,,,,,nptsne,,,,,4.0,4.0,https://pypi.org/project/nptsne,70.0,70.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +818,PandaPy,True,firmai/pandapy,,data-containers,https://github.com/firmai/pandapy,https://github.com/firmai/pandapy,,2020-01-15 18:21:23.000,2021-10-20 11:36:04.000000,2021-10-20 11:36:04,58.0,1.0,1.0,513,85.0,PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x..,3.0,10,2020-11-12 16:12:54,zen,1.0,,pandapy,,,,['pandas'],2.0,2.0,https://pypi.org/project/pandapy,71.0,71.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +819,Hypertunity,True,gdikov/hypertunity,,hyperopt,https://github.com/gdikov/hypertunity,https://github.com/gdikov/hypertunity,Apache-2.0,2019-06-02 12:04:55.000,2020-01-26 23:14:49.000000,2020-01-26 22:53:29,9.0,,2.0,122,64.0,A toolset for black-box hyperparameter optimisation.,2.0,10,2020-01-26 23:01:09,1.0.1,7.0,,hypertunity,,,,,2.0,2.0,https://pypi.org/project/hypertunity,18.0,18.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +820,traintool,True,jrieke/traintool,,ml-experiments,https://github.com/jrieke/traintool,https://github.com/jrieke/traintool,Apache-2.0,2020-09-30 22:23:05.000,2021-03-12 01:44:04.000000,2021-03-12 01:43:14,,,,10,122.0,Train off-the-shelf machine learning models in one..,,7,,,,,traintool,,,,"['pytorch', 'tensorflow', 'sklearn']",,,https://pypi.org/project/traintool,10.0,10.0,,,,,,,,3.0,,,,,,,,,,,,,,,, diff --git a/latest-changes.md b/latest-changes.md index e1ea810..6d22bba 100644 --- a/latest-changes.md +++ b/latest-changes.md @@ -2,19 +2,19 @@ _Projects that have a higher project-quality score compared to the last update. There might be a variety of reasons, such as increased downloads or code activity._ -- DeepSpeech (🥇30 · ⭐ 19K · 📈) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -- Keras Tuner (🥇30 · ⭐ 2.4K · 📈) - Hyperparameter tuning for humans. Apache-2 -- category_encoders (🥇30 · ⭐ 1.8K · 📈) - A library of sklearn compatible categorical variable.. BSD-3 -- Flax (🥈27 · ⭐ 2.4K · 📈) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax -- flashtext (🥈23 · ⭐ 5K · 💀) - Extract Keywords from sentence or Replace keywords in sentences. MIT +- Pillow (🥇36 · ⭐ 10K · 📈) - The friendly PIL fork (Python Imaging Library). ❗️PIL +- Streamlit (🥇30 · ⭐ 20K · 📈) - Streamlit The fastest way to build data apps in Python. Apache-2 +- pmdarima (🥇30 · ⭐ 1.2K · 📈) - A statistical library designed to fill the void in Python's time.. MIT +- TensorFlow Transform (🥈30 · ⭐ 930 · 📈) - Input pipeline framework. Apache-2 +- opencv-python (🥈25 · ⭐ 2.9K · 📈) - Automated CI toolchain to produce precompiled opencv-python,.. MIT ## 📉 Trending Down _Projects that have a lower project-quality score compared to the last update. There might be a variety of reasons such as decreased downloads or code activity._ -- Matplotlib (🥇33 · ⭐ 15K · 📉) - matplotlib: plotting with Python. ❗Unlicensed -- TF Addons (🥇27 · ⭐ 1.4K · 📉) - Useful extra functionality for TensorFlow 2.x maintained.. Apache-2 -- Pillow (🥈24 · ⭐ 9.2K · 📉) - The friendly PIL fork (Python Imaging Library). ❗️PIL -- TensorFlow Transform (🥈22 · ⭐ 900 · 📉) - Input pipeline framework. Apache-2 -- kaggle (🥉19 · ⭐ 4.5K · 💤) - Official Kaggle API. Apache-2 +- pytorch-lightning (🥈29 · ⭐ 20K · 📉) - The lightweight PyTorch wrapper for high-performance.. Apache-2 +- Seaborn (🥈29 · ⭐ 9.7K · 📉) - Statistical data visualization using matplotlib. BSD-3 +- audioread (🥉19 · ⭐ 410 · 📉) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT +- Torch Points 3D (🥉14 · ⭐ 93 · 💤) - Pytorch framework for doing deep learning on point.. BSD-3 +- cleanlab (🥉13 · ⭐ 49 · 🐣) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 From aacdc41719069254919a2104eb0f4feff5fa2b99 Mon Sep 17 00:00:00 2001 From: HanXinzi2020 Date: Fri, 26 Aug 2022 12:29:46 +0800 Subject: [PATCH 2/2] update --- README.md | 1924 ++++++++++++++++++++++++++--------------------------- 1 file changed, 962 insertions(+), 962 deletions(-) diff --git a/README.md b/README.md index 9c99ba2..29d3953 100644 --- a/README.md +++ b/README.md @@ -15,75 +15,75 @@

本资源清单包含820个python机器学习相关的开源工具资源，这些热门工具总共分成32个不同的子板块，这些项目目前在github上已经收到3.5M个点赞。所有的工具资源每周会自动从GitHub和工具维护平台采集信息，并更新排行展示。本清单参考[best-of模板](https://github.com/best-of-lists/best-of)完成，内容参考了[awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)，欢迎大家提PR丰富本清单。 -## Contents - -- [Machine Learning Frameworks](#machine-learning-frameworks) _54 projects_ -- [Data Visualization](#data-visualization) _49 projects_ -- [Text Data & NLP](#text-data--nlp) _82 projects_ -- [Image Data](#image-data) _49 projects_ -- [Graph Data](#graph-data) _29 projects_ -- [Audio Data](#audio-data) _23 projects_ -- [Geospatial Data](#geospatial-data) _22 projects_ -- [Financial Data](#financial-data) _23 projects_ -- [Time Series Data](#time-series-data) _20 projects_ -- [Medical Data](#medical-data) _19 projects_ -- [Optical Character Recognition](#optical-character-recognition) _11 projects_ -- [Data Containers & Structures](#data-containers--structures) _28 projects_ -- [Data Loading & Extraction](#data-loading--extraction) _23 projects_ -- [Web Scraping & Crawling](#web-scraping--crawling) _1 projects_ -- [Data Pipelines & Streaming](#data-pipelines--streaming) _36 projects_ -- [Distributed Machine Learning](#distributed-machine-learning) _26 projects_ -- [Hyperparameter Optimization & AutoML](#hyperparameter-optimization--automl) _45 projects_ -- [Reinforcement Learning](#reinforcement-learning) _19 projects_ -- [Recommender Systems](#recommender-systems) _13 projects_ -- [Privacy Machine Learning](#privacy-machine-learning) _6 projects_ -- [Workflow & Experiment Tracking](#workflow--experiment-tracking) _35 projects_ -- [Model Serialization & Conversion](#model-serialization--conversion) _11 projects_ -- [Model Interpretability](#model-interpretability) _46 projects_ -- [Vector Similarity Search (ANN)](#vector-similarity-search-ann) _12 projects_ -- [Probabilistics & Statistics](#probabilistics--statistics) _21 projects_ -- [Adversarial Robustness](#adversarial-robustness) _7 projects_ -- [GPU Utilities](#gpu-utilities) _18 projects_ -- [Tensorflow Utilities](#tensorflow-utilities) _13 projects_ -- [Sklearn Utilities](#sklearn-utilities) _17 projects_ -- [Pytorch Utilities](#pytorch-utilities) _27 projects_ -- [Database Clients](#database-clients) _1 projects_ -- [Chinese NLP](#chinese-nlp) _2 projects_ -- [Others](#others) _33 projects_ - -## Explanation -- 🥇🥈🥉  Combined project-quality score -- ⭐️  Star count from GitHub -- 🐣  New project _(less than 6 months old)_ -- 💤  Inactive project _(6 months no activity)_ -- 💀  Dead project _(12 months no activity)_ -- 📈📉  Project is trending up or down -- ➕  Project was recently added -- ❗️  Warning _(e.g. missing/risky license)_ -- 👨‍💻  Contributors count from GitHub -- 🔀  Fork count from GitHub -- 📋  Issue count from GitHub -- ⏱️  Last update timestamp on package manager -- 📥  Download count from package manager -- 📦  Number of dependent projects --   Tensorflow related project --   Sklearn related project --   PyTorch related project --   MxNet related project --   Apache Spark related project --   Jupyter related project --   PaddlePaddle related project --   Pandas related project +## 目录 + +- [机器学习框架](#机器学习框架) _54 个项目_ +- [数据可视化](#数据可视化) _49 个项目_ +- [文本数据和NLP](#文本数据和NLP) _82 个项目_ +- [图像数据与CV](#图像数据与CV) _49 个项目_ +- [图数据处理](#图数据处理) _29 个项目_ +- [音频处理](#音频处理) _23 个项目_ +- [地理Geo处理](#地理Geo处理) _22 个项目_ +- [金融数据处理](#金融数据处理) _23 个项目_ +- [时间序列](#时间序列) _20 个项目_ +- [医疗领域](#医疗领域) _19 个项目_ +- [光学字符识别OCR](#光学字符识别OCR) _11 个项目_ +- [数据容器和结构](#数据容器和结构) _28 个项目_ +- [数据读写与提取](#数据读写与提取) _23 个项目_ +- [网页抓取和爬虫](#网页抓取和爬虫) _1 个项目_ +- [数据管道和流处理](#数据管道和流处理) _36 个项目_ +- [分布式机器学习](#分布式机器学习) _26 个项目_ +- [超参数优化和AutoML](#超参数优化和AutoML) _45 个项目_ +- [强化学习](#强化学习) _19 个项目_ +- [推荐系统](#推荐系统) _13 个项目_ +- [隐私机器学习](#隐私机器学习) _6 个项目_ +- [工作流程和实验跟踪](#工作流程和实验跟踪) _35 个项目_ +- [模型序列化和转换](#模型序列化和转换) _11 个项目_ +- [模型的可解释性](#模型的可解释性) _46 个项目_ +- [向量相似度搜索（ANN）](#向量相似度搜索（ANN）) _12 个项目_ +- [概率统计](#概率统计) _21 个项目_ +- [对抗学习与鲁棒性](#对抗学习与鲁棒性) _7 个项目_ +- [GPU实用程序](#GPU实用程序) _18 个项目_ +- [Tensorflow实用程序](#Tensorflow实用程序) _13 个项目_ +- [Sklearn实用程序](#Sklearn实用程序) _17 个项目_ +- [Pytorch实用程序](#Pytorch实用程序) _27 个项目_ +- [数据库客户端](#数据库客户端) _1 个项目_ +- [中文自然语言处理](#中文自然语言处理) _2 个项目_ +- [Others](#Others) _33 个项目_ + +## 图标解释 +- 🥇🥈🥉  综合项目质量分 +- ⭐️  github上star的数量 +- 🐣  小于6个月的新项目 +- 💤  非活跃项目(6个月未更新) +- 💀  沉寂项目(12个月未更新) +- 📈📉  项目趋势(向上or向下) +- ➕  最近添加的项目 +- ❗️  警告(例如 项目没有license) +- 👨‍💻  项目的开发贡献者数量 +- 🔀  项目被fork的数量 +- 📋  项目issue的数量 +- ⏱️  项目包上次更新时间 +- 📥  工具库被下载次数 +- 📦  项目依赖的工具库数量 +-   Tensorflow相关项目 +-   Sklearn相关项目 +-   pytorch相关项目 +-   MxNet相关项目 +-   Apache Spark相关项目 +-   Jupyter相关项目 +-   PaddlePaddle相关项目 +-   Pandas相关项目
-## Machine Learning Frameworks +## 机器学习框架 -Back to top +Back to top -_General-purpose machine learning and deep learning frameworks._ +_通用机器学习和深度学习框架。_ -
Tensorflow (🥇44 · ⭐ 170K) - An Open Source Machine Learning Framework for Everyone. Apache-2 +
Tensorflow (🥇44 · ⭐ 170K) - 适用于所有人的开源机器学习框架。Apache-2 - [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 4.1K · 🔀 70K · 📦 210K · 📋 35K - 5% open · ⏱️ 26.08.2022): @@ -103,7 +103,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull tensorflow/tensorflow ```
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scikit-learn (🥇39 · ⭐ 51K) - scikit-learn: machine learning in Python. BSD-3 +
scikit-learn (🥇39 · ⭐ 51K) - scikit-learn：基于Python的机器学习工具库。BSD-3 - [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.7K · 🔀 23K · 📥 810 · 📦 390K · 📋 9.6K - 16% open · ⏱️ 26.08.2022): @@ -119,7 +119,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge scikit-learn ```
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XGBoost (🥇37 · ⭐ 23K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 +
XGBoost (🥇37 · ⭐ 23K) - 可扩展，高效和分布式梯度增强（GBDT，GBRT等）的boosting工具库。Apache-2 - [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 570 · 🔀 7.9K · 📥 5K · 📦 35K · 📋 4.5K - 5% open · ⏱️ 25.08.2022): @@ -135,7 +135,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge xgboost ```
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LightGBM (🥇35 · ⭐ 14K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT +
LightGBM (🥇35 · ⭐ 14K) - 快速，分布式，高性能梯度提升（GBT，GBDT，GBRT等）的boosting工具库。MIT - [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 270 · 🔀 3.5K · 📥 160K · 📦 15K · 📋 2.8K - 7% open · ⏱️ 25.08.2022): @@ -151,7 +151,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge lightgbm ```
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Fastai (🥇34 · ⭐ 23K) - The fastai deep learning library. Apache-2 +
Fastai (🥇34 · ⭐ 23K) - Fastai深度学习库。Apache-2 - [GitHub](https://github.com/fastai/fastai) (👨‍💻 210 · 🔀 7.1K · 📦 11K · 📋 1.7K - 6% open · ⏱️ 19.08.2022): @@ -163,7 +163,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install fastai ```
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Thinc (🥇34 · ⭐ 2.6K) - A refreshing functional take on deep learning, compatible with your favorite.. MIT +
Thinc (🥇34 · ⭐ 2.6K) - 深度学习工具库。MIT - [GitHub](https://github.com/explosion/thinc) (👨‍💻 53 · 🔀 240 · 📦 23K · 📋 120 - 11% open · ⏱️ 05.08.2022): @@ -179,7 +179,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge thinc ```
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PyTorch (🥈33 · ⭐ 58K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +
PyTorch (🥈33 · ⭐ 58K) - 具有强大GPU的Python中的张量和动态神经网络构建工具库。BSD-3 - [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 3.5K · 🔀 16K · 📥 5.6K · 📋 28K - 32% open · ⏱️ 26.08.2022): @@ -195,7 +195,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c pytorch pytorch ```
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dlib (🥈33 · ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 +
dlib (🥈33 · ⭐ 11K) - 进行现实世界机器学习和数据分析的工具包。❗️BSL-1.0 - [GitHub](https://github.com/davisking/dlib) (👨‍💻 180 · 🔀 2.7K · 📥 25K · 📦 16K · 📋 2.1K - 1% open · ⏱️ 26.08.2022): @@ -211,7 +211,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge dlib ```
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Keras (🥈32 · ⭐ 56K) - Deep Learning for humans. Apache-2 +
Keras (🥈32 · ⭐ 56K) - 易上手的深度学习工具库。Apache-2 - [GitHub](https://github.com/keras-team/keras) (👨‍💻 1.1K · 🔀 18K · 📋 11K - 2% open · ⏱️ 26.08.2022): @@ -227,7 +227,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge keras ```
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PySpark (🥈32 · ⭐ 34K) - Apache Spark Python API. Apache-2 +
PySpark (🥈32 · ⭐ 34K) - Apache Spark Python API。Apache-2 - [GitHub](https://github.com/apache/spark) (👨‍💻 2.7K · 🔀 25K · ⏱️ 26.08.2022): @@ -243,7 +243,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge pyspark ```
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PaddlePaddle (🥈32 · ⭐ 19K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 +
PaddlePaddle (🥈32 · ⭐ 19K) - paddlepaddle机器学习与深度学习工具库。Apache-2 - [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 810 · 🔀 4.5K · 📥 15K · 📦 140 · 📋 15K - 14% open · ⏱️ 26.08.2022): @@ -255,7 +255,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install paddlepaddle ```
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Jina (🥈32 · ⭐ 16K) - An easier way to build neural search on the cloud. Apache-2 +
Jina (🥈32 · ⭐ 16K) - 在云端构建神经搜索的简便方法库。Apache-2 - [GitHub](https://github.com/jina-ai/jina) (👨‍💻 150 · 🔀 1.9K · 📦 350 · 📋 1.6K - 1% open · ⏱️ 25.08.2022): @@ -271,7 +271,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull jinaai/jina ```
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StatsModels (🥈32 · ⭐ 7.7K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 +
StatsModels (🥈32 · ⭐ 7.7K) - Statsmodels：Python中的统计建模和计量经济学工具库。BSD-3 - [GitHub](https://github.com/statsmodels/statsmodels) (👨‍💻 380 · 🔀 2.4K · 📥 26 · 📦 68K · 📋 4.8K - 46% open · ⏱️ 23.08.2022): @@ -287,7 +287,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge statsmodels ```
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jax (🥈31 · ⭐ 20K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 +
jax (🥈31 · ⭐ 20K) - Python + NumPy程序工具库。Apache-2 - [GitHub](https://github.com/google/jax) (👨‍💻 440 · 🔀 1.8K · 📦 5.3K · 📋 3.4K - 24% open · ⏱️ 26.08.2022): @@ -303,7 +303,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge jaxlib ```
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Chainer (🥈31 · ⭐ 5.7K) - A flexible framework of neural networks for deep learning. MIT +
Chainer (🥈31 · ⭐ 5.7K) - 灵活的深度学习神经网络框架。MIT - [GitHub](https://github.com/chainer/chainer) (👨‍💻 320 · 🔀 1.3K · 📦 2.7K · 📋 2K - 0% open · ⏱️ 29.06.2022): @@ -315,7 +315,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install chainer ```
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Theano (🥈30 · ⭐ 9.6K · 💤) - Theano is a Python library that allows you to define,.. ❗Unlicensed +
Theano (🥈30 · ⭐ 9.6K · 💤) - Theano是一个Python神经网络工具库。❗Unlicensed - [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 13K · 📋 2.7K - 21% open · ⏱️ 23.11.2021): @@ -331,7 +331,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge theano ```
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einops (🥈30 · ⭐ 5.5K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT +
einops (🥈30 · ⭐ 5.5K) - 重塑了深度学习操作（用于pytorch，tensorflow，jax等）的工具库。MIT - [GitHub](https://github.com/arogozhnikov/einops) (👨‍💻 20 · 🔀 240 · 📦 3.9K · 📋 120 - 28% open · ⏱️ 24.08.2022): @@ -347,7 +347,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge einops ```
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MXNet (🥈29 · ⭐ 20K) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning.. Apache-2 +
MXNet (🥈29 · ⭐ 20K) - 轻巧，灵活的分布式/移动深度学习工具库。Apache-2 - [GitHub](https://github.com/apache/incubator-mxnet) (👨‍💻 980 · 🔀 6.5K · 📥 25K · 📋 9.5K - 18% open · ⏱️ 23.08.2022): @@ -363,7 +363,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c anaconda mxnet ```
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pytorch-lightning (🥈29 · ⭐ 20K · 📉) - The lightweight PyTorch wrapper for high-performance.. Apache-2 +
pytorch-lightning (🥈29 · ⭐ 20K · 📉) - 轻巧而具备高性能的PyTorch上层封装工具库。Apache-2 - [GitHub](https://github.com/Lightning-AI/lightning) (👨‍💻 740 · 🔀 2.5K · 📥 8K · 📋 5.3K - 8% open · ⏱️ 25.08.2022): @@ -379,7 +379,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge pytorch-lightning ```
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Vowpal Wabbit (🥈28 · ⭐ 8K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 +
Vowpal Wabbit (🥈28 · ⭐ 8K) - Vowpal Wabbit是一个推动机器学习的机器学习系统。BSD-3 - [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 320 · 🔀 1.7K · 📋 1.2K - 10% open · ⏱️ 25.08.2022): @@ -391,7 +391,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install vowpalwabbit ```
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Catboost (🥈28 · ⭐ 6.7K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 +
Catboost (🥈28 · ⭐ 6.7K) - 快速，可扩展，高性能的梯度决策提升工具库。Apache-2 - [GitHub](https://github.com/catboost/catboost) (👨‍💻 1K · 🔀 990 · 📥 86K · 📋 1.9K - 21% open · ⏱️ 21.08.2022): @@ -407,7 +407,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge catboost ```
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Flax (🥈28 · ⭐ 3.5K) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax +
Flax (🥈28 · ⭐ 3.5K) - Flax是专为.NET设计的用于JAX的神经网络库。Apache-2 jax - [GitHub](https://github.com/google/flax) (👨‍💻 170 · 🔀 380 · 📥 42 · 📦 1.3K · 📋 550 - 17% open · ⏱️ 25.08.2022): @@ -419,7 +419,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install flax ```
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dyNET (🥈28 · ⭐ 3.3K) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 +
dyNET (🥈28 · ⭐ 3.3K) - DyNet：动态神经网络工具包。Apache-2 - [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 6.9K · 📦 220 · 📋 920 - 27% open · ⏱️ 14.08.2022): @@ -431,7 +431,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install dyNET ```
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PyFlink (🥉27 · ⭐ 20K) - Apache Flink Python API. Apache-2 +
PyFlink (🥉27 · ⭐ 20K) - Apache Flink Python API。Apache-2 - [GitHub](https://github.com/apache/flink) (👨‍💻 1.6K · 🔀 11K · ⏱️ 26.08.2022): @@ -443,7 +443,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install apache-flink ```
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TFlearn (🥉27 · ⭐ 9.6K · 💀) - Deep learning library featuring a higher-level API for.. ❗Unlicensed +
TFlearn (🥉27 · ⭐ 9.6K · 💀) - 深度学习库，基于TensorFlow构建上层简单易用的API。❗Unlicensed - [GitHub](https://github.com/tflearn/tflearn) (👨‍💻 130 · 🔀 2.3K · 📦 4.1K · 📋 910 - 60% open · ⏱️ 30.11.2020): @@ -455,7 +455,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tflearn ```
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Sonnet (🥉27 · ⭐ 9.4K) - TensorFlow-based neural network library. Apache-2 +
Sonnet (🥉27 · ⭐ 9.4K) - 基于TensorFlow的神经网络库。Apache-2 - [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 54 · 🔀 1.2K · 📦 900 · 📋 180 - 14% open · ⏱️ 23.08.2022): @@ -471,7 +471,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge sonnet ```
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Ludwig (🥉27 · ⭐ 8.5K) - Ludwig is a toolbox that allows to train and evaluate deep.. Apache-2 +
Ludwig (🥉27 · ⭐ 8.5K) - 路德维希（Ludwig）是一个工具箱，可用于深度学习训练和评估。Apache-2 - [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 130 · 🔀 960 · 📦 130 · 📋 820 - 23% open · ⏱️ 25.08.2022): @@ -483,7 +483,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install ludwig ```
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tensorpack (🥉27 · ⭐ 6.2K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 +
tensorpack (🥉27 · ⭐ 6.2K) - TensorFlow上的神经网络训练接口。Apache-2 - [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 58 · 🔀 1.8K · 📥 140 · 📦 1.1K · 📋 1.3K - 0% open · ⏱️ 04.05.2022): @@ -495,7 +495,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tensorpack ```
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skorch (🥉26 · ⭐ 4.6K) - A scikit-learn compatible neural network library that wraps.. BSD-3 +
skorch (🥉26 · ⭐ 4.6K) - 封装成scikit-learn接口模式的神经网络库。BSD-3 - [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 50 · 🔀 310 · 📦 550 · 📋 440 - 9% open · ⏱️ 22.08.2022): @@ -511,7 +511,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge skorch ```
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Ignite (🥉26 · ⭐ 4K) - High-level library to help with training and evaluating neural.. BSD-3 +
Ignite (🥉26 · ⭐ 4K) - 用于训练和评估神经等一系列操作的高级深度学习工具库。BSD-3 - [GitHub](https://github.com/pytorch/ignite) (👨‍💻 180 · 🔀 540 · 📋 1.1K - 10% open · ⏱️ 25.08.2022): @@ -527,7 +527,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c pytorch ignite ```
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ktrain (🥉26 · ⭐ 1K) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 +
ktrain (🥉26 · ⭐ 1K) - ktrain是一个Python库，可以使深度学习和AI更简单。Apache-2 - [GitHub](https://github.com/amaiya/ktrain) (👨‍💻 15 · 🔀 240 · 📦 330 · 📋 420 - 0% open · ⏱️ 04.08.2022): @@ -539,7 +539,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install ktrain ```
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Turi Create (🥉25 · ⭐ 11K · 💤) - Turi Create simplifies the development of custom machine.. BSD-3 +
Turi Create (🥉25 · ⭐ 11K · 💤) - Turi Create简化了自定义机器学习的开发。BSD-3 - [GitHub](https://github.com/apple/turicreate) (👨‍💻 85 · 🔀 1.1K · 📥 6.8K · 📦 320 · 📋 1.8K - 27% open · ⏱️ 29.11.2021): @@ -551,7 +551,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install turicreate ```
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xLearn (🥉25 · ⭐ 3K) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 +
xLearn (🥉25 · ⭐ 3K) - 高性能，易于使用且可扩展的机器学习（ML）工具库。Apache-2 - [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 3.4K · 📦 93 · 📋 300 - 61% open · ⏱️ 05.06.2022): @@ -563,7 +563,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install xlearn ```
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NuPIC (🥉24 · ⭐ 6.3K · 💀) - Numenta Platform for Intelligent Computing is an implementation.. ❗️AGPL-3.0 +
NuPIC (🥉24 · ⭐ 6.3K · 💀) - Numenta智能计算平台。❗️AGPL-3.0 - [GitHub](https://github.com/numenta/nupic) (👨‍💻 120 · 🔀 1.6K · 📦 110 · 📋 1.8K - 25% open · ⏱️ 23.10.2019): @@ -575,7 +575,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nupic ```
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fklearn (🥉24 · ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 +
fklearn (🥉24 · ⭐ 1.4K) - fklearn：机器学习工具库。Apache-2 - [GitHub](https://github.com/nubank/fklearn) (👨‍💻 47 · 🔀 160 · 📦 13 · 📋 48 - 54% open · ⏱️ 25.08.2022): @@ -587,7 +587,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install fklearn ```
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tensorflow-upstream (🥉24 · ⭐ 610) - TensorFlow ROCm port. Apache-2 +
tensorflow-upstream (🥉24 · ⭐ 610) - TensorFlow ROCm端口。Apache-2 - [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 4.1K · 🔀 71 · 📥 20 · 📋 330 - 16% open · ⏱️ 23.08.2022): @@ -599,7 +599,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tensorflow-rocm ```
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mlpack (🥉23 · ⭐ 4.1K) - mlpack: a scalable C++ machine learning library --. ❗Unlicensed +
mlpack (🥉23 · ⭐ 4.1K) - mlpack：可扩展的C++机器学习库-。❗Unlicensed - [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 290 · 🔀 1.4K · 📋 1.4K - 2% open · ⏱️ 18.08.2022): @@ -615,7 +615,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge mlpack ```
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Neural Network Libraries (🥉23 · ⭐ 2.6K) - Neural Network Libraries. Apache-2 +
Neural Network Libraries (🥉23 · ⭐ 2.6K) - 神经网络工具库。Apache-2 - [GitHub](https://github.com/sony/nnabla) (👨‍💻 67 · 🔀 310 · 📥 540 · 📋 72 - 31% open · ⏱️ 25.08.2022): @@ -627,7 +627,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nnabla ```
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Neural Tangents (🥉23 · ⭐ 1.8K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 +
Neural Tangents (🥉23 · ⭐ 1.8K) - Python中的快速简便的无限神经网络。Apache-2 - [GitHub](https://github.com/google/neural-tangents) (👨‍💻 23 · 🔀 200 · 📥 240 · 📦 47 · 📋 120 - 34% open · ⏱️ 19.08.2022): @@ -639,7 +639,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install neural-tangents ```
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CNTK (🥉22 · ⭐ 17K · 💀) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning.. ❗Unlicensed +
CNTK (🥉22 · ⭐ 17K · 💀) - Microsoft认知工具包（CNTK），一种开源的深度学习工具包。❗Unlicensed - [GitHub](https://github.com/microsoft/CNTK) (👨‍💻 270 · 🔀 4.3K · 📥 14K · 📋 3.3K - 22% open · ⏱️ 31.03.2020): @@ -651,7 +651,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install cntk ```
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Lasagne (🥉22 · ⭐ 3.8K · 💀) - Lightweight library to build and train neural networks in.. ❗Unlicensed +
Lasagne (🥉22 · ⭐ 3.8K · 💀) - 轻量级的库，用于在Theano中构建和训练神经网络。❗Unlicensed - [GitHub](https://github.com/Lasagne/Lasagne) (👨‍💻 72 · 🔀 930 · 📦 920 · 📋 520 - 22% open · ⏱️ 20.11.2019): @@ -663,7 +663,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install lasagne ```
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SHOGUN (🥉22 · ⭐ 2.9K · 💀) - Unified and efficient Machine Learning. BSD-3 +
SHOGUN (🥉22 · ⭐ 2.9K · 💀) - 统一高效的机器学习。BSD-3 - [GitHub](https://github.com/shogun-toolbox/shogun) (👨‍💻 250 · 🔀 1K · 📋 1.5K - 27% open · ⏱️ 08.12.2020): @@ -679,7 +679,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull shogun/shogun ```
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NeuPy (🥉22 · ⭐ 710 · 💀) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT +
NeuPy (🥉22 · ⭐ 710 · 💀) - NeuPy是一个基于Tensorflow的python库，用于原型设计和构建。MIT - [GitHub](https://github.com/itdxer/neupy) (👨‍💻 7 · 🔀 150 · 📦 130 · 📋 270 - 12% open · ⏱️ 02.09.2019): @@ -691,7 +691,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install neupy ```
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Haiku (🥉21 · ⭐ 2.1K) - JAX-based neural network library. Apache-2 +
Haiku (🥉21 · ⭐ 2.1K) - 基于JAX的神经网络库。Apache-2 - [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 63 · 🔀 170 · 📦 540 · 📋 180 - 26% open · ⏱️ 25.08.2022): @@ -699,7 +699,7 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/deepmind/dm-haiku ```
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mace (🥉20 · ⭐ 4.7K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 +
mace (🥉20 · ⭐ 4.7K) - MACE是针对移动设备优化的深度学习推理框架。Apache-2 - [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 64 · 🔀 790 · 📥 1.4K · 📋 660 - 7% open · ⏱️ 30.05.2022): @@ -707,7 +707,7 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/XiaoMi/mace ```
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Objax (🥉20 · ⭐ 720) - Objax is a machine learning framework that provides an Object.. Apache-2 jax +
Objax (🥉20 · ⭐ 720) - Objax是加速研究与应用的开源深度学习框架。Apache-2 jax - [GitHub](https://github.com/google/objax) (👨‍💻 23 · 🔀 60 · 📦 25 · 📋 98 - 38% open · ⏱️ 12.07.2022): @@ -719,7 +719,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install objax ```
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MindsDB (🥉19 · ⭐ 9.7K) - Predictive AI layer for existing databases. ❗️GPL-3.0 +
MindsDB (🥉19 · ⭐ 9.7K) - 为各种现有数据库提供预测性AI层。❗️GPL-3.0 - [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 130 · 🔀 1K · 📋 1.2K - 11% open · ⏱️ 25.08.2022): @@ -731,7 +731,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install mindsdb ```
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neon (🥉19 · ⭐ 3.9K · 💀) - Intel Nervana reference deep learning framework committed to best.. Apache-2 +
neon (🥉19 · ⭐ 3.9K · 💀) - 英特尔Nervana深度学习框架。Apache-2 - [GitHub](https://github.com/NervanaSystems/neon) (👨‍💻 110 · 🔀 800 · 📥 340 · 📋 390 - 21% open · ⏱️ 22.05.2019): @@ -743,7 +743,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nervananeon ```
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ThunderSVM (🥉19 · ⭐ 1.4K) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. Apache-2 +
ThunderSVM (🥉19 · ⭐ 1.4K) - ThunderSVM：在GPU和CPU上的快速SVM库。Apache-2 - [GitHub](https://github.com/Xtra-Computing/thundersvm) (👨‍💻 34 · 🔀 190 · 📥 2.5K · 📋 210 - 29% open · ⏱️ 09.04.2022): @@ -755,7 +755,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install thundersvm ```
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Torchbearer (🥉19 · ⭐ 630 · 💀) - torchbearer: A model fitting library for PyTorch. MIT +
Torchbearer (🥉19 · ⭐ 630 · 💀) - torchbearer：PyTorch的模型拟合库。MIT - [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 66 · 📦 64 · 📋 250 - 4% open · ⏱️ 26.03.2021): @@ -767,7 +767,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install torchbearer ```
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elegy (🥉18 · ⭐ 400) - Elegy is a framework-agnostic Trainer interface for the Jax.. MIT jax +
elegy (🥉18 · ⭐ 400) - Elegy是Jax的与框架无关的Trainer工具。MIT jax - [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 17 · 🔀 26 · 📋 100 - 34% open · ⏱️ 23.05.2022): @@ -779,7 +779,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install elegy ```
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ThunderGBM (🥉17 · ⭐ 640) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 +
ThunderGBM (🥉17 · ⭐ 640) - ThunderGBM：GPU上的快速GBDT和随机森林。Apache-2 - [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 82 · 📋 74 - 50% open · ⏱️ 09.08.2022): @@ -791,7 +791,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install thundergbm ```
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NeoML (🥉15 · ⭐ 690) - Machine learning framework for both deep learning and traditional.. Apache-2 +
NeoML (🥉15 · ⭐ 690) - neoml是可以用于深度学习和传统机器学习的工具库。Apache-2 - [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 32 · 🔀 110 · 📋 62 - 22% open · ⏱️ 24.08.2022): @@ -799,7 +799,7 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/neoml-lib/neoml ```
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StarSpace (🥉12 · ⭐ 3.8K · 💀) - Learning embeddings for classification, retrieval and ranking. MIT +
StarSpace (🥉12 · ⭐ 3.8K · 💀) - 学习embedding嵌入用于分类，检索和排序。MIT - [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 510 · 📋 200 - 24% open · ⏱️ 13.12.2019): @@ -809,13 +809,13 @@ _General-purpose machine learning and deep learning frameworks._

-## Data Visualization +## 数据可视化 -Back to top +Back to top -_General-purpose and task-specific data visualization libraries._ +_通用和特定于任务的数据可视化库。_ -
Matplotlib (🥇36 · ⭐ 16K) - matplotlib: plotting with Python. ❗Unlicensed +
Matplotlib (🥇36 · ⭐ 16K) - matplotlib：Python绘图工具库。❗Unlicensed - [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.4K · 🔀 6.3K · 📦 610K · 📋 8.8K - 17% open · ⏱️ 26.08.2022): @@ -831,7 +831,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge matplotlib ```
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pandas-profiling (🥇33 · ⭐ 9.4K) - Create HTML profiling reports from pandas DataFrame.. MIT +
pandas-profiling (🥇33 · ⭐ 9.4K) - 从pandas DataFrame创建HTML分析报告。MIT - [GitHub](https://github.com/ydataai/pandas-profiling) (👨‍💻 92 · 🔀 1.3K · 📦 8.8K · 📋 580 - 19% open · ⏱️ 25.08.2022): @@ -847,7 +847,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pandas-profiling ```
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Altair (🥇33 · ⭐ 7.7K) - Declarative statistical visualization library for Python. BSD-3 +
Altair (🥇33 · ⭐ 7.7K) - 用于Python的声明式统计可视化库。BSD-3 - [GitHub](https://github.com/altair-viz/altair) (👨‍💻 140 · 🔀 650 · 📦 32K · 📋 1.6K - 13% open · ⏱️ 23.08.2022): @@ -863,7 +863,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge altair ```
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dash (🥇32 · ⭐ 17K) - Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript.. MIT +
dash (🥇32 · ⭐ 17K) - 适用于Python，R，Julia和Jupyter的分析型Web应用程序。MIT - [GitHub](https://github.com/plotly/dash) (👨‍💻 120 · 🔀 1.7K · 📦 220 · 📋 1.3K - 47% open · ⏱️ 19.08.2022): @@ -879,7 +879,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dash ```
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Plotly (🥇32 · ⭐ 12K) - The interactive graphing library for Python (includes Plotly Express). MIT +
Plotly (🥇32 · ⭐ 12K) - 适用于Python的交互式图形库（包括Plotly Express）。MIT - [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 200 · 🔀 2.1K · 📦 12 · 📋 2.4K - 49% open · ⏱️ 11.08.2022): @@ -899,7 +899,7 @@ _General-purpose and task-specific data visualization libraries._ npm install plotlywidget ```
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UMAP (🥇32 · ⭐ 5.7K) - Uniform Manifold Approximation and Projection. BSD-3 +
UMAP (🥇32 · ⭐ 5.7K) - 均匀流形逼近和投影。BSD-3 - [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 100 · 🔀 630 · 📦 6K · 📋 640 - 52% open · ⏱️ 23.08.2022): @@ -911,7 +911,7 @@ _General-purpose and task-specific data visualization libraries._ pip install umap-learn ```
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Graphviz (🥈30 · ⭐ 1.3K) - Simple Python interface for Graphviz. MIT +
Graphviz (🥈30 · ⭐ 1.3K) - Graphviz的简单Python界面。MIT - [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 19 · 🔀 180 · 📦 34K · 📋 140 - 4% open · ⏱️ 27.07.2022): @@ -923,7 +923,7 @@ _General-purpose and task-specific data visualization libraries._ pip install graphviz ```
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Seaborn (🥈29 · ⭐ 9.7K · 📉) - Statistical data visualization using matplotlib. BSD-3 +
Seaborn (🥈29 · ⭐ 9.7K · 📉) - 使用matplotlib进行统计数据可视化。BSD-3 - [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 170 · 🔀 1.6K · 📥 230 · 📋 2.1K - 4% open · ⏱️ 26.08.2022): @@ -939,7 +939,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge seaborn ```
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datashader (🥈29 · ⭐ 2.8K) - Quickly and accurately render even the largest data. BSD-3 +
datashader (🥈29 · ⭐ 2.8K) - 快速准确地渲染大数据。BSD-3 - [GitHub](https://github.com/holoviz/datashader) (👨‍💻 49 · 🔀 340 · 📦 1.3K · 📋 500 - 23% open · ⏱️ 10.08.2022): @@ -955,7 +955,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge datashader ```
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Bokeh (🥈28 · ⭐ 17K) - Interactive Data Visualization in the browser, from Python. BSD-3 +
Bokeh (🥈28 · ⭐ 17K) - 浏览器中的Python交互式数据可视化。BSD-3 - [GitHub](https://github.com/bokeh/bokeh) (👨‍💻 610 · 🔀 3.9K · 📦 150 · 📋 7K - 9% open · ⏱️ 24.08.2022): @@ -971,7 +971,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge bokeh ```
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pyecharts (🥈28 · ⭐ 13K) - Python Echarts Plotting Library. MIT +
pyecharts (🥈28 · ⭐ 13K) - Python Echarts绘图库。MIT - [GitHub](https://github.com/pyecharts/pyecharts) (👨‍💻 30 · 🔀 2.7K · 📦 2.4K · 📋 1.6K - 1% open · ⏱️ 25.04.2022): @@ -983,7 +983,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pyecharts ```
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missingno (🥈28 · ⭐ 3.3K) - Missing data visualization module for Python. MIT +
missingno (🥈28 · ⭐ 3.3K) - 在缺失值和混乱数据下，用于数据可视化的python模块。MIT - [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 410 · 📦 8.3K · 📋 120 - 6% open · ⏱️ 27.02.2022): @@ -999,7 +999,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge missingno ```
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D-Tale (🥈27 · ⭐ 3.6K) - Visualizer for pandas data structures. ❗️LGPL-2.1 +
D-Tale (🥈27 · ⭐ 3.6K) - pandas数据结构的可视化工具。❗️LGPL-2.1 - [GitHub](https://github.com/man-group/dtale) (👨‍💻 27 · 🔀 290 · 📦 460 · 📋 470 - 8% open · ⏱️ 07.08.2022): @@ -1015,7 +1015,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dtale ```
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bqplot (🥈27 · ⭐ 3.3K) - Plotting library for IPython/Jupyter notebooks. Apache-2 +
bqplot (🥈27 · ⭐ 3.3K) - 用于IPython / Jupyter笔记本的绘图库。Apache-2 - [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 59 · 🔀 440 · 📦 34 · 📋 570 - 36% open · ⏱️ 22.08.2022): @@ -1035,7 +1035,7 @@ _General-purpose and task-specific data visualization libraries._ npm install bqplot ```
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data-validation (🥈27 · ⭐ 660) - Library for exploring and validating machine learning.. Apache-2 +
data-validation (🥈27 · ⭐ 660) - 用于探索和验证机器学习的库。Apache-2 - [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 24 · 🔀 130 · 📥 370 · 📦 540 · 📋 150 - 16% open · ⏱️ 24.08.2022): @@ -1047,7 +1047,7 @@ _General-purpose and task-specific data visualization libraries._ pip install tensorflow-data-validation ```
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hvPlot (🥈27 · ⭐ 620) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 +
hvPlot (🥈27 · ⭐ 620) - 用于构建的pandas，dask，xarray和networkx的高级绘图API。BSD-3 - [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 37 · 🔀 73 · 📦 1.6K · 📋 480 - 37% open · ⏱️ 25.08.2022): @@ -1063,7 +1063,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge hvplot ```
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wordcloud (🥈26 · ⭐ 8.9K) - A little word cloud generator in Python. MIT +
wordcloud (🥈26 · ⭐ 8.9K) - Python中的词云生成器。MIT - [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 65 · 🔀 2.2K · 📋 470 - 20% open · ⏱️ 27.06.2022): @@ -1079,7 +1079,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge wordcloud ```
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Cufflinks (🥈26 · ⭐ 2.6K · 💀) - Productivity Tools for Plotly + Pandas. MIT +
Cufflinks (🥈26 · ⭐ 2.6K · 💀) - Plotly + Pandas的生产力工具。MIT - [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 600 · 📦 6.5K · 📋 210 - 41% open · ⏱️ 25.02.2021): @@ -1091,7 +1091,7 @@ _General-purpose and task-specific data visualization libraries._ pip install cufflinks ```
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HoloViews (🥈26 · ⭐ 2.3K) - With Holoviews, your data visualizes itself. BSD-3 +
HoloViews (🥈26 · ⭐ 2.3K) - 使用Holoviews，您的数据可以可视化。BSD-3 - [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 120 · 🔀 350 · 📋 2.8K - 31% open · ⏱️ 22.08.2022): @@ -1111,7 +1111,7 @@ _General-purpose and task-specific data visualization libraries._ npm install @pyviz/jupyterlab_pyviz ```
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PyVista (🥈26 · ⭐ 1.4K) - 3D plotting and mesh analysis through a streamlined interface for.. MIT +
PyVista (🥈26 · ⭐ 1.4K) - 通过简化的界面进行3D绘图和网格分析。MIT - [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 100 · 🔀 280 · 📥 660 · 📦 900 · 📋 920 - 28% open · ⏱️ 26.08.2022): @@ -1127,7 +1127,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pyvista ```
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Facets Overview (🥉25 · ⭐ 7K · 💀) - Visualizations for machine learning datasets. Apache-2 +
Facets Overview (🥉25 · ⭐ 7K · 💀) - 机器学习数据集的可视化。Apache-2 - [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 850 · 📦 130 · 📋 150 - 50% open · ⏱️ 06.05.2021): @@ -1139,7 +1139,7 @@ _General-purpose and task-specific data visualization libraries._ pip install facets-overview ```
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Chartify (🥉25 · ⭐ 3.2K · 💀) - Python library that makes it easy for data scientists to create.. Apache-2 +
Chartify (🥉25 · ⭐ 3.2K · 💀) - Python库，使数据科学家可以轻松创建。Apache-2 - [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 280 · 📦 65 · 📋 72 - 56% open · ⏱️ 05.02.2021): @@ -1155,7 +1155,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge chartify ```
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VisPy (🥉24 · ⭐ 2.9K) - High-performance interactive 2D/3D data visualization library. ❗Unlicensed +
VisPy (🥉24 · ⭐ 2.9K) - 高性能交互式2D / 3D数据可视化库。❗Unlicensed - [GitHub](https://github.com/vispy/vispy) (👨‍💻 180 · 🔀 580 · 📦 820 · 📋 1.3K - 20% open · ⏱️ 24.08.2022): @@ -1175,7 +1175,7 @@ _General-purpose and task-specific data visualization libraries._ npm install vispy ```
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HyperTools (🥉24 · ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT +
HyperTools (🥉24 · ⭐ 1.7K) - 一个Python工具箱，用于获得对高维的几何洞察力。MIT - [GitHub](https://github.com/ContextLab/hypertools) (👨‍💻 21 · 🔀 150 · 📥 20 · 📦 210 · 📋 190 - 35% open · ⏱️ 12.02.2022): @@ -1187,7 +1187,7 @@ _General-purpose and task-specific data visualization libraries._ pip install hypertools ```
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pythreejs (🥉24 · ⭐ 830) - A Jupyter - Three.js bridge. ❗Unlicensed +
pythreejs (🥉24 · ⭐ 830) - Jupyter-Three.js桥。❗Unlicensed - [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 30 · 🔀 170 · 📦 21 · 📋 220 - 23% open · ⏱️ 25.08.2022): @@ -1207,7 +1207,7 @@ _General-purpose and task-specific data visualization libraries._ npm install jupyter-threejs ```
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PyQtGraph (🥉23 · ⭐ 2.9K) - Fast data visualization and GUI tools for scientific /.. ❗Unlicensed +
PyQtGraph (🥉23 · ⭐ 2.9K) - 用于科学/工程的快速数据可视化和GUI工具。❗Unlicensed - [GitHub](https://github.com/pyqtgraph/pyqtgraph) (👨‍💻 230 · 🔀 930 · 📋 1K - 31% open · ⏱️ 24.08.2022): @@ -1223,7 +1223,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pyqtgraph ```
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FiftyOne (🥉23 · ⭐ 1.8K) - Visualize, create, and debug image and video datasets.. Apache-2 +
FiftyOne (🥉23 · ⭐ 1.8K) - 可视化，创建和调试图像和视频数据集。Apache-2 - [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 46 · 🔀 220 · 📦 160 · 📋 890 - 31% open · ⏱️ 25.08.2022): @@ -1235,7 +1235,7 @@ _General-purpose and task-specific data visualization libraries._ pip install fiftyone ```
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openTSNE (🥉23 · ⭐ 1K) - Extensible, parallel implementations of t-SNE. BSD-3 +
openTSNE (🥉23 · ⭐ 1K) - t-SNE的可扩展并行实现。BSD-3 - [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 120 · 📦 380 · 📋 110 - 5% open · ⏱️ 18.03.2022): @@ -1251,7 +1251,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge opentsne ```
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python-ternary (🥉23 · ⭐ 580) - Ternary plotting library for python with matplotlib. MIT +
python-ternary (🥉23 · ⭐ 580) - 带有matplotlib的python三元绘图库。MIT - [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 140 · 📥 18 · 📦 100 · 📋 130 - 25% open · ⏱️ 27.02.2022): @@ -1267,7 +1267,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge python-ternary ```
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Sweetviz (🥉22 · ⭐ 2.1K) - Visualize and compare datasets, target values and associations, with one.. MIT +
Sweetviz (🥉22 · ⭐ 2.1K) - 可视化和比较数据集，目标值和相关性。MIT - [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 210 · 📋 100 - 28% open · ⏱️ 08.06.2022): @@ -1279,7 +1279,7 @@ _General-purpose and task-specific data visualization libraries._ pip install sweetviz ```
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lets-plot (🥉22 · ⭐ 780) - An open-source plotting library for statistical data. MIT +
lets-plot (🥉22 · ⭐ 780) - 一个用于统计数据的开源绘图库。MIT - [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 17 · 🔀 34 · 📥 300 · 📦 17 · 📋 270 - 27% open · ⏱️ 23.08.2022): @@ -1291,7 +1291,7 @@ _General-purpose and task-specific data visualization libraries._ pip install lets-plot ```
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PDPbox (🥉22 · ⭐ 700 · 💀) - python partial dependence plot toolbox. MIT +
PDPbox (🥉22 · ⭐ 700 · 💀) - python部分依赖图工具箱。MIT - [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 110 · 📦 510 · 📋 60 - 36% open · ⏱️ 14.03.2021): @@ -1307,7 +1307,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pdpbox ```
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Perspective (🥉21 · ⭐ 4.8K) - Streaming pivot visualization via WebAssembly. Apache-2 +
Perspective (🥉21 · ⭐ 4.8K) - 通过WebAssembly进行流式透视显示。Apache-2 - [GitHub](https://github.com/finos/perspective) (👨‍💻 72 · 🔀 490 · 📦 4 · 📋 540 - 14% open · ⏱️ 25.08.2022): @@ -1323,7 +1323,7 @@ _General-purpose and task-specific data visualization libraries._ npm install @finos/perspective-jupyterlab ```
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plotnine (🥉21 · ⭐ 3.2K) - A grammar of graphics for Python. MIT +
plotnine (🥉21 · ⭐ 3.2K) - Python的图形语法。MIT - [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 96 · 🔀 170 · 📋 500 - 13% open · ⏱️ 01.07.2022): @@ -1339,7 +1339,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge plotnine ```
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Multicore-TSNE (🥉21 · ⭐ 1.7K · 💀) - Parallel t-SNE implementation with Python and Torch.. BSD-3 +
Multicore-TSNE (🥉21 · ⭐ 1.7K · 💀) - 使用Python和Torch并行执行t-SNE。BSD-3 - [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 200 · 📦 310 · 📋 58 - 63% open · ⏱️ 19.08.2020): @@ -1355,7 +1355,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge multicore-tsne ```
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AutoViz (🥉20 · ⭐ 890) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 +
AutoViz (🥉20 · ⭐ 890) - 自动显示任意行的任何大小的任何数据集。Apache-2 - [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 12 · 🔀 120 · 📦 240 · 📋 59 - 5% open · ⏱️ 10.08.2022): @@ -1367,7 +1367,7 @@ _General-purpose and task-specific data visualization libraries._ pip install autoviz ```
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PyWaffle (🥉20 · ⭐ 500) - Make Waffle Charts in Python. MIT +
PyWaffle (🥉20 · ⭐ 500) - 用Python作图。MIT - [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 92 · 📦 150 · 📋 18 - 22% open · ⏱️ 08.06.2022): @@ -1379,7 +1379,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pywaffle ```
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PandasGUI (🥉19 · ⭐ 2.7K) - A GUI for Pandas DataFrames. ❗️MIT-0 +
PandasGUI (🥉19 · ⭐ 2.7K) - pandas Dataframe的GUI。❗️MIT-0 - [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 13 · 🔀 180 · 📦 170 · 📋 160 - 27% open · ⏱️ 16.03.2022): @@ -1391,7 +1391,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pandasgui ```
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HiPlot (🥉19 · ⭐ 2.3K) - HiPlot makes understanding high dimensional data easy. MIT +
HiPlot (🥉19 · ⭐ 2.3K) - HiPlot使理解高维数据变得容易。MIT - [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 8 · 🔀 120 · 📦 5 · 📋 80 - 15% open · ⏱️ 05.07.2022): @@ -1407,7 +1407,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge hiplot ```
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pivottablejs (🥉19 · ⭐ 470 · 💀) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. ❗Unlicensed +
pivottablejs (🥉19 · ⭐ 470 · 💀) - Jupyter/IPython的Dragndrop数据透视表和图表。❗Unlicensed - [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 62 · 📦 260 · 📋 58 - 29% open · ⏱️ 04.12.2018): @@ -1419,7 +1419,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pivottablejs ```
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joypy (🥉19 · ⭐ 440 · 💤) - Joyplots in Python with matplotlib & pandas. MIT +
joypy (🥉19 · ⭐ 440 · 💤) - 带有matplotlib和pandas的Python中的Joyplots。MIT - [GitHub](https://github.com/leotac/joypy) (👨‍💻 6 · 🔀 47 · 📦 190 · 📋 47 - 21% open · ⏱️ 19.12.2021): @@ -1435,7 +1435,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge joypy ```
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ivis (🥉19 · ⭐ 280) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 +
ivis (🥉19 · ⭐ 280) - 使用算法对非常大的数据集进行降维。Apache-2 - [GitHub](https://github.com/beringresearch/ivis) (👨‍💻 10 · 🔀 35 · 📦 26 · 📋 57 - 5% open · ⏱️ 29.07.2022): @@ -1447,7 +1447,7 @@ _General-purpose and task-specific data visualization libraries._ pip install ivis ```
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Pandas-Bokeh (🥉18 · ⭐ 800) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT +
Pandas-Bokeh (🥉18 · ⭐ 800) - pandas和GeoPandas的Bokeh绘图后端。MIT - [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 14 · 🔀 100 · 📋 98 - 31% open · ⏱️ 25.03.2022): @@ -1459,7 +1459,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pandas-bokeh ```
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animatplot (🥉18 · ⭐ 400 · 💀) - A python package for animating plots build on matplotlib. MIT +
animatplot (🥉18 · ⭐ 400 · 💀) - 用于在patpliblib上构建动画图的python程序包。MIT - [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 34 · 📦 35 · 📋 30 - 43% open · ⏱️ 05.10.2020): @@ -1475,7 +1475,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge animatplot ```
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vega (🥉18 · ⭐ 330) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 +
vega (🥉18 · ⭐ 330) - 适用于Vega和Vega-Lite的IPython/Jupyter笔记本模块。BSD-3 - [GitHub](https://github.com/vega/ipyvega) (👨‍💻 11 · 🔀 55 · 📋 95 - 13% open · ⏱️ 01.08.2022): @@ -1491,7 +1491,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge vega ```
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pdvega (🥉16 · ⭐ 340 · 💀) - Interactive plotting for Pandas using Vega-Lite. MIT +
pdvega (🥉16 · ⭐ 340 · 💀) - 使用Vega-Lite交互式绘制pandas数据图。MIT - [GitHub](https://github.com/altair-viz/pdvega) (👨‍💻 9 · 🔀 31 · 📦 67 · 📋 26 - 61% open · ⏱️ 29.03.2019): @@ -1503,7 +1503,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pdvega ```
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data-describe (🥉14 · ⭐ 290 · 💤) - datadescribe: Pythonic EDA Accelerator for Data.. ❗Unlicensed +
data-describe (🥉14 · ⭐ 290 · 💤) - 数据描述：Pythonic EDA数据科学加速器。❗Unlicensed - [GitHub](https://github.com/data-describe/data-describe) (👨‍💻 14 · 🔀 18 · 📋 240 - 28% open · ⏱️ 19.11.2021): @@ -1515,7 +1515,7 @@ _General-purpose and task-specific data visualization libraries._ pip install data-describe ```
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nx-altair (🥉14 · ⭐ 200 · 💀) - Draw interactive NetworkX graphs with Altair. MIT +
nx-altair (🥉14 · ⭐ 200 · 💀) - 使用Altair绘制交互式NetworkX图形。MIT - [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 23 · 📋 10 - 60% open · ⏱️ 02.06.2020): @@ -1527,7 +1527,7 @@ _General-purpose and task-specific data visualization libraries._ pip install nx-altair ```
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nptsne (🥉11 · ⭐ 29 · 💀) - nptsne is a numpy compatible python binary package that offers a.. Apache-2 +
nptsne (🥉11 · ⭐ 29 · 💀) - nptsne是numpy兼容的python二进制包。Apache-2 - [GitHub](https://github.com/biovault/nptsne) (👨‍💻 3 · 🔀 2 · 📦 4 · 📋 13 - 53% open · ⏱️ 03.02.2021): @@ -1541,13 +1541,13 @@ _General-purpose and task-specific data visualization libraries._

-## Text Data & NLP +## 文本数据和NLP -Back to top +Back to top -_Libraries for processing, cleaning, manipulating, and analyzing text data as well as libraries for NLP tasks such as language detection, fuzzy matching, classification, seq2seq learning, conversational AI, keyword extraction, and translation._ +_用于处理，清理，处理和分析文本数据的库，以及用于NLP任务的库，例如语言检测，模糊匹配，文本分类，seq2seq学习，智能对话，关键字提取和机器翻译。_ -
spaCy (🥇38 · ⭐ 24K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT +
spaCy (🥇38 · ⭐ 24K) - Python中的工业级自然语言处理（NLP）工具包。MIT - [GitHub](https://github.com/explosion/spaCy) (👨‍💻 700 · 🔀 3.8K · 📥 3.1K · 📦 43K · 📋 5.2K - 1% open · ⏱️ 23.08.2022): @@ -1563,7 +1563,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge spacy ```
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transformers (🥇37 · ⭐ 69K) - Transformers: State-of-the-art Natural Language.. Apache-2 +
transformers (🥇37 · ⭐ 69K) - transformers：先进的自然语言模型库。Apache-2 - [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1.4K · 🔀 15K · 📥 1.5K · 📦 34K · 📋 9.9K - 4% open · ⏱️ 25.08.2022): @@ -1579,7 +1579,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge transformers ```
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gensim (🥇36 · ⭐ 13K) - Topic Modelling for Humans. ❗️LGPL-2.1 +
gensim (🥇36 · ⭐ 13K) - 主题模型工具库。❗️LGPL-2.1 - [GitHub](https://github.com/RaRe-Technologies/gensim) (👨‍💻 430 · 🔀 4K · 📥 3.8K · 📦 36K · 📋 1.8K - 20% open · ⏱️ 22.08.2022): @@ -1595,7 +1595,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge gensim ```
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sentence-transformers (🥇34 · ⭐ 8.3K) - Sentence Embeddings with BERT & XLNet. Apache-2 +
sentence-transformers (🥇34 · ⭐ 8.3K) - BERT和XLNet的句子嵌入。Apache-2 - [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 93 · 🔀 1.6K · 📦 4K · 📋 1.5K - 51% open · ⏱️ 15.08.2022): @@ -1607,7 +1607,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sentence-transformers ```
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AllenNLP (🥇33 · ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 +
AllenNLP (🥇33 · ⭐ 11K) - 基于PyTorch的开源NLP研究库。Apache-2 - [GitHub](https://github.com/allenai/allennlp) (👨‍💻 260 · 🔀 2.1K · 📥 47 · 📦 2.7K · 📋 2.5K - 3% open · ⏱️ 24.08.2022): @@ -1619,7 +1619,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install allennlp ```
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nltk (🥇33 · ⭐ 11K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 +
nltk (🥇33 · ⭐ 11K) - 用于符号和统计自然的库和程序套件。Apache-2 - [GitHub](https://github.com/nltk/nltk) (👨‍💻 430 · 🔀 2.5K · 📦 150K · 📋 1.6K - 13% open · ⏱️ 29.07.2022): @@ -1635,7 +1635,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge nltk ```
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sentencepiece (🥇33 · ⭐ 6.1K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 +
sentencepiece (🥇33 · ⭐ 6.1K) - 用于基于神经网络的文本的预处理器。Apache-2 - [GitHub](https://github.com/google/sentencepiece) (👨‍💻 68 · 🔀 810 · 📥 22K · 📦 17K · 📋 540 - 2% open · ⏱️ 21.08.2022): @@ -1651,7 +1651,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge sentencepiece ```
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ChatterBot (🥇32 · ⭐ 12K · 💀) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 +
ChatterBot (🥇32 · ⭐ 12K · 💀) - ChatterBot是机器学习的对话引擎。BSD-3 - [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 4K · 📦 4.5K · 📋 1.6K - 19% open · ⏱️ 01.06.2021): @@ -1663,7 +1663,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install chatterbot ```
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fastText (🥇31 · ⭐ 24K) - Library for fast text representation and classification. MIT +
fastText (🥇31 · ⭐ 24K) - 用于快速文本表示和分类的库。MIT - [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 59 · 🔀 4.3K · 📦 3.2K · 📋 1K - 41% open · ⏱️ 04.03.2022): @@ -1679,7 +1679,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge fasttext ```
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TextBlob (🥇31 · ⭐ 8.3K · 💤) - Simple, Pythonic, text processing--Sentiment analysis, part-of-.. MIT +
TextBlob (🥇31 · ⭐ 8.3K · 💤) - 包含情感分析、词性标注等等功能的NLP工具库。MIT - [GitHub](https://github.com/sloria/TextBlob) (👨‍💻 35 · 🔀 1K · 📥 100 · 📦 22K · 📋 250 - 37% open · ⏱️ 22.10.2021): @@ -1695,7 +1695,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textblob ```
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flair (🥈30 · ⭐ 12K) - A very simple framework for state-of-the-art Natural Language.. ❗Unlicensed +
flair (🥈30 · ⭐ 12K) - 一个用于最先进的自然语言处理的非常简单的框架。❗Unlicensed - [GitHub](https://github.com/flairNLP/flair) (👨‍💻 230 · 🔀 1.6K · 📦 1.6K · 📋 1.9K - 6% open · ⏱️ 18.08.2022): @@ -1707,7 +1707,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install flair ```
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fuzzywuzzy (🥈30 · ⭐ 8.7K · 💤) - Fuzzy String Matching in Python. ❗️GPL-2.0 +
fuzzywuzzy (🥈30 · ⭐ 8.7K · 💤) - Python中的模糊字符串匹配。❗️GPL-2.0 - [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 870 · 📦 14K · 📋 180 - 43% open · ⏱️ 09.09.2021): @@ -1723,7 +1723,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge fuzzywuzzy ```
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fairseq (🥈29 · ⭐ 19K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT +
fairseq (🥈29 · ⭐ 19K) - 用Python编写的Facebook AI Research Sequence-to-Sequence工具包。MIT - [GitHub](https://github.com/facebookresearch/fairseq) (👨‍💻 400 · 🔀 4.7K · 📥 260 · 📦 920 · 📋 3.5K - 18% open · ⏱️ 24.08.2022): @@ -1735,7 +1735,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fairseq ```
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TextDistance (🥈29 · ⭐ 2.9K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT +
TextDistance (🥈29 · ⭐ 2.9K) - 计算序列之间的距离，包含30多种算法。MIT - [GitHub](https://github.com/life4/textdistance) (👨‍💻 12 · 🔀 230 · 📥 830 · 📦 2.6K · ⏱️ 21.08.2022): @@ -1751,7 +1751,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textdistance ```
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TensorFlow Text (🥈29 · ⭐ 980) - Making text a first-class citizen in TensorFlow. Apache-2 +
TensorFlow Text (🥈29 · ⭐ 980) - TensorFlow文本处理。Apache-2 - [GitHub](https://github.com/tensorflow/text) (👨‍💻 91 · 🔀 230 · 📦 2.2K · 📋 180 - 18% open · ⏱️ 22.08.2022): @@ -1763,7 +1763,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install tensorflow-text ```
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GluonNLP (🥈28 · ⭐ 2.4K · 💤) - Toolkit that enables easy text preprocessing, datasets.. Apache-2 +
GluonNLP (🥈28 · ⭐ 2.4K · 💤) - 可轻松进行文本预处理，数据集加载和处理的工具包。Apache-2 - [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 920 · 📋 530 - 44% open · ⏱️ 24.08.2021): @@ -1775,7 +1775,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install gluonnlp ```
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DeepPavlov (🥈27 · ⭐ 5.8K) - An open source library for deep learning end-to-end dialog.. Apache-2 +
DeepPavlov (🥈27 · ⭐ 5.8K) - 一个用于深度学习端到端对话的开源库。Apache-2 - [GitHub](https://github.com/deepmipt/DeepPavlov) (👨‍💻 67 · 🔀 1K · 📦 280 · 📋 620 - 8% open · ⏱️ 31.05.2022): @@ -1787,7 +1787,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install deeppavlov ```
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OpenNMT (🥈27 · ⭐ 5.7K) - Open Source Neural Machine Translation in PyTorch. MIT +
OpenNMT (🥈27 · ⭐ 5.7K) - PyTorch中的开源神经机器翻译。MIT - [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 180 · 🔀 2K · 📦 150 · 📋 1.3K - 6% open · ⏱️ 18.08.2022): @@ -1799,7 +1799,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install OpenNMT-py ```
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spark-nlp (🥈27 · ⭐ 2.9K) - State of the Art Natural Language Processing. Apache-2 +
spark-nlp (🥈27 · ⭐ 2.9K) - 最先进的自然语言处理。Apache-2 - [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 130 · 🔀 570 · 📋 700 - 5% open · ⏱️ 24.08.2022): @@ -1811,7 +1811,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install spark-nlp ```
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spacy-transformers (🥈27 · ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy +
spacy-transformers (🥈27 · ⭐ 1.1K) - 使用经过预训练的transformer模型，例如BERT，XLNet和GPT-2。MIT spacy - [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 18 · 🔀 140 · 📦 610 · ⏱️ 23.08.2022): @@ -1823,7 +1823,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install spacy-transformers ```
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ParlAI (🥈26 · ⭐ 9.4K) - A framework for training and evaluating AI models on a variety of.. MIT +
ParlAI (🥈26 · ⭐ 9.4K) - 一个用于训练和评估AI模型的框架。MIT - [GitHub](https://github.com/facebookresearch/ParlAI) (👨‍💻 200 · 🔀 1.8K · 📦 87 · 📋 1.4K - 5% open · ⏱️ 25.08.2022): @@ -1835,7 +1835,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install parlai ```
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Tokenizers (🥈26 · ⭐ 5.8K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 +
Tokenizers (🥈26 · ⭐ 5.8K) - 针对研究和应用进行了优化的快速最先进的分词器。Apache-2 - [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 59 · 🔀 480 · 📦 51 · 📋 650 - 30% open · ⏱️ 25.08.2022): @@ -1851,7 +1851,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge tokenizers ```
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Sumy (🥈26 · ⭐ 2.9K) - Module for automatic summarization of text documents and HTML pages. Apache-2 +
Sumy (🥈26 · ⭐ 2.9K) - 自动汇总文本文档和HTML页面的模块。Apache-2 - [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 23 · 🔀 470 · 📦 1.4K · 📋 110 - 15% open · ⏱️ 31.07.2022): @@ -1863,7 +1863,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sumy ```
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jellyfish (🥈26 · ⭐ 1.7K · 💤) - a python library for doing approximate and phonetic matching of.. BSD-2 +
jellyfish (🥈26 · ⭐ 1.7K · 💤) - 一个python库，用于进行文本相似度和距离计算。BSD-2 - [GitHub](https://github.com/jamesturk/jellyfish) (👨‍💻 25 · 🔀 140 · 📦 4.1K · 📋 110 - 10% open · ⏱️ 07.01.2022): @@ -1879,7 +1879,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge jellyfish ```
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Rasa (🥈25 · ⭐ 15K) - Open source machine learning framework to automate text- and voice-.. Apache-2 +
Rasa (🥈25 · ⭐ 15K) - 开源机器学习框架，可处理文本和语音多场景问题。Apache-2 - [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 550 · 🔀 4K · 📋 6.6K - 12% open · ⏱️ 24.08.2022): @@ -1891,7 +1891,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install rasa ```
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stanza (🥈25 · ⭐ 6.2K) - Official Stanford NLP Python Library for Many Human Languages. ❗Unlicensed +
stanza (🥈25 · ⭐ 6.2K) - 斯坦福NLP官方Python语言库，支持多种语言。❗Unlicensed - [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 48 · 🔀 790 · 📦 1.2K · 📋 720 - 11% open · ⏱️ 23.04.2022): @@ -1907,7 +1907,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c stanfordnlp stanza ```
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ftfy (🥈25 · ⭐ 3.3K) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT +
ftfy (🥈25 · ⭐ 3.3K) - 修复Unicode文本中的故障功能的工具库。MIT - [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 110 · 📦 6.6K · 📋 130 - 9% open · ⏱️ 09.02.2022): @@ -1923,7 +1923,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge ftfy ```
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fastNLP (🥈25 · ⭐ 2.7K) - fastNLP: A Modularized and Extensible NLP Framework. Currently still.. Apache-2 +
fastNLP (🥈25 · ⭐ 2.7K) - fastNLP：模块化和可扩展的NLP框架。Apache-2 - [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 59 · 🔀 420 · 📥 66 · 📦 90 · 📋 190 - 22% open · ⏱️ 23.08.2022): @@ -1935,7 +1935,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fastnlp ```
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neuralcoref (🥈25 · ⭐ 2.6K · 💀) - Fast Coreference Resolution in spaCy with Neural Networks. MIT +
neuralcoref (🥈25 · ⭐ 2.6K · 💀) - 基于SpaCy的神经网络实现快速共指解析。MIT - [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 440 · 📥 450 · 📦 520 · 📋 300 - 16% open · ⏱️ 22.06.2021): @@ -1951,7 +1951,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge neuralcoref ```
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PyTextRank (🥈25 · ⭐ 1.9K) - Python implementation of TextRank for phrase extraction and.. MIT +
PyTextRank (🥈25 · ⭐ 1.9K) - TextRank的Python实现。MIT - [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 18 · 🔀 300 · 📦 280 · 📋 89 - 19% open · ⏱️ 27.07.2022): @@ -1963,7 +1963,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytextrank ```
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SciSpacy (🥈25 · ⭐ 1.2K) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 +
SciSpacy (🥈25 · ⭐ 1.2K) - 完整的科学/生物医学的SpaCy应用案例。Apache-2 - [GitHub](https://github.com/allenai/scispacy) (👨‍💻 24 · 🔀 160 · 📦 500 · 📋 260 - 10% open · ⏱️ 04.08.2022): @@ -1975,7 +1975,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install scispacy ```
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pyahocorasick (🥈25 · ⭐ 740) - Python module (C extension and plain python) implementing Aho-.. BSD-3 +
pyahocorasick (🥈25 · ⭐ 740) - Python文本工具库。BSD-3 - [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 24 · 🔀 110 · 📦 1.2K · 📋 120 - 20% open · ⏱️ 04.05.2022): @@ -1991,7 +1991,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge pyahocorasick ```
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Ciphey (🥈24 · ⭐ 11K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT +
Ciphey (🥈24 · ⭐ 11K) - 在不知道密钥或密码的情况下自动解密加密。MIT - [GitHub](https://github.com/Ciphey/Ciphey) (👨‍💻 46 · 🔀 650 · 📋 290 - 15% open · ⏱️ 28.06.2022): @@ -2007,7 +2007,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we docker pull remnux/ciphey ```
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vaderSentiment (🥈24 · ⭐ 3.7K) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary and.. MIT +
vaderSentiment (🥈24 · ⭐ 3.7K) - VADER情感分析。MIT - [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 11 · 🔀 880 · 📦 4.1K · 📋 110 - 31% open · ⏱️ 01.04.2022): @@ -2019,7 +2019,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install vadersentiment ```
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torchtext (🥈24 · ⭐ 3.1K) - Data loaders and abstractions for text and NLP. BSD-3 +
torchtext (🥈24 · ⭐ 3.1K) - 文本和NLP的数据加载器和抽象。BSD-3 - [GitHub](https://github.com/pytorch/text) (👨‍💻 140 · 🔀 700 · 📋 670 - 33% open · ⏱️ 19.08.2022): @@ -2031,7 +2031,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install torchtext ```
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pytorch-nlp (🥈24 · ⭐ 2.1K · 💀) - Basic Utilities for PyTorch Natural Language Processing.. BSD-3 +
pytorch-nlp (🥈24 · ⭐ 2.1K · 💀) - PyTorch自然语言处理（NLP）的基本实用程序。BSD-3 - [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (👨‍💻 18 · 🔀 250 · 📦 410 · 📋 67 - 26% open · ⏱️ 10.07.2021): @@ -2043,7 +2043,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytorch-nlp ```
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CLTK (🥈24 · ⭐ 740) - The Classical Language Toolkit. MIT +
CLTK (🥈24 · ⭐ 740) - 古典语言工具包。MIT - [GitHub](https://github.com/cltk/cltk) (👨‍💻 120 · 🔀 310 · 📥 25 · 📦 210 · 📋 530 - 5% open · ⏱️ 20.07.2022): @@ -2055,7 +2055,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install cltk ```
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flashtext (🥉23 · ⭐ 5.2K · 💀) - Extract Keywords from sentence or Replace keywords in sentences. MIT +
flashtext (🥉23 · ⭐ 5.2K · 💀) - 从句子中提取关键字或替换句子中的关键字。MIT - [GitHub](https://github.com/vi3k6i5/flashtext) (👨‍💻 7 · 🔀 570 · 📦 850 · 📋 100 - 49% open · ⏱️ 03.05.2020): @@ -2067,7 +2067,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install flashtext ```
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Dedupe (🥉23 · ⭐ 3.5K) - A python library for accurate and scalable fuzzy matching, record.. MIT +
Dedupe (🥉23 · ⭐ 3.5K) - 一个用于准确和可扩展的模糊匹配的python库。MIT - [GitHub](https://github.com/dedupeio/dedupe) (👨‍💻 64 · 🔀 460 · 📦 230 · 📋 760 - 7% open · ⏱️ 17.08.2022): @@ -2079,7 +2079,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install dedupe ```
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snowballstemmer (🥉23 · ⭐ 580 · 💤) - Snowball compiler and stemming algorithms. BSD-3 +
snowballstemmer (🥉23 · ⭐ 580 · 💤) - Snowball编译器和词干算法。BSD-3 - [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 28 · 🔀 160 · 📦 4 · 📋 60 - 26% open · ⏱️ 17.12.2021): @@ -2095,7 +2095,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge snowballstemmer ```
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pySBD (🥉23 · ⭐ 470 · 💀) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT +
pySBD (🥉23 · ⭐ 470 · 💀) - pySBD（Python句子边界歧义消除）。MIT - [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 58 · 📦 390 · 📋 65 - 21% open · ⏱️ 11.02.2021): @@ -2107,7 +2107,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pysbd ```
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stop-words (🥉23 · ⭐ 140 · 💀) - Get list of common stop words in various languages in Python. BSD-3 +
stop-words (🥉23 · ⭐ 140 · 💀) - 获取Python中各种语言的常用停用词表。BSD-3 - [GitHub](https://github.com/Alir3z4/python-stop-words) (👨‍💻 8 · 🔀 26 · 📦 1.6K · 📋 12 - 25% open · ⏱️ 23.07.2018): @@ -2119,7 +2119,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install stop-words ```
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textgenrnn (🥉22 · ⭐ 4.7K · 💀) - Easily train your own text-generating neural network.. ❗Unlicensed +
textgenrnn (🥉22 · ⭐ 4.7K · 💀) - 轻松地训练自己的文本生成神经网络。❗Unlicensed - [GitHub](https://github.com/minimaxir/textgenrnn) (👨‍💻 19 · 🔀 720 · 📥 740 · 📦 1K · 📋 220 - 57% open · ⏱️ 14.07.2020): @@ -2131,7 +2131,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textgenrnn ```
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NeMo (🥉22 · ⭐ 4.6K) - NeMo: a toolkit for conversational AI. Apache-2 +
NeMo (🥉22 · ⭐ 4.6K) - NeMo：用于智能对话的工具包。Apache-2 - [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 170 · 🔀 1.1K · 📥 15K · 📋 1.2K - 3% open · ⏱️ 25.08.2022): @@ -2143,7 +2143,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install nemo-toolkit ```
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T5 (🥉22 · ⭐ 4.4K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 +
T5 (🥉22 · ⭐ 4.4K) - 探索迁移学习的论文源码Apache-2 - [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 50 · 🔀 590 · 📦 110 · 📋 390 - 12% open · ⏱️ 10.08.2022): @@ -2155,7 +2155,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install t5 ```
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phonenumbers (🥉22 · ⭐ 3.1K) - Python port of Google's libphonenumber. Apache-2 +
phonenumbers (🥉22 · ⭐ 3.1K) - Google的libphonenumber的Python端口。Apache-2 - [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 26 · 🔀 370 · 📋 150 - 2% open · ⏱️ 19.08.2022): @@ -2171,7 +2171,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge phonenumbers ```
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langid (🥉22 · ⭐ 2K · 💀) - Stand-alone language identification system. ❗Unlicensed +
langid (🥉22 · ⭐ 2K · 💀) - 独立的语言识别系统。❗Unlicensed - [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 280 · 📦 1.1K · 📋 71 - 35% open · ⏱️ 15.07.2017): @@ -2183,7 +2183,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install langid ```
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scattertext (🥉22 · ⭐ 1.9K) - Beautiful visualizations of how language differs among document.. Apache-2 +
scattertext (🥉22 · ⭐ 1.9K) - 文件之间语言分布的漂亮可视化效果。Apache-2 - [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 12 · 🔀 250 · 📦 310 · 📋 89 - 17% open · ⏱️ 26.03.2022): @@ -2199,7 +2199,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge scattertext ```
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anaGo (🥉22 · ⭐ 1.5K · 💀) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT +
anaGo (🥉22 · ⭐ 1.5K · 💀) - 双向LSTM-CRF和ELMo实现，可用于命名实体识别和文本分类等任务。MIT - [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 30 · 📋 110 - 33% open · ⏱️ 01.04.2021): @@ -2211,7 +2211,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install anago ```
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sense2vec (🥉22 · ⭐ 1.4K · 💤) - Contextually-keyed word vectors. MIT +
sense2vec (🥉22 · ⭐ 1.4K · 💤) - 上下文相关性构建词向量。MIT - [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 220 · 📥 36K · 📦 170 · 📋 110 - 18% open · ⏱️ 16.08.2021): @@ -2227,7 +2227,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge sense2vec ```
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Snips NLU (🥉21 · ⭐ 3.7K · 💀) - Snips Python library to extract meaning from text. Apache-2 +
Snips NLU (🥉21 · ⭐ 3.7K · 💀) - 从文本中提取含义的Python库。Apache-2 - [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 490 · 📋 260 - 23% open · ⏱️ 03.05.2021): @@ -2239,7 +2239,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install snips-nlu ```
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Texthero (🥉21 · ⭐ 2.5K) - Text preprocessing, representation and visualization from zero to hero. MIT +
Texthero (🥉21 · ⭐ 2.5K) - 文本预处理，表示和可视化从入门到精通。MIT - [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 19 · 🔀 220 · 📥 92 · 📋 110 - 45% open · ⏱️ 19.07.2022): @@ -2251,7 +2251,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install texthero ```
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Texar (🥉21 · ⭐ 2.3K · 💀) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 +
Texar (🥉21 · ⭐ 2.3K · 💀) - 机器学习，自然语言处理等工具包。Apache-2 - [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 26 · 📋 160 - 19% open · ⏱️ 29.07.2020): @@ -2263,7 +2263,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install texar ```
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polyglot (🥉21 · ⭐ 2K · 💀) - Multilingual text (NLP) processing toolkit. ❗Unlicensed +
polyglot (🥉21 · ⭐ 2K · 💀) - 多语言文本（NLP）处理工具包。❗Unlicensed - [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 310 · 📦 750 · 📋 210 - 68% open · ⏱️ 22.09.2020): @@ -2275,7 +2275,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install polyglot ```
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YouTokenToMe (🥉21 · ⭐ 820 · 💀) - Unsupervised text tokenizer focused on computational efficiency. MIT +
YouTokenToMe (🥉21 · ⭐ 820 · 💀) - 用于基于神经网络的文本的预处理器。MIT - [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 61 · 📦 290 · 📋 54 - 55% open · ⏱️ 28.01.2021): @@ -2287,7 +2287,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install youtokentome ```
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inflect (🥉21 · ⭐ 690) - Correctly generate plurals, ordinals, indefinite articles; convert numbers.. MIT +
inflect (🥉21 · ⭐ 690) - 辅助功能，正确生成复数，序数，不定冠词，转换数字。MIT - [GitHub](https://github.com/jaraco/inflect) (👨‍💻 45 · 🔀 74 · 📋 91 - 18% open · ⏱️ 26.08.2022): @@ -2303,7 +2303,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge inflect ```
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PyText (🥉20 · ⭐ 6.4K) - A natural language modeling framework based on PyTorch. ❗Unlicensed +
PyText (🥉20 · ⭐ 6.4K) - 基于PyTorch的自然语言建模框架。❗Unlicensed - [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 230 · 🔀 790 · 📥 300 · 📦 110 · 📋 140 - 45% open · ⏱️ 11.08.2022): @@ -2315,7 +2315,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytext-nlp ```
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MatchZoo (🥉20 · ⭐ 3.7K · 💀) - Facilitating the design, comparison and sharing of deep.. Apache-2 +
MatchZoo (🥉20 · ⭐ 3.7K · 💀) - 便于深层设计，比较和共享的工具库。Apache-2 - [GitHub](https://github.com/NTMC-Community/MatchZoo) (👨‍💻 36 · 🔀 900 · 📦 11 · 📋 460 - 7% open · ⏱️ 02.06.2021): @@ -2327,7 +2327,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install matchzoo ```
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NLP Architect (🥉20 · ⭐ 2.9K) - A model library for exploring state-of-the-art deep learning.. Apache-2 +
NLP Architect (🥉20 · ⭐ 2.9K) - 用于探索最先进的深度学习的模型库。Apache-2 - [GitHub](https://github.com/IntelLabs/nlp-architect) (👨‍💻 37 · 🔀 430 · 📦 8 · 📋 130 - 11% open · ⏱️ 29.06.2022): @@ -2339,7 +2339,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install nlp-architect ```
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FARM (🥉20 · ⭐ 1.6K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 +
FARM (🥉20 · ⭐ 1.6K) - NLP的快速和轻松迁移学习。Apache-2 - [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 37 · 🔀 220 · 📋 400 - 0% open · ⏱️ 25.04.2022): @@ -2351,7 +2351,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install farm ```
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DELTA (🥉20 · ⭐ 1.5K · 💀) - DELTA is a deep learning based natural language and speech.. Apache-2 +
DELTA (🥉20 · ⭐ 1.5K · 💀) - DELTA是一个基于深度学习的自然语言和语音处理平台。Apache-2 - [GitHub](https://github.com/Delta-ML/delta) (👨‍💻 41 · 🔀 290 · 📋 75 - 1% open · ⏱️ 17.12.2020): @@ -2367,7 +2367,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we docker pull zh794390558/delta ```
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pyfasttext (🥉20 · ⭐ 230 · 💀) - Yet another Python binding for fastText. ❗️GPL-3.0 +
pyfasttext (🥉20 · ⭐ 230 · 💀) - fastText的另一个Python接口。❗️GPL-3.0 - [GitHub](https://github.com/vrasneur/pyfasttext) (👨‍💻 4 · 🔀 30 · 📥 350 · 📦 240 · 📋 49 - 42% open · ⏱️ 08.12.2018): @@ -2379,7 +2379,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pyfasttext ```
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haystack (🥉19 · ⭐ 5.2K) - End-to-end Python framework for building natural language search.. Apache-2 +
haystack (🥉19 · ⭐ 5.2K) - 用于构建自然语言搜索的端到端Python框架。Apache-2 - [GitHub](https://github.com/deepset-ai/haystack) (👨‍💻 140 · 🔀 830 · 📥 15 · 📋 1.5K - 14% open · ⏱️ 25.08.2022): @@ -2391,7 +2391,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install haystack ```
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Kashgari (🥉19 · ⭐ 2.3K · 💀) - Kashgari is a production-level NLP Transfer learning.. Apache-2 +
Kashgari (🥉19 · ⭐ 2.3K · 💀) - Kashgari是工业级的NLP迁移学习框架。Apache-2 - [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 440 · 📦 54 · 📋 370 - 11% open · ⏱️ 09.07.2021): @@ -2403,7 +2403,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install kashgari-tf ```
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fast-bert (🥉19 · ⭐ 1.8K) - Super easy library for BERT based NLP models. Apache-2 +
fast-bert (🥉19 · ⭐ 1.8K) - 用于基于BERT的NLP模型的简单易用工具库。Apache-2 - [GitHub](https://github.com/utterworks/fast-bert) (👨‍💻 36 · 🔀 330 · 📋 250 - 61% open · ⏱️ 25.08.2022): @@ -2415,7 +2415,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fast-bert ```
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Sockeye (🥉19 · ⭐ 1.1K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 +
Sockeye (🥉19 · ⭐ 1.1K) - 序列到序列框架。Apache-2 - [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 57 · 🔀 300 · 📥 15 · 📋 280 - 2% open · ⏱️ 25.08.2022): @@ -2427,7 +2427,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sockeye ```
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gpt-2-simple (🥉18 · ⭐ 3K) - Python package to easily retrain OpenAI's GPT-2 text-.. ❗Unlicensed +
gpt-2-simple (🥉18 · ⭐ 3K) - 可轻松重新训练OpenAI的GPT-2文本模型的Python软件包。❗Unlicensed - [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 21 · 🔀 600 · 📥 340 · 📋 250 - 61% open · ⏱️ 22.05.2022): @@ -2439,7 +2439,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install gpt-2-simple ```
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textacy (🥉18 · ⭐ 2K) - NLP, before and after spaCy. ❗Unlicensed +
textacy (🥉18 · ⭐ 2K) - spaCy之前和之后的NLP。❗Unlicensed - [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 32 · 🔀 230 · 📋 250 - 11% open · ⏱️ 06.03.2022): @@ -2455,7 +2455,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textacy ```
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finetune (🥉18 · ⭐ 660) - Scikit-learn style model finetuning for NLP. MPL-2.0 +
finetune (🥉18 · ⭐ 660) - 针对NLP的Scikit风格模型微调。MPL-2.0 - [GitHub](https://github.com/IndicoDataSolutions/finetune) (👨‍💻 19 · 🔀 71 · 📦 9 · 📋 140 - 15% open · ⏱️ 16.06.2022): @@ -2467,7 +2467,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install finetune ```
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skift (🥉18 · ⭐ 230) - scikit-learn wrappers for Python fastText. MIT +
skift (🥉18 · ⭐ 230) - 适用于Python fastText的scikit-learn包装器。MIT - [GitHub](https://github.com/shaypal5/skift) (👨‍💻 9 · 🔀 23 · 📦 12 · 📋 11 - 9% open · ⏱️ 07.06.2022): @@ -2479,7 +2479,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install skift ```
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DeepMatcher (🥉17 · ⭐ 440 · 💀) - Python package for performing Entity and Text Matching using.. BSD-3 +
DeepMatcher (🥉17 · ⭐ 440 · 💀) - 用于实体和文本匹配的Python包。BSD-3 - [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 98 · 📦 21 · 📋 86 - 72% open · ⏱️ 13.06.2021): @@ -2491,7 +2491,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install deepmatcher ```
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Camphr (🥉16 · ⭐ 340 · 💤) - spaCy plugin for Transformers , Udify, ELmo, etc. Apache-2 spacy +
Camphr (🥉16 · ⭐ 340 · 💤) - 适用于Transformers，Udify，ELmo等的spaCy插件。Apache-2 spacy - [GitHub](https://github.com/PKSHATechnology-Research/camphr) (👨‍💻 7 · 🔀 16 · 📋 28 - 7% open · ⏱️ 18.08.2021): @@ -2503,7 +2503,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install camphr ```
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textpipe (🥉16 · ⭐ 300 · 💀) - Textpipe: clean and extract metadata from text. MIT +
textpipe (🥉16 · ⭐ 300 · 💀) - Textpipe：从文本中清理并提取元数据。MIT - [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 23 · 📦 8 · 📋 40 - 37% open · ⏱️ 09.06.2021): @@ -2515,7 +2515,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textpipe ```
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NeuroNER (🥉15 · ⭐ 1.6K · 💀) - Named-entity recognition using neural networks. Easy-to-use and.. MIT +
NeuroNER (🥉15 · ⭐ 1.6K · 💀) - 使用神经网络的命名实体识别。MIT - [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 460 · 📋 150 - 55% open · ⏱️ 02.10.2019): @@ -2527,7 +2527,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pyneuroner ```
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Translate (🥉15 · ⭐ 760) - Translate - a PyTorch Language Library. BSD-3 +
Translate (🥉15 · ⭐ 760) - Translate-PyTorch NLP库。BSD-3 - [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 180 · 📋 38 - 28% open · ⏱️ 10.06.2022): @@ -2539,7 +2539,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytorch-translate ```
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NeuralQA (🥉15 · ⭐ 220 · 💀) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT +
NeuralQA (🥉15 · ⭐ 220 · 💀) - NeuralQA：用于对大型数据集进行问答构建。MIT - [GitHub](https://github.com/victordibia/neuralqa) (👨‍💻 3 · 🔀 30 · 📦 4 · 📋 28 - 71% open · ⏱️ 16.12.2020): @@ -2551,7 +2551,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install neuralqa ```
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OpenNRE (🥉14 · ⭐ 3.8K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT +
OpenNRE (🥉14 · ⭐ 3.8K) - 神经关系提取（NRE）的开源软件包。MIT - [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 10 · 🔀 950 · 📋 350 - 2% open · ⏱️ 06.04.2022): @@ -2559,7 +2559,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we git clone https://github.com/thunlp/OpenNRE ```
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TransferNLP (🥉14 · ⭐ 290 · 💀) - NLP library designed for reproducible experimentation.. MIT +
TransferNLP (🥉14 · ⭐ 290 · 💀) - 用于可重复的实验的NLP库。MIT - [GitHub](https://github.com/feedly/transfer-nlp) (👨‍💻 7 · 🔀 17 · 📋 23 - 13% open · ⏱️ 28.05.2020): @@ -2571,7 +2571,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install transfer-nlp ```
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ONNX-T5 (🥉14 · ⭐ 200 · 💀) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 +
ONNX-T5 (🥉14 · ⭐ 200 · 💀) - 文本摘要，翻译，情感分析，文本生成等实现。Apache-2 - [GitHub](https://github.com/abelriboulot/onnxt5) (👨‍💻 3 · 🔀 23 · 📦 1 · 📋 15 - 46% open · ⏱️ 28.01.2021): @@ -2583,7 +2583,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install onnxt5 ```
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textvec (🥉14 · ⭐ 180) - Text vectorization tool to outperform TFIDF for classification tasks. MIT +
textvec (🥉14 · ⭐ 180) - 胜过TF-IDF文本向量化工具。MIT - [GitHub](https://github.com/textvec/textvec) (👨‍💻 10 · 🔀 23 · 📦 4 · 📋 9 - 33% open · ⏱️ 05.07.2022): @@ -2595,7 +2595,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textvec ```
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VizSeq (🥉13 · ⭐ 400) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT +
VizSeq (🥉13 · ⭐ 400) - 用于自然语言生成的分析工具包。MIT - [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 49 · 📦 6 · 📋 15 - 40% open · ⏱️ 20.07.2022): @@ -2607,7 +2607,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install vizseq ```
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Headliner (🥉11 · ⭐ 230 · 💀) - Easy training and deployment of seq2seq models. ❗Unlicensed +
Headliner (🥉11 · ⭐ 230 · 💀) - 轻松训练和部署seq2seq模型。❗Unlicensed - [GitHub](https://github.com/as-ideas/headliner) (👨‍💻 2 · 🔀 41 · 📦 3 · 📋 14 - 7% open · ⏱️ 14.02.2020): @@ -2621,13 +2621,13 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we

-## Image Data +## 图像数据与CV -Back to top +Back to top -_Libraries for image & video processing, manipulation, and augmentation as well as libraries for computer vision tasks such as facial recognition, object detection, and classification._ +_用于图像和视频处理，操纵和扩充的库，以及用于计算机视觉任务（例如面部识别，对象检测和图像分类）的库。_ -
Pillow (🥇36 · ⭐ 10K · 📈) - The friendly PIL fork (Python Imaging Library). ❗️PIL +
Pillow (🥇36 · ⭐ 10K · 📈) - 友好的PIL分支（Python Imaging Library）。❗️PIL - [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 410 · 🔀 1.7K · 📦 820K · 📋 2.6K - 3% open · ⏱️ 25.08.2022): @@ -2643,7 +2643,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge pillow ```
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MoviePy (🥇34 · ⭐ 9.5K) - Video editing with Python. MIT +
MoviePy (🥇34 · ⭐ 9.5K) - 使用Python进行视频编辑。MIT - [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 150 · 🔀 1.2K · 📦 18K · 📋 1.2K - 24% open · ⏱️ 01.06.2022): @@ -2659,7 +2659,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge moviepy ```
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imageio (🥇33 · ⭐ 1.1K) - Python library for reading and writing image data. BSD-2 +
imageio (🥇33 · ⭐ 1.1K) - 用于读取和写入图像数据的Python库。BSD-2 - [GitHub](https://github.com/imageio/imageio) (👨‍💻 91 · 🔀 220 · 📥 360 · 📦 67K · 📋 470 - 12% open · ⏱️ 24.08.2022): @@ -2675,7 +2675,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imageio ```
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imgaug (🥇32 · ⭐ 13K · 💀) - Image augmentation for machine learning experiments. MIT +
imgaug (🥇32 · ⭐ 13K · 💀) - 用于机器学习实验的图像增强。MIT - [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.3K · 📦 11K · 📋 490 - 55% open · ⏱️ 01.06.2020): @@ -2691,7 +2691,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imgaug ```
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Albumentations (🥇32 · ⭐ 11K) - Fast image augmentation library and an easy-to-use wrapper.. MIT +
Albumentations (🥇32 · ⭐ 11K) - 快速的图像增强库和易于使用的包装器。MIT - [GitHub](https://github.com/albumentations-team/albumentations) (👨‍💻 110 · 🔀 1.4K · 📦 9.1K · 📋 660 - 41% open · ⏱️ 24.08.2022): @@ -2707,7 +2707,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge albumentations ```
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Kornia (🥇32 · ⭐ 7K) - Open Source Differentiable Computer Vision Library for PyTorch. Apache-2 +
Kornia (🥇32 · ⭐ 7K) - PyTorch的开源可微分计算机视觉库。Apache-2 - [GitHub](https://github.com/kornia/kornia) (👨‍💻 170 · 🔀 680 · 📥 430 · 📦 1.7K · 📋 600 - 26% open · ⏱️ 24.08.2022): @@ -2719,7 +2719,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install kornia ```
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scikit-image (🥇32 · ⭐ 5K) - Image processing in Python. ❗Unlicensed +
scikit-image (🥇32 · ⭐ 5K) - Python中的图像处理。❗Unlicensed - [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 560 · 🔀 2K · 📦 110K · 📋 2.3K - 19% open · ⏱️ 23.08.2022): @@ -2735,7 +2735,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge scikit-image ```
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Wand (🥇32 · ⭐ 1.2K) - The ctypes-based simple ImageMagick binding for Python. MIT +
Wand (🥇32 · ⭐ 1.2K) - 用于Python的基于ctypes的简单ImageMagick接口。MIT - [GitHub](https://github.com/emcconville/wand) (👨‍💻 100 · 🔀 190 · 📥 8.5K · 📦 12K · 📋 380 - 4% open · ⏱️ 22.08.2022): @@ -2747,7 +2747,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install wand ```
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PyTorch Image Models (🥈31 · ⭐ 21K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 +
PyTorch Image Models (🥈31 · ⭐ 21K) - PyTorch图像模型，脚本，预训练权重。Apache-2 - [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 79 · 🔀 3.3K · 📥 1.7M · 📦 4.3K · 📋 570 - 9% open · ⏱️ 24.08.2022): @@ -2755,7 +2755,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/rwightman/pytorch-image-models ```
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GluonCV (🥈29 · ⭐ 5.3K) - Gluon CV Toolkit. Apache-2 +
GluonCV (🥈29 · ⭐ 5.3K) - Gluon CV工具包。Apache-2 - [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 120 · 🔀 1.2K · 📦 840 · 📋 810 - 5% open · ⏱️ 11.08.2022): @@ -2767,7 +2767,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install gluoncv ```
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ImageHash (🥈29 · ⭐ 2.5K · 💤) - A Python Perceptual Image Hashing Module. BSD-2 +
ImageHash (🥈29 · ⭐ 2.5K · 💤) - Python感知图像哈希模块。BSD-2 - [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 300 · 📦 5.8K · 📋 110 - 13% open · ⏱️ 07.09.2021): @@ -2783,7 +2783,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imagehash ```
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imutils (🥈28 · ⭐ 4.2K · 💤) - A series of convenience functions to make basic image processing.. MIT +
imutils (🥈28 · ⭐ 4.2K · 💤) - 图像处理库。MIT - [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 21 · 🔀 980 · 📦 27K · 📋 160 - 53% open · ⏱️ 27.01.2022): @@ -2799,7 +2799,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imutils ```
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MMDetection (🥈27 · ⭐ 21K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +
MMDetection (🥈27 · ⭐ 21K) - OpenMMLab检测工具箱。Apache-2 - [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 350 · 🔀 6.9K · 📦 550 · 📋 6.2K - 9% open · ⏱️ 28.07.2022): @@ -2807,7 +2807,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/open-mmlab/mmdetection ```
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torchvision (🥈27 · ⭐ 12K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 +
torchvision (🥈27 · ⭐ 12K) - 计算机视觉的数据集，转换和模型。BSD-3 - [GitHub](https://github.com/pytorch/vision) (👨‍💻 500 · 🔀 6K · 📥 11K · 📋 2.5K - 23% open · ⏱️ 25.08.2022): @@ -2823,7 +2823,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge torchvision ```
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glfw (🥈27 · ⭐ 9.5K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib +
glfw (🥈27 · ⭐ 9.5K) - 一个用于OpenGL，Op​​enGL ES，Vulkan，窗口和输入的多平台库。❗️Zlib - [GitHub](https://github.com/glfw/glfw) (👨‍💻 180 · 🔀 3.5K · 📥 2.9M · 📦 1 · 📋 1.6K - 25% open · ⏱️ 22.08.2022): @@ -2839,7 +2839,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge glfw ```
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InsightFace (🥈26 · ⭐ 12K) - Face Analysis Project on MXNet and PyTorch. MIT +
InsightFace (🥈26 · ⭐ 12K) - MXNet和PyTorch上的人脸分析项目。MIT - [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 46 · 🔀 3.9K · 📦 180 · 📋 2K - 55% open · ⏱️ 19.08.2022): @@ -2851,7 +2851,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install insightface ```
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imageai (🥈26 · ⭐ 7.2K · 💀) - A python library built to empower developers to build applications.. MIT +
imageai (🥈26 · ⭐ 7.2K · 💀) - python库旨在使开发人员能够构建应用程序。MIT - [GitHub](https://github.com/OlafenwaMoses/ImageAI) (👨‍💻 15 · 🔀 1.9K · 📥 780K · 📦 1.2K · 📋 690 - 37% open · ⏱️ 08.05.2021): @@ -2863,7 +2863,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install imageai ```
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Face Recognition (🥈25 · ⭐ 46K) - The world's simplest facial recognition api for.. MIT +
Face Recognition (🥈25 · ⭐ 46K) - 简单的面部识别API。MIT - [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 54 · 🔀 12K · 📥 470 · 📋 1.2K - 53% open · ⏱️ 10.06.2022): @@ -2875,7 +2875,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install face_recognition ```
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detectron2 (🥈25 · ⭐ 22K) - Detectron2 is FAIR's next-generation platform for object.. Apache-2 +
detectron2 (🥈25 · ⭐ 22K) - Detectron2是Facebook FAIR的高级目标检测平台。Apache-2 - [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 210 · 🔀 5.7K · 📦 710 · 📋 3.1K - 7% open · ⏱️ 24.08.2022): @@ -2887,7 +2887,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge detectron2 ```
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vit-pytorch (🥈25 · ⭐ 11K) - Implementation of Vision Transformer, a simple way to.. MIT +
vit-pytorch (🥈25 · ⭐ 11K) - 实现视觉transformer，一种简单的方法。MIT - [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 15 · 🔀 1.8K · 📦 140 · 📋 190 - 47% open · ⏱️ 27.07.2022): @@ -2899,7 +2899,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install vit-pytorch ```
-
facenet-pytorch (🥈25 · ⭐ 3K · 💤) - Pretrained Pytorch face detection (MTCNN) and.. MIT +
facenet-pytorch (🥈25 · ⭐ 3K · 💤) - 预训练的Pytorch人脸检测（MTCNN）和识别。MIT - [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 650 · 📥 390K · 📦 850 · 📋 150 - 39% open · ⏱️ 13.12.2021): @@ -2911,7 +2911,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install facenet-pytorch ```
-
opencv-python (🥈25 · ⭐ 2.9K · 📈) - Automated CI toolchain to produce precompiled opencv-python,.. MIT +
opencv-python (🥈25 · ⭐ 2.9K · 📈) - 自动化的CI工具链可生成预编译的opencv-python。MIT - [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 39 · 🔀 580 · 📋 570 - 7% open · ⏱️ 22.08.2022): @@ -2923,7 +2923,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install opencv-python ```
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chainercv (🥈25 · ⭐ 1.5K · 💀) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT +
chainercv (🥈25 · ⭐ 1.5K · 💀) - ChainerCV：一个用于计算机视觉深度学习的库。MIT - [GitHub](https://github.com/chainer/chainercv) (👨‍💻 39 · 🔀 300 · 📦 300 · 📋 200 - 18% open · ⏱️ 07.01.2020): @@ -2935,7 +2935,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install chainercv ```
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mahotas (🥈25 · ⭐ 770) - Computer Vision in Python. ❗Unlicensed +
mahotas (🥈25 · ⭐ 770) - Python中的计算机视觉。❗Unlicensed - [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 32 · 🔀 140 · 📦 870 · 📋 79 - 20% open · ⏱️ 28.06.2022): @@ -2951,7 +2951,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge mahotas ```
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vidgear (🥉24 · ⭐ 2.4K) - High-performance cross-platform Video Processing Python framework.. Apache-2 +
vidgear (🥉24 · ⭐ 2.4K) - 高性能跨平台视频处理Python框架。Apache-2 - [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 13 · 🔀 190 · 📥 640 · 📦 230 · 📋 230 - 1% open · ⏱️ 06.07.2022): @@ -2963,7 +2963,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install vidgear ```
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PyTorch3D (🥉23 · ⭐ 6.4K) - PyTorch3D is FAIR's library of reusable components for.. ❗Unlicensed +
PyTorch3D (🥉23 · ⭐ 6.4K) - PyTorch3D是FAIR的深度学习可重用组件库。❗Unlicensed - [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 96 · 🔀 940 · 📦 270 · 📋 1.1K - 7% open · ⏱️ 25.08.2022): @@ -2979,7 +2979,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c pytorch3d pytorch3d ```
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Face Alignment (🥉23 · ⭐ 5.8K · 💤) - 2D and 3D Face alignment library build using pytorch. BSD-3 +
Face Alignment (🥉23 · ⭐ 5.8K · 💤) - 使用pytorch构建2D和3D人脸对齐库。BSD-3 - [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.2K · 📋 280 - 21% open · ⏱️ 04.08.2021): @@ -2991,7 +2991,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install face-alignment ```
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Augmentor (🥉23 · ⭐ 4.8K) - Image augmentation library in Python for machine learning. MIT +
Augmentor (🥉23 · ⭐ 4.8K) - Python中的图像增强库，用于机器学习。MIT - [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 820 · 📦 480 · 📋 190 - 61% open · ⏱️ 24.05.2022): @@ -3003,7 +3003,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install Augmentor ```
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mtcnn (🥉23 · ⭐ 1.8K · 💀) - MTCNN face detection implementation for TensorFlow, as a PIP.. MIT +
mtcnn (🥉23 · ⭐ 1.8K · 💀) - TensorFlow的MTCNN人脸检测实现。MIT - [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 460 · 📦 2.6K · 📋 100 - 62% open · ⏱️ 09.07.2021): @@ -3015,7 +3015,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install mtcnn ```
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lightly (🥉23 · ⭐ 1.7K) - A python library for self-supervised learning on images. MIT +
lightly (🥉23 · ⭐ 1.7K) - 一个用于对图像进行自监督学习的python库。MIT - [GitHub](https://github.com/lightly-ai/lightly) (👨‍💻 19 · 🔀 140 · 📦 46 · 📋 330 - 20% open · ⏱️ 25.08.2022): @@ -3027,7 +3027,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install lightly ```
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Image Deduplicator (🥉22 · ⭐ 4.1K · 💀) - Finding duplicate images made easy!. Apache-2 +
Image Deduplicator (🥉22 · ⭐ 4.1K · 💀) - 图像查重。Apache-2 - [GitHub](https://github.com/idealo/imagededup) (👨‍💻 10 · 🔀 370 · 📦 26 · 📋 93 - 36% open · ⏱️ 23.11.2020): @@ -3039,7 +3039,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install imagededup ```
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pyvips (🥉22 · ⭐ 440) - python binding for libvips using cffi. MIT +
pyvips (🥉22 · ⭐ 440) - 使用cffi的libvips的python接口。MIT - [GitHub](https://github.com/libvips/pyvips) (👨‍💻 14 · 🔀 40 · 📦 350 · 📋 300 - 36% open · ⏱️ 13.08.2022): @@ -3055,7 +3055,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge pyvips ```
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PaddleDetection (🥉21 · ⭐ 8.3K) - Object detection and instance segmentation toolkit.. Apache-2 +
PaddleDetection (🥉21 · ⭐ 8.3K) - 对象检测和实例分割工具箱。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 100 · 🔀 2.1K · 📦 30 · 📋 3.8K - 20% open · ⏱️ 16.08.2022): @@ -3075,7 +3075,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install segmentation_models ```
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Image Super-Resolution (🥉21 · ⭐ 3.8K · 💀) - Super-scale your images and run experiments with.. Apache-2 +
Image Super-Resolution (🥉21 · ⭐ 3.8K · 💀) - 图像超精度变换。Apache-2 - [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 630 · 📦 97 · 📋 200 - 45% open · ⏱️ 02.06.2021): @@ -3091,7 +3091,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well docker pull idealo/image-super-resolution-gpu ```
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Norfair (🥉21 · ⭐ 1.6K) - Lightweight Python library for adding real-time 2D object tracking to.. BSD-3 +
Norfair (🥉21 · ⭐ 1.6K) - 轻量级Python库，用于向其中添加实时2D对象跟踪。BSD-3 - [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 18 · 🔀 150 · 📥 200 · 📋 75 - 16% open · ⏱️ 24.08.2022): @@ -3103,7 +3103,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install norfair ```
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CellProfiler (🥉21 · ⭐ 700) - An open-source application for biological image analysis. ❗Unlicensed +
CellProfiler (🥉21 · ⭐ 700) - 生物图像分析的开源应用程序。❗Unlicensed - [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 130 · 🔀 320 · 📥 3.4K · 📦 9 · 📋 3.1K - 5% open · ⏱️ 17.08.2022): @@ -3115,7 +3115,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install cellprofiler ```
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MMF (🥉20 · ⭐ 5K) - A modular framework for vision & language multimodal research from.. BSD-3 +
MMF (🥉20 · ⭐ 5K) - 来自视觉和语言多模态研究的模块化框架。BSD-3 - [GitHub](https://github.com/facebookresearch/mmf) (👨‍💻 100 · 🔀 840 · 📦 12 · 📋 620 - 30% open · ⏱️ 11.08.2022): @@ -3127,7 +3127,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install mmf ```
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tensorflow-graphics (🥉20 · ⭐ 2.7K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 +
tensorflow-graphics (🥉20 · ⭐ 2.7K) - TensorFlow图神经网络：可微分的图layerApache-2 - [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 36 · 🔀 340 · 📋 160 - 45% open · ⏱️ 04.04.2022): @@ -3139,7 +3139,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install tensorflow-graphics ```
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nude.py (🥉20 · ⭐ 860 · 💀) - Nudity detection with Python. MIT +
nude.py (🥉20 · ⭐ 860 · 💀) - 使用Python进行裸露检测。MIT - [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 2.6K · 📋 10 - 70% open · ⏱️ 23.11.2020): @@ -3151,7 +3151,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install nudepy ```
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Luminoth (🥉19 · ⭐ 2.4K · 💀) - Deep Learning toolkit for Computer Vision. BSD-3 +
Luminoth (🥉19 · ⭐ 2.4K · 💀) - 用于计算机视觉的深度学习工具包。BSD-3 - [GitHub](https://github.com/tryolabs/luminoth) (👨‍💻 15 · 🔀 400 · 📥 13K · 📦 41 · 📋 180 - 28% open · ⏱️ 07.01.2020): @@ -3163,7 +3163,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install luminoth ```
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Classy Vision (🥉19 · ⭐ 1.5K) - An end-to-end PyTorch framework for image and video.. MIT +
Classy Vision (🥉19 · ⭐ 1.5K) - 用于图像和视频的端到端PyTorch框架。MIT - [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 76 · 🔀 260 · 📋 76 - 17% open · ⏱️ 03.08.2022): @@ -3179,7 +3179,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge classy_vision ```
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Caer (🥉18 · ⭐ 630 · 💤) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT +
Caer (🥉18 · ⭐ 630 · 💤) - 轻量级的计算机视觉库。MIT - [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 8 · 🔀 74 · 📥 19 · 📋 15 - 13% open · ⏱️ 13.10.2021): @@ -3199,7 +3199,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/facebookresearch/detr ```
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Pillow-SIMD (🥉17 · ⭐ 1.9K · 💤) - The friendly PIL fork. ❗️PIL +
Pillow-SIMD (🥉17 · ⭐ 1.9K · 💤) - 友好的PIL fork。❗️PIL - [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 380 · 🔀 74 · 📋 77 - 14% open · ⏱️ 17.01.2022): @@ -3211,7 +3211,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install pillow-simd ```
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PySlowFast (🥉16 · ⭐ 5K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 +
PySlowFast (🥉16 · ⭐ 5K) - PySlowFast：来自FAIR的视频理解代码库。Apache-2 - [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 28 · 🔀 960 · 📦 10 · 📋 550 - 52% open · ⏱️ 25.08.2022): @@ -3219,7 +3219,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/facebookresearch/SlowFast ```
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image-match (🥉16 · ⭐ 2.8K · 💤) - Quickly search over billions of images. ❗Unlicensed +
image-match (🥉16 · ⭐ 2.8K · 💤) - 快速搜索数十亿张图像。❗Unlicensed - [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 380 · 📋 100 - 53% open · ⏱️ 21.09.2021): @@ -3231,7 +3231,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install image_match ```
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pycls (🥉15 · ⭐ 2K) - Codebase for Image Classification Research, written in PyTorch. MIT +
pycls (🥉15 · ⭐ 2K) - 用PyTorch编写的图像分类研究代码库。MIT - [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 17 · 🔀 230 · 📦 6 · 📋 78 - 28% open · ⏱️ 12.07.2022): @@ -3239,7 +3239,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/facebookresearch/pycls ```
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Torch Points 3D (🥉14 · ⭐ 93 · 💤) - Pytorch framework for doing deep learning on point.. BSD-3 +
Torch Points 3D (🥉14 · ⭐ 93 · 💤) - 用于在点云上进行深度学习的Pytorch框架。BSD-3 - [GitHub](https://github.com/nicolas-chaulet/torch-points3d) (👨‍💻 29 · 🔀 19 · ⏱️ 10.12.2021): @@ -3253,13 +3253,13 @@ _Libraries for image & video processing, manipulation, and augmentation as well

-## Graph Data +## 图数据处理 -Back to top +Back to top -_Libraries for graph processing, clustering, embedding, and machine learning tasks._ +_用于图数据处理，聚类，图嵌入和机器学习任务的库。_ -
networkx (🥇32 · ⭐ 11K) - Network Analysis in Python. ❗Unlicensed +
networkx (🥇32 · ⭐ 11K) - Python中的网络分析。❗Unlicensed - [GitHub](https://github.com/networkx/networkx) (👨‍💻 610 · 🔀 2.6K · 📥 60 · 📦 120K · 📋 2.8K - 5% open · ⏱️ 23.08.2022): @@ -3275,7 +3275,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge networkx ```
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dgl (🥇29 · ⭐ 10K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 +
dgl (🥇29 · ⭐ 10K) - 在现有基础之上构建的Python软件包，用于简化图上的深度学习。Apache-2 - [GitHub](https://github.com/dmlc/dgl) (👨‍💻 230 · 🔀 2.4K · 📦 30 · 📋 1.7K - 13% open · ⏱️ 25.08.2022): @@ -3287,7 +3287,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install dgl ```
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PyTorch Geometric (🥇28 · ⭐ 15K) - Geometric Deep Learning Extension Library for PyTorch. MIT +
PyTorch Geometric (🥇28 · ⭐ 15K) - PyTorch的几何深度学习扩展库。MIT - [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 300 · 🔀 2.7K · 📋 2.6K - 35% open · ⏱️ 25.08.2022): @@ -3299,7 +3299,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-geometric ```
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ogb (🥇28 · ⭐ 1.4K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT +
ogb (🥇28 · ⭐ 1.4K) - 用于图机器学习的基准数据集，数据加载器和评估器。MIT - [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 23 · 🔀 310 · 📦 380 · 📋 230 - 0% open · ⏱️ 22.08.2022): @@ -3311,7 +3311,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install ogb ```
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igraph (🥈27 · ⭐ 1K) - Python interface for igraph. ❗️GPL-2.0 +
igraph (🥈27 · ⭐ 1K) - Igraph的Python接口。❗️GPL-2.0 - [GitHub](https://github.com/igraph/python-igraph) (👨‍💻 61 · 🔀 220 · 📥 460K · 📦 850 · 📋 410 - 9% open · ⏱️ 24.08.2022): @@ -3327,7 +3327,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge igraph ```
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StellarGraph (🥈25 · ⭐ 2.5K · 💤) - StellarGraph - Machine Learning on Graphs. Apache-2 +
StellarGraph (🥈25 · ⭐ 2.5K · 💤) - StellarGraph-图机器学习库。Apache-2 - [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 380 · 📦 160 · 📋 1K - 27% open · ⏱️ 29.10.2021): @@ -3339,7 +3339,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install stellargraph ```
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Spektral (🥈25 · ⭐ 2.1K) - Graph Neural Networks with Keras and Tensorflow 2. MIT +
Spektral (🥈25 · ⭐ 2.1K) - 使用Keras和Tensorflow 2的图神经网络。MIT - [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 24 · 🔀 300 · 📦 140 · 📋 230 - 16% open · ⏱️ 22.07.2022): @@ -3351,7 +3351,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install spektral ```
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Karate Club (🥈23 · ⭐ 1.7K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 +
Karate Club (🥈23 · ⭐ 1.7K) - 面向API的开源Python框架。❗️GPL-3.0 - [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 15 · 🔀 210 · 📦 100 · ⏱️ 20.08.2022): @@ -3375,7 +3375,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-geometric-temporal ```
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AmpliGraph (🥈22 · ⭐ 1.8K · 💀) - Python library for Representation Learning on Knowledge.. Apache-2 +
AmpliGraph (🥈22 · ⭐ 1.8K · 💀) - 用于知识表示学习的Python库。Apache-2 - [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 210 · 📦 25 · 📋 210 - 12% open · ⏱️ 25.05.2021): @@ -3387,7 +3387,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install ampligraph ```
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Paddle Graph Learning (🥈22 · ⭐ 1.4K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 +
Paddle Graph Learning (🥈22 · ⭐ 1.4K) - paddle图机器学习。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 28 · 🔀 270 · 📦 33 · 📋 150 - 35% open · ⏱️ 22.08.2022): @@ -3399,7 +3399,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pgl ```
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pygal (🥈21 · ⭐ 2.5K · 💤) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 +
pygal (🥈21 · ⭐ 2.5K · 💤) - PYthon svg GrAph绘图库。❗️LGPL-3.0 - [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 390 · 📋 400 - 39% open · ⏱️ 24.11.2021): @@ -3415,7 +3415,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge pygal ```
-
PyKEEN (🥈21 · ⭐ 960) - A Python library for learning and evaluating knowledge graph embeddings. MIT +
PyKEEN (🥈21 · ⭐ 960) - 一个用于学习和评估知识图嵌入的Python库。MIT - [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 31 · 🔀 130 · 📥 140 · 📋 420 - 13% open · ⏱️ 25.08.2022): @@ -3427,7 +3427,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pykeen ```
-
Node2Vec (🥈21 · ⭐ 950) - Implementation of the node2vec algorithm. MIT +
Node2Vec (🥈21 · ⭐ 950) - node2vec算法的实现。MIT - [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 11 · 🔀 200 · ⏱️ 01.08.2022): @@ -3443,7 +3443,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge node2vec ```
-
torch-cluster (🥈21 · ⭐ 560) - PyTorch Extension Library of Optimized Graph Cluster.. MIT +
torch-cluster (🥈21 · ⭐ 560) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 25 · 🔀 100 · 📋 110 - 17% open · ⏱️ 22.08.2022): @@ -3455,7 +3455,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-cluster ```
-
PyTorch-BigGraph (🥉19 · ⭐ 3.1K) - Generate embeddings from large-scale graph-structured.. ❗Unlicensed +
PyTorch-BigGraph (🥉19 · ⭐ 3.1K) - 从大型图网络结构生成embedding嵌入。❗Unlicensed - [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 27 · 🔀 410 · 📥 140 · 📋 190 - 26% open · ⏱️ 05.07.2022): @@ -3467,7 +3467,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torchbiggraph ```
-
DeepWalk (🥉19 · ⭐ 2.5K · 💀) - DeepWalk - Deep Learning for Graphs. ❗Unlicensed +
DeepWalk (🥉19 · ⭐ 2.5K · 💀) - DeepWalk-图的深度学习。❗Unlicensed - [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 810 · 📦 56 · 📋 110 - 24% open · ⏱️ 02.04.2020): @@ -3479,7 +3479,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install deepwalk ```
-
kglib (🥉17 · ⭐ 520) - Grakn Knowledge Graph Library (ML R&D). Apache-2 +
kglib (🥉17 · ⭐ 520) - Grakn知识图库（ML R＆D）。Apache-2 - [GitHub](https://github.com/vaticle/typedb-ml) (👨‍💻 9 · 🔀 88 · 📥 210 · 📋 60 - 16% open · ⏱️ 01.08.2022): @@ -3491,7 +3491,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install grakn-kglib ```
-
GraphEmbedding (🥉16 · ⭐ 3K) - Implementation and experiments of graph embedding algorithms. MIT +
GraphEmbedding (🥉16 · ⭐ 3K) - 图嵌入算法的实现和实验。MIT - [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 9 · 🔀 860 · 📦 21 · 📋 57 - 59% open · ⏱️ 21.06.2022): @@ -3499,7 +3499,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/shenweichen/GraphEmbedding ```
-
graph-nets (🥉15 · ⭐ 5.2K · 💀) - Build Graph Nets in Tensorflow. Apache-2 +
graph-nets (🥉15 · ⭐ 5.2K · 💀) - 在Tensorflow中构建图神经网络。Apache-2 - [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 770 · 📋 120 - 2% open · ⏱️ 04.12.2020): @@ -3511,7 +3511,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install graph-nets ```
-
Euler (🥉15 · ⭐ 2.8K · 💀) - A distributed graph deep learning framework. Apache-2 +
Euler (🥉15 · ⭐ 2.8K · 💀) - 分布式图深度学习框架。Apache-2 - [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 550 · 📋 320 - 67% open · ⏱️ 29.07.2020): @@ -3523,7 +3523,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install euler-gl ```
-
DeepGraph (🥉15 · ⭐ 260 · 💀) - Analyze Data with Pandas-based Networks... ❗Unlicensed +
DeepGraph (🥉15 · ⭐ 260 · 💀) - 使用基于pandas的网络分析数据。❗Unlicensed - [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 38 · 📦 5 · 📋 14 - 64% open · ⏱️ 14.06.2021): @@ -3539,7 +3539,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge deepgraph ```
-
pyRDF2Vec (🥉15 · ⭐ 160) - Python Implementation and Extension of RDF2Vec. MIT +
pyRDF2Vec (🥉15 · ⭐ 160) - RDF2Vec的Python实现和扩展。MIT - [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 6 · 🔀 32 · 📋 61 - 14% open · ⏱️ 06.05.2022): @@ -3551,7 +3551,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pyrdf2vec ```
-
GraphSAGE (🥉14 · ⭐ 2.8K · 💀) - Representation learning on large graphs using stochastic.. MIT +
GraphSAGE (🥉14 · ⭐ 2.8K · 💀) - 大型图上的表示学习。MIT - [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 770 · 📋 160 - 62% open · ⏱️ 19.09.2018): @@ -3559,7 +3559,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/williamleif/GraphSAGE ```
-
OpenNE (🥉14 · ⭐ 1.6K · 💀) - An Open-Source Package for Network Embedding (NE). MIT +
OpenNE (🥉14 · ⭐ 1.6K · 💀) - 神经关系提取（NRE）的开源软件包。MIT - [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 480 · 📋 97 - 1% open · ⏱️ 12.08.2019): @@ -3567,7 +3567,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/thunlp/OpenNE ```
-
AutoGL (🥉14 · ⭐ 840) - An autoML framework & toolkit for machine learning on graphs. Apache-2 +
AutoGL (🥉14 · ⭐ 840) - 用于图上机器学习的autoML框架和工具包。Apache-2 - [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 13 · 🔀 98 · 📋 23 - 34% open · ⏱️ 19.04.2022): @@ -3579,7 +3579,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install auto-graph-learning ```
-
Sematch (🥉14 · ⭐ 400 · 💀) - semantic similarity framework for knowledge graph. Apache-2 +
Sematch (🥉14 · ⭐ 400 · 💀) - 知识图的语义相似性框架。Apache-2 - [GitHub](https://github.com/gsi-upm/sematch) (👨‍💻 5 · 🔀 100 · 📦 34 · 📋 33 - 42% open · ⏱️ 27.03.2019): @@ -3591,7 +3591,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install sematch ```
-
GraphVite (🥉12 · ⭐ 1.1K · 💀) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 +
GraphVite (🥉12 · ⭐ 1.1K · 💀) - GraphVite：通用的高性能图形嵌入系统。Apache-2 - [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 140 · 📋 100 - 42% open · ⏱️ 14.01.2021): @@ -3603,7 +3603,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c milagraph graphvite ```
-
OpenKE (🥉11 · ⭐ 3.2K · 💀) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed +
OpenKE (🥉11 · ⭐ 3.2K · 💀) - 神经关系提取（NRE）的开源软件包。❗Unlicensed - [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 900 · 📋 350 - 1% open · ⏱️ 06.04.2021): @@ -3613,13 +3613,13 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas

-## Audio Data +## 音频处理 -Back to top +Back to top -_Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks._ +_用于音频分析，处理，转换和提取以及语音识别和音乐生成任务的库。_ -
DeepSpeech (🥇30 · ⭐ 20K · 💤) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +
DeepSpeech (🥇30 · ⭐ 20K · 💤) - DeepSpeech是开源的语音转文本引擎。MPL-2.0 - [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 160 · 🔀 3.4K · 📥 880K · 📦 800 · 📋 2.1K - 5% open · ⏱️ 17.11.2021): @@ -3631,7 +3631,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install deepspeech ```
-
Pydub (🥇30 · ⭐ 6.3K) - Manipulate audio with a simple and easy high level interface. MIT +
Pydub (🥇30 · ⭐ 6.3K) - 使用简单易用的高级界面处理音频。MIT - [GitHub](https://github.com/jiaaro/pydub) (👨‍💻 92 · 🔀 840 · 📦 14K · 📋 490 - 46% open · ⏱️ 14.05.2022): @@ -3647,7 +3647,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge pydub ```
-
espnet (🥇29 · ⭐ 5.4K) - End-to-End Speech Processing Toolkit. Apache-2 +
espnet (🥇29 · ⭐ 5.4K) - 端到端语音处理工具包。Apache-2 - [GitHub](https://github.com/espnet/espnet) (👨‍💻 280 · 🔀 1.6K · 📥 76 · 📦 67 · 📋 1.9K - 15% open · ⏱️ 24.08.2022): @@ -3659,7 +3659,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install espnet ```
-
Magenta (🥈27 · ⭐ 18K) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 +
Magenta (🥈27 · ⭐ 18K) - 借助机器智能进行音乐和艺术创作。Apache-2 - [GitHub](https://github.com/magenta/magenta) (👨‍💻 150 · 🔀 3.5K · 📦 380 · 📋 890 - 34% open · ⏱️ 08.08.2022): @@ -3671,7 +3671,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install magenta ```
-
torchaudio (🥈27 · ⭐ 1.8K) - Data manipulation and transformation for audio signal.. BSD-2 +
torchaudio (🥈27 · ⭐ 1.8K) - 音频信号的数据处理和转换。BSD-2 - [GitHub](https://github.com/pytorch/audio) (👨‍💻 170 · 🔀 450 · 📋 640 - 20% open · ⏱️ 26.08.2022): @@ -3683,7 +3683,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install torchaudio ```
-
aubio (🥈26 · ⭐ 2.8K · 💤) - a library for audio and music analysis. ❗️GPL-3.0 +
aubio (🥈26 · ⭐ 2.8K · 💤) - 用于音频和音乐分析的库。❗️GPL-3.0 - [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 340 · 📦 310 · 📋 310 - 41% open · ⏱️ 25.01.2022): @@ -3699,7 +3699,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge aubio ```
-
spleeter (🥈24 · ⭐ 20K) - Deezer source separation library including pretrained models. MIT +
spleeter (🥈24 · ⭐ 20K) - Deezer源分离库，包括预训练的模型。MIT - [GitHub](https://github.com/deezer/spleeter) (👨‍💻 19 · 🔀 2.2K · 📥 1.8M · 📋 680 - 21% open · ⏱️ 10.06.2022): @@ -3715,7 +3715,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge spleeter ```
-
SpeechRecognition (🥈24 · ⭐ 6.5K) - Speech recognition module for Python, supporting.. BSD-3 +
SpeechRecognition (🥈24 · ⭐ 6.5K) - 适用于Python的语音识别模块。BSD-3 - [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 47 · 🔀 2K · 📋 510 - 44% open · ⏱️ 02.08.2022): @@ -3731,7 +3731,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge speechrecognition ```
-
pyAudioAnalysis (🥈24 · ⭐ 4.9K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 +
pyAudioAnalysis (🥈24 · ⭐ 4.9K) - Python音频分析库。Apache-2 - [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 26 · 🔀 1.1K · 📦 290 · 📋 290 - 59% open · ⏱️ 19.04.2022): @@ -3743,7 +3743,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install pyAudioAnalysis ```
-
Essentia (🥈24 · ⭐ 2.2K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 +
Essentia (🥈24 · ⭐ 2.2K) - C++库，用于音频和音乐分析，描述等。❗️AGPL-3.0 - [GitHub](https://github.com/MTG/essentia) (👨‍💻 74 · 🔀 460 · 📦 320 · 📋 950 - 36% open · ⏱️ 23.08.2022): @@ -3755,7 +3755,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install essentia ```
-
librosa (🥉23 · ⭐ 5.4K) - Python library for audio and music analysis. ISC +
librosa (🥉23 · ⭐ 5.4K) - 用于音频和音乐分析的Python库。ISC - [GitHub](https://github.com/librosa/librosa) (👨‍💻 110 · 🔀 810 · 📋 1K - 4% open · ⏱️ 25.08.2022): @@ -3771,7 +3771,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge librosa ```
-
tinytag (🥉23 · ⭐ 560) - Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and.. MIT +
tinytag (🥉23 · ⭐ 560) - 读取音乐元数据和MP3，OGG，OPUS，MP4，M4A，FLAC，WMA等的长度。MIT - [GitHub](https://github.com/devsnd/tinytag) (👨‍💻 22 · 🔀 88 · 📦 580 · 📋 93 - 12% open · ⏱️ 13.08.2022): @@ -3783,7 +3783,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install tinytag ```
-
kapre (🥉22 · ⭐ 850) - kapre: Keras Audio Preprocessors. MIT +
kapre (🥉22 · ⭐ 850) - kapre：Keras音频预处理器。MIT - [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 140 · 📥 22 · 📦 1.8K · 📋 94 - 12% open · ⏱️ 04.07.2022): @@ -3795,7 +3795,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install kapre ```
-
Porcupine (🥉21 · ⭐ 2.8K) - On-device wake word detection powered by deep learning. Apache-2 +
Porcupine (🥉21 · ⭐ 2.8K) - 深度学习支持的设备上唤醒词识别。Apache-2 - [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 31 · 🔀 380 · 📦 9 · 📋 390 - 0% open · ⏱️ 26.08.2022): @@ -3807,7 +3807,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install pvporcupine ```
-
DDSP (🥉21 · ⭐ 2.2K) - DDSP: Differentiable Digital Signal Processing. Apache-2 +
DDSP (🥉21 · ⭐ 2.2K) - DDSP：微分数字信号处理。Apache-2 - [GitHub](https://github.com/magenta/ddsp) (👨‍💻 31 · 🔀 250 · 📦 28 · 📋 140 - 18% open · ⏱️ 16.05.2022): @@ -3819,7 +3819,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install ddsp ```
-
python-soundfile (🥉21 · ⭐ 470) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 +
python-soundfile (🥉21 · ⭐ 470) - SoundFile是基于libsndfile，CFFI等的音频库。BSD-3 - [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 24 · 🔀 75 · 📥 4K · 📋 170 - 39% open · ⏱️ 23.02.2022): @@ -3843,7 +3843,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install python_speech_features ```
-
TTS (🥉19 · ⭐ 6.2K · 💀) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 +
TTS (🥉19 · ⭐ 6.2K · 💀) - 文本到语音的深度学习。MPL-2.0 - [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 930 · 📥 2.6K · 📋 540 - 0% open · ⏱️ 12.02.2021): @@ -3851,7 +3851,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as git clone https://github.com/mozilla/TTS ```
-
Dejavu (🥉19 · ⭐ 5.8K · 💀) - Audio fingerprinting and recognition in Python. MIT +
Dejavu (🥉19 · ⭐ 5.8K · 💀) - Python中的音频指纹识别。MIT - [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 22 · 🔀 1.3K · 📦 23 · 📋 210 - 39% open · ⏱️ 03.06.2020): @@ -3863,7 +3863,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install PyDejavu ```
-
Madmom (🥉19 · ⭐ 950 · 💤) - Python audio and music signal processing library. ❗Unlicensed +
Madmom (🥉19 · ⭐ 950 · 💤) - Python音频和音乐信号处理库。❗Unlicensed - [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 150 · 📦 210 · 📋 240 - 16% open · ⏱️ 06.01.2022): @@ -3875,7 +3875,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install madmom ```
-
audioread (🥉19 · ⭐ 410 · 📉) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. MIT +
audioread (🥉19 · ⭐ 410 · 📉) - 跨库（GStreamer + Core Audio + MAD + FFmpeg）音频编解码。MIT - [GitHub](https://github.com/beetbox/audioread) (👨‍💻 22 · 🔀 94 · 📋 80 - 38% open · ⏱️ 12.08.2022): @@ -3891,7 +3891,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge audioread ```
-
Muda (🥉17 · ⭐ 210 · 💀) - A library for augmenting annotated audio data. ISC +
Muda (🥉17 · ⭐ 210 · 💀) - 用于扩充带注释的音频数据的库。ISC - [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 32 · 📦 15 · 📋 50 - 12% open · ⏱️ 03.05.2021): @@ -3903,7 +3903,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install muda ```
-
Julius (🥉15 · ⭐ 280 · 💤) - Fast PyTorch based DSP for audio and 1D signals. MIT +
Julius (🥉15 · ⭐ 280 · 💤) - 基于PyTorch的快速DSP，用于音频和一维信号。MIT - [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 18 · 📦 120 · ⏱️ 28.01.2022): @@ -3917,13 +3917,13 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as

-## Geospatial Data +## 地理Geo处理 -Back to top +Back to top -_Libraries to load, process, analyze, and write geographic data as well as libraries for spatial analysis, map visualization, and geocoding._ +_用于加载，处理，分析和写入geo地理数据的库，以及用于空间分析，地图可视化和地理编码的库。_ -
pydeck (🥇35 · ⭐ 10K) - WebGL2 powered geospatial visualization layers. MIT +
pydeck (🥇35 · ⭐ 10K) - WebGL2支持的地理空间可视化图层。MIT - [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 200 · 🔀 1.7K · 📦 4.5K · 📋 2.5K - 5% open · ⏱️ 24.08.2022): @@ -3943,7 +3943,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra npm install deck.gl ```
-
geopy (🥇32 · ⭐ 3.7K) - Geocoding library for Python. MIT +
geopy (🥇32 · ⭐ 3.7K) - 适用于Python的地址解析库。MIT - [GitHub](https://github.com/geopy/geopy) (👨‍💻 130 · 🔀 580 · 📦 41K · 📋 260 - 7% open · ⏱️ 07.08.2022): @@ -3959,7 +3959,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopy ```
-
Shapely (🥇31 · ⭐ 2.9K) - Manipulation and analysis of geometric objects. BSD-3 +
Shapely (🥇31 · ⭐ 2.9K) - 操作和分析几何对象。BSD-3 - [GitHub](https://github.com/shapely/shapely) (👨‍💻 130 · 🔀 460 · 📥 220 · 📦 32K · 📋 910 - 17% open · ⏱️ 23.08.2022): @@ -3975,7 +3975,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge shapely ```
-
Geocoder (🥇31 · ⭐ 1.5K · 💀) - Python Geocoder. MIT +
Geocoder (🥇31 · ⭐ 1.5K · 💀) - Python Geocoder。MIT - [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 73 · 🔀 260 · 📦 5.3K · 📋 290 - 25% open · ⏱️ 12.10.2018): @@ -3991,7 +3991,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geocoder ```
-
GeoPandas (🥈30 · ⭐ 3.3K) - Python tools for geographic data. BSD-3 +
GeoPandas (🥈30 · ⭐ 3.3K) - 用于地理数据的Python工具。BSD-3 - [GitHub](https://github.com/geopandas/geopandas) (👨‍💻 180 · 🔀 700 · 📥 1.6K · 📦 15K · 📋 1.3K - 26% open · ⏱️ 25.08.2022): @@ -4007,7 +4007,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopandas ```
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ipyleaflet (🥈30 · ⭐ 1.3K) - A Jupyter - Leaflet.js bridge. MIT +
ipyleaflet (🥈30 · ⭐ 1.3K) - Jupyter-Leaflet.js桥。MIT - [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 80 · 🔀 320 · 📦 2.6K · 📋 500 - 36% open · ⏱️ 23.08.2022): @@ -4027,7 +4027,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra npm install jupyter-leaflet ```
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Fiona (🥈30 · ⭐ 940) - Fiona reads and writes geographic data files. BSD-3 +
Fiona (🥈30 · ⭐ 940) - Fiona读写地理数据文件。BSD-3 - [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 66 · 🔀 170 · 📦 9.4K · 📋 680 - 10% open · ⏱️ 01.03.2022): @@ -4043,7 +4043,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge fiona ```
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pyproj (🥈29 · ⭐ 780) - Python interface to PROJ (cartographic projections and coordinate.. MIT +
pyproj (🥈29 · ⭐ 780) - 与PROJ的Python界面（图形投影和坐标。MIT - [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 52 · 🔀 180 · 📦 16K · 📋 500 - 1% open · ⏱️ 26.08.2022): @@ -4059,7 +4059,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pyproj ```
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folium (🥈28 · ⭐ 5.9K) - Python Data. Leaflet.js Maps. MIT +
folium (🥈28 · ⭐ 5.9K) - Leaflet.js地图的Python数据。MIT - [GitHub](https://github.com/python-visualization/folium) (👨‍💻 130 · 🔀 2.1K · 📦 18K · 📋 940 - 22% open · ⏱️ 06.05.2022): @@ -4075,7 +4075,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge folium ```
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Rasterio (🥉27 · ⭐ 1.8K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed +
Rasterio (🥉27 · ⭐ 1.8K) - Rasterio读写地理空间栅格数据集。❗Unlicensed - [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 130 · 🔀 470 · 📥 760 · 📦 5.4K · 📋 1.6K - 8% open · ⏱️ 18.08.2022): @@ -4091,7 +4091,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge rasterio ```
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geojson (🥉27 · ⭐ 740) - Python bindings and utilities for GeoJSON. BSD-3 +
geojson (🥉27 · ⭐ 740) - GeoJSON的Python接口。BSD-3 - [GitHub](https://github.com/jazzband/geojson) (👨‍💻 48 · 🔀 93 · 📦 10K · 📋 85 - 25% open · ⏱️ 07.05.2022): @@ -4107,7 +4107,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geojson ```
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Cartopy (🥉26 · ⭐ 1.8K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed +
Cartopy (🥉26 · ⭐ 1.8K) - Rasterio读写地理空间栅格数据集。❗Unlicensed - [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 130 · 🔀 470 · 📥 760 · 📦 5.4K · 📋 1.6K - 8% open · ⏱️ 18.08.2022): @@ -4123,7 +4123,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge cartopy ```
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GeoViews (🥉25 · ⭐ 430) - Simple, concise geographical visualization in Python. BSD-3 +
GeoViews (🥉25 · ⭐ 430) - 使用Python进行简单，简洁的地理可视化。BSD-3 - [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 28 · 🔀 66 · 📦 470 · 📋 300 - 34% open · ⏱️ 24.08.2022): @@ -4139,7 +4139,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geoviews ```
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ArcGIS API (🥉24 · ⭐ 1.4K) - Documentation and samples for ArcGIS API for Python. Apache-2 +
ArcGIS API (🥉24 · ⭐ 1.4K) - ArcGIS API for Python的文档和示例。Apache-2 - [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 81 · 🔀 910 · 📥 5.2K · 📋 470 - 8% open · ⏱️ 17.08.2022): @@ -4155,7 +4155,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra docker pull esridocker/arcgis-api-python-notebook ```
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PySAL (🥉23 · ⭐ 1.1K) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 +
PySAL (🥉23 · ⭐ 1.1K) - PySAL：Python空间分析库元包。BSD-3 - [GitHub](https://github.com/pysal/pysal) (👨‍💻 77 · 🔀 260 · 📋 610 - 1% open · ⏱️ 23.07.2022): @@ -4171,7 +4171,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pysal ```
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Sentinelsat (🥉22 · ⭐ 790) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 +
Sentinelsat (🥉22 · ⭐ 790) - 搜索和下载哥白尼前哨卫星图像。❗️GPL-3.0 - [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 42 · 🔀 200 · 📥 230 · 📦 350 · 📋 330 - 2% open · ⏱️ 01.08.2022): @@ -4183,7 +4183,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install sentinelsat ```
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Mapbox GL (🥉22 · ⭐ 620 · 💀) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT +
Mapbox GL (🥉22 · ⭐ 620 · 💀) - 使用Mapbox GL JS可视化Python Jupyter笔记本中的数据。MIT - [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 21 · 🔀 130 · 📦 140 · 📋 99 - 32% open · ⏱️ 19.04.2021): @@ -4195,7 +4195,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install mapboxgl ```
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Satpy (🥉21 · ⭐ 850) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 +
Satpy (🥉21 · ⭐ 850) - 用于地球观测卫星数据处理的Python软件包。❗️GPL-3.0 - [GitHub](https://github.com/pytroll/satpy) (👨‍💻 130 · 🔀 240 · 📦 72 · 📋 790 - 38% open · ⏱️ 25.08.2022): @@ -4211,7 +4211,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge satpy ```
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EarthPy (🥉21 · ⭐ 380 · 💤) - A package built to support working with spatial data using open.. BSD-3 +
EarthPy (🥉21 · ⭐ 380 · 💤) - 使用开放源代码处理空间数据。BSD-3 - [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 140 · 📦 160 · 📋 230 - 8% open · ⏱️ 20.12.2021): @@ -4227,7 +4227,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge earthpy ```
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geoplotlib (🥉19 · ⭐ 970 · 💀) - python toolbox for visualizing geographical data and making maps. MIT +
geoplotlib (🥉19 · ⭐ 970 · 💀) - python工具箱，用于可视化地理数据和制作地图。MIT - [GitHub](https://github.com/andrea-cuttone/geoplotlib) (👨‍💻 8 · 🔀 160 · 📦 150 · 📋 44 - 56% open · ⏱️ 06.05.2019): @@ -4239,7 +4239,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install geoplotlib ```
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gmaps (🥉18 · ⭐ 740 · 💀) - Google maps for Jupyter notebooks. BSD-3 +
gmaps (🥉18 · ⭐ 740 · 💀) - Google为Jupyter笔记本电脑映射。BSD-3 - [GitHub](https://github.com/pbugnion/gmaps) (👨‍💻 16 · 🔀 140 · 📦 1 · 📋 200 - 32% open · ⏱️ 22.07.2019): @@ -4259,7 +4259,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra npm install jupyter-gmaps ```
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pymap3d (🥉18 · ⭐ 270) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 +
pymap3d (🥉18 · ⭐ 270) - 纯Python实现（Numpy可选）的3D坐标转换。BSD-2 - [GitHub](https://github.com/geospace-code/pymap3d) (👨‍💻 11 · 🔀 68 · 📋 38 - 2% open · ⏱️ 03.07.2022): @@ -4277,13 +4277,13 @@ _Libraries to load, process, analyze, and write geographic data as well as libra

-## Financial Data +## 金融数据处理 -Back to top +Back to top -_Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data._ +_用于算法股票/加密交易，风险分析，回测，技术分析以及其他金融数据任务的库。_ -
zipline (🥇30 · ⭐ 15K · 💀) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 +
zipline (🥇30 · ⭐ 15K · 💀) - Zipline，一个Pythonic算法交易库。Apache-2 - [GitHub](https://github.com/quantopian/zipline) (👨‍💻 160 · 🔀 4K · 📦 880 · 📋 970 - 32% open · ⏱️ 14.10.2020): @@ -4295,7 +4295,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install zipline ```
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yfinance (🥇30 · ⭐ 7.5K) - Yahoo! Finance market data downloader (+faster Pandas Datareader). Apache-2 +
yfinance (🥇30 · ⭐ 7.5K) - Yahoo! 金融市场数据下载器（+更快的Pandas数据加载读取器）。Apache-2 - [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 60 · 🔀 1.6K · 📦 13K · 📋 810 - 56% open · ⏱️ 11.07.2022): @@ -4311,7 +4311,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c ranaroussi yfinance ```
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backtrader (🥇27 · ⭐ 9.2K · 💀) - Python Backtesting library for trading strategies. ❗️GPL-3.0 +
backtrader (🥇27 · ⭐ 9.2K · 💀) - 用于交易策略的Python Backtesting库。❗️GPL-3.0 - [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.7K · 📦 1.1K · ⏱️ 17.07.2021): @@ -4323,7 +4323,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install backtrader ```
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pyfolio (🥈26 · ⭐ 4.5K · 💀) - Portfolio and risk analytics in Python. Apache-2 +
pyfolio (🥈26 · ⭐ 4.5K · 💀) - Python中的投资组合和风险分析。Apache-2 - [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 56 · 🔀 1.4K · 📦 450 · 📋 400 - 34% open · ⏱️ 15.07.2020): @@ -4339,7 +4339,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge pyfolio ```
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ta (🥈26 · ⭐ 3.2K) - Technical Analysis Library using Pandas and Numpy. MIT +
ta (🥈26 · ⭐ 3.2K) - 使用Pandas和Numpy的技术分析库。MIT - [GitHub](https://github.com/bukosabino/ta) (👨‍💻 29 · 🔀 720 · 📦 1.4K · 📋 200 - 51% open · ⏱️ 23.08.2022): @@ -4351,7 +4351,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install ta ```
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ffn (🥈26 · ⭐ 1.3K) - ffn - a financial function library for Python. MIT +
ffn (🥈26 · ⭐ 1.3K) - ffn-Python的金融函数库。MIT - [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 28 · 🔀 220 · 📦 220 · 📋 100 - 20% open · ⏱️ 01.07.2022): @@ -4363,7 +4363,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install ffn ```
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Alphalens (🥈25 · ⭐ 2.4K · 💀) - Performance analysis of predictive (alpha) stock factors. Apache-2 +
Alphalens (🥈25 · ⭐ 2.4K · 💀) - 股票因子预测分析。Apache-2 - [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 880 · 📦 570 · 📋 180 - 20% open · ⏱️ 27.04.2020): @@ -4379,7 +4379,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge alphalens ```
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empyrical (🥈25 · ⭐ 970 · 💀) - Common financial risk and performance metrics. Used by zipline.. Apache-2 +
empyrical (🥈25 · ⭐ 970 · 💀) - 常见的金融风险和绩效指标。Apache-2 - [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 300 · 📦 940 · 📋 49 - 46% open · ⏱️ 14.10.2020): @@ -4395,7 +4395,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge empyrical ```
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Qlib (🥈24 · ⭐ 9.5K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT +
Qlib (🥈24 · ⭐ 9.5K) - Qlib是一个面向AI的量化投资平台。MIT - [GitHub](https://github.com/microsoft/qlib) (👨‍💻 100 · 🔀 1.7K · 📥 330 · 📦 27 · 📋 600 - 27% open · ⏱️ 24.08.2022): @@ -4407,7 +4407,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install pyqlib ```
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bt (🥈24 · ⭐ 1.5K) - bt - flexible backtesting for Python. MIT +
bt (🥈24 · ⭐ 1.5K) - bt-Python的灵活回测。MIT - [GitHub](https://github.com/pmorissette/bt) (👨‍💻 27 · 🔀 320 · 📦 130 · 📋 300 - 20% open · ⏱️ 24.08.2022): @@ -4419,7 +4419,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install bt ```
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FinTA (🥉23 · ⭐ 1.7K) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 +
FinTA (🥉23 · ⭐ 1.7K) - 基于pandas实现的通用金融技术指标。❗️LGPL-3.0 - [GitHub](https://github.com/peerchemist/finta) (👨‍💻 28 · 🔀 550 · 📦 260 · 📋 85 - 24% open · ⏱️ 24.07.2022): @@ -4431,7 +4431,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install finta ```
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arch (🥉23 · ⭐ 970) - ARCH models in Python. ❗Unlicensed +
arch (🥉23 · ⭐ 970) - Python中的ARCH模型。❗Unlicensed - [GitHub](https://github.com/bashtage/arch) (👨‍💻 31 · 🔀 210 · 📦 620 · 📋 180 - 8% open · ⏱️ 17.08.2022): @@ -4443,7 +4443,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install arch ```
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TensorTrade (🥉22 · ⭐ 3.9K) - An open source reinforcement learning framework for training,.. Apache-2 +
TensorTrade (🥉22 · ⭐ 3.9K) - 一个开放源代码的强化学习框架。Apache-2 - [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 61 · 🔀 890 · 📦 36 · 📋 230 - 16% open · ⏱️ 23.08.2022): @@ -4455,7 +4455,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install tensortrade ```
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PyAlgoTrade (🥉22 · ⭐ 3.7K · 💀) - Python Algorithmic Trading Library. Apache-2 +
PyAlgoTrade (🥉22 · ⭐ 3.7K · 💀) - Python算法交易库。Apache-2 - [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 110 · 📋 120 - 31% open · ⏱️ 21.08.2018): @@ -4467,7 +4467,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install pyalgotrade ```
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Alpha Vantage (🥉21 · ⭐ 3.7K · 💀) - A python wrapper for Alpha Vantage API for financial data. MIT +
Alpha Vantage (🥉21 · ⭐ 3.7K · 💀) - 用于金融数据的Alpha Vantage API的python包装器。MIT - [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 640 · 📋 260 - 2% open · ⏱️ 14.06.2021): @@ -4479,7 +4479,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install alpha_vantage ```
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Enigma Catalyst (🥉21 · ⭐ 2.4K · 💤) - An Algorithmic Trading Library for Crypto-Assets in.. Apache-2 +
Enigma Catalyst (🥉21 · ⭐ 2.4K · 💤) - Python中加密资产的算法交易库。Apache-2 - [GitHub](https://github.com/scrtlabs/catalyst) (👨‍💻 150 · 🔀 700 · 📦 25 · 📋 480 - 25% open · ⏱️ 22.09.2021): @@ -4491,7 +4491,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install enigma-catalyst ```
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tf-quant-finance (🥉20 · ⭐ 3.2K) - High-performance TensorFlow library for quantitative.. Apache-2 +
tf-quant-finance (🥉20 · ⭐ 3.2K) - 用于量化投资的高性能TensorFlow库。Apache-2 - [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 41 · 🔀 420 · 📋 40 - 37% open · ⏱️ 19.08.2022): @@ -4503,7 +4503,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install tf-quant-finance ```
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IB-insync (🥉20 · ⭐ 1.9K) - Python sync/async framework for Interactive Brokers API. BSD-2 +
IB-insync (🥉20 · ⭐ 1.9K) - 用于Interactive Brokers API的Python同步/异步框架。BSD-2 - [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 31 · 🔀 490 · 📋 420 - 1% open · ⏱️ 23.08.2022): @@ -4519,7 +4519,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge ib-insync ```
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Crypto Signals (🥉19 · ⭐ 4.1K) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT +
Crypto Signals (🥉19 · ⭐ 4.1K) - CryptoSignal量化交易技术。MIT - [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 1.1K · 📋 260 - 20% open · ⏱️ 09.08.2022): @@ -4531,7 +4531,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te docker pull shadowreaver/crypto-signal ```
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stockstats (🥉19 · ⭐ 1K · 💤) - Supply a wrapper ``StockDataFrame`` based on the.. ❗Unlicensed +
stockstats (🥉19 · ⭐ 1K · 💤) - 提供StockDataFrame包装器❗Unlicensed - [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 260 · 📦 530 · 📋 87 - 11% open · ⏱️ 07.01.2022): @@ -4543,7 +4543,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install stockstats ```
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finmarketpy (🥉18 · ⭐ 3K) - Python library for backtesting trading strategies & analyzing.. Apache-2 +
finmarketpy (🥉18 · ⭐ 3K) - Python库，用于回测交易策略和分析。Apache-2 - [GitHub](https://github.com/cuemacro/finmarketpy) (👨‍💻 14 · 🔀 440 · 📥 40 · 📦 5 · 📋 26 - 88% open · ⏱️ 05.04.2022): @@ -4555,7 +4555,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install finmarketpy ```
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Backtesting.py (🥉17 · ⭐ 2.8K) - Backtest trading strategies in Python. ❗️AGPL-3.0 +
Backtesting.py (🥉17 · ⭐ 2.8K) - 回溯Python中的交易策略。❗️AGPL-3.0 - [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 550 · 📋 330 - 17% open · ⏱️ 27.03.2022): @@ -4567,7 +4567,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install backtesting ```
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surpriver (🥉12 · ⭐ 1.5K · 💀) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 +
surpriver (🥉12 · ⭐ 1.5K · 💀) - 使用机器学习在股票大波动之前找到它。❗️GPL-3.0 - [GitHub](https://github.com/tradytics/surpriver) (👨‍💻 6 · 🔀 280 · 📋 15 - 60% open · ⏱️ 21.09.2020): @@ -4577,13 +4577,13 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te

-## Time Series Data +## 时间序列 -Back to top +Back to top -_Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._ +_用于按时间序列和顺序数据进行预测，异常检测，特征提取和机器学习的库。_ -
pmdarima (🥇30 · ⭐ 1.2K · 📈) - A statistical library designed to fill the void in Python's time.. MIT +
pmdarima (🥇30 · ⭐ 1.2K · 📈) - 一个统计数据库，旨在填补Python时间序列中的空白。MIT - [GitHub](https://github.com/alkaline-ml/pmdarima) (👨‍💻 21 · 🔀 210 · 📦 2.5K · 📋 280 - 9% open · ⏱️ 23.08.2022): @@ -4595,7 +4595,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pmdarima ```
-
sktime (🥇27 · ⭐ 5.6K) - A unified framework for machine learning with time series. BSD-3 +
sktime (🥇27 · ⭐ 5.6K) - 具有时间序列的机器学习的统一框架。BSD-3 - [GitHub](https://github.com/alan-turing-institute/sktime) (👨‍💻 190 · 🔀 890 · 📥 76 · 📦 560 · 📋 1.3K - 33% open · ⏱️ 25.08.2022): @@ -4607,7 +4607,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install sktime ```
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STUMPY (🥈26 · ⭐ 2.4K) - STUMPY is a powerful and scalable Python library for computing a Matrix.. BSD-3 +
STUMPY (🥈26 · ⭐ 2.4K) - STUMPY是一个功能强大且可扩展的Python库，用于矩阵计算。BSD-3 - [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 31 · 🔀 230 · 📦 260 · 📋 340 - 11% open · ⏱️ 04.08.2022): @@ -4623,7 +4623,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge stumpy ```
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Prophet (🥈25 · ⭐ 15K) - Tool for producing high quality forecasts for time series data that has.. MIT +
Prophet (🥈25 · ⭐ 15K) - 产生具有时间序列数据的高质量预测的工具。MIT - [GitHub](https://github.com/facebook/prophet) (👨‍💻 150 · 🔀 4.2K · 📥 810 · 📋 1.9K - 13% open · ⏱️ 07.07.2022): @@ -4635,7 +4635,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install fbprophet ```
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Darts (🥈25 · ⭐ 4.6K) - A python library for easy manipulation and forecasting of time series. Apache-2 +
Darts (🥈25 · ⭐ 4.6K) - 一个易于操作和预测时间序列的python库。Apache-2 - [GitHub](https://github.com/unit8co/darts) (👨‍💻 61 · 🔀 480 · 📦 92 · 📋 600 - 23% open · ⏱️ 25.08.2022): @@ -4651,7 +4651,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l docker pull unit8/darts ```
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tslearn (🥈25 · ⭐ 2.2K) - A machine learning toolkit dedicated to time-series data. BSD-2 +
tslearn (🥈25 · ⭐ 2.2K) - 专门用于时间序列数据的机器学习工具包。BSD-2 - [GitHub](https://github.com/tslearn-team/tslearn) (👨‍💻 39 · 🔀 280 · 📦 560 · 📋 280 - 32% open · ⏱️ 17.06.2022): @@ -4667,7 +4667,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge tslearn ```
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pytorch-forecasting (🥈25 · ⭐ 2.2K) - Time series forecasting with PyTorch. MIT +
pytorch-forecasting (🥈25 · ⭐ 2.2K) - 使用PyTorch进行时间序列预测。MIT - [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 32 · 🔀 350 · 📋 510 - 49% open · ⏱️ 22.08.2022): @@ -4679,7 +4679,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pytorch-forecasting ```
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tsfresh (🥈23 · ⭐ 6.6K · 💤) - Automatic extraction of relevant features from time series:. MIT +
tsfresh (🥈23 · ⭐ 6.6K · 💤) - 从时间序列中自动提取相关特征。MIT - [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 82 · 🔀 1K · 📋 490 - 10% open · ⏱️ 21.12.2021): @@ -4695,7 +4695,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge tsfresh ```
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pyts (🥈23 · ⭐ 1.3K) - A Python package for time series classification. BSD-3 +
pyts (🥈23 · ⭐ 1.3K) - 用于时间序列分类的Python软件包。BSD-3 - [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 11 · 🔀 140 · 📦 240 · 📋 64 - 59% open · ⏱️ 16.06.2022): @@ -4711,7 +4711,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge pyts ```
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Streamz (🥈23 · ⭐ 1.1K) - Real-time stream processing for python. BSD-3 +
Streamz (🥈23 · ⭐ 1.1K) - python的实时流处理。BSD-3 - [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 45 · 🔀 140 · 📦 310 · 📋 240 - 39% open · ⏱️ 27.07.2022): @@ -4727,7 +4727,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge streamz ```
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GluonTS (🥉22 · ⭐ 2.9K) - Probabilistic time series modeling in Python. Apache-2 +
GluonTS (🥉22 · ⭐ 2.9K) - Python中的概率时间序列建模。Apache-2 - [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 93 · 🔀 580 · 📋 740 - 31% open · ⏱️ 25.08.2022): @@ -4739,7 +4739,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install gluonts ```
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PyFlux (🥉22 · ⭐ 2K · 💀) - Open source time series library for Python. BSD-3 +
PyFlux (🥉22 · ⭐ 2K · 💀) - 适用于Python的开源时间序列库。BSD-3 - [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 220 · 📋 150 - 56% open · ⏱️ 16.12.2018): @@ -4751,7 +4751,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pyflux ```
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luminol (🥉20 · ⭐ 1K · 💀) - Anomaly Detection and Correlation library. Apache-2 +
luminol (🥉20 · ⭐ 1K · 💀) - 异常检测和相关库。Apache-2 - [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 200 · 📦 66 · 📋 36 - 66% open · ⏱️ 09.01.2018): @@ -4763,7 +4763,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install luminol ```
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ADTK (🥉18 · ⭐ 850 · 💀) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 +
ADTK (🥉18 · ⭐ 850 · 💀) - 一个Python工具包，用于基于规则的/无监督的异常检测。MPL-2.0 - [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 100 · 📋 67 - 46% open · ⏱️ 17.04.2020): @@ -4775,7 +4775,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install adtk ```
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pydlm (🥉18 · ⭐ 420 · 💀) - A python library for Bayesian time series modeling. BSD-3 +
pydlm (🥉18 · ⭐ 420 · 💀) - 用于贝叶斯时间序列建模的python库。BSD-3 - [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 91 · 📦 27 · 📋 43 - 81% open · ⏱️ 22.10.2019): @@ -4787,7 +4787,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pydlm ```
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tick (🥉18 · ⭐ 400 · 💀) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 +
tick (🥉18 · ⭐ 400 · 💀) - 统计学习模块。BSD-3 - [GitHub](https://github.com/X-DataInitiative/tick) (👨‍💻 16 · 🔀 84 · 📥 200 · 📦 66 · 📋 220 - 25% open · ⏱️ 15.06.2020): @@ -4799,7 +4799,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install tick ```
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matrixprofile-ts (🥉17 · ⭐ 690 · 💀) - A Python library for detecting patterns and anomalies.. Apache-2 +
matrixprofile-ts (🥉17 · ⭐ 690 · 💀) - 一个用于检测模式和异常的Python库。Apache-2 - [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 97 · 📦 19 · 📋 53 - 35% open · ⏱️ 25.04.2020): @@ -4811,7 +4811,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install matrixprofile-ts ```
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seglearn (🥉17 · ⭐ 520) - Python module for machine learning time series:. BSD-3 +
seglearn (🥉17 · ⭐ 520) - 机器学习时间序列的Python模块。BSD-3 - [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 14 · 🔀 61 · 📦 11 · 📋 29 - 20% open · ⏱️ 16.06.2022): @@ -4823,7 +4823,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install seglearn ```
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Auto TS (🥉17 · ⭐ 470) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 +
Auto TS (🥉17 · ⭐ 470) - 自动实现ARIMA，SARIMAX，VAR，FB Prophet和XGBoost等模型时序建模。Apache-2 - [GitHub](https://github.com/AutoViML/Auto_TS) (👨‍💻 6 · 🔀 86 · 📋 75 - 8% open · ⏱️ 16.08.2022): @@ -4835,7 +4835,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install auto-ts ```
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atspy (🥉13 · ⭐ 450 · 💤) - AtsPy: Automated Time Series Models in Python (by @firmai). ❗Unlicensed +
atspy (🥉13 · ⭐ 450 · 💤) - AtsPy：Python中的自动时间序列模型。❗Unlicensed - [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 85 · 📦 6 · 📋 21 - 90% open · ⏱️ 18.12.2021): @@ -4849,13 +4849,13 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l

-## Medical Data +## 医疗领域 -Back to top +Back to top -_Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic data, and other medical imaging formats._ +_用于处理和分析MRI，EEG，基因组数据和其他医学成像格式等医学数据的库。_ -
NIPYPE (🥇31 · ⭐ 640) - Workflows and interfaces for neuroimaging packages. Apache-2 +
NIPYPE (🥇31 · ⭐ 640) - 神经影像软件包的工作流程和接口。Apache-2 - [GitHub](https://github.com/nipy/nipype) (👨‍💻 240 · 🔀 460 · 📦 1K · 📋 1.3K - 28% open · ⏱️ 22.08.2022): @@ -4871,7 +4871,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nipype ```
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Lifelines (🥇30 · ⭐ 1.9K) - Survival analysis in Python. MIT +
Lifelines (🥇30 · ⭐ 1.9K) - Python中的生存分析。MIT - [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 100 · 🔀 480 · 📦 1K · 📋 870 - 25% open · ⏱️ 17.07.2022): @@ -4887,7 +4887,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge lifelines ```
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NiBabel (🥈28 · ⭐ 490) - Python package to access a cacophony of neuro-imaging file formats. ❗Unlicensed +
NiBabel (🥈28 · ⭐ 490) - Python软件包，用于访问神经影像文件格式。❗Unlicensed - [GitHub](https://github.com/nipy/nibabel) (👨‍💻 94 · 🔀 230 · 📦 7.9K · 📋 440 - 26% open · ⏱️ 20.08.2022): @@ -4903,7 +4903,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nibabel ```
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MNE (🥈27 · ⭐ 2K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 +
MNE (🥈27 · ⭐ 2K) - MNE：Python中的磁脑图（MEG）和脑电图（EEG）。BSD-3 - [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 310 · 🔀 1K · 📦 1.8K · 📋 4.2K - 9% open · ⏱️ 25.08.2022): @@ -4919,7 +4919,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge mne ```
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Hail (🥈27 · ⭐ 820) - Scalable genomic data analysis. MIT +
Hail (🥈27 · ⭐ 820) - 可扩展的基因组数据分析。MIT - [GitHub](https://github.com/hail-is/hail) (👨‍💻 81 · 🔀 210 · 📦 75 · 📋 2K - 0% open · ⏱️ 26.08.2022): @@ -4931,7 +4931,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install hail ```
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MONAI (🥈25 · ⭐ 3.3K) - AI Toolkit for Healthcare Imaging. Apache-2 +
MONAI (🥈25 · ⭐ 3.3K) - 用于医疗成像的AI工具包。Apache-2 - [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 110 · 🔀 640 · 📦 460 · 📋 1.9K - 11% open · ⏱️ 25.08.2022): @@ -4943,7 +4943,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install monai ```
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Nilearn (🥈24 · ⭐ 880) - Machine learning for NeuroImaging in Python. ❗Unlicensed +
Nilearn (🥈24 · ⭐ 880) - Python中NeuroImaging的机器学习。❗Unlicensed - [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 190 · 🔀 450 · 📥 64 · 📦 1.7K · 📋 1.6K - 14% open · ⏱️ 25.08.2022): @@ -4959,7 +4959,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nilearn ```
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DIPY (🥈24 · ⭐ 540) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed +
DIPY (🥈24 · ⭐ 540) - DIPY是Python中的Paragon 3D/4D +影像库。❗Unlicensed - [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 340 · 📦 600 · 📋 780 - 14% open · ⏱️ 25.08.2022): @@ -4975,7 +4975,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge dipy ```
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DeepVariant (🥉22 · ⭐ 2.6K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 +
DeepVariant (🥉22 · ⭐ 2.6K) - DeepVariant是使用深度神经网络的分析管道。BSD-3 - [GitHub](https://github.com/google/deepvariant) (👨‍💻 24 · 🔀 620 · 📥 4.1K · 📋 500 - 1% open · ⏱️ 02.06.2022): @@ -4987,7 +4987,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c bioconda deepvariant ```
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NiftyNet (🥉22 · ⭐ 1.3K · 💀) - [unmaintained] An open-source convolutional neural.. Apache-2 +
NiftyNet (🥉22 · ⭐ 1.3K · 💀) - 开源医疗卷积神经网络工具库。Apache-2 - [GitHub](https://github.com/NifTK/NiftyNet) (👨‍💻 59 · 🔀 390 · 📦 38 · 📋 320 - 30% open · ⏱️ 21.04.2020): @@ -4999,7 +4999,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install niftynet ```
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MedPy (🥉22 · ⭐ 430 · 💀) - Medical image processing in Python. ❗️GPL-3.0 +
MedPy (🥉22 · ⭐ 430 · 💀) - Python中的医学图像处理。❗️GPL-3.0 - [GitHub](https://github.com/loli/medpy) (👨‍💻 14 · 🔀 120 · 📦 700 · 📋 80 - 15% open · ⏱️ 01.05.2020): @@ -5011,7 +5011,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install MedPy ```
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Glow (🥉22 · ⭐ 210) - An open-source toolkit for large-scale genomic analysis. Apache-2 +
Glow (🥉22 · ⭐ 210) - 一个用于大规模基因组分析的开源工具包。Apache-2 - [GitHub](https://github.com/projectglow/glow) (👨‍💻 21 · 🔀 78 · 📋 130 - 40% open · ⏱️ 09.05.2022): @@ -5023,7 +5023,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install glow.py ```
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DLTK (🥉18 · ⭐ 1.3K · 💀) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 +
DLTK (🥉18 · ⭐ 1.3K · 💀) - 用于医学图像分析的深度学习工具包。Apache-2 - [GitHub](https://github.com/DLTK/DLTK) (👨‍💻 9 · 🔀 390 · 📦 23 · 📋 31 - 22% open · ⏱️ 21.01.2019): @@ -5035,7 +5035,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install dltk ```
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NIPY (🥉18 · ⭐ 320 · 💀) - Neuroimaging in Python FMRI analysis package. BSD-3 +
NIPY (🥉18 · ⭐ 320 · 💀) - Python FMRI分析软件包中的Neuroimaging。BSD-3 - [GitHub](https://github.com/nipy/nipy) (👨‍💻 63 · 🔀 130 · 📋 150 - 26% open · ⏱️ 29.03.2021): @@ -5051,7 +5051,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nipy ```
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Brainiak (🥉18 · ⭐ 280 · 💀) - Brain Imaging Analysis Kit. Apache-2 +
Brainiak (🥉18 · ⭐ 280 · 💀) - 脑成像分析套件。Apache-2 - [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 34 · 🔀 130 · 📦 16 · 📋 200 - 37% open · ⏱️ 28.05.2021): @@ -5067,7 +5067,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic docker pull brainiak/brainiak ```
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MedicalTorch (🥉15 · ⭐ 790 · 💀) - A medical imaging framework for Pytorch. Apache-2 +
MedicalTorch (🥉15 · ⭐ 790 · 💀) - Pytorch的医学成像框架。Apache-2 - [GitHub](https://github.com/perone/medicaltorch) (👨‍💻 8 · 🔀 110 · 📦 12 · 📋 22 - 59% open · ⏱️ 16.04.2021): @@ -5079,7 +5079,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install medicaltorch ```
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MedicalNet (🥉14 · ⭐ 1.4K · 💀) - Many studies have shown that the performance on deep learning is.. MIT +
MedicalNet (🥉14 · ⭐ 1.4K · 💀) - Transfer Learning for 3D Medical Image Analysis的论文实现。MIT - [GitHub](https://github.com/Tencent/MedicalNet) (🔀 370 · 📋 70 - 78% open · ⏱️ 27.08.2020): @@ -5087,7 +5087,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic git clone https://github.com/Tencent/MedicalNet ```
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Medical Detection Toolkit (🥉14 · ⭐ 1.1K) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 +
Medical Detection Toolkit (🥉14 · ⭐ 1.1K) - Medical Detection Toolkit包含2D + 3D。Apache-2 - [GitHub](https://github.com/MIC-DKFZ/medicaldetectiontoolkit) (👨‍💻 3 · 🔀 280 · 📋 120 - 30% open · ⏱️ 04.04.2022): @@ -5095,7 +5095,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic git clone https://github.com/MIC-DKFZ/medicaldetectiontoolkit ```
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DeepNeuro (🥉11 · ⭐ 110 · 💀) - A deep learning python package for neuroimaging data. Made by:. MIT +
DeepNeuro (🥉11 · ⭐ 110 · 💀) - 用于神经影像数据的深度学习python软件包。MIT - [GitHub](https://github.com/QTIM-Lab/DeepNeuro) (👨‍💻 6 · 🔀 34 · 📦 1 · 📋 41 - 60% open · ⏱️ 24.06.2020): @@ -5109,13 +5109,13 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic

-## Optical Character Recognition +## 光学字符识别OCR -Back to top +Back to top -_Libraries for optical character recognition (OCR) and text extraction from images or videos._ +_用于光学字符识别（OCR）和从图像或视频中提取文本的库。_ -
EasyOCR (🥇31 · ⭐ 16K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 +
EasyOCR (🥇31 · ⭐ 16K) - 即用型OCR，具有80多种受支持的语言和所有流行的手写文字。Apache-2 - [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 110 · 🔀 2.2K · 📥 2M · 📦 1.5K · 📋 640 - 15% open · ⏱️ 25.08.2022): @@ -5127,7 +5127,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install easyocr ```
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PaddleOCR (🥇27 · ⭐ 24K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +
PaddleOCR (🥇27 · ⭐ 24K) - 基于PaddlePaddle的多语言OCR工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 110 · 🔀 4.9K · 📦 780 · 📋 5.1K - 25% open · ⏱️ 26.08.2022): @@ -5139,7 +5139,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install paddleocr ```
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tesserocr (🥈26 · ⭐ 1.7K) - A Python wrapper for the tesseract-ocr API. MIT +
tesserocr (🥈26 · ⭐ 1.7K) - 用于tesseract-ocr API的Python包装器。MIT - [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 220 · 📦 700 · 📋 250 - 31% open · ⏱️ 23.08.2022): @@ -5155,7 +5155,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag conda install -c conda-forge tesserocr ```
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Tesseract (🥈25 · ⭐ 4.4K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 +
Tesseract (🥈25 · ⭐ 4.4K) - Python-tesseract是一种光学字符识别（OCR）工具。Apache-2 - [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 41 · 🔀 600 · 📋 310 - 4% open · ⏱️ 16.08.2022): @@ -5171,7 +5171,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag conda install -c conda-forge pytesseract ```
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OCRmyPDF (🥈22 · ⭐ 7K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 +
OCRmyPDF (🥈22 · ⭐ 7K) - OCRmyPDF将OCR文本层添加到扫描的PDF文件中使用。MPL-2.0 - [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 74 · 🔀 590 · 📋 880 - 9% open · ⏱️ 15.08.2022): @@ -5183,7 +5183,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install ocrmypdf ```
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pdftabextract (🥉19 · ⭐ 2K) - A set of tools for extracting tables from PDF files.. Apache-2 +
pdftabextract (🥉19 · ⭐ 2K) - 一组用于从PDF文件提取表格的工具。Apache-2 - [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 3 · 🔀 350 · 📦 42 · 📋 21 - 14% open · ⏱️ 24.06.2022): @@ -5195,7 +5195,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install pdftabextract ```
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calamari (🥉19 · ⭐ 940) - Line based ATR Engine based on OCRopy. Apache-2 +
calamari (🥉19 · ⭐ 940) - 基于OCRopy的基于行的ATR引擎。Apache-2 - [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 190 · 📋 250 - 19% open · ⏱️ 10.06.2022): @@ -5207,7 +5207,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install calamari_ocr ```
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attention-ocr (🥉19 · ⭐ 920 · 💤) - A Tensorflow model for text recognition (CNN + seq2seq.. MIT +
attention-ocr (🥉19 · ⭐ 920 · 💤) - 用于文本识别的Tensorflow模型。MIT - [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 20 · 📋 150 - 15% open · ⏱️ 29.10.2021): @@ -5219,7 +5219,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install aocr ```
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doc2text (🥉18 · ⭐ 1.3K · 💀) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT +
doc2text (🥉18 · ⭐ 1.3K · 💀) - 批量检测文本块和OCR扫描不良的PDF。MIT - [GitHub](https://github.com/jlsutherland/doc2text) (👨‍💻 5 · 🔀 95 · 📦 60 · 📋 21 - 57% open · ⏱️ 01.12.2020): @@ -5231,7 +5231,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install doc2text ```
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keras-ocr (🥉18 · ⭐ 1.1K) - A packaged and flexible version of the CRAFT text detector and.. MIT +
keras-ocr (🥉18 · ⭐ 1.1K) - CRAFT文本检测器。MIT - [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 15 · 🔀 270 · 📥 300K · 📋 180 - 38% open · ⏱️ 19.05.2022): @@ -5243,7 +5243,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install keras-ocr ```
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Mozart (🥉11 · ⭐ 400) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 +
Mozart (🥉11 · ⭐ 400) - 光学音乐识别（OMR）系统。Apache-2 - [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 58 · 📋 12 - 25% open · ⏱️ 24.08.2022): @@ -5253,13 +5253,13 @@ _Libraries for optical character recognition (OCR) and text extraction from imag

-## Data Containers & Structures +## 数据容器和结构 -Back to top +Back to top -_General-purpose data containers & structures as well as utilities & extensions for pandas._ +_通用数据容器和结构以及pandas的实用程序和扩展。_ -
pandas (🥇39 · ⭐ 35K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 +
pandas (🥇39 · ⭐ 35K) - 灵活而强大的数据分析/操作库。BSD-3 - [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 3.1K · 🔀 15K · 📥 160K · 📦 800K · 📋 23K - 14% open · ⏱️ 25.08.2022): @@ -5275,7 +5275,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge pandas ```
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numpy (🥇38 · ⭐ 21K) - The fundamental package for scientific computing with Python. BSD-3 +
numpy (🥇38 · ⭐ 21K) - 使用Python进行科学计算的基本软件包。BSD-3 - [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.5K · 🔀 7K · 📥 560K · 📦 1.2M · 📋 11K - 18% open · ⏱️ 24.08.2022): @@ -5291,7 +5291,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge numpy ```
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h5py (🥇36 · ⭐ 1.8K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 +
h5py (🥇36 · ⭐ 1.8K) - 适用于Python的HDF5-h5py软件包，HDF5的Pythonic接口。BSD-3 - [GitHub](https://github.com/h5py/h5py) (👨‍💻 180 · 🔀 450 · 📥 2.1K · 📦 170K · 📋 1.3K - 16% open · ⏱️ 01.07.2022): @@ -5307,7 +5307,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge h5py ```
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Arrow (🥈33 · ⭐ 10K) - Apache Arrow is a cross-language development platform for in-.. Apache-2 +
Arrow (🥈33 · ⭐ 10K) - Apache Arrow定义了一种在内存中表示tabular data的格式。Apache-2 - [GitHub](https://github.com/apache/arrow) (👨‍💻 930 · 🔀 2.4K · 📦 77 · 📋 840 - 6% open · ⏱️ 25.08.2022): @@ -5323,7 +5323,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge arrow ```
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Modin (🥈29 · ⭐ 7.7K) - Modin: Speed up your Pandas workflows by changing a single line of.. Apache-2 +
Modin (🥈29 · ⭐ 7.7K) - Modin：通过更改一行来加快Pandas工作流程。Apache-2 - [GitHub](https://github.com/modin-project/modin) (👨‍💻 100 · 🔀 540 · 📥 200K · 📦 710 · 📋 2.9K - 30% open · ⏱️ 25.08.2022): @@ -5335,7 +5335,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install modin ```
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xarray (🥈29 · ⭐ 2.7K) - N-D labeled arrays and datasets in Python. Apache-2 +
xarray (🥈29 · ⭐ 2.7K) - Python中带有N-D标签的数组和数据集。Apache-2 - [GitHub](https://github.com/pydata/xarray) (👨‍💻 390 · 🔀 800 · 📦 12K · 📋 3.4K - 26% open · ⏱️ 25.08.2022): @@ -5351,7 +5351,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge xarray ```
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sklearn-pandas (🥈29 · ⭐ 2.6K) - Pandas integration with sklearn. ❗️Zlib +
sklearn-pandas (🥈29 · ⭐ 2.6K) - pandas与sklearn集成。❗️Zlib - [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 39 · 🔀 380 · 📦 4.4K · 📋 150 - 16% open · ⏱️ 17.07.2022): @@ -5363,7 +5363,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install sklearn-pandas ```
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datasketch (🥈29 · ⭐ 1.8K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT +
datasketch (🥈29 · ⭐ 1.8K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog等实现。MIT - [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 24 · 🔀 240 · 📥 19 · 📦 440 · 📋 140 - 25% open · ⏱️ 19.08.2022): @@ -5375,7 +5375,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install datasketch ```
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Bottleneck (🥈29 · ⭐ 780) - Fast NumPy array functions written in C. BSD-2 +
Bottleneck (🥈29 · ⭐ 780) - 用C编写的快速NumPy数组函数。BSD-2 - [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 25 · 🔀 80 · 📦 35K · 📋 220 - 15% open · ⏱️ 02.07.2022): @@ -5391,7 +5391,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge bottleneck ```
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Koalas (🥈28 · ⭐ 3.2K · 💤) - Koalas: pandas API on Apache Spark. Apache-2 +
Koalas (🥈28 · ⭐ 3.2K · 💤) - Apache Spark上的pandas API。Apache-2 - [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 330 · 📥 1K · 📦 220 · 📋 580 - 16% open · ⏱️ 21.10.2021): @@ -5407,7 +5407,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge koalas ```
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Blaze (🥈28 · ⭐ 3.1K · 💀) - NumPy and Pandas interface to Big Data. BSD-3 +
Blaze (🥈28 · ⭐ 3.1K · 💀) - NumPy和Pandas连接到大数据。BSD-3 - [GitHub](https://github.com/blaze/blaze) (👨‍💻 65 · 🔀 360 · 📦 8.3K · 📋 750 - 33% open · ⏱️ 15.08.2019): @@ -5423,7 +5423,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge blaze ```
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Vaex (🥉26 · ⭐ 7.3K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and.. MIT +
Vaex (🥉26 · ⭐ 7.3K) - 用于Python，ML的核外混合Apache Arrow / NumPy DataFrame可视化等实现。MIT - [GitHub](https://github.com/vaexio/vaex) (👨‍💻 70 · 🔀 550 · 📥 240 · 📦 310 · 📋 1.1K - 31% open · ⏱️ 25.08.2022): @@ -5439,7 +5439,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge vaex ```
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zarr (🥉26 · ⭐ 970) - An implementation of chunked, compressed, N-dimensional arrays for Python. MIT +
zarr (🥉26 · ⭐ 970) - Python的分块，压缩N维数组的实现。MIT - [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 65 · 🔀 160 · 📦 1.4K · 📋 500 - 38% open · ⏱️ 15.08.2022): @@ -5455,7 +5455,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge zarr ```
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numexpr (🥉25 · ⭐ 1.8K) - Fast numerical array expression evaluator for Python, NumPy, PyTables,.. MIT +
numexpr (🥉25 · ⭐ 1.8K) - 适用于Python，NumPy，PyTables等的快速数值数组表达式评估器。MIT - [GitHub](https://github.com/pydata/numexpr) (👨‍💻 63 · 🔀 180 · 📥 62 · 📋 330 - 18% open · ⏱️ 19.07.2022): @@ -5471,7 +5471,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge numexpr ```
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PyTables (🥉25 · ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 +
PyTables (🥉25 · ⭐ 1.1K) - 一个Python包，用于管理大量数据。BSD-3 - [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 110 · 🔀 210 · 📥 170 · 📋 650 - 22% open · ⏱️ 24.08.2022): @@ -5487,7 +5487,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge pytables ```
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Arctic (🥉24 · ⭐ 2.8K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 +
Arctic (🥉24 · ⭐ 2.8K) - Arctic是用于数字数据的高性能数据存储。❗️LGPL-2.1 - [GitHub](https://github.com/man-group/arctic) (👨‍💻 76 · 🔀 530 · 📥 190 · 📦 180 · 📋 530 - 14% open · ⏱️ 02.03.2022): @@ -5515,7 +5515,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandarallel ```
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swifter (🥉24 · ⭐ 2.1K) - A package which efficiently applies any function to a pandas.. MIT +
swifter (🥉24 · ⭐ 2.1K) - 一个可以对pandas Dataframe或者series做高效function映射的工具库。MIT - [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 17 · 🔀 97 · 📦 660 · 📋 120 - 7% open · ⏱️ 16.08.2022): @@ -5531,7 +5531,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge swifter ```
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pandasql (🥉24 · ⭐ 1.1K · 💀) - sqldf for pandas. MIT +
pandasql (🥉24 · ⭐ 1.1K · 💀) - pandas的sqldf。MIT - [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 1.5K · 📋 70 - 65% open · ⏱️ 01.02.2017): @@ -5543,7 +5543,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandasql ```
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bcolz (🥉24 · ⭐ 940 · 💀) - A columnar data container that can be compressed. ❗Unlicensed +
bcolz (🥉24 · ⭐ 940 · 💀) - 可以压缩的列式数据容器。❗Unlicensed - [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 130 · 📦 1.8K · 📋 240 - 50% open · ⏱️ 10.09.2020): @@ -5559,7 +5559,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge bcolz ```
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TinyDB (🥉23 · ⭐ 5.3K) - TinyDB is a lightweight document oriented database optimized for your.. MIT +
TinyDB (🥉23 · ⭐ 5.3K) - TinyDB：轻型面向文档的数据库。MIT - [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 78 · 🔀 450 · 📋 280 - 3% open · ⏱️ 23.07.2022): @@ -5575,7 +5575,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge tinydb ```
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StaticFrame (🥉22 · ⭐ 310) - Immutable and grow-only Pandas-like DataFrames with a more explicit.. MIT +
StaticFrame (🥉22 · ⭐ 310) - 类似Pandas的DataFrame的不可变且仅增长的高效数据结构实现。MIT - [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 20 · 🔀 26 · 📦 11 · 📋 450 - 9% open · ⏱️ 23.08.2022): @@ -5591,7 +5591,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge static-frame ```
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datatable (🥉20 · ⭐ 1.6K) - A Python package for manipulating 2-dimensional tabular data.. MPL-2.0 +
datatable (🥉20 · ⭐ 1.6K) - 一个用于处理二维表格数据的Python包。MPL-2.0 - [GitHub](https://github.com/h2oai/datatable) (👨‍💻 33 · 🔀 140 · 📥 1.7K · 📋 1.4K - 10% open · ⏱️ 12.08.2022): @@ -5603,7 +5603,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install datatable ```
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pickleDB (🥉20 · ⭐ 700 · 💀) - pickleDB is an open source key-value store using Python's json.. BSD-3 +
pickleDB (🥉20 · ⭐ 700 · 💀) - pickleDB是使用Python的json的开源键值存储。BSD-3 - [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 110 · 📦 940 · 📋 57 - 28% open · ⏱️ 15.11.2019): @@ -5615,7 +5615,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pickledb ```
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fletcher (🥉19 · ⭐ 220 · 💀) - Pandas ExtensionDType/Array backed by Apache Arrow. MIT +
fletcher (🥉19 · ⭐ 220 · 💀) - 由Apache Arrow支持的Pandas ExtensionDType/Array。MIT - [GitHub](https://github.com/xhochy/fletcher) (👨‍💻 24 · 🔀 33 · 📥 13 · 📦 4 · 📋 74 - 45% open · ⏱️ 18.02.2021): @@ -5631,7 +5631,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge fletcher ```
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Bounter (🥉18 · ⭐ 940 · 💀) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT +
Bounter (🥉18 · ⭐ 940 · 💀) - 使用有限内存的高效计数器。MIT - [GitHub](https://github.com/RaRe-Technologies/bounter) (👨‍💻 8 · 🔀 44 · 📦 26 · 📋 25 - 64% open · ⏱️ 24.05.2021): @@ -5643,7 +5643,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install bounter ```
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Pandas Summary (🥉16 · ⭐ 430) - An extension to pandas dataframes describe function. Apache-2 +
Pandas Summary (🥉16 · ⭐ 430) - pandas Dataframe的describe函数功能扩展。Apache-2 - [GitHub](https://github.com/polyaxon/datatile) (👨‍💻 8 · 🔀 39 · 📋 13 - 46% open · ⏱️ 14.08.2022): @@ -5655,7 +5655,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandas-summary ```
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PandaPy (🥉10 · ⭐ 510 · 💤) - PandaPy has the speed of NumPy and the usability of.. ❗Unlicensed +
PandaPy (🥉10 · ⭐ 510 · 💤) - PandaPy：具有NumPy的速度，性能高于pandas的表格数据实现。❗Unlicensed - [GitHub](https://github.com/firmai/pandapy) (👨‍💻 3 · 🔀 58 · 📦 2 · 📋 2 - 50% open · ⏱️ 20.10.2021): @@ -5669,13 +5669,13 @@ _General-purpose data containers & structures as well as utilities & extensions

-## Data Loading & Extraction +## 数据读写与提取 -Back to top +Back to top -_Libraries for loading, collecting, and extracting data from a variety of data sources and formats._ +_用于从各种数据源和格式加载，收集和提取数据的库。_ -
Faker (🥇37 · ⭐ 15K) - Faker is a Python package that generates fake data for you. MIT +
Faker (🥇37 · ⭐ 15K) - Faker是一个Python软件包，可为您生成伪造数据。MIT - [GitHub](https://github.com/joke2k/faker) (👨‍💻 470 · 🔀 1.6K · 📦 67K · 📋 580 - 2% open · ⏱️ 17.08.2022): @@ -5691,7 +5691,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge faker ```
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Datasets (🥇32 · ⭐ 14K) - The largest hub of ready-to-use NLP datasets for ML models with.. Apache-2 +
Datasets (🥇32 · ⭐ 14K) - 具有ML模型的最大的即用型NLP数据集合。Apache-2 - [GitHub](https://github.com/huggingface/datasets) (👨‍💻 440 · 🔀 1.8K · 📦 6K · 📋 1.7K - 26% open · ⏱️ 25.08.2022): @@ -5703,7 +5703,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install datasets ```
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Tablib (🥇32 · ⭐ 4.2K) - Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c. MIT +
Tablib (🥇32 · ⭐ 4.2K) - 用于XLS，CSV，JSON，YAML和＆c中表格数据集的Python模块。MIT - [GitHub](https://github.com/jazzband/tablib) (👨‍💻 120 · 🔀 540 · 📦 15K · 📋 240 - 12% open · ⏱️ 11.07.2022): @@ -5719,7 +5719,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge tablib ```
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xmltodict (🥈31 · ⭐ 4.9K) - Python module that makes working with XML feel like you are.. MIT +
xmltodict (🥈31 · ⭐ 4.9K) - 像处理JSON一样处理XML。MIT - [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 49 · 🔀 430 · 📦 42K · 📋 220 - 27% open · ⏱️ 08.05.2022): @@ -5735,7 +5735,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge xmltodict ```
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python-magic (🥈29 · ⭐ 2.2K) - A python wrapper for libmagic. ❗Unlicensed +
python-magic (🥈29 · ⭐ 2.2K) - 用于libmagic的python包装器。❗Unlicensed - [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 55 · 🔀 240 · 📦 31K · 📋 180 - 15% open · ⏱️ 20.06.2022): @@ -5751,7 +5751,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge python-magic ```
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xlrd (🥈29 · ⭐ 2K · 💤) - Please use openpyxl where you can... ❗Unlicensed +
xlrd (🥈29 · ⭐ 2K · 💤) - xlrd是python语言中用于读取excel表格内容的库。❗Unlicensed - [GitHub](https://github.com/python-excel/xlrd) (👨‍💻 51 · 🔀 420 · 📦 100K · ⏱️ 21.08.2021): @@ -5767,7 +5767,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge xlrd ```
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csvkit (🥈28 · ⭐ 5.1K) - A suite of utilities for converting to and working with CSV, the king of.. MIT +
csvkit (🥈28 · ⭐ 5.1K) - 一套实用工具，可转换为CSV并操作。MIT - [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 560 · 📦 1.1K · 📋 860 - 8% open · ⏱️ 11.04.2022): @@ -5783,7 +5783,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge csvkit ```
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TensorFlow Datasets (🥈28 · ⭐ 3.4K) - TFDS is a collection of datasets ready to use with.. Apache-2 +
TensorFlow Datasets (🥈28 · ⭐ 3.4K) - TFDS是一个高级数据集合。Apache-2 - [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 260 · 🔀 1.3K · 📋 980 - 36% open · ⏱️ 25.08.2022): @@ -5795,7 +5795,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install tensorflow-datasets ```
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PDFMiner (🥈26 · ⭐ 4.9K · 💀) - Python PDF Parser (Not actively maintained). Check out pdfminer.six. MIT +
PDFMiner (🥈26 · ⭐ 4.9K · 💀) - Python PDF解析器。MIT - [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 980 · 📦 3.2K · 📋 240 - 82% open · ⏱️ 18.01.2020): @@ -5811,7 +5811,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge pdfminer ```
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smart-open (🥈26 · ⭐ 2.6K) - Utils for streaming large files (S3, HDFS, gzip, bz2...). MIT +
smart-open (🥈26 · ⭐ 2.6K) - 用于大文件（S3，HDFS，gzip，bz2 ...）流传输的实用程序。MIT - [GitHub](https://github.com/RaRe-Technologies/smart_open) (👨‍💻 96 · 🔀 310 · 📋 360 - 16% open · ⏱️ 21.08.2022): @@ -5823,7 +5823,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install smart-open ```
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snorkel (🥉25 · ⭐ 5.2K) - A system for quickly generating training data with weak supervision. Apache-2 +
snorkel (🥉25 · ⭐ 5.2K) - 在弱监督环境下快速生成训练数据的系统。Apache-2 - [GitHub](https://github.com/snorkel-team/snorkel) (👨‍💻 78 · 🔀 820 · 📥 980 · 📦 190 · 📋 970 - 1% open · ⏱️ 29.07.2022): @@ -5839,7 +5839,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge snorkel ```
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Intake (🥉24 · ⭐ 800) - Intake is a lightweight package for finding, investigating, loading and.. BSD-2 +
Intake (🥉24 · ⭐ 800) - Intake是一个轻量级的程序包，用于查找，调查，加载等。BSD-2 - [GitHub](https://github.com/intake/intake) (👨‍💻 78 · 🔀 120 · 📦 480 · 📋 310 - 27% open · ⏱️ 22.08.2022): @@ -5855,7 +5855,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge intake ```
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textract (🥉23 · ⭐ 3.3K) - extract text from any document. no muss. no fuss. MIT +
textract (🥉23 · ⭐ 3.3K) - 从任何文档中提取文本。MIT - [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 40 · 🔀 470 · 📋 210 - 39% open · ⏱️ 10.03.2022): @@ -5871,7 +5871,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge textract ```
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SDV (🥉23 · ⭐ 980) - Synthetic Data Generation for tabular, relational and time series data. ❗Unlicensed +
SDV (🥉23 · ⭐ 980) - 用于表格，关系和时间序列数据的综合数据生成。❗Unlicensed - [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 41 · 🔀 160 · 📦 81 · 📋 580 - 20% open · ⏱️ 19.08.2022): @@ -5883,7 +5883,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install sdv ```
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tabulator-py (🥉22 · ⭐ 230 · 💀) - Python library for reading and writing tabular data via streams. MIT +
tabulator-py (🥉22 · ⭐ 230 · 💀) - 用于读取和写入图像数据的Python库。MIT - [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 830 · ⏱️ 22.03.2021): @@ -5899,7 +5899,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge tabulator-py ```
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pyexcel-xlsx (🥉22 · ⭐ 110 · 💀) - A wrapper library to read, manipulate and write data.. ❗Unlicensed +
pyexcel-xlsx (🥉22 · ⭐ 110 · 💀) - 一个包装器库，用于在xlsx和xlsm等文件格式中读取，操作和写入数据。❗Unlicensed - [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 23 · 📥 51 · 📦 1.7K · 📋 34 - 26% open · ⏱️ 28.11.2020): @@ -5915,7 +5915,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge pyexcel-xlsx ```
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messytables (🥉21 · ⭐ 380 · 💀) - Tools for parsing messy tabular data. This is now.. ❗Unlicensed +
messytables (🥉21 · ⭐ 380 · 💀) - 解析混乱的表格数据的工具。❗Unlicensed - [GitHub](https://github.com/okfn/messytables) (👨‍💻 44 · 🔀 100 · 📦 250 · 📋 85 - 35% open · ⏱️ 13.11.2019): @@ -5927,7 +5927,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install messytables ```
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rows (🥉20 · ⭐ 810) - A common, beautiful interface to tabular data, no matter the format. ❗️LGPL-3.0 +
rows (🥉20 · ⭐ 810) - 通用美观的表格数据界面。❗️LGPL-3.0 - [GitHub](https://github.com/turicas/rows) (👨‍💻 31 · 🔀 140 · 📥 38 · 📦 140 · 📋 290 - 49% open · ⏱️ 18.08.2022): @@ -5939,7 +5939,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install rows ```
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Camelot (🥉19 · ⭐ 3.3K · 💀) - Camelot: PDF Table Extraction for Humans. ❗Unlicensed +
Camelot (🥉19 · ⭐ 3.3K · 💀) - Camelot：简单的PDF表提取。❗Unlicensed - [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 330 · 📋 360 - 23% open · ⏱️ 15.10.2019): @@ -5951,7 +5951,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install camelot-py ```
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pandas-datareader (🥉19 · ⭐ 2.4K) - Extract data from a wide range of Internet sources.. ❗Unlicensed +
pandas-datareader (🥉19 · ⭐ 2.4K) - 从各种各样的网络来源中提取数据。❗Unlicensed - [GitHub](https://github.com/pydata/pandas-datareader) (👨‍💻 85 · 🔀 590 · 📋 500 - 20% open · ⏱️ 16.03.2022): @@ -5967,7 +5967,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge pandas-datareader ```
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datatest (🥉19 · ⭐ 260 · 💤) - Tools for test driven data-wrangling and data validation. ❗Unlicensed +
datatest (🥉19 · ⭐ 260 · 💤) - 用于测试驱动的数据整理和数据验证的工具。❗Unlicensed - [GitHub](https://github.com/shawnbrown/datatest) (👨‍💻 7 · 🔀 13 · 📦 74 · 📋 55 - 21% open · ⏱️ 05.12.2021): @@ -5979,7 +5979,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install datatest ```
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Singer (🥉17 · ⭐ 1K · 💀) - Standard for moving data between databases, web APIs, files,.. ❗️AGPL-3.0 +
Singer (🥉17 · ⭐ 1K · 💀) - 在数据库，Web API，文件，队列等之间移动数据的标准。❗️AGPL-3.0 - [GitHub](https://github.com/singer-io/getting-started) (👨‍💻 26 · 🔀 140 · 📋 38 - 52% open · ⏱️ 29.04.2021): @@ -5991,7 +5991,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install singer-python ```
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openpyxl (🥉16 · ⭐ 45) - A Python library to read/write Excel 2010 xlsx/xlsm files. MIT +
openpyxl (🥉16 · ⭐ 45) - 一个用于读取/写入Excel 2010 xlsx/xlsm文件的Python库。MIT - [PyPi](https://pypi.org/project/openpyxl) (📥 35M / month): ``` @@ -6013,23 +6013,23 @@ _Libraries for loading, collecting, and extracting data from a variety of data s

-## Web Scraping & Crawling +## 网页抓取和爬虫 -Back to top +Back to top -_Libraries for web scraping, crawling, downloading, and mining as well as libraries._ +_用于Web抓取、爬虫，下载和挖掘的库以及库。_ 🔗 Python Web Scraping ( ⭐ 1.6K) - Collection of web-scraping and crawling libraries.
-## Data Pipelines & Streaming +## 数据管道和流处理 -Back to top +Back to top -_Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks._ +_用于数据批处理和流处理，工作流自动化，作业调度和其他数据管道任务的库。_ -
Celery (🥇36 · ⭐ 20K) - Asynchronous task queue/job queue based on distributed message.. ❗Unlicensed +
Celery (🥇36 · ⭐ 20K) - 基于分布式消息传递的异步任务队列/作业队列。❗Unlicensed - [GitHub](https://github.com/celery/celery) (👨‍💻 1.2K · 🔀 4.2K · 📦 75K · 📋 4.7K - 10% open · ⏱️ 25.08.2022): @@ -6045,7 +6045,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge celery ```
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luigi (🥇34 · ⭐ 16K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 +
luigi (🥇34 · ⭐ 16K) - Luigi是一个Python模块，可帮助您构建复杂的批处理管道。Apache-2 - [GitHub](https://github.com/spotify/luigi) (👨‍💻 590 · 🔀 2.3K · 📦 1.8K · 📋 940 - 7% open · ⏱️ 18.08.2022): @@ -6061,7 +6061,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c anaconda luigi ```
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joblib (🥇33 · ⭐ 2.9K) - Computing with Python functions. BSD-3 +
joblib (🥇33 · ⭐ 2.9K) - 使用Python函数进行计算。BSD-3 - [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 330 · 📦 210K · 📋 710 - 43% open · ⏱️ 20.05.2022): @@ -6077,7 +6077,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge joblib ```
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rq (🥇32 · ⭐ 8.5K) - Simple job queues for Python. ❗Unlicensed +
rq (🥇32 · ⭐ 8.5K) - 适用于Python的简单作业队列。❗Unlicensed - [GitHub](https://github.com/rq/rq) (👨‍💻 270 · 🔀 1.3K · 📦 11K · 📋 980 - 19% open · ⏱️ 21.08.2022): @@ -6093,7 +6093,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge rq ```
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Dagster (🥇32 · ⭐ 5.3K) - A data orchestrator for machine learning, analytics, and ETL. Apache-2 +
Dagster (🥇32 · ⭐ 5.3K) - 用于机器学习，分析和ETL的数据协调器。Apache-2 - [GitHub](https://github.com/dagster-io/dagster) (👨‍💻 230 · 🔀 650 · 📦 500 · 📋 4.4K - 23% open · ⏱️ 25.08.2022): @@ -6109,7 +6109,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge dagster ```
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Beam (🥈31 · ⭐ 5.8K) - Unified programming model to define and execute data processing.. Apache-2 +
Beam (🥈31 · ⭐ 5.8K) - 统一的编程模型，用于定义和执行数据处理。Apache-2 - [GitHub](https://github.com/apache/beam) (👨‍💻 1.3K · 🔀 3.5K · 📋 4.4K - 89% open · ⏱️ 25.08.2022): @@ -6121,7 +6121,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install apache-beam ```
-
dbt (🥈30 · ⭐ 5.4K) - dbt (data build tool) enables data analysts and engineers to transform.. Apache-2 +
dbt (🥈30 · ⭐ 5.4K) - dbt（数据构建工具）方便数据分析人员和工程师快速使用。Apache-2 - [GitHub](https://github.com/dbt-labs/dbt-core) (👨‍💻 230 · 🔀 960 · 📥 520 · 📦 660 · 📋 3K - 10% open · ⏱️ 25.08.2022): @@ -6137,7 +6137,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge dbt ```
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Airflow (🥈29 · ⭐ 28K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 +
Airflow (🥈29 · ⭐ 28K) - 代码实现的创建，安排和监视工作流的平台。Apache-2 - [GitHub](https://github.com/apache/airflow) (👨‍💻 2.5K · 🔀 11K · 📥 340K · 📋 6K - 11% open · ⏱️ 25.08.2022): @@ -6157,7 +6157,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched docker pull apache/airflow ```
-
mrjob (🥈29 · ⭐ 2.6K · 💀) - Run MapReduce jobs on Hadoop or Amazon Web Services. Apache-2 +
mrjob (🥈29 · ⭐ 2.6K · 💀) - 在Hadoop或Amazon Web Services上运行MapReduce作业。Apache-2 - [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 580 · 📦 1.1K · 📋 1.3K - 15% open · ⏱️ 16.11.2020): @@ -6173,7 +6173,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge mrjob ```
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Prefect (🥈28 · ⭐ 9.9K) - The easiest way to automate your data. Apache-2 +
Prefect (🥈28 · ⭐ 9.9K) - 自动化数据的最简单方法。Apache-2 - [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 60 · 🔀 950 · 📦 1.1K · 📋 2.6K - 25% open · ⏱️ 25.08.2022): @@ -6189,7 +6189,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge prefect ```
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Kedro (🥈28 · ⭐ 7.5K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 +
Kedro (🥈28 · ⭐ 7.5K) - 用于创建可重现，可维护和模块化的Python框架。Apache-2 - [GitHub](https://github.com/kedro-org/kedro) (👨‍💻 160 · 🔀 680 · 📦 1K · 📋 870 - 17% open · ⏱️ 25.08.2022): @@ -6201,7 +6201,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install kedro ```
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petl (🥈28 · ⭐ 1K) - Python Extract Transform and Load Tables of Data. MIT +
petl (🥈28 · ⭐ 1K) - Python提取转换并加载数据表。MIT - [GitHub](https://github.com/petl-developers/petl) (👨‍💻 55 · 🔀 170 · 📦 790 · 📋 440 - 16% open · ⏱️ 21.08.2022): @@ -6217,7 +6217,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge petl ```
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PyFunctional (🥈26 · ⭐ 2.1K) - Python library for creating data pipelines with chain functional.. MIT +
PyFunctional (🥈26 · ⭐ 2.1K) - 用于创建具有链功能的数据管道的Python库。MIT - [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 26 · 🔀 110 · 📦 460 · 📋 130 - 5% open · ⏱️ 05.08.2022): @@ -6229,7 +6229,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pyfunctional ```
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Great Expectations (🥈25 · ⭐ 7.1K) - Always know what to expect from your data. Apache-2 +
Great Expectations (🥈25 · ⭐ 7.1K) - 通过数据测试，文档编制和性能分析，帮助数据团队加速流水线效率。Apache-2 - [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 320 · 🔀 1K · 📋 1.4K - 12% open · ⏱️ 26.08.2022): @@ -6241,7 +6241,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install great_expectations ```
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faust (🥈25 · ⭐ 6.3K · 💀) - Python Stream Processing. ❗Unlicensed +
faust (🥈25 · ⭐ 6.3K · 💀) - Python流处理。❗Unlicensed - [GitHub](https://github.com/robinhood/faust) (👨‍💻 94 · 🔀 530 · 📦 1.1K · 📋 460 - 48% open · ⏱️ 09.10.2020): @@ -6253,7 +6253,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install faust ```
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TFX (🥈25 · ⭐ 1.8K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 +
TFX (🥈25 · ⭐ 1.8K) - TFX是用于部署机器学习生产流水线的端到端平台。Apache-2 - [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 150 · 🔀 580 · 📋 780 - 26% open · ⏱️ 24.08.2022): @@ -6265,7 +6265,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install tfx ```
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ploomber (🥉24 · ⭐ 2.6K) - Lean Data Science workflows: develop and test locally. Deploy to.. Apache-2 +
ploomber (🥉24 · ⭐ 2.6K) - 精益数据科学工作流程。Apache-2 - [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 59 · 🔀 180 · 📦 51 · 📋 790 - 25% open · ⏱️ 26.08.2022): @@ -6277,7 +6277,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install ploomber ```
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streamparse (🥉24 · ⭐ 1.5K) - Run Python in Apache Storm topologies. Pythonic API, CLI.. Apache-2 +
streamparse (🥉24 · ⭐ 1.5K) - 在Apache Storm拓扑中运行Python。 Pythonic API，CLI 等。Apache-2 - [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 43 · 🔀 210 · 📦 55 · 📋 330 - 19% open · ⏱️ 18.07.2022): @@ -6289,7 +6289,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install streamparse ```
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Hub (🥉23 · ⭐ 4.8K) - Fastest unstructured dataset management for TensorFlow/PyTorch... MPL-2.0 +
Hub (🥉23 · ⭐ 4.8K) - TensorFlow/PyTorch最快的非结构化数据集管理。MPL-2.0 - [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 99 · 🔀 390 · 📋 380 - 11% open · ⏱️ 26.08.2022): @@ -6301,7 +6301,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install hub ```
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bonobo (🥉21 · ⭐ 1.5K · 💀) - Extract Transform Load for Python 3.5+. Apache-2 +
bonobo (🥉21 · ⭐ 1.5K · 💀) - 提取适用于Python 3.5+的Transform Load。Apache-2 - [GitHub](https://github.com/python-bonobo/bonobo) (👨‍💻 37 · 🔀 130 · 📦 140 · 📋 180 - 39% open · ⏱️ 10.03.2021): @@ -6313,7 +6313,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install bonobo ```
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TaskTiger (🥉21 · ⭐ 1.2K) - Python task queue using Redis. MIT +
TaskTiger (🥉21 · ⭐ 1.2K) - 使用Redis的Python任务队列。MIT - [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 24 · 🔀 64 · 📦 23 · 📋 58 - 37% open · ⏱️ 25.04.2022): @@ -6325,7 +6325,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install tasktiger ```
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pdpipe (🥉21 · ⭐ 680) - Easy pipelines for pandas DataFrames. MIT +
pdpipe (🥉21 · ⭐ 680) - pandas DataFrames的简单管道。MIT - [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 10 · 🔀 42 · 📦 41 · 📋 51 - 31% open · ⏱️ 09.08.2022): @@ -6337,7 +6337,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pdpipe ```
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dpark (🥉20 · ⭐ 2.7K · 💀) - Python clone of Spark, a MapReduce alike framework in Python. BSD-3 +
dpark (🥉20 · ⭐ 2.7K · 💀) - dpark是Python中与MapReduce相似的框架。BSD-3 - [GitHub](https://github.com/douban/dpark) (👨‍💻 35 · 🔀 540 · 📦 5 · 📋 61 - 1% open · ⏱️ 25.12.2020): @@ -6349,7 +6349,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install dpark ```
-
zenml (🥉20 · ⭐ 2.3K) - ZenML : MLOps framework to create reproducible ML pipelines for.. Apache-2 +
zenml (🥉20 · ⭐ 2.3K) - ZenML：MLOps框架。Apache-2 - [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 46 · 🔀 190 · 📋 110 - 22% open · ⏱️ 25.08.2022): @@ -6361,7 +6361,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install zenml ```
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Pypeline (🥉20 · ⭐ 1.4K) - Concurrent data pipelines in Python . MIT +
Pypeline (🥉20 · ⭐ 1.4K) - Python中的并发数据管道。MIT - [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 13 · 🔀 80 · 📋 59 - 25% open · ⏱️ 23.06.2022): @@ -6373,7 +6373,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pypeln ```
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pysparkling (🥉20 · ⭐ 250 · 💀) - A pure Python implementation of Apache Spark's RDD and.. ❗Unlicensed +
pysparkling (🥉20 · ⭐ 250 · 💀) - Apache Spark的RDD和DStream的纯Python实现。❗Unlicensed - [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 42 · 📦 120 · 📋 27 - 22% open · ⏱️ 22.02.2021): @@ -6385,7 +6385,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pysparkling ```
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Optimus (🥉19 · ⭐ 1.2K) - Agile Data Preparation Workflows madeeasy with pandas, dask,.. Apache-2 +
Optimus (🥉19 · ⭐ 1.2K) - 基于pandas、dask等的敏捷数据预处理工作流程。Apache-2 - [GitHub](https://github.com/hi-primus/optimus) (👨‍💻 23 · 🔀 210 · 📋 230 - 14% open · ⏱️ 21.06.2022): @@ -6397,7 +6397,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install optimuspyspark ```
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mrq (🥉19 · ⭐ 870 · 💀) - Mr. Queue - A distributed worker task queue in Python using Redis & gevent. MIT +
mrq (🥉19 · ⭐ 870 · 💀) - Mr. Queue - 使用Redis和gevent的Python中的分布式worker任务队列。MIT - [GitHub](https://github.com/pricingassistant/mrq) (👨‍💻 40 · 🔀 110 · 📦 29 · 📋 170 - 30% open · ⏱️ 13.12.2020): @@ -6409,7 +6409,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install mrq ```
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BatchFlow (🥉19 · ⭐ 180) - BatchFlow helps you conveniently work with random or sequential.. Apache-2 +
BatchFlow (🥉19 · ⭐ 180) - BatchFlow可帮助您方便地使用随机或顺序调度数据进行机器学习任务。Apache-2 - [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 32 · 🔀 40 · 📦 2 · 📋 100 - 28% open · ⏱️ 03.08.2022): @@ -6421,7 +6421,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install batchflow ```
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spark-deep-learning (🥉17 · ⭐ 1.9K) - Deep Learning Pipelines for Apache Spark. Apache-2 +
spark-deep-learning (🥉17 · ⭐ 1.9K) - 适用于Apache Spark的深度学习管道。Apache-2 - [GitHub](https://github.com/databricks/spark-deep-learning) (👨‍💻 17 · 🔀 460 · 📦 24 · 📋 100 - 74% open · ⏱️ 21.03.2022): @@ -6429,7 +6429,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched git clone https://github.com/databricks/spark-deep-learning ```
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Mara Pipelines (🥉17 · ⭐ 1.9K) - A lightweight opinionated ETL framework, halfway between plain.. MIT +
Mara Pipelines (🥉17 · ⭐ 1.9K) - 一个轻量级的ETL框架。MIT - [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 17 · 🔀 89 · 📋 30 - 53% open · ⏱️ 18.07.2022): @@ -6441,7 +6441,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install mara-pipelines ```
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riko (🥉15 · ⭐ 1.6K · 💤) - A Python stream processing engine modeled after Yahoo! Pipes. MIT +
riko (🥉15 · ⭐ 1.6K · 💤) - 一个模仿Yahoo!的Python流处理引擎。MIT - [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 68 · 📋 29 - 72% open · ⏱️ 28.12.2021): @@ -6453,7 +6453,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install riko ```
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Databolt Flow (🥉15 · ⭐ 940 · 💤) - Python library for building highly effective data science.. MIT +
Databolt Flow (🥉15 · ⭐ 940 · 💤) - Python库，用于构建高效的数据科学工作流程。MIT - [GitHub](https://github.com/d6t/d6tflow) (👨‍💻 12 · 🔀 71 · 📦 20 · 📋 23 - 43% open · ⏱️ 28.09.2021): @@ -6465,7 +6465,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install d6tflow ```
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flupy (🥉14 · ⭐ 170) - Fluent data pipelines for python and your shell. ❗Unlicensed +
flupy (🥉14 · ⭐ 170) - python中的流利数据管道。❗Unlicensed - [GitHub](https://github.com/olirice/flupy) (👨‍💻 6 · 🔀 12 · ⏱️ 17.02.2022): @@ -6477,7 +6477,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install flupy ```
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bodywork-core (🥉13 · ⭐ 400) - MLOps tool for deploying machine learning projects to.. ❗️AGPL-3.0 +
bodywork-core (🥉13 · ⭐ 400) - MLOps工具，用于将机器学习项目部署到Kubernetes。❗️AGPL-3.0 - [GitHub](https://github.com/bodywork-ml/bodywork-core) (👨‍💻 4 · 🔀 18 · 📦 10 · 📋 77 - 25% open · ⏱️ 04.07.2022): @@ -6489,7 +6489,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install bodywork-core ```
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Botflow (🥉12 · ⭐ 1.2K · 💀) - Python Fast Dataflow programming framework for Data pipeline.. ❗Unlicensed +
Botflow (🥉12 · ⭐ 1.2K · 💀) - 适用于数据管道工作的Python快速数据流编程框架。❗Unlicensed - [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 100 · 📦 1 · 📋 5 - 60% open · ⏱️ 23.05.2019): @@ -6503,13 +6503,13 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched

-## Distributed Machine Learning +## 分布式机器学习 -Back to top +Back to top -_Libraries that provide capabilities to distribute and parallelize machine learning tasks across large-scale compute infrastructure._ +_提供在大型计算基础架构中分布和并行化机器学习任务的功能的库。_ -
Ray (🥇35 · ⭐ 22K) - An open source framework that provides a simple, universal API for.. Apache-2 +
Ray (🥇35 · ⭐ 22K) - 一个开源代码框架，提供了用于构建分布式应用程序的简单通用API。Apache-2 - [GitHub](https://github.com/ray-project/ray) (👨‍💻 740 · 🔀 3.7K · 📦 5.7K · 📋 11K - 21% open · ⏱️ 26.08.2022): @@ -6521,7 +6521,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install ray ```
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dask (🥇32 · ⭐ 10K) - Parallel computing with task scheduling. BSD-3 +
dask (🥇32 · ⭐ 10K) - 具有任务调度的并行计算。BSD-3 - [GitHub](https://github.com/dask/dask) (👨‍💻 550 · 🔀 1.5K · 📦 39K · 📋 4.4K - 15% open · ⏱️ 25.08.2022): @@ -6537,7 +6537,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge dask ```
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horovod (🥇30 · ⭐ 13K) - Distributed training framework for TensorFlow, Keras, PyTorch,.. ❗Unlicensed +
horovod (🥇30 · ⭐ 13K) - 基于TensorFlow，Keras，PyTorch，MXNet等的分布式训练框架。❗Unlicensed - [GitHub](https://github.com/horovod/horovod) (👨‍💻 160 · 🔀 2K · 📦 650 · 📋 2.1K - 15% open · ⏱️ 17.08.2022): @@ -6549,7 +6549,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install horovod ```
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dask.distributed (🥇30 · ⭐ 1.4K) - A distributed task scheduler for Dask. BSD-3 +
dask.distributed (🥇30 · ⭐ 1.4K) - Dask的分布式任务调度规划程序。BSD-3 - [GitHub](https://github.com/dask/distributed) (👨‍💻 280 · 🔀 620 · 📦 25K · 📋 2.9K - 33% open · ⏱️ 26.08.2022): @@ -6565,7 +6565,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge distributed ```
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DeepSpeed (🥈28 · ⭐ 7.7K) - DeepSpeed is a deep learning optimization library that makes.. MIT +
DeepSpeed (🥈28 · ⭐ 7.7K) - DeepSpeed是一个深度学习优化库。MIT - [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 130 · 🔀 830 · 📦 340 · 📋 980 - 48% open · ⏱️ 25.08.2022): @@ -6581,7 +6581,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull deepspeed/deepspeed ```
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DEAP (🥈27 · ⭐ 4.8K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 +
DEAP (🥈27 · ⭐ 4.8K) - Python中的分布式进化算法。❗️LGPL-3.0 - [GitHub](https://github.com/DEAP/deap) (👨‍💻 79 · 🔀 980 · 📦 2.8K · 📋 470 - 43% open · ⏱️ 08.08.2022): @@ -6597,7 +6597,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge deap ```
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petastorm (🥈27 · ⭐ 1.5K) - Petastorm library enables single machine or distributed training.. Apache-2 +
petastorm (🥈27 · ⭐ 1.5K) - Petastorm库单机或分布式训练。Apache-2 - [GitHub](https://github.com/uber/petastorm) (👨‍💻 45 · 🔀 250 · 📥 340 · 📦 74 · 📋 280 - 49% open · ⏱️ 24.08.2022): @@ -6609,7 +6609,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install petastorm ```
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BigDL (🥈26 · ⭐ 4K) - BigDL: Distributed Deep Learning Framework for Apache Spark. Apache-2 +
BigDL (🥈26 · ⭐ 4K) - BigDL：适用于Apache Spark的分布式深度学习框架。Apache-2 - [GitHub](https://github.com/intel-analytics/BigDL) (👨‍💻 170 · 🔀 970 · 📦 38 · 📋 1.4K - 30% open · ⏱️ 26.08.2022): @@ -6629,7 +6629,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn ```
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FairScale (🥈26 · ⭐ 1.8K) - PyTorch extensions for high performance and large scale training. BSD-3 +
FairScale (🥈26 · ⭐ 1.8K) - PyTorch扩展用于高性能和大规模训练。BSD-3 - [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 63 · 🔀 180 · 📦 490 · 📋 320 - 21% open · ⏱️ 26.08.2022): @@ -6641,7 +6641,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install fairscale ```
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Elephas (🥈26 · ⭐ 1.5K) - Distributed Deep learning with Keras & Spark. MIT keras +
Elephas (🥈26 · ⭐ 1.5K) - 使用Keras和Spark进行分布式深度学习。MIT keras - [GitHub](https://github.com/maxpumperla/elephas) (👨‍💻 27 · 🔀 290 · 📦 56 · 📋 160 - 12% open · ⏱️ 30.03.2022): @@ -6653,7 +6653,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install elephas ```
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Mesh (🥈26 · ⭐ 1.3K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 +
Mesh (🥈26 · ⭐ 1.3K) - Mesh TensorFlow：简化模型并行化。Apache-2 - [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 48 · 🔀 220 · 📦 710 · 📋 78 - 82% open · ⏱️ 10.06.2022): @@ -6665,7 +6665,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install mesh-tensorflow ```
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dask-ml (🥉25 · ⭐ 820) - Scalable Machine Learning with Dask. BSD-3 +
dask-ml (🥉25 · ⭐ 820) - 使用Dask进行可扩展的机器学习。BSD-3 - [GitHub](https://github.com/dask/dask-ml) (👨‍💻 76 · 🔀 230 · 📦 660 · 📋 440 - 45% open · ⏱️ 19.06.2022): @@ -6681,7 +6681,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge dask-ml ```
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TensorFlowOnSpark (🥉23 · ⭐ 3.8K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 +
TensorFlowOnSpark (🥉23 · ⭐ 3.8K) - TensorFlowOnSpark将TensorFlow程序引入Spark。Apache-2 - [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 34 · 🔀 920 · 📋 360 - 2% open · ⏱️ 21.04.2022): @@ -6693,7 +6693,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install tensorflowonspark ```
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analytics-zoo (🥉23 · ⭐ 2.5K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 +
analytics-zoo (🥉23 · ⭐ 2.5K) - Apache上的分布式Tensorflow，Keras和PyTorch。Apache-2 - [GitHub](https://github.com/intel-analytics/analytics-zoo) (👨‍💻 100 · 🔀 700 · 📦 3 · 📋 1.3K - 32% open · ⏱️ 01.06.2022): @@ -6705,7 +6705,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install analytics-zoo ```
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Hivemind (🥉23 · ⭐ 1.1K) - Decentralized deep learning in PyTorch. Built to train models on.. MIT +
Hivemind (🥉23 · ⭐ 1.1K) - PyTorch中的分布式深度学习。专为训练模型而设计。MIT - [GitHub](https://github.com/learning-at-home/hivemind) (👨‍💻 23 · 🔀 67 · 📦 10 · 📋 120 - 28% open · ⏱️ 23.08.2022): @@ -6717,7 +6717,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install hivemind ```
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mpi4py (🥉22 · ⭐ 570) - Python bindings for MPI. BSD-2 +
mpi4py (🥉22 · ⭐ 570) - MPI的Python接口。BSD-2 - [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 21 · 🔀 78 · 📥 6.2K · 📋 84 - 11% open · ⏱️ 21.08.2022): @@ -6733,7 +6733,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge mpi4py ```
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MMLSpark (🥉20 · ⭐ 3.5K) - Microsoft Machine Learning for Apache Spark. MIT +
MMLSpark (🥉20 · ⭐ 3.5K) - 适用于Apache Spark的Microsoft机器学习。MIT - [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 97 · 🔀 670 · 📋 570 - 39% open · ⏱️ 26.08.2022): @@ -6745,7 +6745,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install mmlspark ```
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Apache Singa (🥉19 · ⭐ 2.7K) - a distributed deep learning platform. Apache-2 +
Apache Singa (🥉19 · ⭐ 2.7K) - 分布式深度学习平台。Apache-2 - [GitHub](https://github.com/apache/singa) (👨‍💻 79 · 🔀 780 · 📦 1 · 📋 79 - 21% open · ⏱️ 01.06.2022): @@ -6761,7 +6761,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull apache/singa ```
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TensorFrames (🥉19 · ⭐ 760 · 💀) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 +
TensorFrames (🥉19 · ⭐ 760 · 💀) - 用于DataFrames的Tensorflow包装器。Apache-2 - [GitHub](https://github.com/databricks/tensorframes) (👨‍💻 16 · 🔀 160 · 📋 92 - 53% open · ⏱️ 15.11.2019): @@ -6773,7 +6773,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install tensorframes ```
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ipyparallel (🥉18 · ⭐ 2.3K) - Interactive Parallel Computing in Python. ❗Unlicensed +
ipyparallel (🥉18 · ⭐ 2.3K) - Python中的交互式并行计算。❗Unlicensed - [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 110 · 🔀 870 · 📋 330 - 15% open · ⏱️ 16.08.2022): @@ -6789,7 +6789,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge ipyparallel ```
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Submit it (🥉18 · ⭐ 680) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT +
Submit it (🥉18 · ⭐ 680) - 用于将作业提交到Slurm的Python工具箱。MIT - [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 23 · 🔀 74 · 📋 71 - 32% open · ⏱️ 23.08.2022): @@ -6805,7 +6805,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge submitit ```
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sk-dist (🥉18 · ⭐ 280 · 💀) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 +
sk-dist (🥉18 · ⭐ 280 · 💀) - PySpark中的分布式scikit学习元估计器。Apache-2 - [GitHub](https://github.com/Ibotta/sk-dist) (👨‍💻 7 · 🔀 49 · 📦 10 · 📋 17 - 41% open · ⏱️ 07.07.2021): @@ -6817,7 +6817,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install sk-dist ```
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somoclu (🥉17 · ⭐ 240 · 💤) - Massively parallel self-organizing maps: accelerate training on.. MIT +
somoclu (🥉17 · ⭐ 240 · 💤) - 大规模并行的自组织图：加速训练。MIT - [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 62 · 📥 1.6K · 📋 130 - 18% open · ⏱️ 31.10.2021): @@ -6833,7 +6833,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge somoclu ```
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BytePS (🥉16 · ⭐ 3.3K) - A high performance and generic framework for distributed DNN training. Apache-2 +
BytePS (🥉16 · ⭐ 3.3K) - 分布式DNN训练的高性能通用框架。Apache-2 - [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 450 · 📋 260 - 38% open · ⏱️ 10.02.2022): @@ -6849,7 +6849,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull bytepsimage/tensorflow ```
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Fiber (🥉16 · ⭐ 980 · 💀) - Distributed Computing for AI Made Simple. Apache-2 +
Fiber (🥉16 · ⭐ 980 · 💀) - 简化了AI的分布式计算。Apache-2 - [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 110 · 📦 43 · 📋 25 - 68% open · ⏱️ 15.03.2021): @@ -6861,7 +6861,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install fiber ```
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LazyCluster (🥉13 · ⭐ 43 · 💤) - Distributed machine learning made simple. Apache-2 +
LazyCluster (🥉13 · ⭐ 43 · 💤) - 分布式机器学习框架。Apache-2 - [GitHub](https://github.com/ml-tooling/lazycluster) (👨‍💻 2 · 🔀 9 · 📦 17 · ⏱️ 19.08.2021): @@ -6875,13 +6875,13 @@ _Libraries that provide capabilities to distribute and parallelize machine learn

-## Hyperparameter Optimization & AutoML +## 超参数优化和AutoML -Back to top +Back to top -_Libraries for hyperparameter optimization, automl and neural architecture search._ +_用于超参数优化，自动机器学习和神经体系结构搜索的库。_ -
Optuna (🥇34 · ⭐ 6.8K) - A hyperparameter optimization framework. MIT +
Optuna (🥇34 · ⭐ 6.8K) - 超参数优化框架。MIT - [GitHub](https://github.com/optuna/optuna) (👨‍💻 200 · 🔀 730 · 📦 4K · 📋 1.2K - 7% open · ⏱️ 26.08.2022): @@ -6897,7 +6897,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge optuna ```
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NNI (🥇30 · ⭐ 12K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT +
NNI (🥇30 · ⭐ 12K) - 一个开源AutoML工具箱，用于自动化机器学习生命周期。MIT - [GitHub](https://github.com/microsoft/nni) (👨‍💻 180 · 🔀 1.6K · 📦 260 · 📋 1.7K - 17% open · ⏱️ 24.08.2022): @@ -6909,7 +6909,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install nni ```
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AutoKeras (🥇30 · ⭐ 8.6K) - AutoML library for deep learning. Apache-2 +
AutoKeras (🥇30 · ⭐ 8.6K) - 用于深度学习的AutoML库。Apache-2 - [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 140 · 🔀 1.3K · 📥 7.4K · 📦 350 · 📋 840 - 11% open · ⏱️ 25.08.2022): @@ -6921,7 +6921,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autokeras ```
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Keras Tuner (🥇30 · ⭐ 2.6K) - Hyperparameter tuning for humans. Apache-2 +
Keras Tuner (🥇30 · ⭐ 2.6K) - 简单易用的超参数调整。Apache-2 - [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 50 · 🔀 330 · 📦 1.6K · 📋 400 - 43% open · ⏱️ 25.08.2022): @@ -6933,7 +6933,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install keras-tuner ```
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scikit-optimize (🥇30 · ⭐ 2.4K · 💤) - Sequential model-based optimization with a.. BSD-3 +
scikit-optimize (🥇30 · ⭐ 2.4K · 💤) - SMBO模型优化实现。BSD-3 - [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 76 · 🔀 420 · 📦 3K · 📋 600 - 35% open · ⏱️ 12.10.2021): @@ -6949,7 +6949,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge scikit-optimize ```
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TPOT (🥈29 · ⭐ 8.7K) - A Python Automated Machine Learning tool that optimizes machine.. ❗️LGPL-3.0 +
TPOT (🥈29 · ⭐ 8.7K) - Python自动化机器学习工具。❗️LGPL-3.0 - [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.5K · 📦 1.6K · 📋 860 - 29% open · ⏱️ 29.07.2022): @@ -6965,7 +6965,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge tpot ```
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auto-sklearn (🥈29 · ⭐ 6.5K) - Automated Machine Learning with scikit-learn. BSD-3 +
auto-sklearn (🥈29 · ⭐ 6.5K) - 使用scikit-learn的自动化机器学习。BSD-3 - [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 86 · 🔀 1.2K · 📥 37 · 📦 310 · 📋 920 - 12% open · ⏱️ 22.08.2022): @@ -6977,7 +6977,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install auto-sklearn ```
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Bayesian Optimization (🥈29 · ⭐ 6.2K) - A Python implementation of global optimization with.. MIT +
Bayesian Optimization (🥈29 · ⭐ 6.2K) - 全局优化的Python实现。MIT - [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 35 · 🔀 1.3K · 📥 96 · 📦 1.3K · 📋 260 - 7% open · ⏱️ 17.08.2022): @@ -6989,7 +6989,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install bayesian-optimization ```
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Hyperopt (🥈28 · ⭐ 6.4K · 💤) - Distributed Asynchronous Hyperparameter Optimization in.. ❗Unlicensed +
Hyperopt (🥈28 · ⭐ 6.4K · 💤) - Python中的分布式异步超参数优化。❗Unlicensed - [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 93 · 🔀 860 · 📦 7.4K · 📋 610 - 61% open · ⏱️ 29.11.2021): @@ -7005,7 +7005,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge hyperopt ```
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AutoGluon (🥈26 · ⭐ 4.7K) - AutoGluon: AutoML for Text, Image, and Tabular Data. Apache-2 +
AutoGluon (🥈26 · ⭐ 4.7K) - AutoGluon：用于文本，图像和表格数据的AutoML。Apache-2 - [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 85 · 🔀 620 · 📦 160 · 📋 740 - 21% open · ⏱️ 25.08.2022): @@ -7017,7 +7017,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autogluon ```
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BoTorch (🥈26 · ⭐ 2.3K) - Bayesian optimization in PyTorch. MIT +
BoTorch (🥈26 · ⭐ 2.3K) - PyTorch中的贝叶斯优化。MIT - [GitHub](https://github.com/pytorch/botorch) (👨‍💻 80 · 🔀 260 · 📦 300 · 📋 290 - 15% open · ⏱️ 25.08.2022): @@ -7029,7 +7029,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install botorch ```
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Ax (🥈26 · ⭐ 1.9K) - Adaptive Experimentation Platform. MIT +
Ax (🥈26 · ⭐ 1.9K) - 自适应实验平台。MIT - [GitHub](https://github.com/facebook/Ax) (👨‍💻 120 · 🔀 210 · 📦 310 · 📋 430 - 8% open · ⏱️ 25.08.2022): @@ -7041,7 +7041,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install ax-platform ```
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Hyperas (🥈24 · ⭐ 2.1K · 💤) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT +
Hyperas (🥈24 · ⭐ 2.1K · 💤) - Keras + Hyperopt：一个非常简单的包装，方便使用。MIT - [GitHub](https://github.com/maxpumperla/hyperas) (👨‍💻 21 · 🔀 300 · 📦 250 · 📋 250 - 37% open · ⏱️ 19.11.2021): @@ -7053,7 +7053,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install hyperas ```
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mljar-supervised (🥈24 · ⭐ 2K) - Automated Machine Learning Pipeline with Feature Engineering.. MIT +
mljar-supervised (🥈24 · ⭐ 2K) - 使用scikit-learn的自动化机器学习。MIT - [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 19 · 🔀 280 · 📦 50 · 📋 490 - 19% open · ⏱️ 16.08.2022): @@ -7065,7 +7065,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install mljar-supervised ```
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nevergrad (🥈23 · ⭐ 3.3K) - A Python toolbox for performing gradient-free optimization. MIT +
nevergrad (🥈23 · ⭐ 3.3K) - 用于执行无梯度优化(gradient-free optimization)的Python工具箱。MIT - [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 50 · 🔀 310 · 📦 370 · 📋 220 - 30% open · ⏱️ 10.08.2022): @@ -7081,7 +7081,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge nevergrad ```
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GPyOpt (🥈23 · ⭐ 830 · 💀) - Gaussian Process Optimization using GPy. BSD-3 +
GPyOpt (🥈23 · ⭐ 830 · 💀) - 使用GPy进行高斯过程优化。BSD-3 - [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 250 · 📦 310 · 📋 290 - 35% open · ⏱️ 05.11.2020): @@ -7093,7 +7093,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install gpyopt ```
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featuretools (🥈22 · ⭐ 6.3K) - An open source python library for automated feature engineering. BSD-3 +
featuretools (🥈22 · ⭐ 6.3K) - 一个用于自动化特征工程的开源python库。BSD-3 - [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 67 · 🔀 800 · 📋 850 - 18% open · ⏱️ 24.08.2022): @@ -7109,7 +7109,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge featuretools ```
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AdaNet (🥈22 · ⭐ 3.4K · 💤) - Fast and flexible AutoML with learning guarantees. Apache-2 +
AdaNet (🥈22 · ⭐ 3.4K · 💤) - 具有学习保证的快速灵活的AutoML。Apache-2 - [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 44 · 📋 110 - 56% open · ⏱️ 30.08.2021): @@ -7121,7 +7121,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install adanet ```
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Talos (🥈22 · ⭐ 1.5K) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT +
Talos (🥈22 · ⭐ 1.5K) - TensorFlow，Keras和PyTorch的超参数优化。MIT - [GitHub](https://github.com/autonomio/talos) (👨‍💻 22 · 🔀 260 · 📦 150 · 📋 400 - 6% open · ⏱️ 23.04.2022): @@ -7133,7 +7133,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install talos ```
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Orion (🥈22 · ⭐ 240) - Asynchronous Distributed Hyperparameter Optimization. ❗Unlicensed +
Orion (🥈22 · ⭐ 240) - 异步分布式超参数优化。❗Unlicensed - [GitHub](https://github.com/Epistimio/orion) (👨‍💻 27 · 🔀 43 · 📦 73 · 📋 350 - 52% open · ⏱️ 19.08.2022): @@ -7145,7 +7145,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install orion ```
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MLBox (🥉21 · ⭐ 1.3K · 💀) - MLBox is a powerful Automated Machine Learning python library. ❗Unlicensed +
MLBox (🥉21 · ⭐ 1.3K · 💀) - MLBox是功能强大的自动机器学习python库。❗Unlicensed - [GitHub](https://github.com/AxeldeRomblay/MLBox) (👨‍💻 9 · 🔀 270 · 📦 28 · 📋 92 - 19% open · ⏱️ 25.08.2020): @@ -7157,7 +7157,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install mlbox ```
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Neuraxle (🥉21 · ⭐ 540) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 +
Neuraxle (🥉21 · ⭐ 540) - 类似于Sklearn的超参数调整和AutoML输入框架。Apache-2 - [GitHub](https://github.com/Neuraxio/Neuraxle) (👨‍💻 7 · 🔀 52 · 📦 34 · 📋 320 - 19% open · ⏱️ 16.08.2022): @@ -7169,7 +7169,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install neuraxle ```
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optunity (🥉21 · ⭐ 390 · 💀) - optimization routines for hyperparameter tuning. BSD-3 +
optunity (🥉21 · ⭐ 390 · 💀) - 超参数优化的优化例程。BSD-3 - [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 75 · 📥 67 · 📦 81 · 📋 97 - 50% open · ⏱️ 11.05.2020): @@ -7181,7 +7181,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install optunity ```
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HpBandSter (🥉20 · ⭐ 540) - a distributed Hyperband implementation on Steroids. BSD-3 +
HpBandSter (🥉20 · ⭐ 540) - 分布式自动化机器学习库。BSD-3 - [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 110 · 📦 240 · 📋 89 - 60% open · ⏱️ 22.04.2022): @@ -7205,7 +7205,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install auto_ml ```
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lazypredict (🥉19 · ⭐ 380) - Lazy Predict help build a lot of basic models without much code.. MIT +
lazypredict (🥉19 · ⭐ 380) - Lazy Predict帮助您无需大量代码即可构建许多基本模型。MIT - [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 17 · 🔀 67 · 📦 320 · 📋 66 - 48% open · ⏱️ 25.05.2022): @@ -7217,7 +7217,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install lazypredict ```
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Sherpa (🥉19 · ⭐ 310 · 💀) - Hyperparameter optimization that enables researchers to.. ❗️GPL-3.0 +
Sherpa (🥉19 · ⭐ 310 · 💀) - 超参数优化库。❗️GPL-3.0 - [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 48 · 📦 23 · 📋 57 - 28% open · ⏱️ 18.10.2020): @@ -7229,7 +7229,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install parameter-sherpa ```
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SMAC3 (🥉18 · ⭐ 730) - Sequential Model-based Algorithm Configuration. ❗Unlicensed +
SMAC3 (🥉18 · ⭐ 730) - Sequential Model-based算法的配置。❗Unlicensed - [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 170 · 📋 400 - 18% open · ⏱️ 14.07.2022): @@ -7241,7 +7241,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install smac ```
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Test Tube (🥉18 · ⭐ 720 · 💀) - Python library to easily log experiments and parallelize.. MIT +
Test Tube (🥉18 · ⭐ 720 · 💀) - 可轻松记录实验并进行并行化的Python库。MIT - [GitHub](https://github.com/williamFalcon/test-tube) (👨‍💻 16 · 🔀 67 · 📥 12 · 📋 44 - 52% open · ⏱️ 17.03.2020): @@ -7253,7 +7253,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install test_tube ```
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sklearn-deap (🥉18 · ⭐ 700 · 💀) - Use evolutionary algorithms instead of gridsearch in.. MIT +
sklearn-deap (🥉18 · ⭐ 700 · 💀) - 使用进化算法而非gridsearch的超参数优化。MIT - [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 120 · 📦 35 · 📋 50 - 32% open · ⏱️ 30.07.2021): @@ -7265,7 +7265,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install sklearn-deap ```
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Dragonfly (🥉18 · ⭐ 670) - An open source python library for scalable Bayesian optimisation. MIT +
Dragonfly (🥉18 · ⭐ 670) - 一个用于自动化特征工程的开源python库。MIT - [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 13 · 🔀 210 · 📋 56 - 64% open · ⏱️ 14.07.2022): @@ -7277,7 +7277,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install dragonfly-opt ```
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AlphaPy (🥉17 · ⭐ 800) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 +
AlphaPy (🥉17 · ⭐ 800) - 使用scikit-learn的自动化机器学习。Apache-2 - [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 160 · 📦 3 · 📋 41 - 29% open · ⏱️ 23.04.2022): @@ -7289,7 +7289,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install alphapy ```
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Auto Tune Models (🥉17 · ⭐ 520 · 💀) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT +
Auto Tune Models (🥉17 · ⭐ 520 · 💀) - 自动调整模型。MIT - [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 12 · 📋 89 - 20% open · ⏱️ 21.02.2020): @@ -7301,7 +7301,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install atm ```
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Auto ViML (🥉17 · ⭐ 360) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 +
Auto ViML (🥉17 · ⭐ 360) - 用单行代码自动构建多个ML模型。Apache-2 - [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 81 · 📦 17 · 📋 21 - 19% open · ⏱️ 16.08.2022): @@ -7313,7 +7313,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autoviml ```
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Parfit (🥉17 · ⭐ 200 · 💀) - A package for parallelizing the fit and flexibly scoring of.. MIT +
Parfit (🥉17 · ⭐ 200 · 💀) - 并行化拟合与评估工具库。MIT - [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 4 · 🔀 25 · 📦 16 · 📋 11 - 54% open · ⏱️ 04.04.2020): @@ -7325,7 +7325,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install parfit ```
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automl-gs (🥉16 · ⭐ 1.8K · 💀) - Provide an input CSV and a target field to predict, generate a.. MIT +
automl-gs (🥉16 · ⭐ 1.8K · 💀) - 提供输入CSV和目标字段以进行预测，自动生成可运行代码。MIT - [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 32 · 📋 30 - 80% open · ⏱️ 05.04.2019): @@ -7337,7 +7337,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install automl_gs ```
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featurewiz (🥉16 · ⭐ 270) - Use advanced feature engineering strategies and select the.. Apache-2 +
featurewiz (🥉16 · ⭐ 270) - 自动化特征工程并进行特征选择的工具库。Apache-2 - [GitHub](https://github.com/AutoViML/featurewiz) (👨‍💻 4 · 🔀 57 · 📦 14 · ⏱️ 21.08.2022): @@ -7349,7 +7349,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install featurewiz ```
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Advisor (🥉15 · ⭐ 1.5K · 💀) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 +
Advisor (🥉15 · ⭐ 1.5K · 💀) - Google Vizier的超参数开源实现。Apache-2 - [GitHub](https://github.com/tobegit3hub/advisor) (👨‍💻 11 · 🔀 260 · 📋 32 - 59% open · ⏱️ 11.11.2019): @@ -7365,7 +7365,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc docker pull tobegit3hub/advisor ```
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Xcessiv (🥉15 · ⭐ 1.3K · 💀) - A web-based application for quick, scalable, and automated.. Apache-2 +
Xcessiv (🥉15 · ⭐ 1.3K · 💀) - 基于Web的应用程序，高效、可扩展且自动化。Apache-2 - [GitHub](https://github.com/reiinakano/xcessiv) (👨‍💻 6 · 🔀 110 · 📦 1 · 📋 34 - 61% open · ⏱️ 21.08.2017): @@ -7377,7 +7377,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install xcessiv ```
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HyperparameterHunter (🥉15 · ⭐ 690 · 💀) - Easy hyperparameter optimization and automatic result.. MIT +
HyperparameterHunter (🥉15 · ⭐ 690 · 💀) - 轻松进行超参数优化和自动结果评估。MIT - [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (👨‍💻 4 · 🔀 88 · 📥 330 · 📋 120 - 27% open · ⏱️ 20.01.2021): @@ -7389,7 +7389,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install hyperparameter-hunter ```
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ENAS (🥉13 · ⭐ 2.6K · 💀) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 +
ENAS (🥉13 · ⭐ 2.6K · 💀) - Efficient Neural Architecture Search的Pytorch实现。Apache-2 - [GitHub](https://github.com/carpedm20/ENAS-pytorch) (👨‍💻 6 · 🔀 470 · 📋 44 - 84% open · ⏱️ 16.06.2020): @@ -7397,7 +7397,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc git clone https://github.com/carpedm20/ENAS-pytorch ```
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Auptimizer (🥉13 · ⭐ 190 · 💀) - An automatic ML model optimization tool. ❗️GPL-3.0 +
Auptimizer (🥉13 · ⭐ 190 · 💀) - 自动ML模型优化工具。❗️GPL-3.0 - [GitHub](https://github.com/LGE-ARC-AdvancedAI/auptimizer) (👨‍💻 11 · 🔀 22 · 📋 6 - 16% open · ⏱️ 03.03.2021): @@ -7409,7 +7409,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install auptimizer ```
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Hypermax (🥉12 · ⭐ 100 · 💀) - Better, faster hyper-parameter optimization. BSD-3 +
Hypermax (🥉12 · ⭐ 100 · 💀) - 更好更快的超参数优化。BSD-3 - [GitHub](https://github.com/electricbrainio/hypermax) (👨‍💻 9 · 🔀 13 · 📦 4 · 📋 5 - 60% open · ⏱️ 02.08.2020): @@ -7421,7 +7421,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install hypermax ```
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Devol (🥉11 · ⭐ 940 · 💀) - Genetic neural architecture search with Keras. MIT +
Devol (🥉11 · ⭐ 940 · 💀) - 使用Keras进行遗传神经体系结构搜索。MIT - [GitHub](https://github.com/joeddav/devol) (👨‍💻 18 · 🔀 110 · 📋 27 - 25% open · ⏱️ 05.07.2020): @@ -7429,7 +7429,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc git clone https://github.com/joeddav/devol ```
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Hypertunity (🥉10 · ⭐ 120 · 💀) - A toolset for black-box hyperparameter optimisation. Apache-2 +
Hypertunity (🥉10 · ⭐ 120 · 💀) - 黑盒超参数优化的工具集。Apache-2 - [GitHub](https://github.com/gdikov/hypertunity) (👨‍💻 2 · 🔀 9 · 📦 2 · ⏱️ 26.01.2020): @@ -7443,13 +7443,13 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc

-## Reinforcement Learning +## 强化学习 -Back to top +Back to top -_Libraries for building and evaluating reinforcement learning & agent-based systems._ +_用于构建和评估强化学习和基于agent的系统的库。_ -
OpenAI Gym (🥇36 · ⭐ 28K) - A toolkit for developing and comparing reinforcement learning.. MIT +
OpenAI Gym (🥇36 · ⭐ 28K) - 开发和比较强化学习的工具包。MIT - [GitHub](https://github.com/openai/gym) (👨‍💻 380 · 🔀 7.5K · 📦 32K · 📋 1.6K - 0% open · ⏱️ 24.08.2022): @@ -7461,7 +7461,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install gym ```
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TF-Agents (🥇27 · ⭐ 2.3K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 +
TF-Agents (🥇27 · ⭐ 2.3K) - TF-Agents：可靠，可扩展且易于使用的TensorFlow的强化学习库。Apache-2 - [GitHub](https://github.com/tensorflow/agents) (👨‍💻 120 · 🔀 620 · 📦 880 · 📋 560 - 22% open · ⏱️ 24.08.2022): @@ -7473,7 +7473,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tf-agents ```
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keras-rl (🥈25 · ⭐ 5.3K · 💀) - Deep Reinforcement Learning for Keras. MIT +
keras-rl (🥈25 · ⭐ 5.3K · 💀) - Keras的深度强化学习。MIT - [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 610 · 📋 230 - 2% open · ⏱️ 11.11.2019): @@ -7485,7 +7485,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install keras-rl ```
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baselines (🥈24 · ⭐ 13K · 💀) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT +
baselines (🥈24 · ⭐ 13K · 💀) - OpenAI基线：强化学习的高质量实现。MIT - [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.5K · 📦 410 · 📋 830 - 47% open · ⏱️ 31.01.2020): @@ -7497,7 +7497,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install baselines ```
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Acme (🥈24 · ⭐ 2.7K) - A library of reinforcement learning components and agents. Apache-2 +
Acme (🥈24 · ⭐ 2.7K) - 强化学习组件和代理库。Apache-2 - [GitHub](https://github.com/deepmind/acme) (👨‍💻 75 · 🔀 340 · 📦 99 · 📋 210 - 14% open · ⏱️ 25.08.2022): @@ -7509,7 +7509,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install dm-acme ```
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garage (🥈23 · ⭐ 1.5K) - A toolkit for reproducible reinforcement learning research. MIT +
garage (🥈23 · ⭐ 1.5K) - 用于可重复的强化学习研究的工具包。MIT - [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 78 · 🔀 260 · 📦 51 · 📋 1K - 19% open · ⏱️ 20.05.2022): @@ -7521,7 +7521,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install garage ```
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ViZDoom (🥈23 · ⭐ 1.4K) - Doom-based AI Research Platform for Reinforcement Learning from.. ❗Unlicensed +
ViZDoom (🥈23 · ⭐ 1.4K) - 人工智能强化学习工具库。❗Unlicensed - [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 49 · 🔀 330 · 📥 12K · 📦 150 · 📋 440 - 19% open · ⏱️ 26.06.2022): @@ -7533,7 +7533,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install vizdoom ```
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Dopamine (🥈22 · ⭐ 9.9K) - Dopamine is a research framework for fast prototyping of.. Apache-2 +
Dopamine (🥈22 · ⭐ 9.9K) - Dopamine是一个用于快速对强化学习进行原型制作的研究框架。Apache-2 - [GitHub](https://github.com/google/dopamine) (👨‍💻 15 · 🔀 1.3K · 📋 150 - 43% open · ⏱️ 13.06.2022): @@ -7545,7 +7545,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install dopamine-rl ```
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TensorForce (🥈22 · ⭐ 3.2K) - Tensorforce: a TensorFlow library for applied.. Apache-2 +
TensorForce (🥈22 · ⭐ 3.2K) - Tensorforce：一个基于TensorFlow的强化学习库。Apache-2 - [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 82 · 🔀 510 · 📋 650 - 3% open · ⏱️ 10.02.2022): @@ -7557,7 +7557,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tensorforce ```
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ChainerRL (🥈22 · ⭐ 1.1K · 💀) - ChainerRL is a deep reinforcement learning library built on top of.. MIT +
ChainerRL (🥈22 · ⭐ 1.1K · 💀) - ChainerRL是建立在Chainer之上的深度强化学习库。MIT - [GitHub](https://github.com/chainer/chainerrl) (👨‍💻 29 · 🔀 220 · 📦 130 · 📋 200 - 25% open · ⏱️ 17.04.2021): @@ -7569,7 +7569,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install chainerrl ```
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RLax (🥈22 · ⭐ 890) - A library of reinforcement learning building blocks in JAX. Apache-2 jax +
RLax (🥈22 · ⭐ 890) - 强化学习组件和代理库。Apache-2 jax - [GitHub](https://github.com/deepmind/rlax) (👨‍💻 19 · 🔀 66 · 📦 75 · 📋 19 - 21% open · ⏱️ 24.08.2022): @@ -7581,7 +7581,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install rlax ```
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TensorLayer (🥉21 · ⭐ 7.1K) - Deep Learning and Reinforcement Learning Library for.. ❗Unlicensed +
TensorLayer (🥉21 · ⭐ 7.1K) - 深度学习和强化学习库。❗Unlicensed - [GitHub](https://github.com/tensorlayer/TensorLayer) (👨‍💻 130 · 🔀 1.6K · 📥 1.4K · 📋 460 - 4% open · ⏱️ 23.04.2022): @@ -7593,7 +7593,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tensorlayer ```
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Stable Baselines (🥉20 · ⭐ 3.6K · 💤) - A fork of OpenAI Baselines, implementations of.. MIT +
Stable Baselines (🥉20 · ⭐ 3.6K · 💤) - OpenAI Baselines的一个分支，强化学习的实现。MIT - [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 690 · 📋 920 - 11% open · ⏱️ 25.08.2021): @@ -7605,7 +7605,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install stable-baselines ```
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PARL (🥉20 · ⭐ 2.7K) - A high-performance distributed training framework for Reinforcement.. Apache-2 +
PARL (🥉20 · ⭐ 2.7K) - 强化学习高性能分布式训练框架。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 31 · 🔀 730 · 📦 94 · 📋 410 - 15% open · ⏱️ 25.08.2022): @@ -7617,7 +7617,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install parl ```
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PFRL (🥉20 · ⭐ 890) - PFRL: a PyTorch-based deep reinforcement learning library. MIT +
PFRL (🥉20 · ⭐ 890) - PFRL：基于PyTorch的深度强化学习库。MIT - [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 16 · 🔀 120 · 📦 54 · 📋 63 - 38% open · ⏱️ 14.03.2022): @@ -7629,7 +7629,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install pfrl ```
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TRFL (🥉19 · ⭐ 3.1K · 💤) - TensorFlow Reinforcement Learning. Apache-2 +
TRFL (🥉19 · ⭐ 3.1K · 💤) - TensorFlow强化学习。Apache-2 - [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 380 · 📦 89 · 📋 20 - 20% open · ⏱️ 16.08.2021): @@ -7641,7 +7641,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install trfl ```
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Coach (🥉18 · ⭐ 2.2K · 💀) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 +
Coach (🥉18 · ⭐ 2.2K · 💀) - 英特尔AI实验室的强化学习训练器。Apache-2 - [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 430 · 📋 260 - 30% open · ⏱️ 28.06.2021): @@ -7653,7 +7653,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install rl_coach ```
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ReAgent (🥉17 · ⭐ 3.2K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 +
ReAgent (🥉17 · ⭐ 3.2K) - 推理系统平台。BSD-3 - [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 140 · 🔀 460 · 📋 100 - 25% open · ⏱️ 25.08.2022): @@ -7661,7 +7661,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst git clone https://github.com/facebookresearch/ReAgent ```
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DeepMind Lab (🥉15 · ⭐ 6.7K) - A customisable 3D platform for agent-based AI research. ❗Unlicensed +
DeepMind Lab (🥉15 · ⭐ 6.7K) - 可定制的3D平台，用于agent-based AI研究。❗Unlicensed - [GitHub](https://github.com/deepmind/lab) (👨‍💻 8 · 🔀 1.3K · 📋 220 - 25% open · ⏱️ 09.06.2022): @@ -7671,13 +7671,13 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst

-## Recommender Systems +## 推荐系统 -Back to top +Back to top -_Libraries for building and evaluating recommendation systems._ +_用于建立和评估推荐系统的库。_ -
lightfm (🥇26 · ⭐ 4.1K) - A Python implementation of LightFM, a hybrid recommendation algorithm. Apache-2 +
lightfm (🥇26 · ⭐ 4.1K) - 全局优化的Python实现。Apache-2 - [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 630 · 📦 790 · 📋 460 - 24% open · ⏱️ 19.07.2022): @@ -7693,7 +7693,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge lightfm ```
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implicit (🥇26 · ⭐ 2.9K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT +
implicit (🥇26 · ⭐ 2.9K) - 隐式反馈数据集的快速Python协同过滤。MIT - [GitHub](https://github.com/benfred/implicit) (👨‍💻 32 · 🔀 530 · 📥 95 · 📦 650 · 📋 420 - 16% open · ⏱️ 21.08.2022): @@ -7709,7 +7709,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge implicit ```
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TF Recommenders (🥇26 · ⭐ 1.4K) - TensorFlow Recommenders is a library for building.. Apache-2 +
TF Recommenders (🥇26 · ⭐ 1.4K) - TensorFlow Recommenders是一个用于构建推荐系统的工具库。Apache-2 - [GitHub](https://github.com/tensorflow/recommenders) (👨‍💻 37 · 🔀 200 · 📦 140 · 📋 280 - 49% open · ⏱️ 23.08.2022): @@ -7721,7 +7721,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorflow-recommenders ```
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TF Ranking (🥈23 · ⭐ 2.5K) - Learning to Rank in TensorFlow. Apache-2 +
TF Ranking (🥈23 · ⭐ 2.5K) - 在TensorFlow中学习推荐排序。Apache-2 - [GitHub](https://github.com/tensorflow/ranking) (👨‍💻 28 · 🔀 430 · 📋 290 - 19% open · ⏱️ 26.04.2022): @@ -7733,7 +7733,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorflow_ranking ```
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Cornac (🥈23 · ⭐ 630) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 +
Cornac (🥈23 · ⭐ 630) - 多模态推荐系统的比较框架。Apache-2 - [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 15 · 🔀 100 · 📦 120 · 📋 100 - 8% open · ⏱️ 22.07.2022): @@ -7749,7 +7749,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge cornac ```
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scikit-surprise (🥉22 · ⭐ 5.5K) - A Python scikit for building and analyzing recommender.. BSD-3 +
scikit-surprise (🥉22 · ⭐ 5.5K) - 用于构建和分析推荐算法的Python scikit工具库。BSD-3 - [GitHub](https://github.com/NicolasHug/Surprise) (👨‍💻 43 · 🔀 920 · 📋 350 - 15% open · ⏱️ 21.08.2022): @@ -7765,7 +7765,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge scikit-surprise ```
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RecBole (🥉22 · ⭐ 2K) - A unified, comprehensive and efficient recommendation library. MIT +
RecBole (🥉22 · ⭐ 2K) - 统一，全面，高效的推荐库。MIT - [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 47 · 🔀 380 · 📋 460 - 13% open · ⏱️ 26.08.2022): @@ -7781,7 +7781,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c aibox recbole ```
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Recommenders (🥉21 · ⭐ 14K) - Best Practices on Recommendation Systems. MIT +
Recommenders (🥉21 · ⭐ 14K) - 推荐系统最佳实践。MIT - [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 120 · 🔀 2.4K · 📥 230 · 📦 33 · 📋 710 - 20% open · ⏱️ 20.07.2022): @@ -7789,7 +7789,7 @@ _Libraries for building and evaluating recommendation systems._ git clone https://github.com/microsoft/recommenders ```
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fastFM (🥉19 · ⭐ 1K · 💀) - fastFM: A Library for Factorization Machines. ❗Unlicensed +
fastFM (🥉19 · ⭐ 1K · 💀) - fastFM：用于分解机的工具库。❗Unlicensed - [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 200 · 📥 450 · 📦 97 · 📋 110 - 43% open · ⏱️ 24.03.2021): @@ -7801,7 +7801,7 @@ _Libraries for building and evaluating recommendation systems._ pip install fastfm ```
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recmetrics (🥉19 · ⭐ 420) - A library of metrics for evaluating recommender systems. MIT +
recmetrics (🥉19 · ⭐ 420) - 用于评估推荐系统的度量标准库。MIT - [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 16 · 🔀 85 · 📦 29 · 📋 20 - 40% open · ⏱️ 17.04.2022): @@ -7813,7 +7813,7 @@ _Libraries for building and evaluating recommendation systems._ pip install recmetrics ```
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Spotlight (🥉18 · ⭐ 2.8K · 💀) - Deep recommender models using PyTorch. MIT +
Spotlight (🥉18 · ⭐ 2.8K · 💀) - 使用PyTorch的深度推荐系统模型实现。MIT - [GitHub](https://github.com/maciejkula/spotlight) (👨‍💻 11 · 🔀 400 · 📋 110 - 56% open · ⏱️ 09.02.2020): @@ -7825,7 +7825,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c maciejkula spotlight ```
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tensorrec (🥉18 · ⭐ 1.2K · 💀) - A TensorFlow recommendation algorithm and framework in.. Apache-2 +
tensorrec (🥉18 · ⭐ 1.2K · 💀) - TensorFlow推荐算法和框架。Apache-2 - [GitHub](https://github.com/jfkirk/tensorrec) (👨‍💻 9 · 🔀 220 · 📦 27 · 📋 130 - 28% open · ⏱️ 04.02.2020): @@ -7837,7 +7837,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorrec ```
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Case Recommender (🥉17 · ⭐ 420 · 💤) - Case Recommender: A Flexible and Extensible Python.. MIT +
Case Recommender (🥉17 · ⭐ 420 · 💤) - Case Recommender：灵活且可扩展的Python推荐系统工具库。MIT - [GitHub](https://github.com/caserec/CaseRecommender) (👨‍💻 11 · 🔀 79 · 📦 10 · 📋 25 - 20% open · ⏱️ 25.11.2021): @@ -7851,13 +7851,13 @@ _Libraries for building and evaluating recommendation systems._

-## Privacy Machine Learning +## 隐私机器学习 -Back to top +Back to top -_Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy._ +_使用联合学习和差异隐私之类的方法进行加密和保留隐私的机器学习的库。_ -
PySyft (🥇26 · ⭐ 8.3K) - A library for answering questions using data you cannot see. Apache-2 +
PySyft (🥇26 · ⭐ 8.3K) - 基于内部数据自动化回答问题的工具库。Apache-2 - [GitHub](https://github.com/OpenMined/PySyft) (👨‍💻 450 · 🔀 1.8K · 📋 3.1K - 1% open · ⏱️ 25.08.2022): @@ -7869,7 +7869,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install syft ```
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Opacus (🥈24 · ⭐ 1.2K) - Training PyTorch models with differential privacy. Apache-2 +
Opacus (🥈24 · ⭐ 1.2K) - 使用不同的隐私训练PyTorch模型。Apache-2 - [GitHub](https://github.com/pytorch/opacus) (👨‍💻 55 · 🔀 220 · 📥 51 · 📦 130 · 📋 200 - 21% open · ⏱️ 25.08.2022): @@ -7881,7 +7881,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install opacus ```
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TensorFlow Privacy (🥈23 · ⭐ 1.6K) - Library for training machine learning models with.. Apache-2 +
TensorFlow Privacy (🥈23 · ⭐ 1.6K) - 用于训练机器学习模型的库。Apache-2 - [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 49 · 🔀 350 · 📥 80 · 📋 150 - 43% open · ⏱️ 22.08.2022): @@ -7893,7 +7893,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install tensorflow-privacy ```
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FATE (🥉22 · ⭐ 4.4K) - An Industrial Grade Federated Learning Framework. Apache-2 +
FATE (🥉22 · ⭐ 4.4K) - 工业级联邦学习框架。Apache-2 - [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 74 · 🔀 1.3K · 📋 1.3K - 36% open · ⏱️ 15.04.2022): @@ -7901,7 +7901,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l git clone https://github.com/FederatedAI/FATE ```
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TFEncrypted (🥉20 · ⭐ 1K) - A Framework for Encrypted Machine Learning in TensorFlow. Apache-2 +
TFEncrypted (🥉20 · ⭐ 1K) - TensorFlow中的加密机器学习框架。Apache-2 - [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 180 · 📦 62 · 📋 420 - 37% open · ⏱️ 26.08.2022): @@ -7913,7 +7913,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install tf-encrypted ```
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CrypTen (🥉18 · ⭐ 1.1K) - A framework for Privacy Preserving Machine Learning. MIT +
CrypTen (🥉18 · ⭐ 1.1K) - 隐私保护的机器学习框架。MIT - [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 29 · 🔀 180 · 📦 21 · 📋 160 - 12% open · ⏱️ 10.06.2022): @@ -7927,13 +7927,13 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l

-## Workflow & Experiment Tracking +## 工作流程和实验跟踪 -Back to top +Back to top -_Libraries to organize, track, and visualize machine learning experiments._ +_跟踪和可视化机器学习实验的工具库整理。_ -
Tensorboard (🥇37 · ⭐ 6K) - TensorFlow's Visualization Toolkit. Apache-2 +
Tensorboard (🥇37 · ⭐ 6K) - TensorFlow的可视化工具包。Apache-2 - [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 290 · 🔀 1.5K · 📦 120K · 📋 1.7K - 31% open · ⏱️ 25.08.2022): @@ -7949,7 +7949,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge tensorboard ```
-
SageMaker SDK (🥇33 · ⭐ 1.7K) - A library for training and deploying machine learning.. Apache-2 +
SageMaker SDK (🥇33 · ⭐ 1.7K) - 一个用于训练和部署机器学习的库。Apache-2 - [GitHub](https://github.com/aws/sagemaker-python-sdk) (👨‍💻 280 · 🔀 810 · 📦 1.6K · 📋 1.1K - 32% open · ⏱️ 24.08.2022): @@ -7961,7 +7961,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install sagemaker ```
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PyCaret (🥇32 · ⭐ 6.1K) - An open-source, low-code machine learning library in Python. MIT +
PyCaret (🥇32 · ⭐ 6.1K) - Python中的开源代码，低代码机器学习库。MIT - [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 99 · 🔀 1.4K · 📥 610 · 📦 2.4K · 📋 1.7K - 15% open · ⏱️ 13.08.2022): @@ -7973,7 +7973,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install pycaret ```
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wandb client (🥇32 · ⭐ 4.6K) - A tool for visualizing and tracking your machine learning.. MIT +
wandb client (🥇32 · ⭐ 4.6K) - 用于可视化和跟踪机器学习的工具。MIT - [GitHub](https://github.com/wandb/wandb) (👨‍💻 120 · 🔀 340 · 📦 11K · 📋 1.9K - 24% open · ⏱️ 26.08.2022): @@ -7985,7 +7985,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install wandb ```
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tensorboardX (🥈31 · ⭐ 7.4K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT +
tensorboardX (🥈31 · ⭐ 7.4K) - pytorch（和链接器，mxnet，numpy，...）的张量板。MIT - [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 72 · 🔀 850 · 📥 350 · 📦 21K · 📋 430 - 15% open · ⏱️ 08.06.2022): @@ -8001,7 +8001,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge tensorboardx ```
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mlflow (🥈30 · ⭐ 12K) - Open source platform for the machine learning lifecycle. Apache-2 +
mlflow (🥈30 · ⭐ 12K) - 机器学习生命周期的开源平台。Apache-2 - [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 470 · 🔀 2.8K · 📋 2.4K - 33% open · ⏱️ 26.08.2022): @@ -8017,7 +8017,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge mlflow ```
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sacred (🥈30 · ⭐ 3.9K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT +
sacred (🥈30 · ⭐ 3.9K) - Sacred是可帮助您配置，组织，记录和复现的工具。MIT - [GitHub](https://github.com/IDSIA/sacred) (👨‍💻 100 · 🔀 350 · 📦 1.5K · 📋 540 - 16% open · ⏱️ 15.08.2022): @@ -8029,7 +8029,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install sacred ```
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ClearML (🥈29 · ⭐ 3.5K) - ClearML - Auto-Magical Suite of tools to streamline your ML.. Apache-2 +
ClearML (🥈29 · ⭐ 3.5K) - ClearML-自动精简工具套件。Apache-2 - [GitHub](https://github.com/allegroai/clearml) (👨‍💻 52 · 🔀 460 · 📥 500 · 📦 290 · 📋 600 - 44% open · ⏱️ 23.08.2022): @@ -8045,7 +8045,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ docker pull allegroai/trains ```
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Metaflow (🥈28 · ⭐ 5.9K) - Build and manage real-life data science projects with ease. Apache-2 +
Metaflow (🥈28 · ⭐ 5.9K) - 轻松构建和管理现实生活中的数据科学项目。Apache-2 - [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 54 · 🔀 500 · 📦 310 · 📋 420 - 45% open · ⏱️ 24.08.2022): @@ -8061,7 +8061,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge metaflow ```
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VisualDL (🥈27 · ⭐ 4.4K) - Deep Learning Visualization Toolkit. Apache-2 +
VisualDL (🥈27 · ⭐ 4.4K) - 深度学习可视化工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 32 · 🔀 590 · 📥 210 · 📦 1.3K · 📋 420 - 20% open · ⏱️ 23.08.2022): @@ -8073,7 +8073,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install visualdl ```
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Catalyst (🥈27 · ⭐ 3K) - Accelerated deep learning R&D. Apache-2 +
Catalyst (🥈27 · ⭐ 3K) - 加快深度学习研发。Apache-2 - [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 340 · 📦 600 · 📋 340 - 1% open · ⏱️ 29.04.2022): @@ -8085,7 +8085,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install catalyst ```
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snakemake (🥈27 · ⭐ 1.5K) - This is the development home of the workflow management system.. MIT +
snakemake (🥈27 · ⭐ 1.5K) - 工作流管理系统snakemake。MIT - [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 260 · 🔀 360 · 📦 1.2K · 📋 1.1K - 59% open · ⏱️ 25.08.2022): @@ -8101,7 +8101,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c bioconda snakemake ```
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ml-metadata (🥈26 · ⭐ 490) - For recording and retrieving metadata associated with ML.. Apache-2 +
ml-metadata (🥈26 · ⭐ 490) - 用于记录和检索与ML相关的元数据。Apache-2 - [GitHub](https://github.com/google/ml-metadata) (👨‍💻 15 · 🔀 95 · 📥 1.7K · 📦 240 · 📋 91 - 26% open · ⏱️ 23.08.2022): @@ -8113,7 +8113,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install ml-metadata ```
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DVC (🥈25 · ⭐ 10K) - Data Version Control | Git for Data & Models. Apache-2 +
DVC (🥈25 · ⭐ 10K) - 数据版本控制|针对数据和模型的Git。|) - 数据版本控制|针对数据和模型的Git。Apache-2 - [GitHub](https://github.com/iterative/dvc) (👨‍💻 270 · 🔀 950 · 📥 120K · 📋 3.8K - 16% open · ⏱️ 25.08.2022): @@ -8129,7 +8129,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge dvc ```
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AzureML SDK (🥈25 · ⭐ 3.4K) - Python notebooks with ML and deep learning examples with Azure.. MIT +
AzureML SDK (🥈25 · ⭐ 3.4K) - 带有ML的Python笔记本和带有Azure的深度学习示例。MIT - [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 60 · 🔀 2.1K · 📥 460 · 📋 1.3K - 21% open · ⏱️ 19.08.2022): @@ -8141,7 +8141,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install azureml-sdk ```
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aim (🥉24 · ⭐ 2.7K) - Aim a super-easy way to record, search and compare 1000s of ML training.. Apache-2 +
aim (🥉24 · ⭐ 2.7K) - 以一种非常简单的方式来记录，搜索和比较数千次ML训练。Apache-2 - [GitHub](https://github.com/aimhubio/aim) (👨‍💻 42 · 🔀 160 · 📦 100 · 📋 630 - 21% open · ⏱️ 25.08.2022): @@ -8153,7 +8153,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install aim ```
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livelossplot (🥉23 · ⭐ 1.2K) - Live training loss plot in Jupyter Notebook for Keras,.. MIT +
livelossplot (🥉23 · ⭐ 1.2K) - Jupyter Notebook for Keras的实时训练loss图。MIT - [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 840 · 📋 75 - 6% open · ⏱️ 04.04.2022): @@ -8165,7 +8165,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install livelossplot ```
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Labml (🥉23 · ⭐ 1.2K) - Monitor deep learning model training and hardware usage from your mobile.. MIT +
Labml (🥉23 · ⭐ 1.2K) - 从您的手机监控深度学习模型训练和硬件使用情况。MIT - [GitHub](https://github.com/labmlai/labml) (👨‍💻 7 · 🔀 78 · 📦 54 · 📋 29 - 44% open · ⏱️ 15.08.2022): @@ -8177,7 +8177,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install labml ```
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knockknock (🥉22 · ⭐ 2.5K · 💀) - Knock Knock: Get notified when your training ends with only two.. MIT +
knockknock (🥉22 · ⭐ 2.5K · 💀) - 当您的训练结束后通知您。MIT - [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 210 · 📦 380 · 📋 39 - 41% open · ⏱️ 16.03.2020): @@ -8193,7 +8193,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge knockknock ```
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kaggle (🥉21 · ⭐ 4.9K · 💀) - Official Kaggle API. Apache-2 +
kaggle (🥉21 · ⭐ 4.9K · 💀) - 官方Kaggle API。Apache-2 - [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 940 · 📋 350 - 57% open · ⏱️ 15.03.2021): @@ -8209,7 +8209,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge kaggle ```
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Guild AI (🥉21 · ⭐ 730) - Experiment tracking, ML developer tools. Apache-2 +
Guild AI (🥉21 · ⭐ 730) - 实验跟踪，ML开发人员工具库。Apache-2 - [GitHub](https://github.com/guildai/guildai) (👨‍💻 21 · 🔀 66 · 📥 6 · 📦 58 · 📋 380 - 45% open · ⏱️ 24.08.2022): @@ -8221,7 +8221,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install guildai ```
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hiddenlayer (🥉20 · ⭐ 1.6K · 💀) - Neural network graphs and training metrics for.. MIT +
hiddenlayer (🥉20 · ⭐ 1.6K · 💀) - 神经网络图和训练指标。MIT - [GitHub](https://github.com/waleedka/hiddenlayer) (👨‍💻 6 · 🔀 230 · 📦 130 · 📋 85 - 58% open · ⏱️ 24.04.2020): @@ -8233,7 +8233,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install hiddenlayer ```
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TNT (🥉20 · ⭐ 1.4K) - Simple tools for logging and visualizing, loading and training. BSD-3 +
TNT (🥉20 · ⭐ 1.4K) - 用于记录和可视化，加载和训练的简单工具。BSD-3 - [GitHub](https://github.com/pytorch/tnt) (👨‍💻 53 · 🔀 200 · ⏱️ 18.08.2022): @@ -8245,7 +8245,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install torchnet ```
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TensorWatch (🥉19 · ⭐ 3.2K · 💀) - Debugging, monitoring and visualization for Python Machine.. MIT +
TensorWatch (🥉19 · ⭐ 3.2K · 💀) - Python机器学习的调试，监视和可视化。MIT - [GitHub](https://github.com/microsoft/tensorwatch) (👨‍💻 13 · 🔀 340 · 📦 86 · 📋 67 - 77% open · ⏱️ 15.01.2021): @@ -8257,7 +8257,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install tensorwatch ```
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lore (🥉19 · ⭐ 1.5K) - Lore makes machine learning approachable for Software Engineers and.. MIT +
lore (🥉19 · ⭐ 1.5K) - lore使机器学习对软件工程师更易上手，对机器学习研究人员更可维护。MIT - [GitHub](https://github.com/instacart/lore) (👨‍💻 26 · 🔀 120 · 📦 20 · 📋 35 - 45% open · ⏱️ 11.04.2022): @@ -8269,7 +8269,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install lore ```
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gokart (🥉19 · ⭐ 260) - A wrapper of the data pipeline library luigi. MIT +
gokart (🥉19 · ⭐ 260) - 数据管道库luigi的包装。MIT - [GitHub](https://github.com/m3dev/gokart) (👨‍💻 34 · 🔀 45 · 📋 73 - 19% open · ⏱️ 02.08.2022): @@ -8281,7 +8281,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install gokart ```
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Studio.ml (🥉18 · ⭐ 380 · 💤) - Studio: Simplify and expedite model building process. Apache-2 +
Studio.ml (🥉18 · ⭐ 380 · 💤) - Studio：简化和加快模型构建过程。Apache-2 - [GitHub](https://github.com/studioml/studio) (👨‍💻 21 · 🔀 51 · 📦 5 · 📋 250 - 22% open · ⏱️ 14.09.2021): @@ -8293,7 +8293,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install studioml ```
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MXBoard (🥉18 · ⭐ 330 · 💀) - Logging MXNet data for visualization in TensorBoard. Apache-2 +
MXBoard (🥉18 · ⭐ 330 · 💀) - MXNet日志记录器，以在TensorBoard中进行可视化。Apache-2 - [GitHub](https://github.com/awslabs/mxboard) (👨‍💻 9 · 🔀 46 · 📦 160 · 📋 31 - 51% open · ⏱️ 24.01.2020): @@ -8305,7 +8305,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install mxboard ```
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quinn (🥉17 · ⭐ 350 · 💀) - pyspark methods to enhance developer productivity. ❗Unlicensed +
quinn (🥉17 · ⭐ 350 · 💀) - pyspark方法可提高开发人员的工作效率。❗Unlicensed - [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 47 · 📋 24 - 58% open · ⏱️ 09.02.2021): @@ -8317,7 +8317,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install quinn ```
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TensorBoard Logger (🥉15 · ⭐ 620 · 💀) - Log TensorBoard events without touching TensorFlow. MIT +
TensorBoard Logger (🥉15 · ⭐ 620 · 💀) - 简易TensorBoard日志记录库。MIT - [GitHub](https://github.com/TeamHG-Memex/tensorboard_logger) (👨‍💻 5 · 🔀 49 · 📋 24 - 37% open · ⏱️ 21.10.2019): @@ -8329,7 +8329,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install tensorboard_logger ```
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datmo (🥉15 · ⭐ 340 · 💀) - Open source production model management tool for data scientists. MIT +
datmo (🥉15 · ⭐ 340 · 💀) - 面向数据科学家的开源生产模型管理工具。MIT - [GitHub](https://github.com/datmo/datmo) (👨‍💻 6 · 🔀 28 · 📦 5 · 📋 180 - 15% open · ⏱️ 29.11.2019): @@ -8341,7 +8341,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install datmo ```
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steppy (🥉15 · ⭐ 130 · 💀) - Lightweight, Python library for fast and reproducible experimentation. MIT +
steppy (🥉15 · ⭐ 130 · 💀) - 轻量级的Python库，可进行快速且可重复的实验。MIT - [GitHub](https://github.com/minerva-ml/steppy) (👨‍💻 5 · 🔀 33 · 📦 46 · 📋 63 - 20% open · ⏱️ 23.11.2018): @@ -8353,7 +8353,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install steppy ```
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SKLL (🥉14 · ⭐ 530 · 💤) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗Unlicensed +
SKLL (🥉14 · ⭐ 530 · 💤) - SciKit学习实验室（SKLL）使机器学习易于操作。❗Unlicensed - [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 37 · 🔀 65 · 📥 11 · 📦 38 · 📋 400 - 7% open · ⏱️ 21.12.2021): @@ -8365,7 +8365,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install skll ```
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ModelChimp (🥉14 · ⭐ 120 · 💤) - Experiment tracking for machine and deep learning projects. BSD-2 +
ModelChimp (🥉14 · ⭐ 120 · 💤) - 机器和深度学习项目的实验跟踪。BSD-2 - [GitHub](https://github.com/ModelChimp/modelchimp) (👨‍💻 3 · 🔀 12 · 📋 14 - 28% open · ⏱️ 01.08.2021): @@ -8381,7 +8381,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ docker pull modelchimp/modelchimp-server ```
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traintool (🥉7 · ⭐ 10 · 💀) - Train off-the-shelf machine learning models in one.. Apache-2 +
traintool (🥉7 · ⭐ 10 · 💀) - 一站式训练现成的机器学习模型。Apache-2 - [GitHub](https://github.com/jrieke/traintool) (⏱️ 12.03.2021): @@ -8395,13 +8395,13 @@ _Libraries to organize, track, and visualize machine learning experiments._

-## Model Serialization & Conversion +## 模型序列化和转换 -Back to top +Back to top -_Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment._ +_用于将模型序列化为文件，在各种模型格式之间进行转换以及优化模型以进行部署的库。_ -
onnx (🥇32 · ⭐ 13K) - Open standard for machine learning interoperability. Apache-2 +
onnx (🥇32 · ⭐ 13K) - 机器学习互操作性的开放标准。Apache-2 - [GitHub](https://github.com/onnx/onnx) (👨‍💻 250 · 🔀 2.9K · 📥 18K · 📦 8.1K · 📋 2K - 11% open · ⏱️ 25.08.2022): @@ -8417,7 +8417,7 @@ _Libraries to serialize models to files, convert between a variety of model form conda install -c conda-forge onnx ```
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Core ML Tools (🥇25 · ⭐ 2.8K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 +
Core ML Tools (🥇25 · ⭐ 2.8K) - 核心ML工具包含用于核心ML模型的支持工具。BSD-3 - [GitHub](https://github.com/apple/coremltools) (👨‍💻 130 · 🔀 420 · 📥 4.4K · 📦 1K · 📋 970 - 28% open · ⏱️ 24.08.2022): @@ -8429,7 +8429,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install coremltools ```
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m2cgen (🥇25 · ⭐ 2.2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT +
m2cgen (🥇25 · ⭐ 2.2K) - 将ML模型转换成本机代码（Java，C，Python，Go，JavaScript）等。MIT - [GitHub](https://github.com/BayesWitnesses/m2cgen) (👨‍💻 13 · 🔀 200 · 📥 32 · 📦 59 · 📋 92 - 26% open · ⏱️ 14.08.2022): @@ -8441,7 +8441,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install m2cgen ```
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TorchServe (🥈24 · ⭐ 2.8K) - Model Serving on PyTorch. Apache-2 +
TorchServe (🥈24 · ⭐ 2.8K) - 在PyTorch上进行模型服务。Apache-2 - [GitHub](https://github.com/pytorch/serve) (👨‍💻 120 · 🔀 570 · 📥 2K · 📋 970 - 14% open · ⏱️ 25.08.2022): @@ -8461,7 +8461,7 @@ _Libraries to serialize models to files, convert between a variety of model form docker pull pytorch/torchserve ```
-
mmdnn (🥈23 · ⭐ 5.6K · 💀) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT +
mmdnn (🥈23 · ⭐ 5.6K · 💀) - MMdnn是一组工具，可以帮助用户在不同的深度学习框架之间进行互操作。MIT - [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 950 · 📥 3.6K · 📦 85 · 📋 610 - 52% open · ⏱️ 14.08.2020): @@ -8473,7 +8473,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install mmdnn ```
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cortex (🥉22 · ⭐ 7.8K) - Cost-effective serverless computing at scale. Apache-2 +
cortex (🥉22 · ⭐ 7.8K) - 具有成本效益的无服务器大规模计算。Apache-2 - [GitHub](https://github.com/cortexlabs/cortex) (👨‍💻 24 · 🔀 580 · 📋 1.1K - 10% open · ⏱️ 23.04.2022): @@ -8485,7 +8485,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install cortex ```
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Hummingbird (🥉22 · ⭐ 3K) - Hummingbird compiles trained ML models into tensor computation for.. MIT +
Hummingbird (🥉22 · ⭐ 3K) - 蜂鸟将训练有素的机器学习模型编译为张量计算，以用于..MIT - [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 31 · 🔀 240 · 📥 180 · 📦 39 · 📋 250 - 16% open · ⏱️ 17.08.2022): @@ -8497,7 +8497,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install hummingbird-ml ```
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sklearn-porter (🥉20 · ⭐ 1.2K) - Transpile trained scikit-learn estimators to C, Java,.. BSD-3 +
sklearn-porter (🥉20 · ⭐ 1.2K) - 将经过训练的scikit-learn估计器转换为C，Java等。BSD-3 - [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 12 · 🔀 160 · 📦 44 · 📋 68 - 50% open · ⏱️ 22.05.2022): @@ -8509,7 +8509,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install sklearn-porter ```
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pytorch2keras (🥉18 · ⭐ 810 · 💤) - PyTorch to Keras model convertor. MIT +
pytorch2keras (🥉18 · ⭐ 810 · 💤) - PyTorch到Keras模型转换器。MIT - [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 140 · 📦 51 · 📋 120 - 44% open · ⏱️ 06.08.2021): @@ -8521,7 +8521,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install pytorch2keras ```
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Larq Compute Engine (🥉17 · ⭐ 210) - Highly optimized inference engine for Binarized.. Apache-2 +
Larq Compute Engine (🥉17 · ⭐ 210) - 高度优化的二值化推理引擎。Apache-2 - [GitHub](https://github.com/larq/compute-engine) (👨‍💻 18 · 🔀 32 · 📥 730 · 📦 6 · 📋 140 - 9% open · ⏱️ 25.08.2022): @@ -8533,7 +8533,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install larq-compute-engine ```
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tfdeploy (🥉14 · ⭐ 350 · 💀) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 +
tfdeploy (🥉14 · ⭐ 350 · 💀) - 部署张量流图以进行快速评估并导出到无tensorflow环境中基于numpy运行。BSD-3 - [GitHub](https://github.com/riga/tfdeploy) (👨‍💻 4 · 🔀 36 · 📋 34 - 32% open · ⏱️ 08.01.2021): @@ -8547,13 +8547,13 @@ _Libraries to serialize models to files, convert between a variety of model form

-## Model Interpretability +## 模型的可解释性 -Back to top +Back to top -_Libraries to visualize, explain, debug, evaluate, and interpret machine learning models._ +_用于可视化，解释，调试，评估和解释机器学习模型的库。_ -
shap (🥇36 · ⭐ 17K) - A game theoretic approach to explain the output of any machine learning model. MIT +
shap (🥇36 · ⭐ 17K) - 用于解释任何机器学习模型的输出的一种博弈论方法实现。MIT - [GitHub](https://github.com/slundberg/shap) (👨‍💻 200 · 🔀 2.6K · 📦 6.4K · 📋 2K - 69% open · ⏱️ 16.06.2022): @@ -8569,7 +8569,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge shap ```
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Lime (🥇30 · ⭐ 10K · 💀) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 +
Lime (🥇30 · ⭐ 10K · 💀) - Lime：解释任何机器学习分类器的预测。BSD-2 - [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.6K · 📦 2.6K · 📋 580 - 9% open · ⏱️ 29.07.2021): @@ -8585,7 +8585,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge lime ```
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pyLDAvis (🥇29 · ⭐ 1.6K · 💀) - Python library for interactive topic model visualization... BSD-3 +
pyLDAvis (🥇29 · ⭐ 1.6K · 💀) - 用于交互式主题模型可视化的Python库。BSD-3 - [GitHub](https://github.com/bmabey/pyLDAvis) (👨‍💻 32 · 🔀 330 · 📦 3.8K · 📋 160 - 51% open · ⏱️ 24.03.2021): @@ -8601,7 +8601,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge pyldavis ```
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InterpretML (🥇28 · ⭐ 4.9K) - Fit interpretable models. Explain blackbox machine learning. MIT +
InterpretML (🥇28 · ⭐ 4.9K) - 拟合可解释的模型。对机器学习黑匣子进行解释。MIT - [GitHub](https://github.com/interpretml/interpret) (👨‍💻 31 · 🔀 590 · 📦 260 · 📋 300 - 32% open · ⏱️ 26.08.2022): @@ -8613,7 +8613,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install interpret ```
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dtreeviz (🥇28 · ⭐ 2.2K) - A python library for decision tree visualization and model interpretation. MIT +
dtreeviz (🥇28 · ⭐ 2.2K) - 用于决策树可视化和模型解释的python库。MIT - [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 21 · 🔀 280 · 📦 450 · 📋 120 - 19% open · ⏱️ 23.08.2022): @@ -8625,7 +8625,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dtreeviz ```
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arviz (🥇28 · ⭐ 1.3K) - Exploratory analysis of Bayesian models with Python. Apache-2 +
arviz (🥇28 · ⭐ 1.3K) - 使用Python探索性分析贝叶斯模型。Apache-2 - [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 130 · 🔀 290 · 📥 110 · 📦 2.7K · 📋 760 - 20% open · ⏱️ 17.08.2022): @@ -8641,7 +8641,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge arviz ```
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Captum (🥈27 · ⭐ 3.4K) - Model interpretability and understanding for PyTorch. BSD-3 +
Captum (🥈27 · ⭐ 3.4K) - PyTorch的模型可解释性和理解。BSD-3 - [GitHub](https://github.com/pytorch/captum) (👨‍💻 88 · 🔀 350 · 📦 650 · 📋 380 - 24% open · ⏱️ 23.08.2022): @@ -8653,7 +8653,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install captum ```
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scikit-plot (🥈26 · ⭐ 2.2K · 💀) - An intuitive library to add plotting functionality to.. MIT +
scikit-plot (🥈26 · ⭐ 2.2K · 💀) - 一个直观的库，可向其中添加绘图功能。MIT - [GitHub](https://github.com/reiinakano/scikit-plot) (👨‍💻 13 · 🔀 260 · 📦 2.3K · 📋 58 - 32% open · ⏱️ 19.08.2018): @@ -8669,7 +8669,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge scikit-plot ```
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explainerdashboard (🥈26 · ⭐ 1.3K) - Quickly build Explainable AI dashboards that show the inner.. MIT +
explainerdashboard (🥈26 · ⭐ 1.3K) - 快速构建可显示内部信息的可解释AI仪表板。MIT - [GitHub](https://github.com/oegedijk/explainerdashboard) (👨‍💻 15 · 🔀 160 · 📦 160 · 📋 180 - 8% open · ⏱️ 16.06.2022): @@ -8681,7 +8681,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install explainerdashboard ```
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Model Analysis (🥈26 · ⭐ 1.2K) - Model analysis tools for TensorFlow. Apache-2 +
Model Analysis (🥈26 · ⭐ 1.2K) - TensorFlow的模型分析工具。Apache-2 - [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 47 · 🔀 240 · 📋 65 - 24% open · ⏱️ 25.08.2022): @@ -8693,7 +8693,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tensorflow-model-analysis ```
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Alibi (🥈25 · ⭐ 1.7K) - Algorithms for monitoring and explaining machine learning models. Apache-2 +
Alibi (🥈25 · ⭐ 1.7K) - 监视和解释机器学习模型的算法。Apache-2 - [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 18 · 🔀 190 · 📦 190 · 📋 300 - 36% open · ⏱️ 24.08.2022): @@ -8705,7 +8705,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install alibi ```
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Lucid (🥈24 · ⭐ 4.4K · 💀) - A collection of infrastructure and tools for research in.. Apache-2 +
Lucid (🥈24 · ⭐ 4.4K · 💀) - 用于神经科学研究的基础设施和工具的集合。Apache-2 - [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 600 · 📦 650 · 📋 170 - 42% open · ⏱️ 19.03.2021): @@ -8717,7 +8717,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lucid ```
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Fairness 360 (🥈24 · ⭐ 1.8K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 +
Fairness 360 (🥈24 · ⭐ 1.8K) - 一整套用于数据集的公平度量标准。Apache-2 - [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 52 · 🔀 580 · 📦 170 · 📋 140 - 54% open · ⏱️ 25.08.2022): @@ -8729,7 +8729,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aif360 ```
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CausalNex (🥈24 · ⭐ 1.6K) - A Python library that helps data scientists to infer.. Apache-2 +
CausalNex (🥈24 · ⭐ 1.6K) - 一个可帮助数据科学家进行因果推断的Python库。Apache-2 - [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 180 · 📦 53 · 📋 110 - 17% open · ⏱️ 06.07.2022): @@ -8741,7 +8741,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install causalnex ```
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Explainability 360 (🥈24 · ⭐ 1.1K) - Interpretability and explainability of data and.. Apache-2 +
Explainability 360 (🥈24 · ⭐ 1.1K) - 数据和机器学习的可解释性。Apache-2 - [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 31 · 🔀 240 · 📦 55 · 📋 65 - 56% open · ⏱️ 26.07.2022): @@ -8753,7 +8753,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aix360 ```
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keras-vis (🥈23 · ⭐ 2.9K · 💀) - Neural network visualization toolkit for keras. MIT +
keras-vis (🥈23 · ⭐ 2.9K · 💀) - 用于Keras的神经网络可视化工具包。MIT - [GitHub](https://github.com/raghakot/keras-vis) (👨‍💻 10 · 🔀 630 · 📦 2.1K · 📋 210 - 52% open · ⏱️ 20.04.2020): @@ -8765,7 +8765,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install keras-vis ```
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yellowbrick (🥈22 · ⭐ 3.7K) - Visual analysis and diagnostic tools to facilitate machine.. Apache-2 +
yellowbrick (🥈22 · ⭐ 3.7K) - 可视化分析和诊断工具，方便机器使用。Apache-2 - [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 110 · 🔀 510 · 📋 670 - 11% open · ⏱️ 21.08.2022): @@ -8777,7 +8777,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install yellowbrick ```
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eli5 (🥈22 · ⭐ 2.6K · 💀) - A library for debugging/inspecting machine learning classifiers and.. MIT +
eli5 (🥈22 · ⭐ 2.6K · 💀) - 一个用于调试/检查机器学习分类器的库。MIT - [GitHub](https://github.com/TeamHG-Memex/eli5) (👨‍💻 14 · 🔀 310 · 📋 250 - 55% open · ⏱️ 22.01.2020): @@ -8793,7 +8793,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge eli5 ```
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imodels (🥈22 · ⭐ 890) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT +
imodels (🥈22 · ⭐ 890) - 可解释的ML包，用于简洁，透明和准确的预测。MIT - [GitHub](https://github.com/csinva/imodels) (👨‍💻 13 · 🔀 83 · 📦 20 · 📋 40 - 35% open · ⏱️ 25.08.2022): @@ -8805,7 +8805,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install imodels ```
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DoWhy (🥉21 · ⭐ 5.1K) - DoWhy is a Python library for causal inference that supports explicit.. MIT +
DoWhy (🥉21 · ⭐ 5.1K) - DoWhy是用于因果推断的Python库。MIT - [GitHub](https://github.com/py-why/dowhy) (👨‍💻 60 · 🔀 700 · 📥 31 · 📋 250 - 31% open · ⏱️ 23.08.2022): @@ -8821,7 +8821,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge dowhy ```
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checklist (🥉21 · ⭐ 1.7K) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT +
checklist (🥉21 · ⭐ 1.7K) - 超越准确性：使用CheckList对NLP模型进行行为测试。MIT - [GitHub](https://github.com/marcotcr/checklist) (👨‍💻 13 · 🔀 170 · 📦 150 · 📋 83 - 2% open · ⏱️ 12.08.2022): @@ -8833,7 +8833,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install checklist ```
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fairlearn (🥉21 · ⭐ 1.4K) - A Python package to assess and improve fairness of machine.. MIT +
fairlearn (🥉21 · ⭐ 1.4K) - 一个用于评估和改善机器公平性的Python程序包。MIT - [GitHub](https://github.com/fairlearn/fairlearn) (👨‍💻 68 · 🔀 310 · 📋 360 - 39% open · ⏱️ 24.08.2022): @@ -8849,7 +8849,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge fairlearn ```
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DALEX (🥉21 · ⭐ 1.1K) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 +
DALEX (🥉21 · ⭐ 1.1K) - 用于模型探索和扩展的模块。❗️GPL-3.0 - [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 140 · 📦 57 · 📋 370 - 5% open · ⏱️ 03.08.2022): @@ -8861,7 +8861,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dalex ```
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keract (🥉21 · ⭐ 990) - Layers Outputs and Gradients in Keras. Made easy. MIT +
keract (🥉21 · ⭐ 990) - 在Keras中分层输出和渐变。MIT - [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 140 · 📋 87 - 5% open · ⏱️ 23.07.2022): @@ -8873,7 +8873,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install keract ```
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tf-explain (🥉21 · ⭐ 940) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT +
tf-explain (🥉21 · ⭐ 940) - 使用Tensorflow 2.x的tf.keras模型的可解释性方法。MIT - [GitHub](https://github.com/sicara/tf-explain) (👨‍💻 18 · 🔀 100 · 📦 130 · 📋 88 - 42% open · ⏱️ 30.06.2022): @@ -8885,7 +8885,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tf-explain ```
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random-forest-importances (🥉21 · ⭐ 510 · 💀) - Code to compute permutation and drop-column.. MIT +
random-forest-importances (🥉21 · ⭐ 510 · 💀) - 随机森林特征重要度计算。MIT - [GitHub](https://github.com/parrt/random-forest-importances) (👨‍💻 14 · 🔀 120 · 📦 100 · 📋 34 - 14% open · ⏱️ 30.01.2021): @@ -8897,7 +8897,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install rfpimp ```
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sklearn-evaluation (🥉21 · ⭐ 340) - Machine learning model evaluation made easy: plots,.. MIT +
sklearn-evaluation (🥉21 · ⭐ 340) - 机器学习模型评估变得容易。MIT - [GitHub](https://github.com/ploomber/sklearn-evaluation) (👨‍💻 8 · 🔀 28 · 📦 49 · 📋 39 - 20% open · ⏱️ 22.08.2022): @@ -8909,7 +8909,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install sklearn-evaluation ```
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DiCE (🥉20 · ⭐ 890) - Generate Diverse Counterfactual Explanations for any machine.. MIT +
DiCE (🥉20 · ⭐ 890) - 生成任何机器学习的各种反事实说明。MIT - [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 14 · 🔀 120 · 📋 130 - 44% open · ⏱️ 06.07.2022): @@ -8921,7 +8921,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dice-ml ```
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TreeInterpreter (🥉20 · ⭐ 720 · 💀) - Package for interpreting scikit-learn's decision tree.. BSD-3 +
TreeInterpreter (🥉20 · ⭐ 720 · 💀) - 解释scikit-learn决策树的程序包。BSD-3 - [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 140 · 📦 280 · 📋 23 - 82% open · ⏱️ 28.02.2021): @@ -8933,7 +8933,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install treeinterpreter ```
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LIT (🥉19 · ⭐ 3K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 +
LIT (🥉19 · ⭐ 3K) - 语言可解释性工具：交互式分析NLP模型。Apache-2 - [GitHub](https://github.com/PAIR-code/lit) (👨‍💻 18 · 🔀 310 · 📦 11 · 📋 110 - 37% open · ⏱️ 15.03.2022): @@ -8945,7 +8945,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lit-nlp ```
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What-If Tool (🥉19 · ⭐ 740 · 💤) - Source code/webpage/demos for the What-If Tool. Apache-2 +
What-If Tool (🥉19 · ⭐ 740 · 💤) - What-If工具的源代码/网页/演示。Apache-2 - [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 20 · 🔀 140 · 📋 110 - 52% open · ⏱️ 05.01.2022): @@ -8961,7 +8961,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin npm install wit-widget ```
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deeplift (🥉19 · ⭐ 650 · 💤) - Public facing deeplift repo. MIT +
deeplift (🥉19 · ⭐ 650 · 💤) - Public facing deeplift repo。MIT - [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 150 · 📦 62 · 📋 85 - 43% open · ⏱️ 11.11.2021): @@ -8973,7 +8973,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install deeplift ```
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aequitas (🥉19 · ⭐ 490 · 💀) - Bias and Fairness Audit Toolkit. MIT +
aequitas (🥉19 · ⭐ 490 · 💀) - 偏差和公平审计工具包。MIT - [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 90 · 📦 110 · 📋 61 - 65% open · ⏱️ 27.05.2021): @@ -8985,7 +8985,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aequitas ```
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model-card-toolkit (🥉19 · ⭐ 300) - a tool that leverages rich metadata and lineage.. Apache-2 +
model-card-toolkit (🥉19 · ⭐ 300) - 模型解释与分析卡片工具库。Apache-2 - [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 13 · 🔀 60 · 📦 10 · 📋 14 - 85% open · ⏱️ 28.04.2022): @@ -8997,7 +8997,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install model-card-toolkit ```
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fairness-indicators (🥉19 · ⭐ 270) - Tensorflow's Fairness Evaluation and Visualization.. Apache-2 +
fairness-indicators (🥉19 · ⭐ 270) - Tensorflow的公平性评估和可视化。Apache-2 - [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 33 · 🔀 68 · 📋 11 - 27% open · ⏱️ 26.07.2022): @@ -9009,7 +9009,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install fairness-indicators ```
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iNNvestigate (🥉18 · ⭐ 1K) - A toolbox to iNNvestigate neural networks' predictions!. BSD-2 +
iNNvestigate (🥉18 · ⭐ 1K) - 神经网络预估分析工具箱。BSD-2 - [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 220 · 📥 16 · 📋 230 - 19% open · ⏱️ 01.08.2022): @@ -9021,7 +9021,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install innvestigate ```
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Skater (🥉17 · ⭐ 1K) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 +
Skater (🥉17 · ⭐ 1K) - 用于模型解释/说明的Python库。❗️UPL-1.0 - [GitHub](https://github.com/oracle/Skater) (👨‍💻 36 · 🔀 170 · 📋 160 - 40% open · ⏱️ 11.02.2022): @@ -9037,7 +9037,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge skater ```
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FlashTorch (🥉17 · ⭐ 680 · 💀) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT +
FlashTorch (🥉17 · ⭐ 680 · 💀) - PyTorch中用于神经网络的可视化工具包。MIT - [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 84 · 📦 10 · 📋 31 - 29% open · ⏱️ 27.04.2021): @@ -9049,7 +9049,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install flashtorch ```
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tcav (🥉17 · ⭐ 530 · 💤) - Code for the TCAV ML interpretability project. Apache-2 +
tcav (🥉17 · ⭐ 530 · 💤) - TCAV ML可解释性项目的代码。Apache-2 - [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 130 · 📦 14 · 📋 61 - 11% open · ⏱️ 16.09.2021): @@ -9061,7 +9061,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tcav ```
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ExplainX.ai (🥉17 · ⭐ 320 · 💀) - Explainable AI framework for data scientists. Explain & debug any.. MIT +
ExplainX.ai (🥉17 · ⭐ 320 · 💀) - 适用于数据科学家的可解释AI框架。MIT - [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 42 · 📥 4 · 📋 26 - 34% open · ⏱️ 02.02.2021): @@ -9073,7 +9073,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install explainx ```
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XAI (🥉15 · ⭐ 840 · 💤) - XAI - An eXplainability toolbox for machine learning. MIT +
XAI (🥉15 · ⭐ 840 · 💤) - XAI-用于机器学习的可解释性工具箱。MIT - [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 120 · 📦 19 · 📋 9 - 22% open · ⏱️ 30.10.2021): @@ -9085,7 +9085,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install xai ```
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Anchor (🥉15 · ⭐ 720) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 +
Anchor (🥉15 · ⭐ 720) - High-Precision Model-Agnostic Explanations论文代码。BSD-2 - [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 10 · 🔀 99 · 📋 70 - 27% open · ⏱️ 19.07.2022): @@ -9097,7 +9097,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install anchor_exp ```
-
LOFO (🥉15 · ⭐ 480) - Leave One Feature Out Importance. MIT +
LOFO (🥉15 · ⭐ 480) - Leave One Feature Out特征重要度。MIT - [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 56 · 📦 19 · 📋 18 - 11% open · ⏱️ 27.04.2022): @@ -9109,7 +9109,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lofo-importance ```
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contextual-ai (🥉13 · ⭐ 81 · 💤) - Contextual AI adds explainability to different stages of.. Apache-2 +
contextual-ai (🥉13 · ⭐ 81 · 💤) - AI 模型可解释性工具。Apache-2 - [GitHub](https://github.com/SAP/contextual-ai) (👨‍💻 12 · 🔀 10 · 📋 12 - 8% open · ⏱️ 11.11.2021): @@ -9121,7 +9121,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install contextual-ai ```
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Attribution Priors (🥉11 · ⭐ 100 · 💀) - Tools for training explainable models using.. MIT +
Attribution Priors (🥉11 · ⭐ 100 · 💀) - 训练可解释模型的工具。MIT - [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 10 · 📦 3 · 📋 5 - 40% open · ⏱️ 19.03.2021): @@ -9133,7 +9133,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install attributionpriors ```
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bias-detector (🥉11 · ⭐ 40 · 💤) - Bias Detector is a python package for detecting bias in machine.. MIT +
bias-detector (🥉11 · ⭐ 40 · 💤) - Bias Detector是用于检测机器偏差的python软件包。MIT - [GitHub](https://github.com/intuit/bias-detector) (👨‍💻 4 · 🔀 11 · ⏱️ 20.12.2021): @@ -9147,15 +9147,15 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin

-## Vector Similarity Search (ANN) +## 向量相似度搜索（ANN） -Back to top +Back to top -_Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search._ +_用于近似最近邻居搜索和向量索引/相似性搜索的库。_ 🔗 ANN Benchmarks ( ⭐ 3K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Annoy (🥇31 · ⭐ 10K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 +
Annoy (🥇31 · ⭐ 10K) - C++/Python中的近似最近邻居实现，并针对内存使用进行了优化。Apache-2 - [GitHub](https://github.com/spotify/annoy) (👨‍💻 82 · 🔀 1K · 📦 2.2K · 📋 350 - 10% open · ⏱️ 08.08.2022): @@ -9167,7 +9167,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install annoy ```
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Milvus (🥇29 · ⭐ 12K) - An open source embedding vector similarity search engine powered by.. Apache-2 +
Milvus (🥇29 · ⭐ 12K) - 一个开源的embedding嵌入向量相似度搜索引擎。Apache-2 - [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 220 · 🔀 1.4K · 📥 44K · 📋 5.7K - 4% open · ⏱️ 26.08.2022): @@ -9183,7 +9183,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit docker pull milvusdb/milvus ```
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NMSLIB (🥈28 · ⭐ 2.8K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 +
NMSLIB (🥈28 · ⭐ 2.8K) - 非度量空间库（NMSLIB）：一种有效的相似度搜索。Apache-2 - [GitHub](https://github.com/nmslib/nmslib) (👨‍💻 48 · 🔀 400 · 📦 660 · 📋 400 - 14% open · ⏱️ 31.05.2022): @@ -9199,7 +9199,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge nmslib ```
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PyNNDescent (🥈28 · ⭐ 660) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 +
PyNNDescent (🥈28 · ⭐ 660) - 适用于近似最近邻查找的Python库。BSD-2 - [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 21 · 🔀 88 · 📦 2K · 📋 110 - 47% open · ⏱️ 21.07.2022): @@ -9215,7 +9215,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge pynndescent ```
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Faiss (🥈27 · ⭐ 18K) - A library for efficient similarity search and clustering of dense vectors. MIT +
Faiss (🥈27 · ⭐ 18K) - 一个用于高效相似性搜索和密集向量聚类的库。MIT - [GitHub](https://github.com/facebookresearch/faiss) (👨‍💻 100 · 🔀 2.6K · 📦 720 · 📋 1.9K - 11% open · ⏱️ 08.08.2022): @@ -9231,7 +9231,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge faiss ```
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hnswlib (🥈27 · ⭐ 2.1K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 +
hnswlib (🥈27 · ⭐ 2.1K) - 仅标头的C++/python库，用于快速近似最近邻查找。Apache-2 - [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 56 · 🔀 380 · 📦 280 · 📋 250 - 50% open · ⏱️ 16.04.2022): @@ -9243,7 +9243,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install hnswlib ```
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Magnitude (🥉22 · ⭐ 1.5K · 💀) - A fast, efficient universal vector embedding utility package. MIT +
Magnitude (🥉22 · ⭐ 1.5K · 💀) - 快速，高效的通用向量嵌入实用程序包。MIT - [GitHub](https://github.com/plasticityai/magnitude) (👨‍💻 4 · 🔀 110 · 📦 240 · 📋 83 - 38% open · ⏱️ 17.07.2020): @@ -9255,7 +9255,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install pymagnitude ```
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NGT (🥉19 · ⭐ 930) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 +
NGT (🥉19 · ⭐ 930) - 最近邻搜索算法实现包。Apache-2 - [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 14 · 🔀 94 · 📋 100 - 11% open · ⏱️ 15.08.2022): @@ -9267,7 +9267,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install ngt ```
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NearPy (🥉19 · ⭐ 710 · 💀) - Python framework for fast (approximated) nearest neighbour search in.. MIT +
NearPy (🥉19 · ⭐ 710 · 💀) - 用于快速（近似）最近邻搜索的Python框架。MIT - [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 70 · 📋 62 - 38% open · ⏱️ 21.10.2018): @@ -9279,7 +9279,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install NearPy ```
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N2 (🥉18 · ⭐ 520 · 💀) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 +
N2 (🥉18 · ⭐ 520 · 💀) - TOROS N2-快速运行的轻量级近似最近邻库。Apache-2 - [GitHub](https://github.com/kakao/n2) (👨‍💻 18 · 🔀 64 · 📦 23 · 📋 33 - 33% open · ⏱️ 20.05.2021): @@ -9291,7 +9291,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install n2 ```
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PySparNN (🥉11 · ⭐ 900 · 💀) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3 +
PySparNN (🥉11 · ⭐ 900 · 💀) - C++/Python中的近似最近邻居实现，并针对内存使用进行了优化。BSD-3 - [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 140 · 📋 29 - 51% open · ⏱️ 31.01.2018): @@ -9301,13 +9301,13 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit

-## Probabilistics & Statistics +## 概率统计 -Back to top +Back to top -_Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics._ +_提供概率编程/推理，贝叶斯推理，高斯过程或统计信息的功能的库。_ -
Pyro (🥇30 · ⭐ 7.6K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 +
Pyro (🥇30 · ⭐ 7.6K) - 使用Python和PyTorch进行深度通用概率编程。Apache-2 - [GitHub](https://github.com/pyro-ppl/pyro) (👨‍💻 130 · 🔀 900 · 📦 820 · 📋 970 - 20% open · ⏱️ 05.08.2022): @@ -9319,7 +9319,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pyro-ppl ```
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GPyTorch (🥇29 · ⭐ 2.8K) - A highly efficient and modular implementation of Gaussian Processes.. MIT +
GPyTorch (🥇29 · ⭐ 2.8K) - 高斯过程的高效和模块化实现。MIT - [GitHub](https://github.com/cornellius-gp/gpytorch) (👨‍💻 99 · 🔀 420 · 📦 680 · 📋 1.1K - 24% open · ⏱️ 24.08.2022): @@ -9331,7 +9331,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install gpytorch ```
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filterpy (🥇28 · ⭐ 2.4K) - Python Kalman filtering and optimal estimation library. Implements.. MIT +
filterpy (🥇28 · ⭐ 2.4K) - Python卡尔曼过滤和最佳估计库。MIT - [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 43 · 🔀 520 · 📦 1.6K · 📋 200 - 23% open · ⏱️ 22.08.2022): @@ -9347,7 +9347,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge filterpy ```
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GPflow (🥇28 · ⭐ 1.7K) - Gaussian processes in TensorFlow. Apache-2 +
GPflow (🥇28 · ⭐ 1.7K) - TensorFlow中的高斯过程。Apache-2 - [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 78 · 🔀 410 · 📦 390 · 📋 780 - 15% open · ⏱️ 17.08.2022): @@ -9363,7 +9363,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge gpflow ```
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pingouin (🥈27 · ⭐ 1.2K) - Statistical package in Python based on Pandas. ❗️GPL-3.0 +
pingouin (🥈27 · ⭐ 1.2K) - 基于Pandas的Python统计软件包。❗️GPL-3.0 - [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 33 · 🔀 110 · 📦 680 · 📋 220 - 14% open · ⏱️ 18.07.2022): @@ -9379,7 +9379,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pingouin ```
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patsy (🥈27 · ⭐ 850) - Describing statistical models in Python using symbolic formulas. ❗Unlicensed +
patsy (🥈27 · ⭐ 850) - 使用符号公式描述Python中的统计模型。❗Unlicensed - [GitHub](https://github.com/pydata/patsy) (👨‍💻 17 · 🔀 88 · 📦 56K · 📋 130 - 46% open · ⏱️ 16.08.2022): @@ -9395,7 +9395,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge patsy ```
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PyMC3 (🥈26 · ⭐ 6.9K) - Probabilistic Programming in Python: Bayesian Modeling and.. ❗Unlicensed +
PyMC3 (🥈26 · ⭐ 6.9K) - Python中的概率编程。❗Unlicensed - [GitHub](https://github.com/pymc-devs/pymc) (👨‍💻 410 · 🔀 1.6K · 📥 1.9K · 📦 690 · 📋 2.8K - 6% open · ⏱️ 25.08.2022): @@ -9411,7 +9411,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pymc3 ```
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pomegranate (🥈26 · ⭐ 2.9K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT +
pomegranate (🥈26 · ⭐ 2.9K) - 在Python中快速，灵活且易于使用的概率建模。MIT - [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 66 · 🔀 530 · 📦 740 · 📋 670 - 8% open · ⏱️ 04.07.2022): @@ -9427,7 +9427,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pomegranate ```
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hmmlearn (🥈26 · ⭐ 2.6K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 +
hmmlearn (🥈26 · ⭐ 2.6K) - Python中的隐马尔可夫模型，具有类似于scikit-learn的API。BSD-3 - [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 41 · 🔀 660 · 📦 1.4K · 📋 390 - 13% open · ⏱️ 04.07.2022): @@ -9443,7 +9443,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge hmmlearn ```
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pgmpy (🥉25 · ⭐ 2.1K) - Python Library for learning (Structure and Parameter) and inference.. MIT +
pgmpy (🥉25 · ⭐ 2.1K) - 用于学习（结构和参数）和推理的Python库。MIT - [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 110 · 🔀 630 · 📥 160 · 📦 400 · 📋 770 - 24% open · ⏱️ 22.08.2022): @@ -9455,7 +9455,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pgmpy ```
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tensorflow-probability (🥉24 · ⭐ 3.8K) - Probabilistic reasoning and statistical analysis in.. Apache-2 +
tensorflow-probability (🥉24 · ⭐ 3.8K) - 概率推理与统计分析。Apache-2 - [GitHub](https://github.com/tensorflow/probability) (👨‍💻 460 · 🔀 960 · 📋 1.2K - 42% open · ⏱️ 26.08.2022): @@ -9471,7 +9471,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge tensorflow-probability ```
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Edward (🥉23 · ⭐ 4.7K · 💀) - A probabilistic programming language in TensorFlow. Deep.. ❗Unlicensed +
Edward (🥉23 · ⭐ 4.7K · 💀) - TensorFlow中的一种概率编程语言。❗Unlicensed - [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 750 · 📥 15 · 📦 270 · 📋 510 - 36% open · ⏱️ 25.07.2018): @@ -9483,7 +9483,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install edward ```
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Orbit (🥉21 · ⭐ 1.5K) - A Python package for Bayesian forecasting with object-oriented.. ❗Unlicensed +
Orbit (🥉21 · ⭐ 1.5K) - 用于贝叶斯预测的Python软件包，具有面向对象的设计。❗Unlicensed - [GitHub](https://github.com/uber/orbit) (👨‍💻 18 · 🔀 110 · 📦 9 · 📋 370 - 12% open · ⏱️ 17.08.2022): @@ -9495,7 +9495,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install orbit-ml ```
-
bambi (🥉20 · ⭐ 820) - BAyesian Model-Building Interface (Bambi) in Python. MIT +
bambi (🥉20 · ⭐ 820) - Python中的贝叶斯模型构建接口（Bambi）。MIT - [GitHub](https://github.com/bambinos/bambi) (👨‍💻 26 · 🔀 89 · 📦 32 · 📋 270 - 18% open · ⏱️ 21.08.2022): @@ -9507,7 +9507,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install bambi ```
-
SALib (🥉20 · ⭐ 620) - Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,.. MIT +
SALib (🥉20 · ⭐ 620) - Python（Numpy）中的灵敏度分析库。MIT - [GitHub](https://github.com/SALib/SALib) (👨‍💻 37 · 🔀 190 · 📋 280 - 15% open · ⏱️ 21.08.2022): @@ -9523,7 +9523,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge salib ```
-
scikit-posthocs (🥉20 · ⭐ 250) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT +
scikit-posthocs (🥉20 · ⭐ 250) - Python中的多个成对比较（Post Hoc）测试。MIT - [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 10 · 🔀 28 · 📥 25 · 📋 47 - 12% open · ⏱️ 21.08.2022): @@ -9535,7 +9535,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install scikit-posthocs ```
-
Funsor (🥉19 · ⭐ 200) - Functional tensors for probabilistic programming. Apache-2 +
Funsor (🥉19 · ⭐ 200) - 用于概率编程的函数张量。Apache-2 - [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 10 · 🔀 17 · 📦 32 · 📋 140 - 47% open · ⏱️ 08.04.2022): @@ -9547,7 +9547,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install funsor ```
-
Baal (🥉18 · ⭐ 630) - Using approximate bayesian posteriors in deep nets for active learning. Apache-2 +
Baal (🥉18 · ⭐ 630) - 在深度网络中使用近似贝叶斯后验进行主动学习。Apache-2 - [GitHub](https://github.com/baal-org/baal) (👨‍💻 16 · 🔀 60 · 📋 84 - 27% open · ⏱️ 22.08.2022): @@ -9559,7 +9559,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install baal ```
-
PyStan (🥉18 · ⭐ 200) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC +
PyStan (🥉18 · ⭐ 200) - PyStan是Stan的Python接口。ISC - [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 10 · 🔀 39 · 📋 180 - 2% open · ⏱️ 07.07.2022): @@ -9575,7 +9575,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pystan ```
-
pyhsmm (🥉17 · ⭐ 520 · 💀) - Bayesian inference in HSMMs and HMMs. MIT +
pyhsmm (🥉17 · ⭐ 520 · 💀) - HSMM和HMM中的贝叶斯推断。MIT - [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 25 · 📋 96 - 37% open · ⏱️ 24.08.2020): @@ -9587,7 +9587,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pyhsmm ```
-
ZhuSuan (🥉14 · ⭐ 2.1K · 💀) - A probabilistic programming library for Bayesian deep learning,.. MIT +
ZhuSuan (🥉14 · ⭐ 2.1K · 💀) - TensorFlow中的一种概率编程语言。MIT - [GitHub](https://github.com/thu-ml/zhusuan) (👨‍💻 20 · 🔀 400 · 📋 60 - 11% open · ⏱️ 05.08.2019): @@ -9597,13 +9597,13 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes

-## Adversarial Robustness +## 对抗学习与鲁棒性 -Back to top +Back to top -_Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples._ +_用于测试机器学习模型抵抗攻击性/恶意示例的鲁棒性的库。_ -
Foolbox (🥇27 · ⭐ 2.3K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT +
Foolbox (🥇27 · ⭐ 2.3K) - 一个Python工具箱，用于创建欺骗神经网络的对抗示例。MIT - [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 400 · 📦 320 · 📋 350 - 5% open · ⏱️ 25.05.2022): @@ -9615,7 +9615,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install foolbox ```
-
CleverHans (🥈26 · ⭐ 5.6K · 💤) - An adversarial example library for constructing attacks,.. MIT +
CleverHans (🥈26 · ⭐ 5.6K · 💤) - 一个用于构造攻击的对抗性示例库。MIT - [GitHub](https://github.com/cleverhans-lab/cleverhans) (👨‍💻 130 · 🔀 1.3K · 📦 350 · 📋 450 - 5% open · ⏱️ 23.09.2021): @@ -9627,7 +9627,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install cleverhans ```
-
TextAttack (🥈26 · ⭐ 2.1K) - TextAttack is a Python framework for adversarial attacks, data.. MIT +
TextAttack (🥈26 · ⭐ 2.1K) - TextAttack是用于对抗攻击，数据的Python框架。MIT - [GitHub](https://github.com/QData/TextAttack) (👨‍💻 53 · 🔀 250 · 📦 93 · 📋 220 - 9% open · ⏱️ 14.08.2022): @@ -9639,7 +9639,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install textattack ```
-
ART (🥉24 · ⭐ 3.2K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT +
ART (🥉24 · ⭐ 3.2K) - 对抗性鲁棒性工具箱（ART）- 用于机器学习的Python库。MIT - [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (👨‍💻 110 · 🔀 850 · 📦 250 · 📋 710 - 12% open · ⏱️ 25.08.2022): @@ -9651,7 +9651,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install adversarial-robustness-toolbox ```
-
advertorch (🥉18 · ⭐ 1.1K) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 +
advertorch (🥉18 · ⭐ 1.1K) - 对抗性鲁棒性研究的工具箱。❗️GPL-3.0 - [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 21 · 🔀 170 · 📦 85 · 📋 52 - 34% open · ⏱️ 29.05.2022): @@ -9663,7 +9663,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install advertorch ```
-
robustness (🥉17 · ⭐ 720) - A library for experimenting with, training and evaluating neural.. MIT +
robustness (🥉17 · ⭐ 720) - 一个用于实验，训练和评估神经网络的库。MIT - [GitHub](https://github.com/MadryLab/robustness) (👨‍💻 13 · 🔀 140 · 📦 81 · 📋 75 - 25% open · ⏱️ 14.02.2022): @@ -9675,7 +9675,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install robustness ```
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AdvBox (🥉15 · ⭐ 1.2K) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 +
AdvBox (🥉15 · ⭐ 1.2K) - Advbox是一个工具箱，用于生成对抗示例。Apache-2 - [GitHub](https://github.com/advboxes/AdvBox) (👨‍💻 19 · 🔀 240 · 📋 38 - 21% open · ⏱️ 08.08.2022): @@ -9689,13 +9689,13 @@ _Libraries for testing the robustness of machine learning models against attacks

-## GPU Utilities +## GPU实用程序 -Back to top +Back to top -_Libraries that require and make use of CUDA/GPU system capabilities to optimize data handling and machine learning tasks._ +_需要并利用CUDA / GPU系统功能来优化数据处理和机器学习任务的库。_ -
CuPy (🥇32 · ⭐ 6.3K) - A NumPy-compatible array library accelerated by CUDA. MIT +
CuPy (🥇32 · ⭐ 6.3K) - CUDA加速了与NumPy兼容的数组库。MIT - [GitHub](https://github.com/cupy/cupy) (👨‍💻 310 · 🔀 590 · 📥 42K · 📦 1.2K · 📋 1.8K - 21% open · ⏱️ 23.08.2022): @@ -9715,7 +9715,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize docker pull cupy/cupy ```
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gpustat (🥇28 · ⭐ 3K) - A simple command-line utility for querying and monitoring GPU status. MIT +
gpustat (🥇28 · ⭐ 3K) - 一个简单的命令行实用程序，用于查询和监控GPU状态。MIT - [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 14 · 🔀 220 · 📦 2.1K · 📋 86 - 22% open · ⏱️ 09.08.2022): @@ -9731,7 +9731,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c conda-forge gpustat ```
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ArrayFire (🥈25 · ⭐ 3.9K) - ArrayFire: a general purpose GPU library. BSD-3 +
ArrayFire (🥈25 · ⭐ 3.9K) - ArrayFire：通用GPU库。BSD-3 - [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 81 · 🔀 490 · 📥 2.7K · 📋 1.5K - 16% open · ⏱️ 09.07.2022): @@ -9743,7 +9743,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install arrayfire ```
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GPUtil (🥈25 · ⭐ 900 · 💀) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT +
GPUtil (🥈25 · ⭐ 900 · 💀) - 一个Python模块，用于从NVIDA GPU获取GPU状态。MIT - [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 98 · 📦 2.3K · 📋 26 - 46% open · ⏱️ 16.08.2019): @@ -9755,7 +9755,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install gputil ```
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Apex (🥈24 · ⭐ 6.6K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 +
Apex (🥈24 · ⭐ 6.6K) - PyTorch扩展：易于实现混合精度和分布式的工具。BSD-3 - [GitHub](https://github.com/NVIDIA/apex) (👨‍💻 100 · 🔀 1K · 📦 1.2K · 📋 1K - 53% open · ⏱️ 25.08.2022): @@ -9767,7 +9767,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c conda-forge nvidia-apex ```
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py3nvml (🥈23 · ⭐ 210) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 +
py3nvml (🥈23 · ⭐ 210) - NVML库的Python3接口。在内部获取NVIDIA GPU状态。BSD-3 - [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 9 · 🔀 30 · 📦 510 · 📋 13 - 7% open · ⏱️ 14.04.2022): @@ -9783,7 +9783,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c conda-forge py3nvml ```
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PyCUDA (🥈22 · ⭐ 1.4K) - CUDA integration for Python, plus shiny features. ❗Unlicensed +
PyCUDA (🥈22 · ⭐ 1.4K) - 适用于Python的CUDA集成，有着出色的功能。❗Unlicensed - [GitHub](https://github.com/inducer/pycuda) (👨‍💻 76 · 🔀 250 · 📦 1.5K · 📋 220 - 27% open · ⏱️ 16.08.2022): @@ -9795,7 +9795,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install pycuda ```
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cuDF (🥉20 · ⭐ 4.9K) - cuDF - GPU DataFrame Library. Apache-2 +
cuDF (🥉20 · ⭐ 4.9K) - cuDF-GPU DataFrame库。Apache-2 - [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 250 · 🔀 630 · 📋 4.8K - 12% open · ⏱️ 26.08.2022): @@ -9807,7 +9807,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cudf ```
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scikit-cuda (🥉20 · ⭐ 910) - Python interface to GPU-powered libraries. ❗Unlicensed +
scikit-cuda (🥉20 · ⭐ 910) - GPU工具库的python接口。❗Unlicensed - [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 46 · 🔀 170 · 📦 200 · 📋 220 - 22% open · ⏱️ 31.03.2022): @@ -9819,7 +9819,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install scikit-cuda ```
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cuML (🥉19 · ⭐ 2.9K) - cuML - RAPIDS Machine Learning Library. Apache-2 +
cuML (🥉19 · ⭐ 2.9K) - cuML-RAPIDS机器学习库。Apache-2 - [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 160 · 🔀 420 · 📋 2.1K - 32% open · ⏱️ 25.08.2022): @@ -9831,7 +9831,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cuml ```
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Vulkan Kompute (🥉18 · ⭐ 920) - General purpose GPU compute framework for cross vendor.. Apache-2 +
Vulkan Kompute (🥉18 · ⭐ 920) - 适用于跨供应商的通用GPU计算框架。Apache-2 - [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 19 · 🔀 64 · 📥 170 · 📦 4 · 📋 180 - 32% open · ⏱️ 21.06.2022): @@ -9843,7 +9843,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install kp ```
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DALI (🥉17 · ⭐ 4K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 +
DALI (🥉17 · ⭐ 4K) - GPU加速的库，其中包含高度优化的构建块。Apache-2 - [GitHub](https://github.com/NVIDIA/DALI) (👨‍💻 77 · 🔀 500 · 📋 1.2K - 15% open · ⏱️ 25.08.2022): @@ -9851,7 +9851,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize git clone https://github.com/NVIDIA/DALI ```
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nvidia-ml-py3 (🥉17 · ⭐ 86 · 💀) - Python 3 Bindings for the NVIDIA Management Library. ❗Unlicensed +
nvidia-ml-py3 (🥉17 · ⭐ 86 · 💀) - NVIDIA Management Library的Python3接口。❗Unlicensed - [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 18 · 📦 6.2K · ⏱️ 06.03.2019): @@ -9863,7 +9863,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install nvidia-ml-py3 ```
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cuGraph (🥉16 · ⭐ 1.1K) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 +
cuGraph (🥉16 · ⭐ 1.1K) - cuGraph-RAPIDS图形分析库。Apache-2 - [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 90 · 🔀 210 · 📋 990 - 20% open · ⏱️ 25.08.2022): @@ -9875,7 +9875,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cugraph ```
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BlazingSQL (🥉15 · ⭐ 1.8K · 💤) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 +
BlazingSQL (🥉15 · ⭐ 1.8K · 💤) - BlazingSQL是一种用于GPU的轻量级，GPU加速的引擎。Apache-2 - [GitHub](https://github.com/BlazingDB/blazingsql) (👨‍💻 49 · 🔀 170 · 📋 710 - 17% open · ⏱️ 30.09.2021): @@ -9887,7 +9887,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c blazingsql blazingsql-protocol ```
-
SpeedTorch (🥉14 · ⭐ 660 · 💀) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT +
SpeedTorch (🥉14 · ⭐ 660 · 💀) - 用于更快的Pytorch中CPU-GPU传输的工具库。MIT - [GitHub](https://github.com/Santosh-Gupta/SpeedTorch) (👨‍💻 3 · 🔀 39 · 📦 4 · 📋 6 - 66% open · ⏱️ 21.02.2020): @@ -9899,7 +9899,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install SpeedTorch ```
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cuSignal (🥉14 · ⭐ 610) - GPU accelerated signal processing. Apache-2 +
cuSignal (🥉14 · ⭐ 610) - GPU加速信号处理。Apache-2 - [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 39 · 🔀 96 · 📋 140 - 11% open · ⏱️ 10.08.2022): @@ -9907,7 +9907,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize git clone https://github.com/rapidsai/cusignal ```
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ipyexperiments (🥉11 · ⭐ 150 · 💤) - jupyter/ipython experiment containers for GPU and.. ❗Unlicensed +
ipyexperiments (🥉11 · ⭐ 150 · 💤) - jupyter/ipython实验容器。❗Unlicensed - [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 11 · 📦 6 · ⏱️ 07.12.2021): @@ -9921,13 +9921,13 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize

-## Tensorflow Utilities +## Tensorflow实用程序 -Back to top +Back to top -_Libraries that extend TensorFlow with additional capabilities._ +_TensorFlow的拓展工具库。_ -
TF Addons (🥇33 · ⭐ 1.6K) - Useful extra functionality for TensorFlow 2.x maintained by.. Apache-2 +
TF Addons (🥇33 · ⭐ 1.6K) - 由TensorFlow 2.x维护的有用额外功能。Apache-2 - [GitHub](https://github.com/tensorflow/addons) (👨‍💻 200 · 🔀 530 · 📦 7.2K · 📋 920 - 21% open · ⏱️ 24.08.2022): @@ -9939,7 +9939,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-addons ```
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tensor2tensor (🥇31 · ⭐ 13K) - Library of deep learning models and datasets designed to.. Apache-2 +
tensor2tensor (🥇31 · ⭐ 13K) - 设计深度学习模型和数据集的库。Apache-2 - [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 3K · 📦 1.2K · 📋 1.2K - 45% open · ⏱️ 09.08.2022): @@ -9951,7 +9951,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensor2tensor ```
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tensorflow-hub (🥇31 · ⭐ 3.2K) - A library for transfer learning by reusing parts of.. Apache-2 +
tensorflow-hub (🥇31 · ⭐ 3.2K) - 通过重用部分库来进行迁移学习的库。Apache-2 - [GitHub](https://github.com/tensorflow/hub) (👨‍💻 94 · 🔀 1.6K · 📦 13K · 📋 650 - 2% open · ⏱️ 23.08.2022): @@ -9967,7 +9967,7 @@ _Libraries that extend TensorFlow with additional capabilities._ conda install -c conda-forge tensorflow-hub ```
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TensorFlow Transform (🥈30 · ⭐ 930 · 📈) - Input pipeline framework. Apache-2 +
TensorFlow Transform (🥈30 · ⭐ 930 · 📈) - 输入管道框架。Apache-2 - [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 190 · 📦 1K · 📋 190 - 17% open · ⏱️ 25.08.2022): @@ -9979,7 +9979,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-transform ```
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TF Model Optimization (🥈29 · ⭐ 1.3K) - A toolkit to optimize ML models for deployment for.. Apache-2 +
TF Model Optimization (🥈29 · ⭐ 1.3K) - 用于优化ML模型以进行部署的工具包。Apache-2 - [GitHub](https://github.com/tensorflow/model-optimization) (👨‍💻 71 · 🔀 280 · 📦 2K · 📋 300 - 48% open · ⏱️ 23.08.2022): @@ -9991,7 +9991,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-model-optimization ```
-
Neural Structured Learning (🥉26 · ⭐ 930) - Training neural models with structured signals. Apache-2 +
Neural Structured Learning (🥉26 · ⭐ 930) - 用结构化信号训练神经模型。Apache-2 - [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 34 · 🔀 170 · 📦 260 · 📋 65 - 3% open · ⏱️ 19.08.2022): @@ -10015,7 +10015,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-io ```
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efficientnet (🥉24 · ⭐ 2K · 💀) - Implementation of EfficientNet model. Keras and.. Apache-2 +
efficientnet (🥉24 · ⭐ 2K · 💀) - EfficientNet模型的实现。Apache-2 - [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 450 · 📥 240K · 📦 1.1K · 📋 110 - 48% open · ⏱️ 16.07.2021): @@ -10027,7 +10027,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install efficientnet ```
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TensorFlow Cloud (🥉23 · ⭐ 330) - The TensorFlow Cloud repository provides APIs that.. Apache-2 +
TensorFlow Cloud (🥉23 · ⭐ 330) - TensorFlow Cloud存储库提供的API。Apache-2 - [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 27 · 🔀 71 · 📦 170 · 📋 82 - 68% open · ⏱️ 24.03.2022): @@ -10039,7 +10039,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-cloud ```
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TensorNets (🥉20 · ⭐ 1K · 💀) - High level network definitions with pre-trained weights in.. MIT +
TensorNets (🥉20 · ⭐ 1K · 💀) - 具有预先训练的权重的高级网络定义。MIT - [GitHub](https://github.com/taehoonlee/tensornets) (👨‍💻 6 · 🔀 180 · 📦 52 · 📋 58 - 27% open · ⏱️ 02.01.2021): @@ -10051,7 +10051,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensornets ```
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TF Compression (🥉19 · ⭐ 640) - Data compression in TensorFlow. Apache-2 +
TF Compression (🥉19 · ⭐ 640) - TensorFlow中的数据压缩。Apache-2 - [GitHub](https://github.com/tensorflow/compression) (👨‍💻 16 · 🔀 210 · 📋 87 - 2% open · ⏱️ 25.08.2022): @@ -10063,7 +10063,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-compression ```
-
Saliency (🥉17 · ⭐ 810) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 +
Saliency (🥉17 · ⭐ 810) - 与框架无关的实现，可实现最新的显着性。Apache-2 - [GitHub](https://github.com/PAIR-code/saliency) (👨‍💻 15 · 🔀 170 · 📦 41 · ⏱️ 13.05.2022): @@ -10075,7 +10075,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install saliency ```
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tffm (🥉17 · ⭐ 780 · 💤) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT +
tffm (🥉17 · ⭐ 780 · 💤) - 任意阶乘分解机的TensorFlow实现。MIT - [GitHub](https://github.com/geffy/tffm) (👨‍💻 10 · 🔀 180 · 📦 11 · 📋 40 - 45% open · ⏱️ 17.01.2022): @@ -10089,13 +10089,13 @@ _Libraries that extend TensorFlow with additional capabilities._

-## Sklearn Utilities +## Sklearn实用程序 -Back to top +Back to top -_Libraries that extend scikit-learn with additional capabilities._ +_scikit-learn的拓展工具库。_ -
imbalanced-learn (🥇32 · ⭐ 6K) - A Python Package to Tackle the Curse of Imbalanced.. MIT +
imbalanced-learn (🥇32 · ⭐ 6K) - 一个解决不平衡类别数据建模的Python程序包。MIT - [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (👨‍💻 63 · 🔀 1.1K · 📦 12K · 📋 510 - 8% open · ⏱️ 16.05.2022): @@ -10111,7 +10111,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge imbalanced-learn ```
-
MLxtend (🥇30 · ⭐ 4.1K) - A library of extension and helper modules for Python's data.. ❗Unlicensed +
MLxtend (🥇30 · ⭐ 4.1K) - 用于Python数据的扩展和帮助程序模块库。❗Unlicensed - [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 90 · 🔀 760 · 📦 6.6K · 📋 420 - 25% open · ⏱️ 10.08.2022): @@ -10143,7 +10143,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge category_encoders ```
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fancyimpute (🥈25 · ⭐ 1.1K · 💤) - Multivariate imputation and matrix completion.. Apache-2 +
fancyimpute (🥈25 · ⭐ 1.1K · 💤) - 多元插补和矩阵补全算法。Apache-2 - [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 12 · 🔀 160 · 📦 1.2K · 📋 110 - 1% open · ⏱️ 21.10.2021): @@ -10155,7 +10155,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install fancyimpute ```
-
scikit-multilearn (🥈24 · ⭐ 770) - A scikit-learn based module for multi-label et. al... BSD-2 +
scikit-multilearn (🥈24 · ⭐ 770) - 基于scikit-learn的多标签等模块。BSD-2 - [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 17 · 🔀 140 · 📦 820 · 📋 180 - 46% open · ⏱️ 09.07.2022): @@ -10167,7 +10167,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-multilearn ```
-
scikit-opt (🥈23 · ⭐ 3.5K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT +
scikit-opt (🥈23 · ⭐ 3.5K) - 遗传算法，粒子群优化等实现。MIT - [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 16 · 🔀 800 · 📦 83 · 📋 150 - 30% open · ⏱️ 15.07.2022): @@ -10179,7 +10179,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-opt ```
-
scikit-lego (🥈22 · ⭐ 880) - Extra blocks for scikit-learn pipelines. MIT +
scikit-lego (🥈22 · ⭐ 880) - scikit学习管道的额外块。MIT - [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 52 · 🔀 90 · 📦 59 · 📋 240 - 9% open · ⏱️ 18.08.2022): @@ -10195,7 +10195,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge scikit-lego ```
-
iterative-stratification (🥈22 · ⭐ 710) - scikit-learn cross validators for iterative.. BSD-3 +
iterative-stratification (🥈22 · ⭐ 710) - scikit-learn交叉验证器。BSD-3 - [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 7 · 🔀 64 · 📦 220 · 📋 20 - 5% open · ⏱️ 06.06.2022): @@ -10207,7 +10207,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install iterative-stratification ```
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sklearn-crfsuite (🥈22 · ⭐ 410 · 💀) - scikit-learn inspired API for CRFsuite. ❗Unlicensed +
sklearn-crfsuite (🥈22 · ⭐ 410 · 💀) - 用于CRFsuite的scikit-learn启发式API。❗Unlicensed - [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 190 · 📦 4K · 📋 56 - 58% open · ⏱️ 05.12.2019): @@ -10219,7 +10219,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install sklearn-crfsuite ```
-
combo (🥉20 · ⭐ 590) - (AAAI' 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost +
combo (🥉20 · ⭐ 590) - （AAAI'20）用于机器学习模型的Python工具箱。BSD-2 xgboost - [GitHub](https://github.com/yzhao062/combo) (👨‍💻 2 · 🔀 100 · 📦 480 · 📋 13 - 76% open · ⏱️ 07.07.2022): @@ -10231,7 +10231,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install combo ```
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skope-rules (🥉20 · ⭐ 480 · 💀) - machine learning with logical rules in Python. ❗Unlicensed +
skope-rules (🥉20 · ⭐ 480 · 💀) - 使用Python中的逻辑规则进行机器学习。❗Unlicensed - [GitHub](https://github.com/scikit-learn-contrib/skope-rules) (👨‍💻 18 · 🔀 79 · 📦 130 · 📋 31 - 80% open · ⏱️ 23.10.2020): @@ -10243,7 +10243,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install skope-rules ```
-
sklearn-contrib-lightning (🥉19 · ⭐ 1.6K · 💤) - Large-scale linear classification, regression and.. ❗Unlicensed +
sklearn-contrib-lightning (🥉19 · ⭐ 1.6K · 💤) - 大规模线性分类，回归分析等。❗Unlicensed - [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 180 · 📥 230 · 📦 100 · 📋 88 - 52% open · ⏱️ 30.01.2022): @@ -10259,7 +10259,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge sklearn-contrib-lightning ```
-
DESlib (🥉17 · ⭐ 420) - A Python library for dynamic classifier and ensemble selection. BSD-3 +
DESlib (🥉17 · ⭐ 420) - 一个用于动态分类器和集成选择的Python库。BSD-3 - [GitHub](https://github.com/scikit-learn-contrib/DESlib) (👨‍💻 14 · 🔀 63 · 📦 29 · 📋 150 - 10% open · ⏱️ 07.06.2022): @@ -10271,7 +10271,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install deslib ```
-
celer (🥉17 · ⭐ 160) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 +
celer (🥉17 · ⭐ 160) - L1型问题的快速求解器：Lasso，稀疏Logisitic回归等BSD-3 - [GitHub](https://github.com/mathurinm/celer) (👨‍💻 11 · 🔀 25 · 📦 13 · 📋 90 - 20% open · ⏱️ 23.08.2022): @@ -10283,7 +10283,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install celer ```
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scikit-tda (🥉16 · ⭐ 360) - Topological Data Analysis for Python. ❗Unlicensed +
scikit-tda (🥉16 · ⭐ 360) - Python的拓扑数据分析。❗Unlicensed - [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 4 · 🔀 44 · 📦 33 · 📋 19 - 78% open · ⏱️ 13.03.2022): @@ -10295,7 +10295,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-tda ```
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skggm (🥉16 · ⭐ 210) - Scikit-learn compatible estimation of general graphical models. MIT +
skggm (🥉16 · ⭐ 210) - 通用图形模型的Scikit学习兼容估计。MIT - [GitHub](https://github.com/skggm/skggm) (👨‍💻 6 · 🔀 36 · 📦 8 · 📋 75 - 37% open · ⏱️ 11.03.2022): @@ -10307,7 +10307,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install skggm ```
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dabl (🥉13 · ⭐ 120 · 💀) - Data Analysis Baseline Library. BSD-3 +
dabl (🥉13 · ⭐ 120 · 💀) - 数据分析基准库。BSD-3 - [GitHub](https://github.com/amueller/dabl) (👨‍💻 21 · 🔀 10 · ⏱️ 09.07.2021): @@ -10321,13 +10321,13 @@ _Libraries that extend scikit-learn with additional capabilities._

-## Pytorch Utilities +## Pytorch实用程序 -Back to top +Back to top -_Libraries that extend Pytorch with additional capabilities._ +_Pytorch的拓展工具库。_ -
PML (🥇28 · ⭐ 4.7K) - The easiest way to use deep metric learning in your application. Modular,.. MIT +
PML (🥇28 · ⭐ 4.7K) - 在应用程序中使用深度度量学习的最简单方法。MIT - [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 27 · 🔀 560 · 📦 320 · 📋 380 - 13% open · ⏱️ 13.08.2022): @@ -10343,7 +10343,7 @@ _Libraries that extend Pytorch with additional capabilities._ conda install -c metric-learning pytorch-metric-learning ```
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pretrainedmodels (🥇27 · ⭐ 8.6K · 💀) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 +
pretrainedmodels (🥇27 · ⭐ 8.6K · 💀) - pytorch预训练的ConvNets：NASNet，ResNeXt等BSD-3 - [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.8K · 📦 1.8K · 📋 180 - 46% open · ⏱️ 16.04.2020): @@ -10355,7 +10355,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pretrainedmodels ```
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pytorch-optimizer (🥇26 · ⭐ 2.5K · 💤) - torch-optimizer -- collection of optimizers for.. Apache-2 +
pytorch-optimizer (🥇26 · ⭐ 2.5K · 💤) - torch-optimizer - pytorch的优化器集合。Apache-2 - [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 25 · 🔀 240 · 📦 670 · 📋 50 - 42% open · ⏱️ 11.11.2021): @@ -10367,7 +10367,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch_optimizer ```
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pytorch-summary (🥈25 · ⭐ 3.6K · 💀) - Model summary in PyTorch similar to `model.summary()`.. MIT +
pytorch-summary (🥈25 · ⭐ 3.6K · 💀) - PyTorch中的模型摘要类似于`model.summary（）`。MIT - [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 400 · 📦 5.7K · 📋 140 - 69% open · ⏱️ 10.05.2021): @@ -10379,7 +10379,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchsummary ```
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torchdiffeq (🥈24 · ⭐ 4.2K) - Differentiable ODE solvers with full GPU support and.. MIT +
torchdiffeq (🥈24 · ⭐ 4.2K) - 具有完整GPU支持的可微分ODE求解器。MIT - [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 21 · 🔀 720 · 📦 300 · 📋 180 - 21% open · ⏱️ 10.08.2022): @@ -10391,7 +10391,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchdiffeq ```
-
SRU (🥈22 · ⭐ 2.1K · 💀) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT +
SRU (🥈22 · ⭐ 2.1K · 💀) - 与CNN一样快地训练RNN（https://arxiv.org/abs/1709.02755）。MIT - [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 300 · 📦 18 · 📋 130 - 46% open · ⏱️ 19.05.2021): @@ -10403,7 +10403,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install sru ```
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EfficientNet-PyTorch (🥈21 · ⭐ 7.1K · 💀) - A PyTorch implementation of EfficientNet and.. Apache-2 +
EfficientNet-PyTorch (🥈21 · ⭐ 7.1K · 💀) - EfficientNet等模型的PyTorch实现Apache-2 - [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.4K · 📥 1.9M · 📋 280 - 50% open · ⏱️ 15.04.2021): @@ -10415,7 +10415,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install efficientnet-pytorch ```
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TabNet (🥈21 · ⭐ 1.8K) - PyTorch implementation of TabNet paper :.. MIT +
TabNet (🥈21 · ⭐ 1.8K) - Efficient Neural Architecture Search的Pytorch实现。MIT - [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 19 · 🔀 370 · 📋 230 - 7% open · ⏱️ 27.06.2022): @@ -10427,7 +10427,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pytorch-tabnet ```
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EfficientNets (🥈21 · ⭐ 1.5K · 💀) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 +
EfficientNets (🥈21 · ⭐ 1.5K · 💀) - 预训练的EfficientNet，EfficientNet-Lite，MixNet等Apache-2 - [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 200 · 📦 120 · 📋 54 - 5% open · ⏱️ 08.07.2021): @@ -10439,7 +10439,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install geffnet ```
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Pytorch Toolbelt (🥈21 · ⭐ 1.3K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT +
Pytorch Toolbelt (🥈21 · ⭐ 1.3K) - PyTorch扩展用于快速研发原型和Kaggle实验。MIT - [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 7 · 🔀 100 · 📋 24 - 8% open · ⏱️ 20.08.2022): @@ -10451,7 +10451,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pytorch_toolbelt ```
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PyTorch Sparse (🥈21 · ⭐ 710) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT +
PyTorch Sparse (🥈21 · ⭐ 710) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 32 · 🔀 100 · 📋 200 - 13% open · ⏱️ 22.08.2022): @@ -10463,7 +10463,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch-sparse ```
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reformer-pytorch (🥉20 · ⭐ 1.8K) - Reformer, the efficient Transformer, in Pytorch. MIT +
reformer-pytorch (🥉20 · ⭐ 1.8K) - Reformer，Pytorch中高效的transformer实现。MIT - [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 11 · 🔀 240 · 📋 120 - 11% open · ⏱️ 24.06.2022): @@ -10475,7 +10475,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install reformer-pytorch ```
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Torchmeta (🥉20 · ⭐ 1.7K · 💤) - A collection of extensions and data-loaders for few-shot.. MIT +
Torchmeta (🥉20 · ⭐ 1.7K · 💤) - 少量学习的扩展程序和数据加载器的集合。MIT - [GitHub](https://github.com/tristandeleu/pytorch-meta) (👨‍💻 12 · 🔀 220 · 📦 97 · 📋 130 - 32% open · ⏱️ 20.09.2021): @@ -10487,7 +10487,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchmeta ```
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torch-scatter (🥉20 · ⭐ 1.1K) - PyTorch Extension Library of Optimized Scatter Operations. MIT +
torch-scatter (🥉20 · ⭐ 1.1K) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 22 · 🔀 120 · 📋 270 - 6% open · ⏱️ 18.08.2022): @@ -10499,7 +10499,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch-scatter ```
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Performer Pytorch (🥉20 · ⭐ 860) - An implementation of Performer, a linear attention-.. MIT +
Performer Pytorch (🥉20 · ⭐ 860) - Performer的实现。MIT - [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 6 · 🔀 120 · 📦 49 · 📋 78 - 44% open · ⏱️ 02.02.2022): @@ -10511,7 +10511,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install performer-pytorch ```
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Poutyne (🥉20 · ⭐ 530) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 +
Poutyne (🥉20 · ⭐ 530) - PyTorch的简化框架和实用程序。❗️LGPL-3.0 - [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 18 · 🔀 62 · 📦 91 · 📋 53 - 15% open · ⏱️ 16.07.2022): @@ -10523,7 +10523,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install poutyne ```
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AdaBound (🥉19 · ⭐ 2.9K · 💀) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 +
AdaBound (🥉19 · ⭐ 2.9K · 💀) - 训练速度与Adam一样快且与SGD一样好的优化器。Apache-2 - [GitHub](https://github.com/Luolc/AdaBound) (👨‍💻 2 · 🔀 320 · 📦 140 · 📋 25 - 72% open · ⏱️ 06.03.2019): @@ -10535,7 +10535,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install adabound ```
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Antialiased CNNs (🥉19 · ⭐ 1.6K · 💤) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 +
Antialiased CNNs (🥉19 · ⭐ 1.6K · 💤) - pip安装antialiased-cnns以提高稳定性等。❗️CC BY-NC-SA 4.0 - [GitHub](https://github.com/adobe/antialiased-cnns) (👨‍💻 6 · 🔀 200 · 📦 29 · 📋 44 - 29% open · ⏱️ 29.09.2021): @@ -10547,7 +10547,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install antialiased-cnns ```
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Higher (🥉19 · ⭐ 1.4K · 💤) - higher is a pytorch library allowing users to obtain higher.. Apache-2 +
Higher (🥉19 · ⭐ 1.4K · 💤) - Higher是一个pytorch库，允许用户在跨训练循环而不是单个训练步骤的损失上获得更高阶的梯度。Apache-2 - [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 100 · 📦 160 · 📋 100 - 50% open · ⏱️ 26.10.2021): @@ -10567,7 +10567,7 @@ _Libraries that extend Pytorch with additional capabilities._ git clone https://github.com/geohot/tinygrad ```
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Tensor Sensor (🥉17 · ⭐ 650) - The goal of this library is to generate more helpful.. MIT +
Tensor Sensor (🥉17 · ⭐ 650) - 该库的目标是为numpy/pytorch矩阵代数表达式生成更有用的异常消息。MIT - [GitHub](https://github.com/parrt/tensor-sensor) (👨‍💻 4 · 🔀 34 · 📦 7 · 📋 23 - 34% open · ⏱️ 07.04.2022): @@ -10579,7 +10579,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install tensor-sensor ```
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micrograd (🥉16 · ⭐ 2.4K · 💀) - A tiny scalar-valued autograd engine and a neural net library.. MIT +
micrograd (🥉16 · ⭐ 2.4K · 💀) - 一个微型的标量值autograd引擎和一个神经网络库。MIT - [GitHub](https://github.com/karpathy/micrograd) (👨‍💻 2 · 🔀 210 · 📦 7 · 📋 5 - 40% open · ⏱️ 18.04.2020): @@ -10591,7 +10591,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install micrograd ```
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Lambda Networks (🥉16 · ⭐ 1.5K · 💀) - Implementation of LambdaNetworks, a new approach to.. MIT +
Lambda Networks (🥉16 · ⭐ 1.5K · 💀) - LambdaNetworks的实现。MIT - [GitHub](https://github.com/lucidrains/lambda-networks) (👨‍💻 3 · 🔀 160 · 📦 6 · 📋 28 - 46% open · ⏱️ 18.11.2020): @@ -10603,7 +10603,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install lambda-networks ```
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Tez (🥉16 · ⭐ 1.1K) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 +
Tez (🥉16 · ⭐ 1.1K) - Tez是用于PyTorch的超级简单且轻巧的Trainer。Apache-2 - [GitHub](https://github.com/abhishekkrthakur/tez) (👨‍💻 2 · 🔀 140 · 📦 33 · 📋 37 - 54% open · ⏱️ 10.08.2022): @@ -10615,7 +10615,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install tez ```
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torchsde (🥉16 · ⭐ 1K · 💀) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +
torchsde (🥉16 · ⭐ 1K · 💀) - 具有GPU支持且高效的可微分SDE求解器。Apache-2 - [GitHub](https://github.com/google-research/torchsde) (👨‍💻 5 · 🔀 110 · 📦 19 · 📋 50 - 18% open · ⏱️ 26.07.2021): @@ -10623,7 +10623,7 @@ _Libraries that extend Pytorch with additional capabilities._ git clone https://github.com/google-research/torchsde ```
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Pywick (🥉14 · ⭐ 370 · 💤) - High-level batteries-included neural network training.. ❗Unlicensed +
Pywick (🥉14 · ⭐ 370 · 💤) - 更高层次的pytorch神经网络训练库。❗Unlicensed - [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 39 · 📦 7 · 📋 14 - 7% open · ⏱️ 22.10.2021): @@ -10635,7 +10635,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pywick ```
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Torch-Struct (🥉13 · ⭐ 1K · 💤) - Fast, general, and tested differentiable structured.. MIT +
Torch-Struct (🥉13 · ⭐ 1K · 💤) - 快速，通用和经过测试的微分结构化预测。MIT - [GitHub](https://github.com/harvardnlp/pytorch-struct) (👨‍💻 16 · 🔀 83 · 📋 54 - 44% open · ⏱️ 30.01.2022): @@ -10645,19 +10645,19 @@ _Libraries that extend Pytorch with additional capabilities._

-## Database Clients +## 数据库客户端 -Back to top +Back to top -_Libraries for connecting to, operating, and querying databases._ +_用于连接，操作和查询数据库的库。_ 🔗 Python DB Clients ( ⭐ 7 · 💤) - Collection of database clients for python.
-## Chinese NLP +## 中文自然语言处理 -Back to top +Back to top
jieba (🥇32 · ⭐ 29K · 💀) - Chinese Words Segementation Utilities. MIT @@ -10691,9 +10691,9 @@ _Libraries for connecting to, operating, and querying databases._ ## Others -Back to top +Back to top -
scipy (🥇38 · ⭐ 10K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 +
scipy (🥇38 · ⭐ 10K) - 用于数学，科学和工程的开源软件生态系统。BSD-3 - [GitHub](https://github.com/scipy/scipy) (👨‍💻 1.3K · 🔀 4.3K · 📥 350K · 📦 560K · 📋 8.4K - 16% open · ⏱️ 25.08.2022): @@ -10709,7 +10709,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge scipy ```
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SymPy (🥇35 · ⭐ 9.5K) - A computer algebra system written in pure Python. ❗Unlicensed +
SymPy (🥇35 · ⭐ 9.5K) - 用纯Python编写的计算机代数系统。❗Unlicensed - [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.2K · 🔀 3.6K · 📥 460K · 📦 45K · 📋 12K - 32% open · ⏱️ 26.08.2022): @@ -10725,7 +10725,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge sympy ```
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PyOD (🥇31 · ⭐ 6.1K) - (JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 +
PyOD (🥇31 · ⭐ 6.1K) - （JMLR'19）用于可扩展离群值检测的Python工具箱。BSD-2 - [GitHub](https://github.com/yzhao062/pyod) (👨‍💻 41 · 🔀 1.1K · 📦 1.5K · 📋 260 - 47% open · ⏱️ 29.07.2022): @@ -10737,7 +10737,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install pyod ```
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Streamlit (🥇30 · ⭐ 20K · 📈) - Streamlit The fastest way to build data apps in Python. Apache-2 +
Streamlit (🥇30 · ⭐ 20K · 📈) - Streamlit用Python构建数据应用程序的最快方法。Apache-2 - [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 150 · 🔀 1.8K · 📦 380 · 📋 2.6K - 23% open · ⏱️ 25.08.2022): @@ -10749,7 +10749,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install streamlit ```
-
Gradio (🥇30 · ⭐ 8.5K) - Wrap UIs around any model, share with anyone. Apache-2 +
Gradio (🥇30 · ⭐ 8.5K) - 对任何模型做UI封装并与他人共享。Apache-2 - [GitHub](https://github.com/gradio-app/gradio) (👨‍💻 92 · 🔀 530 · 📦 1.1K · 📋 1K - 18% open · ⏱️ 25.08.2022): @@ -10761,7 +10761,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install gradio ```
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Autograd (🥈29 · ⭐ 5.9K) - Efficiently computes derivatives of numpy code. MIT +
Autograd (🥈29 · ⭐ 5.9K) - 高效地计算导数的numpy代码。MIT - [GitHub](https://github.com/HIPS/autograd) (👨‍💻 52 · 🔀 800 · 📦 3.8K · 📋 370 - 39% open · ⏱️ 15.06.2022): @@ -10777,7 +10777,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge autograd ```
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Datasette (🥈28 · ⭐ 6.4K) - An open source multi-tool for exploring and publishing data. Apache-2 +
Datasette (🥈28 · ⭐ 6.4K) - 用于探索和发布数据的开源多功能工具。Apache-2 - [GitHub](https://github.com/simonw/datasette) (👨‍💻 67 · 🔀 410 · 📥 39 · 📦 730 · 📋 1.4K - 27% open · ⏱️ 24.08.2022): @@ -10789,7 +10789,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install datasette ```
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DeepChem (🥈28 · ⭐ 3.8K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT +
DeepChem (🥈28 · ⭐ 3.8K) - 在药物发现，量子化学，材料科学和生物学方面普及深度学习。MIT - [GitHub](https://github.com/deepchem/deepchem) (👨‍💻 200 · 🔀 1.3K · 📦 120 · 📋 1.4K - 29% open · ⏱️ 26.08.2022): @@ -10801,7 +10801,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install deepchem ```
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hdbscan (🥈28 · ⭐ 2.2K) - A high performance implementation of HDBSCAN clustering. BSD-3 +
hdbscan (🥈28 · ⭐ 2.2K) - HDBSCAN群集的高性能实现。BSD-3 - [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 80 · 🔀 390 · 📦 1.5K · 📋 440 - 63% open · ⏱️ 23.08.2022): @@ -10817,7 +10817,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge hdbscan ```
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agate (🥈28 · ⭐ 1.1K · 💀) - A Python data analysis library that is optimized for humans instead of.. MIT +
agate (🥈28 · ⭐ 1.1K · 💀) - 为人而不是为机器优化的Python数据分析库。MIT - [GitHub](https://github.com/wireservice/agate) (👨‍💻 49 · 🔀 140 · 📦 1.1K · 📋 640 - 1% open · ⏱️ 15.07.2021): @@ -10833,7 +10833,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge agate ```
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Cython BLIS (🥈28 · ⭐ 190) - Fast matrix-multiplication as a self-contained Python.. ❗Unlicensed +
Cython BLIS (🥈28 · ⭐ 190) - 快速矩阵乘法库。❗Unlicensed - [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 12 · 🔀 34 · 📦 20K · 📋 28 - 17% open · ⏱️ 04.08.2022): @@ -10849,7 +10849,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge cython-blis ```
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PaddleHub (🥈27 · ⭐ 8.3K) - Awesome pre-trained models toolkit based on.. Apache-2 +
PaddleHub (🥈27 · ⭐ 8.3K) - 基于PaddlePaddle的出色的预训练模型工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 62 · 🔀 1.7K · 📥 580 · 📦 890 · 📋 1.1K - 41% open · ⏱️ 19.08.2022): @@ -10861,7 +10861,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install paddlehub ```
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carla (🥈27 · ⭐ 8.2K · 💤) - Open-source simulator for autonomous driving research. ❗Unlicensed +
carla (🥈27 · ⭐ 8.2K · 💤) - 用于自动驾驶研究的开源模拟器。❗Unlicensed - [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 140 · 🔀 2.4K · 📦 230 · 📋 4K - 16% open · ⏱️ 19.11.2021): @@ -10873,7 +10873,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install carla ```
-
Pythran (🥈27 · ⭐ 1.8K) - Ahead of Time compiler for numeric kernels. BSD-3 +
Pythran (🥈27 · ⭐ 1.8K) - 用于数字内核的时间编译器。BSD-3 - [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 66 · 🔀 170 · 📦 220 · 📋 760 - 14% open · ⏱️ 19.07.2022): @@ -10889,7 +10889,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pythran ```
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pyjanitor (🥈27 · ⭐ 960) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT +
pyjanitor (🥈27 · ⭐ 960) - 用于数据清理的API。MIT - [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 100 · 🔀 150 · 📦 220 · 📋 490 - 20% open · ⏱️ 24.08.2022): @@ -10905,7 +10905,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyjanitor ```
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metric-learn (🥉26 · ⭐ 1.3K) - Metric learning algorithms in Python. MIT +
metric-learn (🥉26 · ⭐ 1.3K) - Python中的度量学习算法。MIT - [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 22 · 🔀 220 · 📦 230 · 📋 160 - 26% open · ⏱️ 21.06.2022): @@ -10917,7 +10917,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install metric-learn ```
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Trax (🥉25 · ⭐ 7.1K) - Trax Deep Learning with Clear Code and Speed. Apache-2 +
Trax (🥉25 · ⭐ 7.1K) - 借助清晰的代码和速度来进行深度学习。Apache-2 - [GitHub](https://github.com/google/trax) (👨‍💻 78 · 🔀 720 · 📦 75 · 📋 210 - 41% open · ⏱️ 08.08.2022): @@ -10929,7 +10929,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install trax ```
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TabPy (🥉25 · ⭐ 1.3K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT +
TabPy (🥉25 · ⭐ 1.3K) - 快速执行Python代码，并在Tableau可视化文件中显示结果。MIT - [GitHub](https://github.com/tableau/TabPy) (👨‍💻 47 · 🔀 480 · 📦 93 · 📋 290 - 1% open · ⏱️ 10.06.2022): @@ -10941,7 +10941,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install tabpy ```
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causalml (🥉24 · ⭐ 3.2K) - Uplift modeling and causal inference with machine learning.. ❗Unlicensed +
causalml (🥉24 · ⭐ 3.2K) - 利用机器学习提升建模和因果推理。❗Unlicensed - [GitHub](https://github.com/uber/causalml) (👨‍💻 44 · 🔀 520 · 📦 52 · 📋 280 - 21% open · ⏱️ 22.08.2022): @@ -10953,7 +10953,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install causalml ```
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pyclustering (🥉24 · ⭐ 990 · 💀) - pyclustring is a Python, C++ data mining library. BSD-3 +
pyclustering (🥉24 · ⭐ 990 · 💀) - pyclustring是Python，C++数据挖掘库。BSD-3 - [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 220 · 📥 410 · 📦 350 · 📋 650 - 9% open · ⏱️ 12.02.2021): @@ -10969,7 +10969,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyclustering ```
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PySwarms (🥉23 · ⭐ 960) - A research toolkit for particle swarm optimization in Python. MIT +
PySwarms (🥉23 · ⭐ 960) - 用于Python中粒子群优化的研究工具包。MIT - [GitHub](https://github.com/ljvmiranda921/pyswarms) (👨‍💻 44 · 🔀 300 · 📦 180 · 📋 210 - 3% open · ⏱️ 03.07.2022): @@ -10981,7 +10981,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install pyswarms ```
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gplearn (🥉22 · ⭐ 1.2K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 +
gplearn (🥉22 · ⭐ 1.2K) - 使用scikit-learn启发式API进行Python遗传编程。BSD-3 - [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 10 · 🔀 200 · 📦 280 · 📋 190 - 7% open · ⏱️ 04.08.2022): @@ -10993,7 +10993,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install gplearn ```
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pyopencl (🥉22 · ⭐ 910) - OpenCL integration for Python, plus shiny features. ❗Unlicensed +
pyopencl (🥉22 · ⭐ 910) - 适用于Python的OpenCL集成。❗Unlicensed - [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 92 · 🔀 220 · 📦 800 · 📋 300 - 20% open · ⏱️ 23.08.2022): @@ -11009,7 +11009,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyopencl ```
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Prince (🥉22 · ⭐ 850 · 💤) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT +
Prince (🥉22 · ⭐ 850 · 💤) - Python因子分析库（PCA，CA，MCA，MFA，FAMD）。MIT - [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 12 · 🔀 150 · 📦 240 · 📋 110 - 35% open · ⏱️ 28.12.2021): @@ -11021,7 +11021,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install prince ```
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findspark (🥉22 · ⭐ 440) - Find pyspark to make it importable. BSD-3 +
findspark (🥉22 · ⭐ 440) - 查找pyspark并导入的工具库。BSD-3 - [GitHub](https://github.com/minrk/findspark) (👨‍💻 15 · 🔀 68 · 📦 2.7K · 📋 22 - 50% open · ⏱️ 11.02.2022): @@ -11037,7 +11037,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge findspark ```
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River (🥉20 · ⭐ 3.6K) - Online machine learning in Python. BSD-3 +
River (🥉20 · ⭐ 3.6K) - Python中的在线机器学习。BSD-3 - [GitHub](https://github.com/online-ml/river) (👨‍💻 81 · 🔀 380 · 📦 160 · 📋 370 - 1% open · ⏱️ 24.08.2022): @@ -11045,7 +11045,7 @@ _Libraries for connecting to, operating, and querying databases._ git clone https://github.com/online-ml/river ```
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BioPandas (🥉20 · ⭐ 500) - Working with molecular structures in pandas DataFrames. BSD-3 +
BioPandas (🥉20 · ⭐ 500) - 在pandas DataFrames中处理分子结构。BSD-3 - [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 10 · 🔀 100 · 📦 120 · 📋 47 - 42% open · ⏱️ 06.08.2022): @@ -11061,7 +11061,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge biopandas ```
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StreamAlert (🥉19 · ⭐ 2.7K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 +
StreamAlert (🥉19 · ⭐ 2.7K) - StreamAlert是无服务器的实时数据分析框架。Apache-2 - [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 33 · 🔀 320 · 📋 340 - 24% open · ⏱️ 20.07.2022): @@ -11069,7 +11069,7 @@ _Libraries for connecting to, operating, and querying databases._ git clone https://github.com/airbnb/streamalert ```
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SUOD (🥉19 · ⭐ 330) - (MLSys' 21) An Acceleration System for Large-scare Unsupervised.. BSD-2 +
SUOD (🥉19 · ⭐ 330) - （MLSys' 21）大型无人驾驶加速系统。BSD-2 - [GitHub](https://github.com/yzhao062/SUOD) (👨‍💻 2 · 🔀 41 · 📦 430 · 📋 9 - 66% open · ⏱️ 07.07.2022): @@ -11081,7 +11081,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install suod ```
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impyute (🥉19 · ⭐ 320 · 💤) - Data imputations library to preprocess datasets with missing data. MIT +
impyute (🥉19 · ⭐ 320 · 💤) - 数据插补库可对缺少数据的数据集进行预处理。MIT - [GitHub](https://github.com/eltonlaw/impyute) (👨‍💻 11 · 🔀 46 · 📦 140 · 📋 64 - 42% open · ⏱️ 06.11.2021): @@ -11093,7 +11093,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install impyute ```
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AstroML (🥉17 · ⭐ 840) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 +
AstroML (🥉17 · ⭐ 840) - 天文学和天体物理学的机器学习，统计和数据挖掘.BSD-2 - [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 270 · 📋 150 - 37% open · ⏱️ 17.08.2022): @@ -11109,7 +11109,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge astroml ```
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Feature Engine (🥉16 · ⭐ 22) - Feature engineering package with sklearn like functionality. BSD-3 +
Feature Engine (🥉16 · ⭐ 22) - 具有sklearn类功能的功能工程包。BSD-3 - [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 36 · 🔀 8 · ⏱️ 05.07.2022): @@ -11125,7 +11125,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge feature_engine ```
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cleanlab (🥉13 · ⭐ 49 · 🐣) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 +
cleanlab (🥉13 · ⭐ 49 · 🐣) - 机器学习的标准软件包。❗️AGPL-3.0 - [GitHub](https://github.com/cgnorthcutt/cleanlab) (👨‍💻 10 · 🔀 9 · ⏱️ 21.08.2022):