From 296bbb1f44d3cf306882ea7f452653edbfaa6711 Mon Sep 17 00:00:00 2001 From: HanXinzi2020 Date: Thu, 16 Dec 2021 14:29:22 +0000 Subject: [PATCH 1/2] Update best-of list for version 2021.12.16 --- README.md | 8600 ++++++++++++++++--------------- history/2021-12-16_changes.md | 20 + history/2021-12-16_projects.csv | 822 +++ latest-changes.md | 20 +- 4 files changed, 5158 insertions(+), 4304 deletions(-) create mode 100644 history/2021-12-16_changes.md create mode 100644 history/2021-12-16_projects.csv diff --git a/README.md b/README.md index 7d754d9..9200938 100644 --- a/README.md +++ b/README.md @@ -14,254 +14,254 @@

-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3M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) _22 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3.1M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。 +## 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 · ⭐ 160K) - An Open Source Machine Learning Framework for Everyone. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 3.8K · 🔀 69K · 📦 160K · 📋 33K - 8% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 3.9K · 🔀 69K · 📦 170K · 📋 34K - 7% open · ⏱️ 16.12.2021): ``` git clone https://github.com/tensorflow/tensorflow ``` -- [PyPi](https://pypi.org/project/tensorflow) (📥 12M / month): +- [PyPi](https://pypi.org/project/tensorflow) (📥 15M / month): ``` pip install tensorflow ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow) (📥 2.8M · ⏱️ 25.09.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow) (📥 2.9M · ⏱️ 08.12.2021): ``` conda install -c conda-forge tensorflow ``` -- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (📥 60M · ⭐ 2K · ⏱️ 12.10.2021): +- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (📥 63M · ⭐ 2K · ⏱️ 16.12.2021): ``` docker pull tensorflow/tensorflow ```
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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 +
scikit-learn (🥇38 · ⭐ 48K) - scikit-learn: machine learning in Python. BSD-3 -- [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 540 · 🔀 7.7K · 📥 3.1K · 📦 22K · 📋 4.2K - 6% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.4K · 🔀 22K · 📥 760 · 📦 290K · 📋 9K - 18% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/dmlc/xgboost + git clone https://github.com/scikit-learn/scikit-learn ``` -- [PyPi](https://pypi.org/project/xgboost) (📥 7.9M / month): +- [PyPi](https://pypi.org/project/scikit-learn) (📥 25M / month): ``` - pip install xgboost + pip install scikit-learn ``` -- [Conda](https://anaconda.org/conda-forge/xgboost) (📥 2M · ⏱️ 17.09.2021): +- [Conda](https://anaconda.org/conda-forge/scikit-learn) (📥 11M · ⏱️ 14.12.2021): ``` - conda install -c conda-forge xgboost + conda install -c conda-forge scikit-learn ```
-
scikit-learn (🥇36 · ⭐ 48K) - scikit-learn：基于Python的机器学习工具库。BSD-3 +
XGBoost (🥇37 · ⭐ 22K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 -- [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.4K · 🔀 21K · 📥 740 · 📦 270K · 📋 8.8K - 19% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 540 · 🔀 7.7K · 📥 3.5K · 📦 25K · 📋 4.2K - 6% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/scikit-learn/scikit-learn + git clone https://github.com/dmlc/xgboost ``` -- [PyPi](https://pypi.org/project/scikit-learn) (📥 23M / month): +- [PyPi](https://pypi.org/project/xgboost) (📥 8.8M / month): ``` - pip install scikit-learn + pip install xgboost ``` -- [Conda](https://anaconda.org/conda-forge/scikit-learn) (📥 9.8M · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/xgboost) (📥 2.2M · ⏱️ 20.11.2021): ``` - conda install -c conda-forge scikit-learn + 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 (🥇36 · ⭐ 13K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT -- [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 240 · 🔀 3.3K · 📥 120K · 📦 9.3K · 📋 2.4K - 4% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 250 · 🔀 3.4K · 📥 130K · 📦 10K · 📋 2.5K - 5% open · ⏱️ 15.12.2021): ``` git clone https://github.com/microsoft/LightGBM ``` -- [PyPi](https://pypi.org/project/lightgbm) (📥 15M / month): +- [PyPi](https://pypi.org/project/lightgbm) (📥 11M / month): ``` pip install lightgbm ``` -- [Conda](https://anaconda.org/conda-forge/lightgbm) (📥 750K · ⏱️ 20.04.2021): +- [Conda](https://anaconda.org/conda-forge/lightgbm) (📥 830K · ⏱️ 20.11.2021): ``` conda install -c conda-forge lightgbm ```
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pytorch-lightning (🥇35 · ⭐ 16K) - 轻巧而具备高性能的PyTorch上层封装工具库。Apache-2 +
pytorch-lightning (🥇35 · ⭐ 17K) - The lightweight PyTorch wrapper for high-performance.. Apache-2 -- [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (👨‍💻 550 · 🔀 1.9K · 📥 4.4K · 📦 5K · 📋 4K - 7% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (👨‍💻 590 · 🔀 2K · 📥 4.9K · 📦 6K · 📋 4.3K - 8% open · ⏱️ 16.12.2021): ``` git clone https://github.com/PyTorchLightning/pytorch-lightning ``` -- [PyPi](https://pypi.org/project/pytorch-lightning) (📥 650K / month): +- [PyPi](https://pypi.org/project/pytorch-lightning) (📥 870K / month): ``` pip install pytorch-lightning ``` -- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (📥 300K · ⏱️ 30.09.2021): +- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (📥 380K · ⏱️ 16.12.2021): ``` conda install -c conda-forge pytorch-lightning ```
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PyTorch (🥇33 · ⭐ 51K) - 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 +
Thinc (🥇34 · ⭐ 2.4K) - 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): + + ``` + git clone https://github.com/explosion/thinc + ``` +- [PyPi](https://pypi.org/project/thinc) (📥 5.7M / month): + ``` + pip install thinc + ``` +- [Conda](https://anaconda.org/conda-forge/thinc) (📥 1.8M · ⏱️ 08.12.2021): + ``` + conda install -c conda-forge thinc + ``` +
+
PyTorch (🥈33 · ⭐ 53K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 -- [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 2.9K · 🔀 14K · 📋 23K - 30% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 3K · 🔀 14K · 📥 600 · 📋 24K - 31% open · ⏱️ 16.12.2021): ``` git clone https://github.com/pytorch/pytorch ``` -- [PyPi](https://pypi.org/project/torch) (📥 5.2M / month): +- [PyPi](https://pypi.org/project/torch) (📥 6.3M / month): ``` pip install torch ``` -- [Conda](https://anaconda.org/pytorch/pytorch) (📥 13M · ⏱️ 20.09.2021): +- [Conda](https://anaconda.org/pytorch/pytorch) (📥 14M · ⏱️ 15.12.2021): ``` conda install -c pytorch pytorch ```
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StatsModels (🥇33 · ⭐ 6.7K) - Statsmodels：Python中的统计建模和计量经济学工具库。BSD-3 +
StatsModels (🥈33 · ⭐ 6.9K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 -- [GitHub](https://github.com/statsmodels/statsmodels) (👨‍💻 340 · 🔀 2.2K · 📥 26 · 📦 51K · 📋 4.4K - 45% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/statsmodels/statsmodels) (👨‍💻 350 · 🔀 2.2K · 📥 26 · 📦 55K · 📋 4.5K - 46% open · ⏱️ 15.12.2021): ``` git clone https://github.com/statsmodels/statsmodels ``` -- [PyPi](https://pypi.org/project/statsmodels) (📥 6.2M / month): +- [PyPi](https://pypi.org/project/statsmodels) (📥 7.5M / month): ``` pip install statsmodels ``` -- [Conda](https://anaconda.org/conda-forge/statsmodels) (📥 5M · ⏱️ 03.10.2021): +- [Conda](https://anaconda.org/conda-forge/statsmodels) (📥 5.4M · ⏱️ 13.11.2021): ``` conda install -c conda-forge statsmodels ```
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Thinc (🥈32 · ⭐ 2.4K) - 深度学习工具库。MIT +
PaddlePaddle (🥈32 · ⭐ 17K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 -- [GitHub](https://github.com/explosion/thinc) (👨‍💻 41 · 🔀 210 · 📦 16K · 📋 110 - 12% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 670 · 🔀 4K · 📥 15K · 📦 83 · 📋 14K - 14% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/explosion/thinc - ``` -- [PyPi](https://pypi.org/project/thinc) (📥 2.6M / month): - ``` - pip install thinc + git clone https://github.com/PaddlePaddle/Paddle ``` -- [Conda](https://anaconda.org/conda-forge/thinc) (📥 1.6M · ⏱️ 25.09.2021): +- [PyPi](https://pypi.org/project/paddlepaddle) (📥 110K / month): ``` - conda install -c conda-forge thinc + pip install paddlepaddle ```
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PySpark (🥈31 · ⭐ 31K) - Apache Spark Python API。Apache-2 +
PySpark (🥈31 · ⭐ 32K) - Apache Spark Python API. Apache-2 -- [GitHub](https://github.com/apache/spark) (👨‍💻 2.5K · 🔀 24K · ⏱️ 13.10.2021): +- [GitHub](https://github.com/apache/spark) (👨‍💻 2.6K · 🔀 24K · ⏱️ 16.12.2021): ``` git clone https://github.com/apache/spark ``` -- [PyPi](https://pypi.org/project/pyspark) (📥 14M / month): +- [PyPi](https://pypi.org/project/pyspark) (📥 15M / month): ``` pip install pyspark ``` -- [Conda](https://anaconda.org/conda-forge/pyspark) (📥 1.3M · ⏱️ 29.05.2021): +- [Conda](https://anaconda.org/conda-forge/pyspark) (📥 1.4M · ⏱️ 18.10.2021): ``` conda install -c conda-forge pyspark ```
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PaddlePaddle (🥈31 · ⭐ 17K) - paddlepaddle机器学习与深度学习工具库。Apache-2 - -- [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 650 · 🔀 3.9K · 📥 15K · 📦 71 · 📋 14K - 15% open · ⏱️ 13.10.2021): - - ``` - git clone https://github.com/PaddlePaddle/Paddle - ``` -- [PyPi](https://pypi.org/project/paddlepaddle) (📥 36K / month): - ``` - pip install paddlepaddle - ``` -
-
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 +
dlib (🥈31 · ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 -- [GitHub](https://github.com/davisking/dlib) (👨‍💻 170 · 🔀 2.5K · 📥 25K · 📦 12K · 📋 2K - 1% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/davisking/dlib) (👨‍💻 170 · 🔀 2.6K · 📥 25K · 📦 12K · 📋 2K - 1% open · ⏱️ 16.12.2021): ``` git clone https://github.com/davisking/dlib ``` -- [PyPi](https://pypi.org/project/dlib) (📥 110K / month): +- [PyPi](https://pypi.org/project/dlib) (📥 130K / month): ``` pip install dlib ``` -- [Conda](https://anaconda.org/conda-forge/dlib) (📥 360K · ⏱️ 03.04.2021): +- [Conda](https://anaconda.org/conda-forge/dlib) (📥 380K · ⏱️ 03.04.2021): ``` conda install -c conda-forge dlib ```
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Theano (🥈31 · ⭐ 9.5K) - Theano是一个Python神经网络工具库。❗Unlicensed +
Theano (🥈31 · ⭐ 9.5K) - Theano is a Python library that allows you to define, optimize,.. ❗Unlicensed -- [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 12K · 📋 2.7K - 21% open · ⏱️ 13.04.2021): +- [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 12K · 📋 2.7K - 21% open · ⏱️ 23.11.2021): ``` git clone https://github.com/Theano/Theano @@ -270,376 +270,388 @@ _通用机器学习和深度学习框架。_ ``` pip install theano ``` -- [Conda](https://anaconda.org/conda-forge/theano) (📥 1.7M · ⏱️ 05.06.2021): +- [Conda](https://anaconda.org/conda-forge/theano) (📥 1.8M · ⏱️ 10.11.2021): ``` conda install -c conda-forge theano ```
-
Chainer (🥈31 · ⭐ 5.6K) - 灵活的深度学习神经网络框架。MIT +
jax (🥈30 · ⭐ 16K) - 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): + + ``` + git clone https://github.com/google/jax + ``` +- [PyPi](https://pypi.org/project/jax) (📥 1.4M / month): + ``` + pip install jax + ``` +- [Conda](https://anaconda.org/conda-forge/jaxlib) (📥 250K · ⏱️ 10.12.2021): + ``` + conda install -c conda-forge jaxlib + ``` +
+
Chainer (🥈30 · ⭐ 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): ``` git clone https://github.com/chainer/chainer ``` -- [PyPi](https://pypi.org/project/chainer) (📥 27K / month): +- [PyPi](https://pypi.org/project/chainer) (📥 23K / month): ``` pip install chainer ```
-
jax (🥈30 · ⭐ 14K) - Python + NumPy程序工具库。Apache-2 +
Keras (🥈29 · ⭐ 53K) - Deep Learning for humans. ❗Unlicensed -- [GitHub](https://github.com/google/jax) (👨‍💻 330 · 🔀 1.3K · 📦 2.6K · 📋 2.6K - 28% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/keras-team/keras) (👨‍💻 1K · 🔀 18K · 📋 11K - 1% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/google/jax + git clone https://github.com/keras-team/keras ``` -- [PyPi](https://pypi.org/project/jax) (📥 760K / month): +- [PyPi](https://pypi.org/project/keras) (📥 7.6M / month): ``` - pip install jax + pip install keras ``` -- [Conda](https://anaconda.org/conda-forge/jaxlib) (📥 200K · ⏱️ 13.10.2021): +- [Conda](https://anaconda.org/conda-forge/keras) (📥 2M · ⏱️ 25.11.2021): ``` - conda install -c conda-forge jaxlib + conda install -c conda-forge keras ```
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Jina (🥈30 · ⭐ 12K · 📈) - 在云端构建神经搜索的简便方法库。Apache-2 +
Jina (🥈29 · ⭐ 13K) - An easier way to build neural search on the cloud. Apache-2 -- [GitHub](https://github.com/jina-ai/jina) (👨‍💻 120 · 🔀 1.3K · 📦 150 · 📋 1.1K - 7% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/jina-ai/jina) (👨‍💻 130 · 🔀 1.7K · 📦 190 · 📋 1.2K - 5% open · ⏱️ 16.12.2021): ``` git clone https://github.com/jina-ai/jina ``` -- [PyPi](https://pypi.org/project/jina) (📥 25K / month): +- [PyPi](https://pypi.org/project/jina) (📥 13K / month): ``` pip install jina ``` -- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (📥 900K · ⭐ 5 · ⏱️ 12.10.2021): +- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (📥 990K · ⭐ 6 · ⏱️ 16.12.2021): ``` docker pull jinaai/jina ```
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Vowpal Wabbit (🥈30 · ⭐ 7.7K) - Vowpal Wabbit是一个推动机器学习的机器学习系统。BSD-3 +
Catboost (🥈29 · ⭐ 6.3K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 -- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 300 · 🔀 1.7K · 📦 170 · 📋 1.1K - 14% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/catboost/catboost) (👨‍💻 930 · 🔀 910 · 📥 70K · 📋 1.7K - 19% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/VowpalWabbit/vowpal_wabbit + git clone https://github.com/catboost/catboost ``` -- [PyPi](https://pypi.org/project/vowpalwabbit) (📥 26K / month): +- [PyPi](https://pypi.org/project/catboost) (📥 3.3M / month): ``` - pip install vowpalwabbit + pip install catboost + ``` +- [Conda](https://anaconda.org/conda-forge/catboost) (📥 880K · ⏱️ 09.11.2021): + ``` + conda install -c conda-forge catboost ```
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Keras (🥈29 · ⭐ 53K) - 易上手的深度学习工具库。❗Unlicensed +
einops (🥈29 · ⭐ 4K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT -- [GitHub](https://github.com/keras-team/keras) (👨‍💻 990 · 🔀 18K · 📋 11K - 2% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/arogozhnikov/einops) (👨‍💻 13 · 🔀 160 · 📦 1.6K · 📋 87 - 33% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/keras-team/keras + git clone https://github.com/arogozhnikov/einops ``` -- [PyPi](https://pypi.org/project/keras) (📥 6M / month): +- [PyPi](https://pypi.org/project/einops) (📥 1.3M / month): ``` - pip install keras + pip install einops ``` -- [Conda](https://anaconda.org/conda-forge/keras) (📥 1.9M · ⏱️ 03.09.2021): +- [Conda](https://anaconda.org/conda-forge/einops) (📥 9.3K · ⏱️ 31.08.2021): ``` - conda install -c conda-forge keras + conda install -c conda-forge einops ```
-
Fastai (🥈28 · ⭐ 22K) - Fastai深度学习库。Apache-2 +
Fastai (🥈28 · ⭐ 22K) - The fastai deep learning library. Apache-2 -- [GitHub](https://github.com/fastai/fastai) (👨‍💻 180 · 🔀 7K · 📋 1.5K - 5% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/fastai/fastai) (👨‍💻 180 · 🔀 7K · 📋 1.5K - 5% open · ⏱️ 29.11.2021): ``` git clone https://github.com/fastai/fastai ``` -- [PyPi](https://pypi.org/project/fastai) (📥 310K / month): +- [PyPi](https://pypi.org/project/fastai) (📥 240K / month): ``` pip install fastai ```
-
MXNet (🥈28 · ⭐ 20K) - 轻巧，灵活的分布式/移动深度学习工具库。Apache-2 +
MXNet (🥈28 · ⭐ 20K) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning.. Apache-2 -- [GitHub](https://github.com/apache/incubator-mxnet) (👨‍💻 960 · 🔀 6.5K · 📥 24K · 📋 9.4K - 18% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/apache/incubator-mxnet) (👨‍💻 970 · 🔀 6.5K · 📥 24K · 📋 9.4K - 18% open · ⏱️ 16.12.2021): ``` git clone https://github.com/apache/incubator-mxnet ``` -- [PyPi](https://pypi.org/project/mxnet) (📥 430K / month): +- [PyPi](https://pypi.org/project/mxnet) (📥 340K / month): ``` pip install mxnet ``` -- [Conda](https://anaconda.org/anaconda/mxnet) (📥 6.6K · ⏱️ 29.02.2020): +- [Conda](https://anaconda.org/anaconda/mxnet) (📥 6.8K · ⏱️ 29.02.2020): ``` conda install -c anaconda mxnet ```
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Catboost (🥈28 · ⭐ 6.1K) - 快速，可扩展，高性能的梯度决策提升工具库。Apache-2 +
tensorpack (🥈28 · ⭐ 6.1K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 -- [GitHub](https://github.com/catboost/catboost) (👨‍💻 890 · 🔀 880 · 📥 65K · 📋 1.6K - 17% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 58 · 🔀 1.8K · 📥 130 · 📦 920 · 📋 1.3K - 0% open · ⏱️ 27.11.2021): ``` - git clone https://github.com/catboost/catboost - ``` -- [PyPi](https://pypi.org/project/catboost) (📥 2.6M / month): - ``` - pip install catboost + git clone https://github.com/tensorpack/tensorpack ``` -- [Conda](https://anaconda.org/conda-forge/catboost) (📥 830K · ⏱️ 05.08.2021): +- [PyPi](https://pypi.org/project/tensorpack) (📥 27K / month): ``` - conda install -c conda-forge catboost + pip install tensorpack ```
-
tensorpack (🥈28 · ⭐ 6.1K) - TensorFlow上的神经网络训练接口。Apache-2 +
PyFlink (🥈27 · ⭐ 18K) - Apache Flink Python API. Apache-2 -- [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 57 · 🔀 1.8K · 📥 130 · 📦 880 · 📋 1.3K - 0% open · ⏱️ 10.08.2021): +- [GitHub](https://github.com/apache/flink) (👨‍💻 1.4K · 🔀 9.8K · ⏱️ 16.12.2021): ``` - git clone https://github.com/tensorpack/tensorpack + git clone https://github.com/apache/flink ``` -- [PyPi](https://pypi.org/project/tensorpack) (📥 17K / month): +- [PyPi](https://pypi.org/project/apache-flink) (📥 8.2K / month): ``` - pip install tensorpack + pip install apache-flink ```
-
Sonnet (🥈27 · ⭐ 9K) - 基于TensorFlow的神经网络库。Apache-2 +
Sonnet (🥈27 · ⭐ 9.1K) - TensorFlow-based neural network library. Apache-2 -- [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 52 · 🔀 1.2K · 📦 670 · 📋 160 - 11% open · ⏱️ 08.09.2021): +- [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 53 · 🔀 1.2K · 📦 730 · 📋 170 - 11% open · ⏱️ 15.12.2021): ``` git clone https://github.com/deepmind/sonnet ``` -- [PyPi](https://pypi.org/project/dm-sonnet) (📥 360K / month): +- [PyPi](https://pypi.org/project/dm-sonnet) (📥 380K / month): ``` pip install dm-sonnet ``` -- [Conda](https://anaconda.org/conda-forge/sonnet) (📥 12K · ⏱️ 14.11.2020): +- [Conda](https://anaconda.org/conda-forge/sonnet) (📥 13K · ⏱️ 14.11.2020): ``` conda install -c conda-forge sonnet ```
-
einops (🥈27 · ⭐ 3.7K) - 重塑了深度学习操作（用于pytorch，tensorflow，jax等）的工具库。MIT +
Vowpal Wabbit (🥈27 · ⭐ 7.8K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 -- [GitHub](https://github.com/arogozhnikov/einops) (👨‍💻 12 · 🔀 140 · 📦 1.2K · 📋 79 - 34% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 310 · 🔀 1.7K · 📋 1.1K - 12% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/arogozhnikov/einops - ``` -- [PyPi](https://pypi.org/project/einops) (📥 380K / month): - ``` - pip install einops + git clone https://github.com/VowpalWabbit/vowpal_wabbit ``` -- [Conda](https://anaconda.org/conda-forge/einops) (📥 7.6K · ⏱️ 31.08.2021): +- [PyPi](https://pypi.org/project/vowpalwabbit) (📥 54K / month): ``` - conda install -c conda-forge einops + pip install vowpalwabbit ```
-
dyNET (🥈27 · ⭐ 3.3K · 💤) - DyNet：动态神经网络工具包。Apache-2 +
skorch (🥈27 · ⭐ 4.2K) - A scikit-learn compatible neural network library that wraps.. BSD-3 -- [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 3.8K · 📦 190 · 📋 920 - 27% open · ⏱️ 27.01.2021): +- [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 47 · 🔀 290 · 📦 420 · 📋 420 - 11% open · ⏱️ 28.11.2021): ``` - git clone https://github.com/clab/dynet + git clone https://github.com/skorch-dev/skorch ``` -- [PyPi](https://pypi.org/project/dyNET) (📥 20K / month): +- [PyPi](https://pypi.org/project/skorch) (📥 19K / month): ``` - pip install dyNET + pip install skorch + ``` +- [Conda](https://anaconda.org/conda-forge/skorch) (📥 490K · ⏱️ 30.11.2021): + ``` + conda install -c conda-forge skorch ```
-
PyFlink (🥉26 · ⭐ 17K) - Apache Flink Python API。Apache-2 +
dyNET (🥈27 · ⭐ 3.3K · 💤) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 -- [GitHub](https://github.com/apache/flink) (👨‍💻 1.4K · 🔀 9.5K · ⏱️ 12.10.2021): +- [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 4.3K · 📦 200 · 📋 920 - 27% open · ⏱️ 27.01.2021): ``` - git clone https://github.com/apache/flink + git clone https://github.com/clab/dynet ``` -- [PyPi](https://pypi.org/project/apache-flink) (📥 7K / month): +- [PyPi](https://pypi.org/project/dyNET) (📥 20K / month): ``` - pip install apache-flink + pip install dyNET ```
-
TFlearn (🥉26 · ⭐ 9.6K · 💤) - 深度学习库，基于TensorFlow构建上层简单易用的API。❗Unlicensed +
Flax (🥈27 · ⭐ 2.4K · 📈) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax -- [GitHub](https://github.com/tflearn/tflearn) (👨‍💻 130 · 🔀 2.3K · 📦 3.6K · 📋 910 - 60% open · ⏱️ 30.11.2020): +- [GitHub](https://github.com/google/flax) (👨‍💻 120 · 🔀 270 · 📥 31 · 📦 560 · 📋 410 - 32% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/tflearn/tflearn + git clone https://github.com/google/flax ``` -- [PyPi](https://pypi.org/project/tflearn) (📥 23K / month): +- [PyPi](https://pypi.org/project/flax) (📥 1.3M / month): ``` - pip install tflearn + pip install flax ```
-
skorch (🥉26 · ⭐ 4.2K) - 封装成scikit-learn接口模式的神经网络库。BSD-3 +
TFlearn (🥉26 · ⭐ 9.6K · 💀) - Deep learning library featuring a higher-level API for.. ❗Unlicensed -- [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 44 · 🔀 290 · 📦 400 · 📋 400 - 11% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/tflearn/tflearn) (👨‍💻 130 · 🔀 2.3K · 📦 3.7K · 📋 910 - 60% open · ⏱️ 30.11.2020): ``` - git clone https://github.com/skorch-dev/skorch - ``` -- [PyPi](https://pypi.org/project/skorch) (📥 16K / month): - ``` - pip install skorch + git clone https://github.com/tflearn/tflearn ``` -- [Conda](https://anaconda.org/conda-forge/skorch) (📥 410K · ⏱️ 24.03.2021): +- [PyPi](https://pypi.org/project/tflearn) (📥 13K / month): ``` - conda install -c conda-forge skorch + pip install tflearn ```
-
Ignite (🥉26 · ⭐ 3.7K) - 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 · ⭐ 3.8K) - High-level library to help with training and evaluating neural.. BSD-3 -- [GitHub](https://github.com/pytorch/ignite) (👨‍💻 150 · 🔀 490 · 📋 910 - 11% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pytorch/ignite) (👨‍💻 160 · 🔀 500 · 📋 950 - 11% open · ⏱️ 15.12.2021): ``` git clone https://github.com/pytorch/ignite ``` -- [PyPi](https://pypi.org/project/pytorch-ignite) (📥 67K / month): +- [PyPi](https://pypi.org/project/pytorch-ignite) (📥 76K / month): ``` pip install pytorch-ignite ``` -- [Conda](https://anaconda.org/pytorch/ignite) (📥 70K · ⏱️ 02.08.2021): +- [Conda](https://anaconda.org/pytorch/ignite) (📥 75K · ⏱️ 19.10.2021): ``` conda install -c pytorch ignite ```
-
ktrain (🥉26 · ⭐ 910) - ktrain是一个Python库，可以使深度学习和AI更简单。Apache-2 +
ktrain (🥉26 · ⭐ 930) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 -- [GitHub](https://github.com/amaiya/ktrain) (👨‍💻 12 · 🔀 220 · 📦 220 · 📋 360 - 1% open · ⏱️ 03.09.2021): +- [GitHub](https://github.com/amaiya/ktrain) (👨‍💻 12 · 🔀 220 · 📦 240 · 📋 380 - 1% open · ⏱️ 23.11.2021): ``` git clone https://github.com/amaiya/ktrain ``` -- [PyPi](https://pypi.org/project/ktrain) (📥 20K / month): +- [PyPi](https://pypi.org/project/ktrain) (📥 26K / month): ``` pip install ktrain ```
-
Turi Create (🥉25 · ⭐ 10K) - 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 learning.. BSD-3 -- [GitHub](https://github.com/apple/turicreate) (👨‍💻 82 · 🔀 1.1K · 📥 4.9K · 📦 270 · 📋 1.7K - 26% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/apple/turicreate) (👨‍💻 82 · 🔀 1.1K · 📥 4.9K · 📦 280 · 📋 1.8K - 26% open · ⏱️ 29.11.2021): ``` git clone https://github.com/apple/turicreate ``` -- [PyPi](https://pypi.org/project/turicreate) (📥 25K / month): +- [PyPi](https://pypi.org/project/turicreate) (📥 26K / month): ``` pip install turicreate ```
-
Ludwig (🥉25 · ⭐ 7.9K) - 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 +
Ludwig (🥉24 · ⭐ 8K) - Ludwig is a toolbox that allows to train and evaluate deep.. Apache-2 -- [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 96 · 🔀 900 · 📦 96 · 📋 590 - 21% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 110 · 🔀 910 · 📦 98 · 📋 630 - 23% open · ⏱️ 16.12.2021): ``` git clone https://github.com/ludwig-ai/ludwig ``` -- [PyPi](https://pypi.org/project/ludwig) (📥 4K / month): +- [PyPi](https://pypi.org/project/ludwig) (📥 3.8K / month): ``` pip install ludwig ```
-
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 · 🔀 1.5K · 📦 100 · 📋 1.8K - 25% open · ⏱️ 23.10.2019): +- [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) (📥 3.8K / month): +- [PyPi](https://pypi.org/project/nupic) (📥 3.3K / month): ``` pip install nupic ```
-
xLearn (🥉24 · ⭐ 2.9K · 💀) - 高性能，易于使用且可扩展的机器学习（ML）工具库。Apache-2 +
xLearn (🥉24 · ⭐ 3K · 💀) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 -- [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 2.9K · 📦 68 · 📋 290 - 63% open · ⏱️ 03.03.2020): +- [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 3K · 📦 72 · 📋 300 - 62% open · ⏱️ 03.03.2020): ``` git clone https://github.com/aksnzhy/xlearn ``` -- [PyPi](https://pypi.org/project/xlearn) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/xlearn) (📥 2.9K / month): ``` pip install xlearn ```
-
tensorflow-upstream (🥉24 · ⭐ 570) - TensorFlow ROCm端口。Apache-2 +
tensorflow-upstream (🥉24 · ⭐ 580) - TensorFlow ROCm port. Apache-2 -- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 3.8K · 🔀 65 · 📥 17 · 📋 300 - 16% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 3.9K · 🔀 66 · 📥 17 · 📋 310 - 15% open · ⏱️ 14.12.2021): ``` git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` -- [PyPi](https://pypi.org/project/tensorflow-rocm) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/tensorflow-rocm) (📥 1.4K / month): ``` pip install tensorflow-rocm ```
-
CNTK (🥉23 · ⭐ 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): - - ``` - git clone https://github.com/microsoft/CNTK - ``` -- [PyPi](https://pypi.org/project/cntk) (📥 1.6K / month): - ``` - pip install cntk - ``` -
-
mlpack (🥉23 · ⭐ 3.8K) - mlpack：可扩展的C++机器学习库-。❗Unlicensed +
mlpack (🥉23 · ⭐ 3.9K) - mlpack: a scalable C++ machine learning library --. ❗Unlicensed -- [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 280 · 🔀 1.4K · 📋 1.4K - 3% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 280 · 🔀 1.4K · 📋 1.4K - 3% open · ⏱️ 15.12.2021): ``` git clone https://github.com/mlpack/mlpack ``` -- [PyPi](https://pypi.org/project/mlpack) (📥 780 / month): +- [PyPi](https://pypi.org/project/mlpack) (📥 270 / month): ``` pip install mlpack ``` -- [Conda](https://anaconda.org/conda-forge/mlpack) (📥 91K · ⏱️ 07.07.2021): +- [Conda](https://anaconda.org/conda-forge/mlpack) (📥 96K · ⏱️ 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 · ⭐ 2.5K) - Neural Network Libraries. Apache-2 -- [GitHub](https://github.com/sony/nnabla) (👨‍💻 64 · 🔀 300 · 📥 530 · 📋 60 - 30% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/sony/nnabla) (👨‍💻 63 · 🔀 300 · 📥 530 · 📋 61 - 27% open · ⏱️ 16.12.2021): ``` git clone https://github.com/sony/nnabla ``` -- [PyPi](https://pypi.org/project/nnabla) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/nnabla) (📥 3.5K / month): ``` pip install nnabla ```
-
neon (🥉22 · ⭐ 3.9K · 💀) - 英特尔Nervana深度学习框架。Apache-2 +
fklearn (🥉23 · ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 -- [GitHub](https://github.com/NervanaSystems/neon) (👨‍💻 110 · 🔀 810 · 📥 320 · 📦 50 · 📋 390 - 21% open · ⏱️ 22.05.2019): +- [GitHub](https://github.com/nubank/fklearn) (👨‍💻 40 · 🔀 150 · 📦 10 · 📋 40 - 47% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/NervanaSystems/neon + git clone https://github.com/nubank/fklearn ``` -- [PyPi](https://pypi.org/project/nervananeon) (📥 110 / month): +- [PyPi](https://pypi.org/project/fklearn) (📥 4K / month): ``` - pip install nervananeon + pip install fklearn + ``` +
+
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): + ``` + 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 · 🔀 930 · 📦 860 · 📋 520 - 22% open · ⏱️ 20.11.2019): +- [GitHub](https://github.com/Lasagne/Lasagne) (👨‍💻 72 · 🔀 940 · 📦 880 · 📋 520 - 22% open · ⏱️ 20.11.2019): ``` git clone https://github.com/Lasagne/Lasagne ``` -- [PyPi](https://pypi.org/project/lasagne) (📥 3.2K / month): +- [PyPi](https://pypi.org/project/lasagne) (📥 3K / month): ``` pip install lasagne ```
-
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): @@ -655,153 +667,141 @@ _通用机器学习和深度学习框架。_ docker pull shogun/shogun ```
-
NeuPy (🥉22 · ⭐ 690 · 💀) - NeuPy是一个基于Tensorflow的python库，用于原型设计和构建。MIT +
NeuPy (🥉21 · ⭐ 700 · 💀) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT -- [GitHub](https://github.com/itdxer/neupy) (👨‍💻 7 · 🔀 140 · 📦 110 · 📋 260 - 10% open · ⏱️ 02.09.2019): +- [GitHub](https://github.com/itdxer/neupy) (👨‍💻 7 · 🔀 150 · 📦 120 · 📋 260 - 11% open · ⏱️ 02.09.2019): ``` git clone https://github.com/itdxer/neupy ``` -- [PyPi](https://pypi.org/project/neupy) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/neupy) (📥 3K / month): ``` pip install neupy ```
-
Objax (🥉22 · ⭐ 650) - 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) (👨‍💻 22 · 🔀 54 · 📦 16 · 📋 92 - 39% open · ⏱️ 20.09.2021): - - ``` - git clone https://github.com/google/objax - ``` -- [PyPi](https://pypi.org/project/objax) (📥 16K / month): - ``` - pip install objax - ``` -
-
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 +
mace (🥉20 · ⭐ 4.5K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 -- [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 64 · 🔀 770 · 📥 1.4K · 📋 650 - 5% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 63 · 🔀 770 · 📥 1.4K · 📋 650 - 5% open · ⏱️ 06.12.2021): ``` git clone https://github.com/XiaoMi/mace ```
-
Flax (🥉20 · ⭐ 2.2K · 📉) - Flax是专为.NET设计的用于JAX的神经网络库。Apache-2 jax +
Haiku (🥉20 · ⭐ 1.6K) - JAX-based neural network library. Apache-2 -- [GitHub](https://github.com/google/flax) (👨‍💻 120 · 🔀 250 · 📥 26 · 📦 420 · 📋 380 - 34% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 53 · 🔀 120 · 📦 270 · 📋 120 - 20% open · ⏱️ 02.12.2021): ``` - git clone https://github.com/google/flax - ``` -- [PyPi](https://pypi.org/project/flax): - ``` - pip install flax + git clone https://github.com/deepmind/dm-haiku ```
-
Neural Tangents (🥉20 · ⭐ 1.6K) - Python中的快速简便的无限神经网络。Apache-2 +
Objax (🥉20 · ⭐ 660) - Objax is a machine learning framework that provides an Object.. Apache-2 jax -- [GitHub](https://github.com/google/neural-tangents) (👨‍💻 20 · 🔀 170 · 📥 140 · 📦 23 · 📋 94 - 28% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/google/objax) (👨‍💻 22 · 🔀 56 · 📦 17 · 📋 93 - 39% open · ⏱️ 20.09.2021): ``` - git clone https://github.com/google/neural-tangents + git clone https://github.com/google/objax ``` -- [PyPi](https://pypi.org/project/neural-tangents) (📥 590 / month): +- [PyPi](https://pypi.org/project/objax) (📥 2.5K / month): ``` - pip install neural-tangents + pip install objax ```
-
MindsDB (🥉19 · ⭐ 4K) - 为各种现有数据库提供预测性AI层。❗️GPL-3.0 +
MindsDB (🥉19 · ⭐ 4.2K) - Predictive AI layer for existing databases. ❗️GPL-3.0 -- [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 57 · 🔀 500 · 📋 700 - 10% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 89 · 🔀 550 · 📋 780 - 10% open · ⏱️ 16.12.2021): ``` git clone https://github.com/mindsdb/mindsdb ``` -- [PyPi](https://pypi.org/project/mindsdb) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/mindsdb) (📥 3.2K / month): ``` pip install mindsdb ```
-
Haiku (🥉19 · ⭐ 1.4K) - 基于JAX的神经网络库。Apache-2 +
neon (🥉19 · ⭐ 3.9K · 💀) - Intel Nervana reference deep learning framework committed to best.. Apache-2 -- [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 50 · 🔀 100 · 📦 200 · 📋 110 - 21% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/NervanaSystems/neon) (👨‍💻 110 · 🔀 810 · 📥 320 · 📋 390 - 21% open · ⏱️ 22.05.2019): ``` - git clone https://github.com/deepmind/dm-haiku + git clone https://github.com/NervanaSystems/neon + ``` +- [PyPi](https://pypi.org/project/nervananeon) (📥 99 / month): + ``` + pip install nervananeon ```
-
fklearn (🥉19 · ⭐ 1.3K) - fklearn：机器学习工具库。Apache-2 +
Neural Tangents (🥉19 · ⭐ 1.6K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 -- [GitHub](https://github.com/nubank/fklearn) (👨‍💻 37 · 🔀 150 · 📦 10 · 📋 39 - 48% open · ⏱️ 01.09.2021): +- [GitHub](https://github.com/google/neural-tangents) (👨‍💻 21 · 🔀 180 · 📥 180 · 📦 27 · 📋 100 - 29% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/nubank/fklearn + git clone https://github.com/google/neural-tangents ``` -- [PyPi](https://pypi.org/project/fklearn): +- [PyPi](https://pypi.org/project/neural-tangents): ``` - pip install fklearn + pip install neural-tangents ```
-
ThunderSVM (🥉19 · ⭐ 1.3K · 💤) - 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 - 27% open · ⏱️ 10.02.2021): +- [GitHub](https://github.com/Xtra-Computing/thundersvm) (👨‍💻 33 · 🔀 180 · 📥 2.3K · 📋 200 - 28% open · ⏱️ 10.02.2021): ``` git clone https://github.com/Xtra-Computing/thundersvm ``` -- [PyPi](https://pypi.org/project/thundersvm) (📥 550 / month): +- [PyPi](https://pypi.org/project/thundersvm) (📥 730 / month): ``` pip install thundersvm ```
-
Torchbearer (🥉19 · ⭐ 610 · 💤) - torchbearer：PyTorch的模型拟合库。MIT +
Torchbearer (🥉19 · ⭐ 620 · 💤) - torchbearer: A model fitting library for PyTorch. MIT -- [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 68 · 📦 54 · 📋 240 - 3% open · ⏱️ 26.03.2021): +- [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 68 · 📦 56 · 📋 240 - 3% open · ⏱️ 26.03.2021): ``` git clone https://github.com/pytorchbearer/torchbearer ``` -- [PyPi](https://pypi.org/project/torchbearer) (📥 810 / month): +- [PyPi](https://pypi.org/project/torchbearer) (📥 560 / month): ``` pip install torchbearer ```
-
elegy (🥉17 · ⭐ 270) - Elegy是Jax的与框架无关的Trainer工具。Apache-2 jax +
ThunderGBM (🥉16 · ⭐ 620 · 💤) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 -- [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 14 · 🔀 16 · 📋 64 - 37% open · ⏱️ 13.08.2021): +- [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 80 · 📋 60 - 50% open · ⏱️ 05.01.2021): ``` - git clone https://github.com/poets-ai/elegy + git clone https://github.com/Xtra-Computing/thundergbm ``` -- [PyPi](https://pypi.org/project/elegy) (📥 190 / month): +- [PyPi](https://pypi.org/project/thundergbm) (📥 81 / month): ``` - pip install elegy + pip install thundergbm ```
-
NeoML (🥉16 · ⭐ 650) - neoml是可以用于深度学习和传统机器学习的工具库。Apache-2 +
elegy (🥉16 · ⭐ 300) - Elegy is a framework-agnostic Trainer interface for the Jax.. MIT jax -- [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 23 · 🔀 93 · 📋 44 - 52% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 14 · 🔀 21 · 📋 80 - 22% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/neoml-lib/neoml + git clone https://github.com/poets-ai/elegy + ``` +- [PyPi](https://pypi.org/project/elegy): + ``` + pip install elegy ```
-
ThunderGBM (🥉15 · ⭐ 610 · 💤) - ThunderGBM：GPU上的快速GBDT和随机森林。Apache-2 +
NeoML (🥉15 · ⭐ 660) - Machine learning framework for both deep learning and traditional.. Apache-2 -- [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 79 · 📋 50 - 44% open · ⏱️ 05.01.2021): +- [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 25 · 🔀 97 · 📋 50 - 48% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/Xtra-Computing/thundergbm - ``` -- [PyPi](https://pypi.org/project/thundergbm) (📥 98 / month): - ``` - pip install thundergbm + git clone https://github.com/neoml-lib/neoml ```
-
StarSpace (🥉13 · ⭐ 3.7K · 💀) - 学习embedding嵌入用于分类，检索和排序。MIT +
StarSpace (🥉13 · ⭐ 3.7K · 💀) - Learning embeddings for classification, retrieval and ranking. MIT -- [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 490 · 📋 200 - 24% open · ⏱️ 13.12.2019): +- [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 500 · 📋 200 - 24% open · ⏱️ 13.12.2019): ``` git clone https://github.com/facebookresearch/StarSpace @@ -809,123 +809,135 @@ _通用机器学习和深度学习框架。_

-## 数据可视化 +## Data Visualization -Back to top +Back to top -_通用和特定于任务的数据可视化库。_ +_General-purpose and task-specific data visualization libraries._ -
Matplotlib (🥇40 · ⭐ 14K) - matplotlib：Python绘图工具库。❗Unlicensed +
Seaborn (🥇35 · ⭐ 9K) - Statistical data visualization using matplotlib. BSD-3 -- [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.3K · 🔀 5.9K · 📦 440K · 📋 8K - 17% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 160 · 🔀 1.5K · 📥 210 · 📦 130K · 📋 1.9K - 4% open · ⏱️ 27.11.2021): ``` - git clone https://github.com/matplotlib/matplotlib + git clone https://github.com/mwaskom/seaborn ``` -- [PyPi](https://pypi.org/project/matplotlib) (📥 31M / month): +- [PyPi](https://pypi.org/project/seaborn): ``` - pip install matplotlib + pip install seaborn ``` -- [Conda](https://anaconda.org/conda-forge/matplotlib) (📥 10M · ⏱️ 23.09.2021): +- [Conda](https://anaconda.org/conda-forge/seaborn) (📥 3.2M · ⏱️ 16.08.2021): ``` - conda install -c conda-forge matplotlib + conda install -c conda-forge seaborn ```
-
Seaborn (🥇38 · ⭐ 8.8K) - 使用matplotlib进行统计数据可视化。BSD-3 +
Matplotlib (🥇33 · ⭐ 15K · 📉) - matplotlib: plotting with Python. ❗Unlicensed -- [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 160 · 🔀 1.4K · 📥 190 · 📦 120K · 📋 1.9K - 4% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.3K · 🔀 6K · 📦 470K · 📋 8.2K - 17% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/mwaskom/seaborn + git clone https://github.com/matplotlib/matplotlib ``` -- [PyPi](https://pypi.org/project/seaborn) (📥 16M / month): +- [PyPi](https://pypi.org/project/matplotlib): ``` - pip install seaborn + pip install matplotlib ``` -- [Conda](https://anaconda.org/conda-forge/seaborn) (📥 2.9M · ⏱️ 16.08.2021): +- [Conda](https://anaconda.org/conda-forge/matplotlib) (📥 11M · ⏱️ 13.12.2021): ``` - conda install -c conda-forge seaborn + conda install -c conda-forge matplotlib ```
-
pandas-profiling (🥇33 · ⭐ 8.1K) - 从pandas DataFrame创建HTML分析报告。MIT +
pandas-profiling (🥇33 · ⭐ 8.3K) - Create HTML profiling reports from pandas DataFrame.. MIT -- [GitHub](https://github.com/pandas-profiling/pandas-profiling) (👨‍💻 81 · 🔀 1.2K · 📦 5.4K · 📋 510 - 16% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/pandas-profiling/pandas-profiling) (👨‍💻 83 · 🔀 1.2K · 📦 6.1K · 📋 530 - 17% open · ⏱️ 06.12.2021): ``` git clone https://github.com/pandas-profiling/pandas-profiling ``` -- [PyPi](https://pypi.org/project/pandas-profiling) (📥 11M / month): +- [PyPi](https://pypi.org/project/pandas-profiling) (📥 2.3M / month): ``` pip install pandas-profiling ``` -- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (📥 170K · ⏱️ 28.09.2021): +- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (📥 180K · ⏱️ 28.09.2021): ``` conda install -c conda-forge pandas-profiling ```
-
dash (🥇31 · ⭐ 15K) - 适用于Python，R，Julia和Jupyter的分析型Web应用程序。MIT +
Altair (🥇33 · ⭐ 7.1K) - Declarative statistical visualization library for Python. BSD-3 -- [GitHub](https://github.com/plotly/dash) (👨‍💻 100 · 🔀 1.5K · 📦 150 · 📋 1.1K - 44% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/altair-viz/altair) (👨‍💻 130 · 🔀 600 · 📦 20K · 📋 1.6K - 14% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/plotly/dash + git clone https://github.com/altair-viz/altair ``` -- [PyPi](https://pypi.org/project/dash) (📥 730K / month): +- [PyPi](https://pypi.org/project/altair) (📥 4M / month): ``` - pip install dash + pip install altair ``` -- [Conda](https://anaconda.org/conda-forge/dash) (📥 310K · ⏱️ 21.09.2021): +- [Conda](https://anaconda.org/conda-forge/altair) (📥 1M · ⏱️ 01.04.2020): ``` - conda install -c conda-forge dash + conda install -c conda-forge altair ```
-
Altair (🥇31 · ⭐ 7K) - 用于Python的声明式统计可视化库。BSD-3 +
UMAP (🥇32 · ⭐ 5.3K) - Uniform Manifold Approximation and Projection. BSD-3 -- [GitHub](https://github.com/altair-viz/altair) (👨‍💻 130 · 🔀 590 · 📦 17K · 📋 1.5K - 13% open · ⏱️ 18.08.2021): +- [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 94 · 🔀 560 · 📦 4.2K · 📋 580 - 50% open · ⏱️ 03.12.2021): ``` - git clone https://github.com/altair-viz/altair - ``` -- [PyPi](https://pypi.org/project/altair) (📥 2.9M / month): - ``` - pip install altair + git clone https://github.com/lmcinnes/umap ``` -- [Conda](https://anaconda.org/conda-forge/altair) (📥 940K · ⏱️ 01.04.2020): +- [PyPi](https://pypi.org/project/umap-learn) (📥 1.6M / month): ``` - conda install -c conda-forge altair + pip install umap-learn ```
-
Bokeh (🥈30 · ⭐ 16K) - 浏览器中的Python交互式数据可视化。BSD-3 +
Bokeh (🥈31 · ⭐ 16K) - Interactive Data Visualization in the browser, from Python. BSD-3 -- [GitHub](https://github.com/bokeh/bokeh) (👨‍💻 570 · 🔀 3.7K · 📦 40K · 📋 6.7K - 9% open · ⏱️ 07.10.2021): +- [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): +- [PyPi](https://pypi.org/project/bokeh) (📥 2.1M / month): ``` pip install bokeh ``` -- [Conda](https://anaconda.org/conda-forge/bokeh) (📥 5.6M · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/bokeh) (📥 6.2M · ⏱️ 22.11.2021): ``` conda install -c conda-forge bokeh ```
-
UMAP (🥈30 · ⭐ 5.1K) - 均匀流形逼近和投影。BSD-3 +
dash (🥈31 · ⭐ 16K) - Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript.. MIT -- [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 93 · 🔀 540 · 📦 3.8K · 📋 560 - 50% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/plotly/dash) (👨‍💻 100 · 🔀 1.6K · 📦 160 · 📋 1.1K - 46% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/lmcinnes/umap + git clone https://github.com/plotly/dash ``` -- [PyPi](https://pypi.org/project/umap-learn) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/dash) (📥 840K / month): ``` - pip install umap-learn + pip install dash + ``` +- [Conda](https://anaconda.org/conda-forge/dash) (📥 330K · ⏱️ 21.09.2021): + ``` + conda install -c conda-forge dash + ``` +
+
pyecharts (🥈29 · ⭐ 12K) - Python Echarts Plotting Library. 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 · ⭐ 10K) - 适用于Python的交互式图形库（包括Plotly Express）。MIT +
Plotly (🥈29 · ⭐ 11K) - The interactive graphing library for Python (includes Plotly Express). MIT -- [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 180 · 🔀 1.9K · 📦 5 · 📋 2.1K - 45% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 190 · 🔀 2K · 📦 9 · 📋 2.1K - 46% open · ⏱️ 16.12.2021): ``` git clone https://github.com/plotly/plotly.py @@ -934,138 +946,126 @@ _通用和特定于任务的数据可视化库。_ ``` pip install plotly ``` -- [Conda](https://anaconda.org/conda-forge/plotly) (📥 1.9M · ⏱️ 01.09.2021): +- [Conda](https://anaconda.org/conda-forge/plotly) (📥 2.1M · ⏱️ 15.11.2021): ``` conda install -c conda-forge plotly ``` -- [NPM](https://www.npmjs.com/package/plotlywidget) (📥 44K / month): +- [NPM](https://www.npmjs.com/package/plotlywidget) (📥 59K / month): ``` npm install plotlywidget ```
-
missingno (🥈29 · ⭐ 2.9K) - 在缺失值和混乱数据下，用于数据可视化的python模块。MIT +
missingno (🥈29 · ⭐ 3K) - Missing data visualization module for Python. MIT -- [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 370 · 📦 5.1K · 📋 110 - 8% open · ⏱️ 04.07.2021): +- [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 380 · 📦 5.7K · 📋 110 - 9% open · ⏱️ 04.07.2021): ``` git clone https://github.com/ResidentMario/missingno ``` -- [PyPi](https://pypi.org/project/missingno) (📥 650K / month): +- [PyPi](https://pypi.org/project/missingno) (📥 720K / month): ``` pip install missingno ``` -- [Conda](https://anaconda.org/conda-forge/missingno) (📥 130K · ⏱️ 15.02.2020): +- [Conda](https://anaconda.org/conda-forge/missingno) (📥 140K · ⏱️ 15.02.2020): ``` conda install -c conda-forge missingno ```
-
Graphviz (🥈28 · ⭐ 1.1K) - Graphviz的简单Python界面。MIT - -- [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 15 · 🔀 160 · 📦 24K · 📋 110 - 6% open · ⏱️ 31.07.2021): - - ``` - git clone https://github.com/xflr6/graphviz - ``` -- [PyPi](https://pypi.org/project/graphviz) (📥 7.4M / month): - ``` - pip install graphviz - ``` -
-
data-validation (🥈28 · ⭐ 580) - 用于探索和验证机器学习的库。Apache-2 - -- [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 23 · 🔀 100 · 📥 290 · 📦 330 · 📋 130 - 21% open · ⏱️ 12.10.2021): - - ``` - git clone https://github.com/tensorflow/data-validation - ``` -- [PyPi](https://pypi.org/project/tensorflow-data-validation) (📥 12M / month): - ``` - pip install tensorflow-data-validation - ``` -
-
bqplot (🥈27 · ⭐ 3.2K) - 用于IPython / Jupyter笔记本的绘图库。Apache-2 +
plotnine (🥈27 · ⭐ 2.9K) - A grammar of graphics for Python. ❗️GPL-2.0 -- [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 55 · 🔀 420 · 📦 28 · 📋 540 - 35% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 89 · 🔀 150 · 📦 2.8K · 📋 460 - 16% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/bqplot/bqplot - ``` -- [PyPi](https://pypi.org/project/bqplot) (📥 62K / month): - ``` - pip install bqplot + git clone https://github.com/has2k1/plotnine ``` -- [Conda](https://anaconda.org/conda-forge/bqplot) (📥 810K · ⏱️ 01.10.2021): +- [PyPi](https://pypi.org/project/plotnine) (📥 190K / month): ``` - conda install -c conda-forge bqplot + pip install plotnine ``` -- [NPM](https://www.npmjs.com/package/bqplot) (📥 16K / month): +- [Conda](https://anaconda.org/conda-forge/plotnine) (📥 140K · ⏱️ 25.03.2021): ``` - npm install bqplot + conda install -c conda-forge plotnine ```
-
plotnine (🥈27 · ⭐ 2.8K) - Python的图形语法。❗️GPL-2.0 +
datashader (🥈27 · ⭐ 2.7K) - Quickly and accurately render even the largest data. ❗Unlicensed -- [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 86 · 🔀 140 · 📦 2.5K · 📋 440 - 14% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/holoviz/datashader) (👨‍💻 45 · 🔀 330 · 📦 900 · 📋 480 - 26% open · ⏱️ 29.11.2021): ``` - git clone https://github.com/has2k1/plotnine + git clone https://github.com/holoviz/datashader ``` -- [PyPi](https://pypi.org/project/plotnine) (📥 180K / month): +- [PyPi](https://pypi.org/project/datashader) (📥 63K / month): ``` - pip install plotnine + pip install datashader ``` -- [Conda](https://anaconda.org/conda-forge/plotnine) (📥 130K · ⏱️ 25.03.2021): +- [Conda](https://anaconda.org/conda-forge/datashader) (📥 250K · ⏱️ 10.06.2021): ``` - conda install -c conda-forge plotnine + conda install -c conda-forge datashader ```
-
Cufflinks (🥈27 · ⭐ 2.4K · 💤) - Plotly + Pandas的生产力工具。MIT +
Cufflinks (🥈27 · ⭐ 2.4K · 💤) - Productivity Tools for Plotly + Pandas. MIT -- [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 550 · 📦 4.4K · 📋 200 - 38% open · ⏱️ 25.02.2021): +- [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 560 · 📦 4.8K · 📋 200 - 39% open · ⏱️ 25.02.2021): ``` git clone https://github.com/santosjorge/cufflinks ``` -- [PyPi](https://pypi.org/project/cufflinks) (📥 260K / month): +- [PyPi](https://pypi.org/project/cufflinks) (📥 280K / month): ``` pip install cufflinks ```
-
PyVista (🥈27 · ⭐ 950) - 通过简化的界面进行3D绘图和网格分析。MIT +
PyVista (🥈27 · ⭐ 1K) - 3D plotting and mesh analysis through a streamlined interface for the.. MIT -- [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 61 · 🔀 190 · 📥 320 · 📦 480 · 📋 580 - 29% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 64 · 🔀 200 · 📥 380 · 📦 540 · 📋 640 - 27% open · ⏱️ 15.12.2021): ``` git clone https://github.com/pyvista/pyvista ``` -- [PyPi](https://pypi.org/project/pyvista) (📥 23K / month): +- [PyPi](https://pypi.org/project/pyvista) (📥 36K / month): ``` pip install pyvista ``` -- [Conda](https://anaconda.org/conda-forge/pyvista) (📥 120K · ⏱️ 12.09.2021): +- [Conda](https://anaconda.org/conda-forge/pyvista) (📥 130K · ⏱️ 12.09.2021): ``` conda install -c conda-forge pyvista ```
-
wordcloud (🥈26 · ⭐ 8.4K) - Python中的词云生成器。MIT +
hvPlot (🥈27 · ⭐ 490) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 -- [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 62 · 🔀 2.1K · 📋 440 - 20% open · ⏱️ 15.09.2021): +- [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 33 · 🔀 62 · 📦 940 · 📋 400 - 34% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/amueller/word_cloud + git clone https://github.com/holoviz/hvplot ``` -- [PyPi](https://pypi.org/project/wordcloud) (📥 640K / month): +- [PyPi](https://pypi.org/project/hvplot) (📥 80K / month): ``` - pip install wordcloud + pip install hvplot ``` -- [Conda](https://anaconda.org/conda-forge/wordcloud) (📥 240K · ⏱️ 30.08.2021): +- [Conda](https://anaconda.org/conda-forge/hvplot) (📥 140K · ⏱️ 23.07.2021): + ``` + conda install -c conda-forge hvplot + ``` +
+
wordcloud (🥈26 · ⭐ 8.5K) - A little word cloud generator in Python. MIT + +- [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 64 · 🔀 2.1K · 📋 450 - 20% open · ⏱️ 13.11.2021): + + ``` + git clone https://github.com/amueller/word_cloud + ``` +- [PyPi](https://pypi.org/project/wordcloud) (📥 680K / month): + ``` + pip install wordcloud + ``` +- [Conda](https://anaconda.org/conda-forge/wordcloud) (📥 250K · ⏱️ 15.11.2021): ``` conda install -c conda-forge wordcloud ```
-
Facets Overview (🥈26 · ⭐ 6.7K) - 机器学习数据集的可视化。Apache-2 +
Facets Overview (🥈26 · ⭐ 6.7K · 💤) - Visualizations for machine learning datasets. Apache-2 -- [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 810 · 📦 70 · 📋 150 - 50% open · ⏱️ 06.05.2021): +- [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 820 · 📦 92 · 📋 150 - 50% open · ⏱️ 06.05.2021): ``` git clone https://github.com/pair-code/facets @@ -1075,413 +1075,425 @@ _通用和特定于任务的数据可视化库。_ pip install facets-overview ```
-
datashader (🥈26 · ⭐ 2.6K) - 快速准确地渲染大数据。❗Unlicensed +
bqplot (🥈26 · ⭐ 3.2K) - Plotting library for IPython/Jupyter notebooks. Apache-2 -- [GitHub](https://github.com/holoviz/datashader) (👨‍💻 44 · 🔀 320 · 📦 830 · 📋 480 - 26% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 55 · 🔀 430 · 📦 28 · 📋 550 - 35% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/holoviz/datashader + git clone https://github.com/bqplot/bqplot ``` -- [PyPi](https://pypi.org/project/datashader) (📥 43K / month): +- [PyPi](https://pypi.org/project/bqplot): ``` - pip install datashader + pip install bqplot ``` -- [Conda](https://anaconda.org/conda-forge/datashader) (📥 230K · ⏱️ 10.06.2021): +- [Conda](https://anaconda.org/conda-forge/bqplot) (📥 910K · ⏱️ 01.10.2021): ``` - conda install -c conda-forge datashader + conda install -c conda-forge bqplot + ``` +- [NPM](https://www.npmjs.com/package/bqplot) (📥 26K / month): + ``` + npm install bqplot + ``` +
+
D-Tale (🥈25 · ⭐ 2.9K) - Visualizer for pandas data structures. ❗️LGPL-2.1 + +- [GitHub](https://github.com/man-group/dtale) (👨‍💻 18 · 🔀 220 · 📦 270 · 📋 440 - 8% open · ⏱️ 12.12.2021): + + ``` + git clone https://github.com/man-group/dtale + ``` +- [PyPi](https://pypi.org/project/dtale) (📥 48K / month): + ``` + pip install dtale + ``` +- [Conda](https://anaconda.org/conda-forge/dtale) (📥 100K · ⏱️ 18.11.2021): + ``` + conda install -c conda-forge dtale ```
-
HoloViews (🥈26 · ⭐ 2K) - 使用Holoviews，您的数据可以可视化。BSD-3 +
HoloViews (🥈25 · ⭐ 2.1K) - With Holoviews, your data visualizes itself. BSD-3 -- [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 110 · 🔀 320 · 📋 2.7K - 29% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 120 · 🔀 330 · 📋 2.7K - 29% open · ⏱️ 15.12.2021): ``` git clone https://github.com/holoviz/holoviews ``` -- [PyPi](https://pypi.org/project/holoviews) (📥 170K / month): +- [PyPi](https://pypi.org/project/holoviews): ``` pip install holoviews ``` -- [Conda](https://anaconda.org/conda-forge/holoviews) (📥 580K · ⏱️ 17.09.2021): +- [Conda](https://anaconda.org/conda-forge/holoviews) (📥 620K · ⏱️ 17.09.2021): ``` conda install -c conda-forge holoviews ``` -- [NPM](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (📥 4K / month): +- [NPM](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (📥 3.2K / month): ``` npm install @pyviz/jupyterlab_pyviz ```
-
hvPlot (🥈26 · ⭐ 460) - 用于构建的pandas，dask，xarray和networkx的高级绘图API。BSD-3 +
Perspective (🥉24 · ⭐ 4K) - Streaming pivot visualization via WebAssembly. Apache-2 -- [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 32 · 🔀 61 · 📦 820 · 📋 380 - 32% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/finos/perspective) (👨‍💻 65 · 🔀 410 · 📦 220 · 📋 470 - 12% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/holoviz/hvplot + git clone https://github.com/finos/perspective ``` -- [PyPi](https://pypi.org/project/hvplot) (📥 60K / month): +- [PyPi](https://pypi.org/project/perspective-python) (📥 5.5K / month): ``` - pip install hvplot + pip install perspective-python ``` -- [Conda](https://anaconda.org/conda-forge/hvplot) (📥 130K · ⏱️ 23.07.2021): +- [NPM](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (📥 2.2K / month): ``` - conda install -c conda-forge hvplot + npm install @finos/perspective-jupyterlab ```
-
D-Tale (🥉25 · ⭐ 2.7K) - pandas数据结构的可视化工具。❗️LGPL-2.1 +
VisPy (🥉24 · ⭐ 2.8K) - High-performance interactive 2D/3D data visualization library. ❗Unlicensed -- [GitHub](https://github.com/man-group/dtale) (👨‍💻 18 · 🔀 200 · 📦 240 · 📋 420 - 8% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/vispy/vispy) (👨‍💻 170 · 🔀 570 · 📦 650 · 📋 1.3K - 20% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/man-group/dtale + git clone https://github.com/vispy/vispy ``` -- [PyPi](https://pypi.org/project/dtale) (📥 55K / month): +- [PyPi](https://pypi.org/project/vispy) (📥 45K / month): ``` - pip install dtale + pip install vispy ``` -- [Conda](https://anaconda.org/conda-forge/dtale) (📥 89K · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/conda-forge/vispy) (📥 200K · ⏱️ 24.11.2021): ``` - conda install -c conda-forge dtale + conda install -c conda-forge vispy + ``` +- [NPM](https://www.npmjs.com/package/vispy) (📥 11 / month): + ``` + npm install vispy ```
-
HyperTools (🥉25 · ⭐ 1.7K) - 一个Python工具箱，用于获得对高维的几何洞察力。MIT +
HyperTools (🥉23 · ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT -- [GitHub](https://github.com/ContextLab/hypertools) (👨‍💻 21 · 🔀 150 · 📥 2 · 📦 140 · 📋 190 - 35% open · ⏱️ 19.07.2021): +- [GitHub](https://github.com/ContextLab/hypertools) (👨‍💻 21 · 🔀 160 · 📥 8 · 📦 160 · 📋 190 - 35% open · ⏱️ 19.07.2021): ``` git clone https://github.com/ContextLab/hypertools ``` -- [PyPi](https://pypi.org/project/hypertools) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/hypertools) (📥 990 / month): ``` pip install hypertools ```
-
pyecharts (🥉24 · ⭐ 12K) - Python Echarts绘图库。MIT +
Graphviz (🥉23 · ⭐ 1.1K) - Simple Python interface for Graphviz. MIT -- [GitHub](https://github.com/pyecharts/pyecharts) (👨‍💻 30 · 🔀 2.5K · 📦 1.8K · 📋 1.5K - 1% open · ⏱️ 07.05.2021): +- [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 17 · 🔀 160 · 📦 26K · 📋 120 - 3% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/pyecharts/pyecharts + git clone https://github.com/xflr6/graphviz ``` -- [PyPi](https://pypi.org/project/pyecharts): +- [PyPi](https://pypi.org/project/graphviz): ``` - pip install pyecharts + pip install graphviz ```
-
Perspective (🥉24 · ⭐ 3.6K) - 通过WebAssembly进行流式透视显示。Apache-2 +
Pandas-Bokeh (🥉23 · ⭐ 740 · 💤) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT -- [GitHub](https://github.com/finos/perspective) (👨‍💻 64 · 🔀 390 · 📦 210 · 📋 450 - 13% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 12 · 🔀 93 · 📦 260 · 📋 93 - 29% open · ⏱️ 10.05.2021): ``` - git clone https://github.com/finos/perspective + git clone https://github.com/PatrikHlobil/Pandas-Bokeh ``` -- [PyPi](https://pypi.org/project/perspective-python): +- [PyPi](https://pypi.org/project/pandas-bokeh) (📥 11K / month): ``` - pip install perspective-python + pip install pandas-bokeh ``` -- [NPM](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (📥 1.9K / month): +
+
python-ternary (🥉23 · ⭐ 500) - Ternary plotting library for python with matplotlib. MIT + +- [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 130 · 📥 17 · 📦 76 · 📋 120 - 21% open · ⏱️ 21.10.2021): + ``` - npm install @finos/perspective-jupyterlab + git clone https://github.com/marcharper/python-ternary + ``` +- [PyPi](https://pypi.org/project/python-ternary) (📥 21K / month): + ``` + pip install python-ternary + ``` +- [Conda](https://anaconda.org/conda-forge/python-ternary) (📥 60K · ⏱️ 17.02.2021): + ``` + conda install -c conda-forge python-ternary ```
-
Chartify (🥉24 · ⭐ 3K · 💤) - Python库，使数据科学家可以轻松创建。Apache-2 +
Chartify (🥉22 · ⭐ 3.1K · 💤) - Python library that makes it easy for data scientists to create.. Apache-2 -- [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 260 · 📦 57 · 📋 71 - 57% open · ⏱️ 05.02.2021): +- [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 270 · 📦 61 · 📋 71 - 56% open · ⏱️ 05.02.2021): ``` git clone https://github.com/spotify/chartify ``` -- [PyPi](https://pypi.org/project/chartify) (📥 2.3K / month): +- [PyPi](https://pypi.org/project/chartify): ``` pip install chartify ``` -- [Conda](https://anaconda.org/conda-forge/chartify) (📥 16K · ⏱️ 07.11.2020): +- [Conda](https://anaconda.org/conda-forge/chartify) (📥 17K · ⏱️ 07.11.2020): ``` conda install -c conda-forge chartify ```
-
VisPy (🥉23 · ⭐ 2.7K) - 高性能交互式2D / 3D数据可视化库。❗Unlicensed +
PandasGUI (🥉22 · ⭐ 2.5K) - A GUI for Pandas DataFrames. MIT -- [GitHub](https://github.com/vispy/vispy) (👨‍💻 160 · 🔀 560 · 📦 600 · 📋 1.2K - 26% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 10 · 🔀 150 · 📦 120 · 📋 140 - 22% open · ⏱️ 25.09.2021): ``` - git clone https://github.com/vispy/vispy - ``` -- [PyPi](https://pypi.org/project/vispy): - ``` - pip install vispy - ``` -- [Conda](https://anaconda.org/conda-forge/vispy) (📥 180K · ⏱️ 29.09.2021): - ``` - conda install -c conda-forge vispy + git clone https://github.com/adamerose/pandasgui ``` -- [NPM](https://www.npmjs.com/package/vispy) (📥 15 / month): +- [PyPi](https://pypi.org/project/pandasgui) (📥 9.3K / month): ``` - npm install vispy + pip install pandasgui ```
-
PyQtGraph (🥉23 · ⭐ 2.6K) - 用于科学/工程的快速数据可视化和GUI工具。❗Unlicensed +
openTSNE (🥉22 · ⭐ 930) - Extensible, parallel implementations of t-SNE. BSD-3 -- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (👨‍💻 210 · 🔀 860 · 📋 900 - 29% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 97 · 📦 270 · 📋 98 - 3% open · ⏱️ 25.10.2021): ``` - git clone https://github.com/pyqtgraph/pyqtgraph + git clone https://github.com/pavlin-policar/openTSNE ``` -- [PyPi](https://pypi.org/project/pyqtgraph) (📥 71K / month): +- [PyPi](https://pypi.org/project/opentsne): ``` - pip install pyqtgraph + pip install opentsne ``` -- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (📥 200K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/opentsne) (📥 130K · ⏱️ 13.11.2021): ``` - conda install -c conda-forge pyqtgraph + conda install -c conda-forge opentsne ```
-
PDPbox (🥉23 · ⭐ 620 · 💤) - python部分依赖图工具箱。MIT +
PyQtGraph (🥉21 · ⭐ 2.7K) - Fast data visualization and GUI tools for scientific /.. ❗Unlicensed -- [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 98 · 📦 440 · 📋 55 - 30% open · ⏱️ 14.03.2021): +- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (👨‍💻 210 · 🔀 880 · 📋 950 - 29% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/SauceCat/PDPbox + git clone https://github.com/pyqtgraph/pyqtgraph ``` -- [PyPi](https://pypi.org/project/pdpbox) (📥 87K / month): +- [PyPi](https://pypi.org/project/pyqtgraph): ``` - pip install pdpbox + pip install pyqtgraph ``` -- [Conda](https://anaconda.org/conda-forge/pdpbox) (📥 9.6K · ⏱️ 14.03.2021): +- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (📥 210K · ⏱️ 11.10.2021): ``` - conda install -c conda-forge pdpbox + conda install -c conda-forge pyqtgraph ```
-
python-ternary (🥉23 · ⭐ 480) - 带有matplotlib的python三元绘图库。MIT +
pythreejs (🥉21 · ⭐ 780) - A Jupyter - Three.js bridge. ❗Unlicensed -- [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 120 · 📥 17 · 📦 70 · 📋 110 - 21% open · ⏱️ 24.08.2021): +- [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 29 · 🔀 160 · 📦 19 · 📋 210 - 31% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/marcharper/python-ternary + git clone https://github.com/jupyter-widgets/pythreejs ``` -- [PyPi](https://pypi.org/project/python-ternary) (📥 18K / month): +- [PyPi](https://pypi.org/project/pythreejs) (📥 39K / month): ``` - pip install python-ternary + pip install pythreejs ``` -- [Conda](https://anaconda.org/conda-forge/python-ternary) (📥 59K · ⏱️ 17.02.2021): +- [Conda](https://anaconda.org/conda-forge/pythreejs) (📥 360K · ⏱️ 02.03.2021): ``` - conda install -c conda-forge python-ternary + conda install -c conda-forge pythreejs + ``` +- [NPM](https://www.npmjs.com/package/jupyter-threejs) (📥 6.1K / month): + ``` + npm install jupyter-threejs ```
-
Multicore-TSNE (🥉22 · ⭐ 1.6K · 💀) - 使用Python和Torch并行执行t-SNE。BSD-3 +
data-validation (🥉21 · ⭐ 600) - Library for exploring and validating machine learning.. Apache-2 -- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 180 · 📦 250 · 📋 52 - 61% open · ⏱️ 19.08.2020): +- [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 23 · 🔀 110 · 📥 290 · 📦 360 · 📋 140 - 19% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/DmitryUlyanov/Multicore-TSNE - ``` -- [PyPi](https://pypi.org/project/MulticoreTSNE) (📥 7.8K / month): - ``` - pip install MulticoreTSNE + git clone https://github.com/tensorflow/data-validation ``` -- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (📥 10K · ⏱️ 23.04.2021): +- [PyPi](https://pypi.org/project/tensorflow-data-validation): ``` - conda install -c conda-forge multicore-tsne + pip install tensorflow-data-validation ```
-
openTSNE (🥉22 · ⭐ 890) - t-SNE的可扩展并行实现。BSD-3 +
HiPlot (🥉20 · ⭐ 2.2K) - HiPlot makes understanding high dimensional data easy. MIT -- [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 93 · 📦 250 · 📋 94 - 8% open · ⏱️ 06.06.2021): +- [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 7 · 🔀 100 · 📦 3 · 📋 71 - 14% open · ⏱️ 05.11.2021): ``` - git clone https://github.com/pavlin-policar/openTSNE + git clone https://github.com/facebookresearch/hiplot ``` -- [PyPi](https://pypi.org/project/opentsne): +- [PyPi](https://pypi.org/project/hiplot) (📥 10K / month): ``` - pip install opentsne + pip install hiplot ``` -- [Conda](https://anaconda.org/conda-forge/opentsne) (📥 120K · ⏱️ 09.08.2021): +- [Conda](https://anaconda.org/conda-forge/hiplot) (📥 73K · ⏱️ 05.11.2021): ``` - conda install -c conda-forge opentsne + conda install -c conda-forge hiplot ```
-
Pandas-Bokeh (🥉22 · ⭐ 720) - pandas和GeoPandas的Bokeh绘图后端。MIT +
Sweetviz (🥉20 · ⭐ 1.8K) - Visualize and compare datasets, target values and associations, with one.. MIT -- [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 12 · 🔀 88 · 📦 230 · 📋 89 - 25% open · ⏱️ 10.05.2021): +- [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 180 · 📋 90 - 22% open · ⏱️ 08.07.2021): ``` - git clone https://github.com/PatrikHlobil/Pandas-Bokeh + git clone https://github.com/fbdesignpro/sweetviz ``` -- [PyPi](https://pypi.org/project/pandas-bokeh) (📥 9.1K / month): +- [PyPi](https://pypi.org/project/sweetviz) (📥 60K / month): ``` - pip install pandas-bokeh + pip install sweetviz ```
-
Sweetviz (🥉21 · ⭐ 1.8K) - 可视化和比较数据集，目标值和相关性。MIT +
Multicore-TSNE (🥉20 · ⭐ 1.7K · 💀) - Parallel t-SNE implementation with Python and Torch.. BSD-3 -- [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 180 · 📋 87 - 20% open · ⏱️ 08.07.2021): +- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 190 · 📦 260 · 📋 55 - 61% open · ⏱️ 19.08.2020): ``` - git clone https://github.com/fbdesignpro/sweetviz + git clone https://github.com/DmitryUlyanov/Multicore-TSNE ``` -- [PyPi](https://pypi.org/project/sweetviz) (📥 53K / month): +- [PyPi](https://pypi.org/project/MulticoreTSNE): ``` - pip install sweetviz + pip install MulticoreTSNE + ``` +- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (📥 12K · ⏱️ 09.11.2021): + ``` + conda install -c conda-forge multicore-tsne ```
-
pythreejs (🥉21 · ⭐ 760 · 💤) - Jupyter-Three.js桥。❗Unlicensed +
PDPbox (🥉20 · ⭐ 640 · 💤) - python partial dependence plot toolbox. MIT -- [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 27 · 🔀 160 · 📦 18 · 📋 210 - 30% open · ⏱️ 26.02.2021): +- [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 100 · 📦 460 · 📋 55 - 30% open · ⏱️ 14.03.2021): ``` - git clone https://github.com/jupyter-widgets/pythreejs - ``` -- [PyPi](https://pypi.org/project/pythreejs) (📥 39K / month): - ``` - pip install pythreejs + git clone https://github.com/SauceCat/PDPbox ``` -- [Conda](https://anaconda.org/conda-forge/pythreejs) (📥 340K · ⏱️ 02.03.2021): +- [PyPi](https://pypi.org/project/pdpbox): ``` - conda install -c conda-forge pythreejs + pip install pdpbox ``` -- [NPM](https://www.npmjs.com/package/jupyter-threejs) (📥 7.1K / month): +- [Conda](https://anaconda.org/conda-forge/pdpbox) (📥 10K · ⏱️ 14.03.2021): ``` - npm install jupyter-threejs + conda install -c conda-forge pdpbox ```
-
PandasGUI (🥉20 · ⭐ 2.4K) - pandas Dataframe的GUI。MIT +
PyWaffle (🥉19 · ⭐ 460) - Make Waffle Charts in Python. MIT -- [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 10 · 🔀 150 · 📦 99 · 📋 140 - 22% open · ⏱️ 25.09.2021): +- [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 80 · 📦 100 · 📋 14 - 21% open · ⏱️ 28.07.2021): ``` - git clone https://github.com/adamerose/pandasgui + git clone https://github.com/gyli/PyWaffle ``` -- [PyPi](https://pypi.org/project/pandasgui) (📥 6.7K / month): +- [PyPi](https://pypi.org/project/pywaffle) (📥 2.6K / month): ``` - pip install pandasgui + pip install pywaffle ```
-
lets-plot (🥉20 · ⭐ 690) - 一个用于统计数据的开源绘图库。❗Unlicensed +
pivottablejs (🥉19 · ⭐ 450 · 💀) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. ❗Unlicensed -- [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 16 · 🔀 28 · 📥 110 · 📦 12 · 📋 200 - 34% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 61 · 📦 210 · 📋 56 - 28% open · ⏱️ 04.12.2018): ``` - git clone https://github.com/JetBrains/lets-plot + git clone https://github.com/nicolaskruchten/jupyter_pivottablejs ``` -- [PyPi](https://pypi.org/project/lets-plot) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/pivottablejs) (📥 17K / month): ``` - pip install lets-plot + pip install pivottablejs ```
-
ivis (🥉20 · ⭐ 250) - 使用算法对非常大的数据集进行降维。Apache-2 +
ivis (🥉19 · ⭐ 250) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 -- [GitHub](https://github.com/beringresearch/ivis) (👨‍💻 10 · 🔀 26 · 📦 17 · 📋 50 - 4% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/beringresearch/ivis) (👨‍💻 10 · 🔀 26 · 📦 19 · 📋 53 - 5% open · ⏱️ 08.11.2021): ``` git clone https://github.com/beringresearch/ivis ``` -- [PyPi](https://pypi.org/project/ivis) (📥 390 / month): +- [PyPi](https://pypi.org/project/ivis) (📥 890 / month): ``` pip install ivis ```
-
HiPlot (🥉19 · ⭐ 2.2K) - HiPlot使理解高维数据变得容易。MIT +
FiftyOne (🥉18 · ⭐ 860) - Visualize, create, and debug image and video datasets.. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 6 · 🔀 100 · 📦 3 · 📋 68 - 13% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 20 · 🔀 98 · 📦 64 · 📋 600 - 30% open · ⏱️ 30.11.2021): ``` - git clone https://github.com/facebookresearch/hiplot - ``` -- [PyPi](https://pypi.org/project/hiplot): - ``` - pip install hiplot + git clone https://github.com/voxel51/fiftyone ``` -- [Conda](https://anaconda.org/conda-forge/hiplot) (📥 67K · ⏱️ 08.10.2021): +- [PyPi](https://pypi.org/project/fiftyone): ``` - conda install -c conda-forge hiplot + pip install fiftyone ```
-
joypy (🥉19 · ⭐ 350) - 带有matplotlib和pandas的Python中的Joyplots。MIT +
animatplot (🥉18 · ⭐ 380 · 💀) - A python package for animating plots build on matplotlib. MIT -- [GitHub](https://github.com/leotac/joypy) (👨‍💻 5 · 🔀 39 · 📦 96 · 📋 44 - 18% open · ⏱️ 13.06.2021): +- [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 35 · 📦 29 · 📋 30 - 43% open · ⏱️ 05.10.2020): ``` - git clone https://github.com/sbebo/joypy + git clone https://github.com/t-makaro/animatplot ``` -- [PyPi](https://pypi.org/project/joypy) (📥 20K / month): +- [PyPi](https://pypi.org/project/animatplot) (📥 270 / month): ``` - pip install joypy + pip install animatplot ``` -- [Conda](https://anaconda.org/conda-forge/joypy) (📥 11K · ⏱️ 28.12.2020): +- [Conda](https://anaconda.org/conda-forge/animatplot) (📥 7.2K · ⏱️ 06.10.2020): ``` - conda install -c conda-forge joypy + conda install -c conda-forge animatplot ```
-
animatplot (🥉18 · ⭐ 380 · 💤) - 用于在patpliblib上构建动画图的python程序包。MIT +
joypy (🥉18 · ⭐ 370) - Joyplots in Python with matplotlib & pandas. MIT -- [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 34 · 📦 28 · 📋 30 - 46% open · ⏱️ 05.10.2020): +- [GitHub](https://github.com/leotac/joypy) (👨‍💻 5 · 🔀 43 · 📦 110 · 📋 45 - 20% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/t-makaro/animatplot + git clone https://github.com/sbebo/joypy ``` -- [PyPi](https://pypi.org/project/animatplot) (📥 520 / month): +- [PyPi](https://pypi.org/project/joypy): ``` - pip install animatplot + pip install joypy ``` -- [Conda](https://anaconda.org/conda-forge/animatplot) (📥 6.8K · ⏱️ 06.10.2020): +- [Conda](https://anaconda.org/conda-forge/joypy) (📥 12K · ⏱️ 28.12.2020): ``` - conda install -c conda-forge animatplot + conda install -c conda-forge joypy ```
-
vega (🥉18 · ⭐ 310) - 适用于Vega和Vega-Lite的IPython/Jupyter笔记本模块。BSD-3 +
vega (🥉18 · ⭐ 320) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 -- [GitHub](https://github.com/vega/ipyvega) (👨‍💻 10 · 🔀 51 · 📋 91 - 12% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/vega/ipyvega) (👨‍💻 10 · 🔀 52 · 📋 92 - 11% open · ⏱️ 02.12.2021): ``` git clone https://github.com/vega/ipyvega ``` -- [PyPi](https://pypi.org/project/vega) (📥 24K / month): +- [PyPi](https://pypi.org/project/vega) (📥 21K / month): ``` pip install vega ``` -- [Conda](https://anaconda.org/conda-forge/vega) (📥 460K · ⏱️ 11.08.2021): +- [Conda](https://anaconda.org/conda-forge/vega) (📥 470K · ⏱️ 18.11.2021): ``` conda install -c conda-forge vega ```
-
FiftyOne (🥉17 · ⭐ 670) - 可视化，创建和调试图像和视频数据集。❗Unlicensed +
lets-plot (🥉17 · ⭐ 700) - An open-source plotting library for statistical data. ❗Unlicensed -- [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 18 · 🔀 80 · 📦 24 · 📋 530 - 29% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 16 · 🔀 29 · 📥 140 · 📦 12 · 📋 220 - 32% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/voxel51/fiftyone + git clone https://github.com/JetBrains/lets-plot ``` -- [PyPi](https://pypi.org/project/fiftyone): +- [PyPi](https://pypi.org/project/lets-plot): ``` - pip install fiftyone + pip install lets-plot ```
-
pdvega (🥉17 · ⭐ 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 · 🔀 31 · 📦 52 · 📋 26 - 61% open · ⏱️ 29.03.2019): +- [GitHub](https://github.com/altair-viz/pdvega) (👨‍💻 9 · 🔀 30 · 📦 59 · 📋 26 - 61% open · ⏱️ 29.03.2019): ``` git clone https://github.com/altair-viz/pdvega ``` -- [PyPi](https://pypi.org/project/pdvega) (📥 210 / month): +- [PyPi](https://pypi.org/project/pdvega) (📥 140 / month): ``` pip install pdvega ```
-
PyWaffle (🥉16 · ⭐ 450) - 用Python作图。MIT - -- [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 76 · 📦 87 · 📋 14 - 21% open · ⏱️ 28.07.2021): - - ``` - git clone https://github.com/gyli/PyWaffle - ``` -- [PyPi](https://pypi.org/project/pywaffle): - ``` - pip install pywaffle - ``` -
-
AutoViz (🥉15 · ⭐ 510) - 自动显示任意行的任何大小的任何数据集。Apache-2 +
AutoViz (🥉15 · ⭐ 580) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 -- [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 10 · 🔀 81 · 📦 100 · 📋 32 - 12% open · ⏱️ 27.08.2021): +- [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 11 · 🔀 86 · 📦 120 · 📋 41 - 17% open · ⏱️ 13.12.2021): ``` git clone https://github.com/AutoViML/AutoViz @@ -1491,21 +1503,21 @@ _通用和特定于任务的数据可视化库。_ pip install autoviz ```
-
pivottablejs (🥉15 · ⭐ 450 · 💀) - Jupyter/IPython的Dragndrop数据透视表和图表。❗Unlicensed +
nx-altair (🥉15 · ⭐ 180 · 💀) - Draw interactive NetworkX graphs with Altair. MIT -- [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 59 · 📦 200 · 📋 56 - 30% open · ⏱️ 04.12.2018): +- [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 22 · 📋 10 - 60% open · ⏱️ 02.06.2020): ``` - git clone https://github.com/nicolaskruchten/jupyter_pivottablejs + git clone https://github.com/Zsailer/nx_altair ``` -- [PyPi](https://pypi.org/project/pivottablejs): +- [PyPi](https://pypi.org/project/nx-altair) (📥 3.1K / month): ``` - pip install pivottablejs + pip install nx-altair ```
-
data-describe (🥉12 · ⭐ 280 · 💤) - 数据描述：Pythonic EDA数据科学加速器。❗Unlicensed +
data-describe (🥉13 · ⭐ 290) - datadescribe: Pythonic EDA Accelerator for Data Science. ❗Unlicensed -- [GitHub](https://github.com/data-describe/data-describe) (👨‍💻 14 · 🔀 15 · 📋 240 - 28% open · ⏱️ 02.03.2021): +- [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 @@ -1515,258 +1527,250 @@ _通用和特定于任务的数据可视化库。_ pip install data-describe ```
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nptsne (🥉12 · ⭐ 25 · 💤) - nptsne是numpy兼容的python二进制包。Apache-2 +
nptsne (🥉11 · ⭐ 27 · 💤) - 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): ``` git clone https://github.com/biovault/nptsne ``` -- [PyPi](https://pypi.org/project/nptsne) (📥 59 / month): +- [PyPi](https://pypi.org/project/nptsne): ``` pip install nptsne ```
-
nx-altair (🥉10 · ⭐ 170 · 💀) - 使用Altair绘制交互式NetworkX图形。MIT - -- [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 20 · 📋 10 - 60% open · ⏱️ 02.06.2020): - - ``` - git clone https://github.com/Zsailer/nx_altair - ``` -- [PyPi](https://pypi.org/project/nx-altair): - ``` - pip install nx-altair - ``` -

-## 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 (🥇37 · ⭐ 52K) - transformers：先进的自然语言模型库。Apache-2 +
transformers (🥇38 · ⭐ 56K) - Transformers: State-of-the-art Natural Language.. Apache-2 -- [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1K · 🔀 12K · 📥 1.4K · 📦 17K · 📋 7.9K - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1.1K · 🔀 13K · 📥 1.4K · 📦 20K · 📋 8.3K - 3% open · ⏱️ 16.12.2021): ``` git clone https://github.com/huggingface/transformers ``` -- [PyPi](https://pypi.org/project/transformers) (📥 3M / month): +- [PyPi](https://pypi.org/project/transformers) (📥 3.2M / month): ``` pip install transformers ``` -- [Conda](https://anaconda.org/conda-forge/transformers) (📥 75K · ⏱️ 01.10.2021): +- [Conda](https://anaconda.org/conda-forge/transformers) (📥 87K · ⏱️ 16.12.2021): ``` conda install -c conda-forge transformers ```
-
gensim (🥇36 · ⭐ 13K) - 主题模型工具库。❗️LGPL-2.1 +
spaCy (🥇38 · ⭐ 22K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT -- [GitHub](https://github.com/RaRe-Technologies/gensim) (👨‍💻 410 · 🔀 3.9K · 📥 3.5K · 📦 27K · 📋 1.7K - 20% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/explosion/spaCy) (👨‍💻 640 · 🔀 3.6K · 📥 3.1K · 📦 33K · 📋 5K - 1% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/RaRe-Technologies/gensim + git clone https://github.com/explosion/spaCy ``` -- [PyPi](https://pypi.org/project/gensim) (📥 14M / month): +- [PyPi](https://pypi.org/project/spacy) (📥 5.9M / month): ``` - pip install gensim + pip install spacy ``` -- [Conda](https://anaconda.org/conda-forge/gensim) (📥 730K · ⏱️ 20.09.2021): +- [Conda](https://anaconda.org/conda-forge/spacy) (📥 2.5M · ⏱️ 14.12.2021): ``` - conda install -c conda-forge gensim + conda install -c conda-forge spacy ```
-
spaCy (🥇35 · ⭐ 21K) - Python中的工业级自然语言处理（NLP）工具包。MIT +
gensim (🥇36 · ⭐ 13K) - Topic Modelling for Humans. ❗️LGPL-2.1 -- [GitHub](https://github.com/explosion/spaCy) (👨‍💻 630 · 🔀 3.5K · 📥 3.1K · 📦 31K · 📋 4.9K - 1% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/RaRe-Technologies/gensim) (👨‍💻 420 · 🔀 3.9K · 📥 3.5K · 📦 29K · 📋 1.7K - 20% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/explosion/spaCy + git clone https://github.com/RaRe-Technologies/gensim ``` -- [PyPi](https://pypi.org/project/spacy): +- [PyPi](https://pypi.org/project/gensim) (📥 10M / month): ``` - pip install spacy + pip install gensim ``` -- [Conda](https://anaconda.org/conda-forge/spacy) (📥 2.3M · ⏱️ 21.09.2021): +- [Conda](https://anaconda.org/conda-forge/gensim) (📥 760K · ⏱️ 09.11.2021): ``` - conda install -c conda-forge spacy + conda install -c conda-forge gensim ```
-
nltk (🥇33 · ⭐ 10K) - 用于符号和统计自然的库和程序套件。Apache-2 +
nltk (🥇33 · ⭐ 10K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 -- [GitHub](https://github.com/nltk/nltk) (👨‍💻 400 · 🔀 2.4K · 📦 120K · 📋 1.5K - 13% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/nltk/nltk) (👨‍💻 410 · 🔀 2.4K · 📦 120K · 📋 1.6K - 12% open · ⏱️ 16.12.2021): ``` git clone https://github.com/nltk/nltk ``` -- [PyPi](https://pypi.org/project/nltk) (📥 9.6M / month): +- [PyPi](https://pypi.org/project/nltk) (📥 9.5M / month): ``` pip install nltk ``` -- [Conda](https://anaconda.org/conda-forge/nltk) (📥 940K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/nltk) (📥 1.1M · ⏱️ 11.10.2021): ``` conda install -c conda-forge nltk ```
-
ChatterBot (🥇32 · ⭐ 12K) - ChatterBot是机器学习的对话引擎。BSD-3 +
AllenNLP (🥇32 · ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 -- [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 3.8K · 📦 3.9K · 📋 1.5K - 17% open · ⏱️ 01.06.2021): +- [GitHub](https://github.com/allenai/allennlp) (👨‍💻 250 · 🔀 2.1K · 📥 43 · 📦 2.1K · 📋 2.5K - 3% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/gunthercox/ChatterBot + git clone https://github.com/allenai/allennlp ``` -- [PyPi](https://pypi.org/project/chatterbot) (📥 70K / month): +- [PyPi](https://pypi.org/project/allennlp) (📥 37K / month): ``` - pip install chatterbot + pip install allennlp ```
-
AllenNLP (🥇32 · ⭐ 11K) - 基于PyTorch的开源NLP研究库。Apache-2 +
fastText (🥇31 · ⭐ 23K · 💀) - Library for fast text representation and classification. MIT -- [GitHub](https://github.com/allenai/allennlp) (👨‍💻 250 · 🔀 2.1K · 📥 43 · 📦 2K · 📋 2.4K - 3% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 58 · 🔀 4.3K · 📦 2.4K · 📋 1K - 40% open · ⏱️ 18.07.2020): ``` - git clone https://github.com/allenai/allennlp + git clone https://github.com/facebookresearch/fastText ``` -- [PyPi](https://pypi.org/project/allennlp) (📥 39K / month): +- [PyPi](https://pypi.org/project/fasttext) (📥 470K / month): ``` - pip install allennlp + pip install fasttext + ``` +- [Conda](https://anaconda.org/conda-forge/fasttext) (📥 25K · ⏱️ 08.11.2021): + ``` + conda install -c conda-forge fasttext + ``` +
+
ChatterBot (🥇31 · ⭐ 12K) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 + +- [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 3.8K · 📦 4K · 📋 1.5K - 18% open · ⏱️ 01.06.2021): + + ``` + git clone https://github.com/gunthercox/ChatterBot + ``` +- [PyPi](https://pypi.org/project/chatterbot) (📥 33K / month): + ``` + pip install chatterbot ```
-
fuzzywuzzy (🥇31 · ⭐ 8.5K) - Python中的模糊字符串匹配。❗️GPL-2.0 +
fuzzywuzzy (🥇31 · ⭐ 8.6K) - Fuzzy String Matching in Python. ❗️GPL-2.0 -- [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 860 · 📦 10K · 📋 180 - 43% open · ⏱️ 09.09.2021): +- [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 860 · 📦 11K · 📋 180 - 43% open · ⏱️ 09.09.2021): ``` git clone https://github.com/seatgeek/fuzzywuzzy ``` -- [PyPi](https://pypi.org/project/fuzzywuzzy) (📥 4.9M / month): +- [PyPi](https://pypi.org/project/fuzzywuzzy) (📥 5.3M / month): ``` pip install fuzzywuzzy ``` -- [Conda](https://anaconda.org/conda-forge/fuzzywuzzy) (📥 330K · ⏱️ 18.11.2020): +- [Conda](https://anaconda.org/conda-forge/fuzzywuzzy) (📥 340K · ⏱️ 18.11.2020): ``` conda install -c conda-forge fuzzywuzzy ```
-
sentence-transformers (🥇31 · ⭐ 6.2K) - BERT和XLNet的句子嵌入。Apache-2 +
sentence-transformers (🥇31 · ⭐ 6.7K) - Sentence Embeddings with BERT & XLNet. Apache-2 -- [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 64 · 🔀 1.2K · 📦 1.7K · 📋 1.1K - 49% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 67 · 🔀 1.3K · 📦 2.1K · 📋 1.2K - 49% open · ⏱️ 15.12.2021): ``` git clone https://github.com/UKPLab/sentence-transformers ``` -- [PyPi](https://pypi.org/project/sentence-transformers) (📥 530K / month): +- [PyPi](https://pypi.org/project/sentence-transformers) (📥 560K / month): ``` pip install sentence-transformers ```
-
sentencepiece (🥇31 · ⭐ 5.4K) - 用于基于神经网络的文本的预处理器。Apache-2 +
sentencepiece (🥇31 · ⭐ 5.5K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 -- [GitHub](https://github.com/google/sentencepiece) (👨‍💻 57 · 🔀 720 · 📥 17K · 📦 10K · 📋 480 - 8% open · ⏱️ 02.07.2021): +- [GitHub](https://github.com/google/sentencepiece) (👨‍💻 57 · 🔀 730 · 📥 19K · 📦 12K · 📋 490 - 9% open · ⏱️ 02.07.2021): ``` git clone https://github.com/google/sentencepiece ``` -- [PyPi](https://pypi.org/project/sentencepiece) (📥 2.7M / month): +- [PyPi](https://pypi.org/project/sentencepiece) (📥 3.3M / month): ``` pip install sentencepiece ``` -- [Conda](https://anaconda.org/conda-forge/sentencepiece) (📥 100K · ⏱️ 09.02.2021): +- [Conda](https://anaconda.org/conda-forge/sentencepiece) (📥 130K · ⏱️ 05.11.2021): ``` conda install -c conda-forge sentencepiece ```
-
fastText (🥈30 · ⭐ 23K · 💀) - 用于快速文本表示和分类的库。MIT +
flair (🥈30 · ⭐ 11K) - A very simple framework for state-of-the-art Natural Language.. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 58 · 🔀 4.2K · 📦 2.2K · 📋 990 - 39% open · ⏱️ 18.07.2020): +- [GitHub](https://github.com/flairNLP/flair) (👨‍💻 210 · 🔀 1.5K · 📦 1.1K · 📋 1.7K - 4% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/facebookresearch/fastText - ``` -- [PyPi](https://pypi.org/project/fasttext) (📥 400K / month): - ``` - pip install fasttext + git clone https://github.com/flairNLP/flair ``` -- [Conda](https://anaconda.org/conda-forge/fasttext) (📥 23K · ⏱️ 06.08.2021): +- [PyPi](https://pypi.org/project/flair) (📥 67K / month): ``` - conda install -c conda-forge fasttext + pip install flair ```
-
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 +
TextBlob (🥈30 · ⭐ 8K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT -- [GitHub](https://github.com/flairNLP/flair) (👨‍💻 210 · 🔀 1.4K · 📦 980 · 📋 1.7K - 4% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/sloria/TextBlob) (👨‍💻 35 · 🔀 1K · 📥 97 · 📦 16K · 📋 240 - 36% open · ⏱️ 22.10.2021): ``` - git clone https://github.com/flairNLP/flair + git clone https://github.com/sloria/TextBlob ``` -- [PyPi](https://pypi.org/project/flair) (📥 100K / month): +- [PyPi](https://pypi.org/project/textblob) (📥 820K / month): ``` - pip install flair + pip install textblob + ``` +- [Conda](https://anaconda.org/conda-forge/textblob) (📥 150K · ⏱️ 24.02.2019): + ``` + conda install -c conda-forge textblob ```
-
ParlAI (🥈29 · ⭐ 8.4K) - 一个用于训练和评估AI模型的框架。MIT +
ParlAI (🥈29 · ⭐ 8.5K) - A framework for training and evaluating AI models on a variety of.. MIT -- [GitHub](https://github.com/facebookresearch/ParlAI) (👨‍💻 160 · 🔀 1.6K · 📦 46 · 📋 1.1K - 8% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/facebookresearch/ParlAI) (👨‍💻 170 · 🔀 1.7K · 📦 54 · 📋 1.2K - 7% open · ⏱️ 15.12.2021): ``` git clone https://github.com/facebookresearch/ParlAI ``` -- [PyPi](https://pypi.org/project/parlai) (📥 3K / month): +- [PyPi](https://pypi.org/project/parlai) (📥 2.3K / month): ``` pip install parlai ```
-
DeepPavlov (🥈28 · ⭐ 5.4K) - 一个用于深度学习端到端对话的开源库。Apache-2 +
DeepPavlov (🥈28 · ⭐ 5.5K) - An open source library for deep learning end-to-end dialog.. Apache-2 -- [GitHub](https://github.com/deepmipt/DeepPavlov) (👨‍💻 67 · 🔀 970 · 📦 220 · 📋 590 - 21% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/deepmipt/DeepPavlov) (👨‍💻 67 · 🔀 970 · 📦 240 · 📋 600 - 16% open · ⏱️ 28.09.2021): ``` git clone https://github.com/deepmipt/DeepPavlov ``` -- [PyPi](https://pypi.org/project/deeppavlov) (📥 10K / month): +- [PyPi](https://pypi.org/project/deeppavlov) (📥 11K / month): ``` pip install deeppavlov ```
-
OpenNMT (🥈28 · ⭐ 5.3K) - PyTorch中的开源神经机器翻译。MIT - -- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 170 · 🔀 1.8K · 📦 110 · 📋 1.3K - 7% open · ⏱️ 06.10.2021): - - ``` - git clone https://github.com/OpenNMT/OpenNMT-py - ``` -- [PyPi](https://pypi.org/project/OpenNMT-py) (📥 4.6K / month): - ``` - pip install OpenNMT-py - ``` -
-
Tokenizers (🥈28 · ⭐ 4.9K) - 针对研究和应用进行了优化的快速最先进的分词器。Apache-2 +
Tokenizers (🥈28 · ⭐ 5.1K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 -- [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 46 · 🔀 390 · 📦 38 · 📋 510 - 26% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 46 · 🔀 410 · 📦 38 · 📋 530 - 27% open · ⏱️ 15.12.2021): ``` git clone https://github.com/huggingface/tokenizers ``` -- [PyPi](https://pypi.org/project/tokenizers) (📥 3.5M / month): +- [PyPi](https://pypi.org/project/tokenizers) (📥 3.8M / month): ``` pip install tokenizers ``` -- [Conda](https://anaconda.org/conda-forge/tokenizers) (📥 92K · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/tokenizers) (📥 110K · ⏱️ 22.09.2021): ``` conda install -c conda-forge tokenizers ```
-
ftfy (🥈28 · ⭐ 3.1K) - 修复Unicode文本中的故障功能的工具库。MIT +
ftfy (🥈28 · ⭐ 3.1K · 💤) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT -- [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 100 · 📦 4K · 📋 120 - 6% open · ⏱️ 17.05.2021): +- [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 100 · 📦 4.5K · 📋 120 - 9% open · ⏱️ 17.05.2021): ``` git clone https://github.com/LuminosoInsight/python-ftfy ``` -- [PyPi](https://pypi.org/project/ftfy) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/ftfy) (📥 970K / month): ``` pip install ftfy ``` @@ -1775,205 +1779,213 @@ _用于处理，清理，处理和分析文本数据的库，以及用于NLP任 conda install -c conda-forge ftfy ```
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TextBlob (🥈27 · ⭐ 7.9K) - 包含情感分析、词性标注等等功能的NLP工具库。MIT +
GluonNLP (🥈27 · ⭐ 2.3K) - Toolkit that enables easy text preprocessing, datasets loading.. Apache-2 -- [GitHub](https://github.com/sloria/TextBlob) (👨‍💻 34 · 🔀 1K · 📥 96 · 📦 15K · 📋 240 - 35% open · ⏱️ 10.05.2021): +- [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 680 · 📋 530 - 44% open · ⏱️ 24.08.2021): ``` - git clone https://github.com/sloria/TextBlob - ``` -- [PyPi](https://pypi.org/project/textblob): - ``` - pip install textblob + git clone https://github.com/dmlc/gluon-nlp ``` -- [Conda](https://anaconda.org/conda-forge/textblob) (📥 140K · ⏱️ 24.02.2019): +- [PyPi](https://pypi.org/project/gluonnlp) (📥 160K / month): ``` - conda install -c conda-forge textblob + pip install gluonnlp ```
-
spark-nlp (🥈27 · ⭐ 2.4K) - 最先进的自然语言处理。Apache-2 +
Dedupe (🥈26 · ⭐ 3.2K) - A python library for accurate and scalable fuzzy matching, record.. MIT -- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 99 · 🔀 490 · 📋 560 - 13% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/dedupeio/dedupe) (👨‍💻 61 · 🔀 440 · 📦 210 · 📋 670 - 9% open · ⏱️ 14.10.2021): ``` - git clone https://github.com/JohnSnowLabs/spark-nlp + git clone https://github.com/dedupeio/dedupe ``` -- [PyPi](https://pypi.org/project/spark-nlp) (📥 1.2M / month): +- [PyPi](https://pypi.org/project/dedupe) (📥 250K / month): ``` - pip install spark-nlp + pip install dedupe ```
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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 +
TextDistance (🥈26 · ⭐ 2.6K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT -- [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 600 · 📋 530 - 43% open · ⏱️ 24.08.2021): +- [GitHub](https://github.com/life4/textdistance) (👨‍💻 11 · 🔀 200 · 📥 410 · 📦 1.4K · ⏱️ 29.11.2021): ``` - git clone https://github.com/dmlc/gluon-nlp - ``` -- [PyPi](https://pypi.org/project/gluonnlp) (📥 140K / month): - ``` - pip install gluonnlp + git clone https://github.com/life4/textdistance ``` -
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Dedupe (🥈26 · ⭐ 3.2K) - 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) (👨‍💻 59 · 🔀 430 · 📦 200 · 📋 660 - 9% open · ⏱️ 03.09.2021): - +- [PyPi](https://pypi.org/project/textdistance) (📥 280K / month): ``` - git clone https://github.com/dedupeio/dedupe + pip install textdistance ``` -- [PyPi](https://pypi.org/project/dedupe) (📥 230K / month): +- [Conda](https://anaconda.org/conda-forge/textdistance) (📥 67K · ⏱️ 27.10.2021): ``` - pip install dedupe + conda install -c conda-forge textdistance ```
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spacy-transformers (🥈26 · ⭐ 1K) - 使用经过预训练的transformer模型，例如BERT，XLNet和GPT-2。MIT spacy +
spacy-transformers (🥈26 · ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy -- [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 17 · 🔀 120 · 📦 290 · ⏱️ 12.10.2021): +- [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 18 · 🔀 130 · 📦 340 · ⏱️ 16.12.2021): ``` git clone https://github.com/explosion/spacy-transformers ``` -- [PyPi](https://pypi.org/project/spacy-transformers) (📥 70K / month): +- [PyPi](https://pypi.org/project/spacy-transformers) (📥 85K / month): ``` pip install spacy-transformers ```
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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 +
Rasa (🥈25 · ⭐ 13K) - Open source machine learning framework to automate text- and voice-.. Apache-2 -- [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 500 · 🔀 3.6K · 📋 5.9K - 12% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 520 · 🔀 3.7K · 📋 6.3K - 13% open · ⏱️ 16.12.2021): ``` git clone https://github.com/RasaHQ/rasa ``` -- [PyPi](https://pypi.org/project/rasa) (📥 210K / month): +- [PyPi](https://pypi.org/project/rasa) (📥 230K / month): ``` pip install rasa ```
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Ciphey (🥈25 · ⭐ 8.5K) - 在不知道密钥或密码的情况下自动解密加密。MIT +
OpenNMT (🥈25 · ⭐ 5.4K) - Open Source Neural Machine Translation in PyTorch. MIT -- [GitHub](https://github.com/Ciphey/Ciphey) (👨‍💻 46 · 🔀 500 · 📋 260 - 18% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 170 · 🔀 1.9K · 📦 120 · 📋 1.3K - 6% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/Ciphey/Ciphey - ``` -- [PyPi](https://pypi.org/project/ciphey) (📥 16K / month): - ``` - pip install ciphey + git clone https://github.com/OpenNMT/OpenNMT-py ``` -- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (📥 12K · ⭐ 5 · ⏱️ 06.06.2021): +- [PyPi](https://pypi.org/project/OpenNMT-py): ``` - docker pull remnux/ciphey + pip install OpenNMT-py ```
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Sumy (🥈25 · ⭐ 2.7K) - 自动汇总文本文档和HTML页面的模块。Apache-2 +
haystack (🥈25 · ⭐ 3.4K) - End-to-end Python framework for building natural language search.. Apache-2 -- [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 21 · 🔀 450 · 📦 930 · 📋 93 - 16% open · ⏱️ 17.06.2021): +- [GitHub](https://github.com/deepset-ai/haystack) (👨‍💻 87 · 🔀 580 · 📦 94 · 📋 1K - 13% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/miso-belica/sumy + git clone https://github.com/deepset-ai/haystack ``` -- [PyPi](https://pypi.org/project/sumy) (📥 26K / month): +- [PyPi](https://pypi.org/project/haystack) (📥 1.5K / month): ``` - pip install sumy + pip install haystack ```
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TextDistance (🥈25 · ⭐ 2.5K) - 计算序列之间的距离，包含30多种算法。MIT +
neuralcoref (🥈25 · ⭐ 2.5K) - Fast Coreference Resolution in spaCy with Neural Networks. MIT -- [GitHub](https://github.com/life4/textdistance) (👨‍💻 11 · 🔀 200 · 📥 240 · 📦 1.1K · ⏱️ 29.07.2021): +- [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 420 · 📥 300 · 📦 430 · 📋 290 - 20% open · ⏱️ 22.06.2021): ``` - git clone https://github.com/life4/textdistance + git clone https://github.com/huggingface/neuralcoref ``` -- [PyPi](https://pypi.org/project/textdistance) (📥 230K / month): +- [PyPi](https://pypi.org/project/neuralcoref) (📥 53K / month): ``` - pip install textdistance + pip install neuralcoref ``` -- [Conda](https://anaconda.org/conda-forge/textdistance) (📥 56K · ⏱️ 29.01.2021): +- [Conda](https://anaconda.org/conda-forge/neuralcoref) (📥 10K · ⏱️ 21.02.2020): ``` - conda install -c conda-forge textdistance + conda install -c conda-forge neuralcoref ```
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haystack (🥈25 · ⭐ 2.5K) - 用于构建自然语言搜索的端到端Python框架。Apache-2 +
fastNLP (🥈25 · ⭐ 2.4K) - fastNLP: A Modularized and Extensible NLP Framework. Currently still.. Apache-2 -- [GitHub](https://github.com/deepset-ai/haystack) (👨‍💻 72 · 🔀 500 · 📦 89 · 📋 900 - 14% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 54 · 🔀 400 · 📥 65 · 📦 52 · 📋 180 - 19% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/deepset-ai/haystack + git clone https://github.com/fastnlp/fastNLP ``` -- [PyPi](https://pypi.org/project/haystack) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/fastnlp) (📥 1.7K / month): ``` - pip install haystack + pip install fastnlp ```
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CLTK (🥈25 · ⭐ 690) - 古典语言工具包。MIT +
jellyfish (🥈25 · ⭐ 1.6K) - a python library for doing approximate and phonetic matching of.. BSD-2 -- [GitHub](https://github.com/cltk/cltk) (👨‍💻 110 · 🔀 300 · 📥 22 · 📦 180 · 📋 510 - 24% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/jamesturk/jellyfish) (👨‍💻 25 · 🔀 140 · 📦 3K · 📋 110 - 8% open · ⏱️ 16.11.2021): ``` - git clone https://github.com/cltk/cltk + git clone https://github.com/jamesturk/jellyfish ``` -- [PyPi](https://pypi.org/project/cltk) (📥 1.6K / month): +- [PyPi](https://pypi.org/project/jellyfish) (📥 1.7M / month): ``` - pip install cltk + pip install jellyfish + ``` +- [Conda](https://anaconda.org/conda-forge/jellyfish) (📥 160K · ⏱️ 15.12.2021): + ``` + conda install -c conda-forge jellyfish + ``` +
+
Ciphey (🥈24 · ⭐ 9.1K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT + +- [GitHub](https://github.com/Ciphey/Ciphey) (👨‍💻 46 · 🔀 560 · 📋 270 - 15% open · ⏱️ 03.11.2021): + + ``` + git clone https://github.com/Ciphey/Ciphey + ``` +- [PyPi](https://pypi.org/project/ciphey) (📥 15K / month): + ``` + pip install ciphey + ``` +- [Docker Hub](https://hub.docker.com/r/remnux/ciphey) (📥 14K · ⭐ 5 · ⏱️ 16.11.2021): + ``` + docker pull remnux/ciphey ```
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stanza (🥈24 · ⭐ 5.7K) - 斯坦福NLP官方Python语言库，支持多种语言。❗Unlicensed +
stanza (🥈24 · ⭐ 5.9K) - Official Stanford NLP Python Library for Many Human Languages. ❗Unlicensed -- [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 41 · 🔀 720 · 📦 680 · 📋 580 - 10% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 41 · 🔀 740 · 📦 780 · 📋 610 - 11% open · ⏱️ 18.11.2021): ``` git clone https://github.com/stanfordnlp/stanza ``` -- [PyPi](https://pypi.org/project/stanza) (📥 62K / month): +- [PyPi](https://pypi.org/project/stanza) (📥 250K / month): ``` pip install stanza ``` -- [Conda](https://anaconda.org/stanfordnlp/stanza) (📥 4.2K · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/stanfordnlp/stanza) (📥 4.5K · ⏱️ 05.10.2021): ``` conda install -c stanfordnlp stanza ```
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torchtext (🥈24 · ⭐ 2.9K) - 文本和NLP的数据加载器和抽象。BSD-3 +
torchtext (🥈24 · ⭐ 2.9K) - Data loaders and abstractions for text and NLP. BSD-3 -- [GitHub](https://github.com/pytorch/text) (👨‍💻 110 · 🔀 630 · 📋 580 - 43% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/pytorch/text) (👨‍💻 120 · 🔀 640 · 📋 590 - 43% open · ⏱️ 13.12.2021): ``` git clone https://github.com/pytorch/text ``` -- [PyPi](https://pypi.org/project/torchtext) (📥 110K / month): +- [PyPi](https://pypi.org/project/torchtext) (📥 120K / month): ``` pip install torchtext ```
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pytorch-nlp (🥈24 · ⭐ 2K) - PyTorch自然语言处理（NLP）的基本实用程序。BSD-3 +
PyTextRank (🥈24 · ⭐ 1.7K) - Python implementation of TextRank for phrase extraction and.. MIT -- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (👨‍💻 18 · 🔀 240 · 📦 300 · 📋 64 - 23% open · ⏱️ 10.07.2021): +- [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 17 · 🔀 290 · 📦 220 · 📋 79 - 27% open · ⏱️ 10.10.2021): ``` - git clone https://github.com/PetrochukM/PyTorch-NLP + git clone https://github.com/DerwenAI/pytextrank ``` -- [PyPi](https://pypi.org/project/pytorch-nlp) (📥 5.6K / month): +- [PyPi](https://pypi.org/project/pytextrank) (📥 18K / month): ``` - pip install pytorch-nlp + pip install pytextrank ```
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PyTextRank (🥈24 · ⭐ 1.6K) - TextRank的Python实现。MIT +
pyahocorasick (🥈24 · ⭐ 660) - Python module (C extension and plain python) implementing Aho-.. BSD-3 -- [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 17 · 🔀 280 · 📦 190 · 📋 79 - 27% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 23 · 🔀 95 · 📦 840 · 📋 110 - 34% open · ⏱️ 22.11.2021): ``` - git clone https://github.com/DerwenAI/pytextrank + git clone https://github.com/WojciechMula/pyahocorasick ``` -- [PyPi](https://pypi.org/project/pytextrank) (📥 16K / month): +- [PyPi](https://pypi.org/project/pyahocorasick) (📥 320K / month): ``` - pip install pytextrank + pip install pyahocorasick + ``` +- [Conda](https://anaconda.org/conda-forge/pyahocorasick) (📥 140K · ⏱️ 13.10.2020): + ``` + conda install -c conda-forge pyahocorasick ```
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fairseq (🥈23 · ⭐ 14K · 📉) - 用Python编写的Facebook AI Research Sequence-to-Sequence工具包。MIT +
fairseq (🥈23 · ⭐ 15K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT -- [GitHub](https://github.com/pytorch/fairseq) (👨‍💻 360 · 🔀 3.5K · 📥 150 · 📦 540 · 📋 3K - 33% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/pytorch/fairseq) (👨‍💻 370 · 🔀 3.8K · 📥 160 · 📦 610 · 📋 3.1K - 34% open · ⏱️ 16.12.2021): ``` git clone https://github.com/pytorch/fairseq @@ -1983,189 +1995,177 @@ _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 fairseq ```
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vaderSentiment (🥈23 · ⭐ 3.2K · 💤) - VADER情感分析。MIT +
flashtext (🥈23 · ⭐ 5K · 💀) - Extract Keywords from sentence or Replace keywords in sentences. MIT -- [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 10 · 🔀 810 · 📦 3.1K · 📋 100 - 26% open · ⏱️ 15.03.2021): +- [GitHub](https://github.com/vi3k6i5/flashtext) (👨‍💻 7 · 🔀 550 · 📦 650 · 📋 96 - 46% open · ⏱️ 03.05.2020): ``` - git clone https://github.com/cjhutto/vaderSentiment + git clone https://github.com/vi3k6i5/flashtext ``` -- [PyPi](https://pypi.org/project/vadersentiment) (📥 170K / month): +- [PyPi](https://pypi.org/project/flashtext) (📥 460K / month): ``` - pip install vadersentiment + pip install flashtext ```
-
neuralcoref (🥈23 · ⭐ 2.4K) - 基于SpaCy的神经网络实现快速共指解析。MIT +
vaderSentiment (🥈23 · ⭐ 3.3K · 💤) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT -- [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 420 · 📥 260 · 📦 400 · 📋 280 - 20% open · ⏱️ 22.06.2021): +- [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 10 · 🔀 820 · 📦 3.3K · 📋 100 - 28% open · ⏱️ 15.03.2021): ``` - git clone https://github.com/huggingface/neuralcoref - ``` -- [PyPi](https://pypi.org/project/neuralcoref): - ``` - pip install neuralcoref + git clone https://github.com/cjhutto/vaderSentiment ``` -- [Conda](https://anaconda.org/conda-forge/neuralcoref) (📥 9.9K · ⏱️ 21.02.2020): +- [PyPi](https://pypi.org/project/vadersentiment) (📥 220K / month): ``` - conda install -c conda-forge neuralcoref + pip install vadersentiment ```
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polyglot (🥈23 · ⭐ 1.9K · 💀) - 多语言文本（NLP）处理工具包。❗️GPL-3.0 +
pytorch-nlp (🥈23 · ⭐ 2K) - Basic Utilities for PyTorch Natural Language Processing (NLP). BSD-3 -- [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 300 · 📦 580 · 📋 200 - 67% open · ⏱️ 22.09.2020): +- [GitHub](https://github.com/PetrochukM/PyTorch-NLP) (👨‍💻 18 · 🔀 240 · 📦 310 · 📋 66 - 25% open · ⏱️ 10.07.2021): ``` - git clone https://github.com/aboSamoor/polyglot + git clone https://github.com/PetrochukM/PyTorch-NLP ``` -- [PyPi](https://pypi.org/project/polyglot) (📥 74K / month): +- [PyPi](https://pypi.org/project/pytorch-nlp) (📥 7.9K / month): ``` - pip install polyglot + pip install pytorch-nlp ```
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FARM (🥈23 · ⭐ 1.4K) - NLP的快速和轻松迁移学习。Apache-2 +
polyglot (🥈23 · ⭐ 1.9K · 💀) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 -- [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 35 · 🔀 210 · 📋 390 - 5% open · ⏱️ 09.09.2021): +- [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 300 · 📦 620 · 📋 200 - 68% open · ⏱️ 22.09.2020): ``` - git clone https://github.com/deepset-ai/FARM + git clone https://github.com/aboSamoor/polyglot ``` -- [PyPi](https://pypi.org/project/farm) (📥 9.2K / month): +- [PyPi](https://pypi.org/project/polyglot) (📥 86K / month): ``` - pip install farm + pip install polyglot ```
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sense2vec (🥈23 · ⭐ 1.3K) - 上下文相关性构建词向量。MIT +
scattertext (🥈23 · ⭐ 1.7K) - Beautiful visualizations of how language differs among document.. Apache-2 -- [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 210 · 📥 21K · 📦 88 · 📋 100 - 15% open · ⏱️ 16.08.2021): +- [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 12 · 🔀 230 · 📦 250 · 📋 82 - 20% open · ⏱️ 15.11.2021): ``` - git clone https://github.com/explosion/sense2vec + git clone https://github.com/JasonKessler/scattertext ``` -- [PyPi](https://pypi.org/project/sense2vec) (📥 3.5K / month): +- [PyPi](https://pypi.org/project/scattertext) (📥 3.2K / month): ``` - pip install sense2vec + pip install scattertext ``` -- [Conda](https://anaconda.org/conda-forge/sense2vec) (📥 23K · ⏱️ 14.07.2021): +- [Conda](https://anaconda.org/conda-forge/scattertext) (📥 59K · ⏱️ 15.11.2021): ``` - conda install -c conda-forge sense2vec + conda install -c conda-forge scattertext ```
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pyahocorasick (🥈23 · ⭐ 640 · 💤) - Python文本工具库。BSD-3 +
TensorFlow Text (🥈23 · ⭐ 860) - Making text a first-class citizen in TensorFlow. Apache-2 -- [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 21 · 🔀 93 · 📦 770 · 📋 100 - 32% open · ⏱️ 27.03.2021): +- [GitHub](https://github.com/tensorflow/text) (👨‍💻 66 · 🔀 160 · 📦 1.2K · 📋 140 - 17% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/WojciechMula/pyahocorasick - ``` -- [PyPi](https://pypi.org/project/pyahocorasick) (📥 230K / month): - ``` - pip install pyahocorasick + git clone https://github.com/tensorflow/text ``` -- [Conda](https://anaconda.org/conda-forge/pyahocorasick) (📥 130K · ⏱️ 13.10.2020): +- [PyPi](https://pypi.org/project/tensorflow-text): ``` - conda install -c conda-forge pyahocorasick + pip install tensorflow-text ```
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snowballstemmer (🥈23 · ⭐ 530) - Snowball编译器和词干算法。BSD-3 +
snowballstemmer (🥈23 · ⭐ 530) - Snowball compiler and stemming algorithms. BSD-3 -- [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 27 · 🔀 140 · 📦 4 · 📋 56 - 21% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 28 · 🔀 140 · 📦 4 · 📋 57 - 22% open · ⏱️ 16.11.2021): ``` git clone https://github.com/snowballstem/snowball ``` -- [PyPi](https://pypi.org/project/snowballstemmer) (📥 5.2M / month): +- [PyPi](https://pypi.org/project/snowballstemmer) (📥 5.7M / month): ``` pip install snowballstemmer ``` -- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (📥 3.2M · ⏱️ 21.01.2021): +- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (📥 3.5M · ⏱️ 17.11.2021): ``` conda install -c conda-forge snowballstemmer ```
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T5 (🥉22 · ⭐ 3.7K) - 探索迁移学习的论文源码Apache-2 +
T5 (🥉22 · ⭐ 3.8K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 -- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 41 · 🔀 500 · 📦 53 · 📋 360 - 9% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 44 · 🔀 530 · 📦 72 · 📋 370 - 10% open · ⏱️ 13.12.2021): ``` git clone https://github.com/google-research/text-to-text-transfer-transformer ``` -- [PyPi](https://pypi.org/project/t5) (📥 54K / month): +- [PyPi](https://pypi.org/project/t5) (📥 8.1K / month): ``` pip install t5 ```
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Texar (🥉22 · ⭐ 2.2K · 💀) - 机器学习，自然语言处理等工具包。Apache-2 +
Snips NLU (🥉22 · ⭐ 3.6K · 💤) - Snips Python library to extract meaning from text. Apache-2 -- [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 17 · 📋 160 - 19% open · ⏱️ 29.07.2020): +- [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 480 · 📋 250 - 21% open · ⏱️ 03.05.2021): ``` - git clone https://github.com/asyml/texar + git clone https://github.com/snipsco/snips-nlu ``` -- [PyPi](https://pypi.org/project/texar) (📥 130 / month): +- [PyPi](https://pypi.org/project/snips-nlu) (📥 4.5K / month): ``` - pip install texar + pip install snips-nlu ```
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scattertext (🥉22 · ⭐ 1.7K) - 文件之间语言分布的漂亮可视化效果。Apache-2 +
Sumy (🥉22 · ⭐ 2.7K) - Module for automatic summarization of text documents and HTML pages. Apache-2 -- [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 11 · 🔀 230 · 📦 220 · 📋 81 - 19% open · ⏱️ 07.07.2021): +- [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 21 · 🔀 450 · 📦 1K · 📋 93 - 13% open · ⏱️ 23.11.2021): ``` - git clone https://github.com/JasonKessler/scattertext - ``` -- [PyPi](https://pypi.org/project/scattertext) (📥 3.1K / month): - ``` - pip install scattertext + git clone https://github.com/miso-belica/sumy ``` -- [Conda](https://anaconda.org/conda-forge/scattertext) (📥 57K · ⏱️ 07.07.2021): +- [PyPi](https://pypi.org/project/sumy): ``` - conda install -c conda-forge scattertext + pip install sumy ```
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jellyfish (🥉22 · ⭐ 1.5K) - 一个python库，用于进行文本相似度和距离计算。BSD-2 +
Texar (🥉22 · ⭐ 2.2K · 💀) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 -- [GitHub](https://github.com/jamesturk/jellyfish) (👨‍💻 23 · 🔀 140 · 📦 2.8K · 📋 100 - 8% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 17 · 📋 160 - 19% open · ⏱️ 29.07.2020): ``` - git clone https://github.com/jamesturk/jellyfish - ``` -- [PyPi](https://pypi.org/project/jellyfish): - ``` - pip install jellyfish + git clone https://github.com/asyml/texar ``` -- [Conda](https://anaconda.org/conda-forge/jellyfish) (📥 150K · ⏱️ 27.09.2021): +- [PyPi](https://pypi.org/project/texar) (📥 180 / month): ``` - conda install -c conda-forge jellyfish + pip install texar ```
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SciSpacy (🥉22 · ⭐ 1K) - 完整的科学/生物医学的SpaCy应用案例。Apache-2 +
langid (🥉22 · ⭐ 1.9K · 💀) - Stand-alone language identification system. ❗Unlicensed -- [GitHub](https://github.com/allenai/scispacy) (👨‍💻 21 · 🔀 140 · 📦 340 · 📋 220 - 13% open · ⏱️ 15.07.2021): +- [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 280 · 📦 870 · 📋 71 - 36% open · ⏱️ 15.07.2017): ``` - git clone https://github.com/allenai/scispacy + git clone https://github.com/saffsd/langid.py ``` -- [PyPi](https://pypi.org/project/scispacy) (📥 30K / month): +- [PyPi](https://pypi.org/project/langid) (📥 330K / month): ``` - pip install scispacy + pip install langid ```
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TensorFlow Text (🥉22 · ⭐ 830 · 📉) - TensorFlow文本处理。Apache-2 +
sense2vec (🥉22 · ⭐ 1.3K) - Contextually-keyed word vectors. MIT -- [GitHub](https://github.com/tensorflow/text) (👨‍💻 57 · 🔀 130 · 📦 1K · 📋 130 - 18% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 220 · 📥 23K · 📦 100 · 📋 100 - 15% open · ⏱️ 16.08.2021): ``` - git clone https://github.com/tensorflow/text + git clone https://github.com/explosion/sense2vec ``` -- [PyPi](https://pypi.org/project/tensorflow-text): +- [PyPi](https://pypi.org/project/sense2vec): ``` - pip install tensorflow-text + pip install sense2vec + ``` +- [Conda](https://anaconda.org/conda-forge/sense2vec) (📥 24K · ⏱️ 14.07.2021): + ``` + conda install -c conda-forge sense2vec ```
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pySBD (🥉22 · ⭐ 370 · 💤) - pySBD（Python句子边界歧义消除）。MIT +
pySBD (🥉22 · ⭐ 390 · 💤) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT -- [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 40 · 📦 220 · 📋 59 - 18% open · ⏱️ 11.02.2021): +- [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 42 · 📦 250 · 📋 60 - 20% open · ⏱️ 11.02.2021): ``` git clone https://github.com/nipunsadvilkar/pySBD @@ -2175,150 +2175,162 @@ _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 pysbd ```
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stop-words (🥉22 · ⭐ 130 · 💀) - 获取Python中各种语言的常用停用词表。BSD-3 +
stop-words (🥉22 · ⭐ 130 · 💀) - Get list of common stop words in various languages in Python. BSD-3 -- [GitHub](https://github.com/Alir3z4/python-stop-words) (👨‍💻 8 · 🔀 23 · 📦 1.3K · 📋 12 - 25% open · ⏱️ 23.07.2018): +- [GitHub](https://github.com/Alir3z4/python-stop-words) (👨‍💻 8 · 🔀 24 · 📦 1.4K · 📋 12 - 25% open · ⏱️ 23.07.2018): ``` git clone https://github.com/Alir3z4/python-stop-words ``` -- [PyPi](https://pypi.org/project/stop-words) (📥 150K / month): +- [PyPi](https://pypi.org/project/stop-words) (📥 200K / month): ``` pip install stop-words ```
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textgenrnn (🥉21 · ⭐ 4.5K · 💀) - 轻松地训练自己的文本生成神经网络。❗Unlicensed +
textgenrnn (🥉21 · ⭐ 4.6K · 💀) - Easily train your own text-generating neural network.. ❗Unlicensed -- [GitHub](https://github.com/minimaxir/textgenrnn) (👨‍💻 19 · 🔀 700 · 📥 580 · 📦 940 · 📋 200 - 56% open · ⏱️ 14.07.2020): +- [GitHub](https://github.com/minimaxir/textgenrnn) (👨‍💻 19 · 🔀 710 · 📥 620 · 📦 950 · 📋 200 - 57% open · ⏱️ 14.07.2020): ``` git clone https://github.com/minimaxir/textgenrnn ``` -- [PyPi](https://pypi.org/project/textgenrnn) (📥 590 / month): +- [PyPi](https://pypi.org/project/textgenrnn) (📥 850 / month): ``` pip install textgenrnn ```
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MatchZoo (🥉21 · ⭐ 3.5K) - 便于深层设计，比较和共享的工具库。Apache-2 +
MatchZoo (🥉21 · ⭐ 3.6K) - Facilitating the design, comparison and sharing of deep.. Apache-2 - [GitHub](https://github.com/NTMC-Community/MatchZoo) (👨‍💻 36 · 🔀 890 · 📦 10 · 📋 460 - 6% open · ⏱️ 02.06.2021): ``` git clone https://github.com/NTMC-Community/MatchZoo ``` -- [PyPi](https://pypi.org/project/matchzoo) (📥 250 / month): +- [PyPi](https://pypi.org/project/matchzoo) (📥 200 / month): ``` pip install matchzoo ```
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phonenumbers (🥉21 · ⭐ 2.8K) - Google的libphonenumber的Python端口。Apache-2 +
phonenumbers (🥉21 · ⭐ 2.9K) - Python port of Google's libphonenumber. Apache-2 -- [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 25 · 🔀 340 · 📋 130 - 2% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 25 · 🔀 350 · 📋 130 - 2% open · ⏱️ 14.12.2021): ``` git clone https://github.com/daviddrysdale/python-phonenumbers ``` -- [PyPi](https://pypi.org/project/phonenumbers) (📥 2.2M / month): +- [PyPi](https://pypi.org/project/phonenumbers) (📥 2.7M / month): ``` pip install phonenumbers ``` -- [Conda](https://anaconda.org/conda-forge/phonenumbers) (📥 480K · ⏱️ 07.10.2021): +- [Conda](https://anaconda.org/conda-forge/phonenumbers) (📥 500K · ⏱️ 07.12.2021): ``` conda install -c conda-forge phonenumbers ```
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Texthero (🥉21 · ⭐ 2.4K) - 文本预处理，表示和可视化从入门到精通。MIT +
spark-nlp (🥉21 · ⭐ 2.5K) - State of the Art Natural Language Processing. Apache-2 + +- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 100 · 🔀 510 · 📋 600 - 12% open · ⏱️ 16.12.2021): + + ``` + git clone https://github.com/JohnSnowLabs/spark-nlp + ``` +- [PyPi](https://pypi.org/project/spark-nlp): + ``` + pip install spark-nlp + ``` +
+
Texthero (🥉21 · ⭐ 2.4K) - Text preprocessing, representation and visualization from zero to hero. MIT -- [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 18 · 🔀 200 · 📥 83 · 📋 100 - 43% open · ⏱️ 19.07.2021): +- [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 18 · 🔀 200 · 📥 87 · 📋 110 - 44% open · ⏱️ 19.07.2021): ``` git clone https://github.com/jbesomi/texthero ``` -- [PyPi](https://pypi.org/project/texthero) (📥 14K / month): +- [PyPi](https://pypi.org/project/texthero) (📥 18K / month): ``` pip install texthero ```
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langid (🥉21 · ⭐ 1.9K · 💀) - 独立的语言识别系统。❗Unlicensed +
FARM (🥉21 · ⭐ 1.4K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 -- [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 270 · 📦 810 · 📋 71 - 36% open · ⏱️ 15.07.2017): +- [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 36 · 🔀 210 · 📋 400 - 3% open · ⏱️ 23.11.2021): ``` - git clone https://github.com/saffsd/langid.py + git clone https://github.com/deepset-ai/FARM ``` -- [PyPi](https://pypi.org/project/langid) (📥 350K / month): +- [PyPi](https://pypi.org/project/farm) (📥 5.7K / month): ``` - pip install langid + pip install farm ```
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anaGo (🥉21 · ⭐ 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 +
SciSpacy (🥉21 · ⭐ 1.1K) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 -- [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 27 · 📋 110 - 33% open · ⏱️ 01.04.2021): +- [GitHub](https://github.com/allenai/scispacy) (👨‍💻 21 · 🔀 140 · 📦 370 · 📋 230 - 15% open · ⏱️ 15.07.2021): ``` - git clone https://github.com/Hironsan/anago + git clone https://github.com/allenai/scispacy ``` -- [PyPi](https://pypi.org/project/anago) (📥 700 / month): +- [PyPi](https://pypi.org/project/scispacy) (📥 28K / month): ``` - pip install anago + pip install scispacy ```
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PyText (🥉20 · ⭐ 6.3K) - 基于PyTorch的自然语言建模框架。❗Unlicensed +
CLTK (🥉21 · ⭐ 700) - The Classical Language Toolkit. MIT -- [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 210 · 🔀 790 · 📥 270 · 📦 99 · 📋 130 - 44% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/cltk/cltk) (👨‍💻 110 · 🔀 300 · 📥 22 · 📦 180 · 📋 510 - 4% open · ⏱️ 21.10.2021): ``` - git clone https://github.com/facebookresearch/pytext + git clone https://github.com/cltk/cltk ``` -- [PyPi](https://pypi.org/project/pytext-nlp) (📥 280 / month): +- [PyPi](https://pypi.org/project/cltk): ``` - pip install pytext-nlp + pip install cltk ```
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NeMo (🥉20 · ⭐ 3.4K) - NeMo：用于智能对话的工具包。Apache-2 +
PyText (🥉20 · ⭐ 6.3K) - A natural language modeling framework based on PyTorch. ❗Unlicensed -- [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 110 · 🔀 680 · 📥 11K · 📋 770 - 8% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 220 · 🔀 790 · 📥 280 · 📦 100 · 📋 130 - 44% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/NVIDIA/NeMo + git clone https://github.com/facebookresearch/pytext ``` -- [PyPi](https://pypi.org/project/nemo-toolkit) (📥 4.3K / month): +- [PyPi](https://pypi.org/project/pytext-nlp) (📥 240 / month): ``` - pip install nemo-toolkit + pip install pytext-nlp ```
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NLP Architect (🥉20 · ⭐ 2.7K) - 用于探索最先进的深度学习的模型库。Apache-2 +
NeMo (🥉20 · ⭐ 3.7K) - NeMo: a toolkit for conversational AI. Apache-2 -- [GitHub](https://github.com/IntelLabs/nlp-architect) (👨‍💻 37 · 🔀 420 · 📦 8 · 📋 130 - 11% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 120 · 🔀 790 · 📥 17K · 📋 870 - 4% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/IntelLabs/nlp-architect + git clone https://github.com/NVIDIA/NeMo ``` -- [PyPi](https://pypi.org/project/nlp-architect) (📥 280 / month): +- [PyPi](https://pypi.org/project/nemo-toolkit) (📥 6.9K / month): ``` - pip install nlp-architect + pip install nemo-toolkit ```
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fastNLP (🥉20 · ⭐ 2.3K) - fastNLP：模块化和可扩展的NLP框架。Apache-2 +
Kashgari (🥉20 · ⭐ 2.2K) - Kashgari is a production-level NLP Transfer learning framework.. Apache-2 -- [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 50 · 🔀 390 · 📥 65 · 📦 41 · 📋 170 - 17% open · ⏱️ 13.07.2021): +- [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 420 · 📦 49 · 📋 360 - 9% open · ⏱️ 09.07.2021): ``` - git clone https://github.com/fastnlp/fastNLP + git clone https://github.com/BrikerMan/Kashgari ``` -- [PyPi](https://pypi.org/project/fastnlp): +- [PyPi](https://pypi.org/project/kashgari-tf) (📥 73 / month): ``` - pip install fastnlp + pip install kashgari-tf ```
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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 +
DELTA (🥉20 · ⭐ 1.5K · 💤) - DELTA is a deep learning based natural language and speech.. Apache-2 - [GitHub](https://github.com/Delta-ML/delta) (👨‍💻 41 · 🔀 290 · 📋 75 - 1% open · ⏱️ 17.12.2020): ``` git clone https://github.com/Delta-ML/delta ``` -- [PyPi](https://pypi.org/project/delta-nlp) (📥 18 / month): +- [PyPi](https://pypi.org/project/delta-nlp) (📥 20 / month): ``` pip install delta-nlp ``` @@ -2327,1271 +2339,1247 @@ _用于处理，清理，处理和分析文本数据的库，以及用于NLP任 docker pull zh794390558/delta ```
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Sockeye (🥉20 · ⭐ 1K) - 序列到序列框架。Apache-2 - -- [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 53 · 🔀 280 · 📥 6 · 📋 250 - 6% open · ⏱️ 30.09.2021): - - ``` - git clone https://github.com/awslabs/sockeye - ``` -- [PyPi](https://pypi.org/project/sockeye) (📥 510 / month): - ``` - pip install sockeye - ``` -
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YouTokenToMe (🥉20 · ⭐ 770 · 💤) - 用于基于神经网络的文本的预处理器。MIT +
anaGo (🥉20 · ⭐ 1.4K · 💤) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT -- [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 54 · 📦 150 · 📋 49 - 55% open · ⏱️ 28.01.2021): +- [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 27 · 📋 110 - 33% open · ⏱️ 01.04.2021): ``` - git clone https://github.com/vkcom/youtokentome + git clone https://github.com/Hironsan/anago ``` -- [PyPi](https://pypi.org/project/youtokentome) (📥 14K / month): +- [PyPi](https://pypi.org/project/anago) (📥 490 / month): ``` - pip install youtokentome + pip install anago ```
-
inflect (🥉20 · ⭐ 580 · 💤) - 辅助功能，正确生成复数，序数，不定冠词，转换数字。MIT +
inflect (🥉20 · ⭐ 590 · 💤) - Correctly generate plurals, ordinals, indefinite articles; convert.. MIT -- [GitHub](https://github.com/jaraco/inflect) (👨‍💻 29 · 🔀 62 · 📋 80 - 21% open · ⏱️ 23.03.2021): +- [GitHub](https://github.com/jaraco/inflect) (👨‍💻 29 · 🔀 65 · 📋 80 - 21% open · ⏱️ 23.03.2021): ``` git clone https://github.com/jaraco/inflect ``` -- [PyPi](https://pypi.org/project/inflect) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/inflect) (📥 1.3M / month): ``` pip install inflect ``` -- [Conda](https://anaconda.org/conda-forge/inflect) (📥 180K · ⏱️ 06.07.2021): +- [Conda](https://anaconda.org/conda-forge/inflect) (📥 190K · ⏱️ 02.11.2021): ``` conda install -c conda-forge inflect ```
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Kashgari (🥉19 · ⭐ 2.2K) - Kashgari是工业级的NLP迁移学习框架。Apache-2 +
pyfasttext (🥉20 · ⭐ 230 · 💀) - Yet another Python binding for fastText. ❗️GPL-3.0 -- [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 410 · 📦 42 · 📋 350 - 8% open · ⏱️ 09.07.2021): +- [GitHub](https://github.com/vrasneur/pyfasttext) (👨‍💻 4 · 🔀 30 · 📥 340 · 📦 200 · 📋 49 - 42% open · ⏱️ 08.12.2018): ``` - git clone https://github.com/BrikerMan/Kashgari + git clone https://github.com/vrasneur/pyfasttext ``` -- [PyPi](https://pypi.org/project/kashgari-tf) (📥 82 / month): +- [PyPi](https://pypi.org/project/pyfasttext) (📥 5.6K / month): ``` - pip install kashgari-tf + pip install pyfasttext ```
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fast-bert (🥉19 · ⭐ 1.7K) - 用于基于BERT的NLP模型的简单易用工具库。Apache-2 +
NLP Architect (🥉19 · ⭐ 2.8K) - A model library for exploring state-of-the-art deep learning.. Apache-2 -- [GitHub](https://github.com/utterworks/fast-bert) (👨‍💻 35 · 🔀 320 · 📋 240 - 60% open · ⏱️ 31.08.2021): +- [GitHub](https://github.com/IntelLabs/nlp-architect) (👨‍💻 37 · 🔀 420 · 📦 8 · 📋 130 - 11% open · ⏱️ 12.09.2021): ``` - git clone https://github.com/kaushaltrivedi/fast-bert + git clone https://github.com/IntelLabs/nlp-architect ``` -- [PyPi](https://pypi.org/project/fast-bert) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/nlp-architect) (📥 480 / month): ``` - pip install fast-bert + pip install nlp-architect ```
-
pyfasttext (🥉19 · ⭐ 230 · 💀) - fastText的另一个Python接口。❗️GPL-3.0 +
textacy (🥉19 · ⭐ 1.8K) - NLP, before and after spaCy. ❗Unlicensed -- [GitHub](https://github.com/vrasneur/pyfasttext) (👨‍💻 4 · 🔀 30 · 📥 340 · 📦 180 · 📋 49 - 42% open · ⏱️ 08.12.2018): +- [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 31 · 🔀 230 · 📋 240 - 10% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/vrasneur/pyfasttext - ``` -- [PyPi](https://pypi.org/project/pyfasttext) (📥 3.8K / month): - ``` - pip install pyfasttext + git clone https://github.com/chartbeat-labs/textacy ``` -
-
Snips NLU (🥉18 · ⭐ 3.6K) - 从文本中提取含义的Python库。Apache-2 - -- [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 480 · 📋 250 - 21% open · ⏱️ 03.05.2021): - +- [PyPi](https://pypi.org/project/textacy) (📥 36K / month): ``` - git clone https://github.com/snipsco/snips-nlu + pip install textacy ``` -- [PyPi](https://pypi.org/project/snips-nlu): +- [Conda](https://anaconda.org/conda-forge/textacy) (📥 100K · ⏱️ 13.04.2021): ``` - pip install snips-nlu + conda install -c conda-forge textacy ```
-
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 +
gpt-2-simple (🥉18 · ⭐ 2.8K) - Python package to easily retrain OpenAI's GPT-2 text-.. ❗Unlicensed -- [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 17 · 🔀 560 · 📥 270 · 📋 230 - 59% open · ⏱️ 14.02.2021): +- [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 18 · 🔀 570 · 📥 280 · 📋 230 - 60% open · ⏱️ 18.10.2021): ``` git clone https://github.com/minimaxir/gpt-2-simple ``` -- [PyPi](https://pypi.org/project/gpt-2-simple) (📥 8.3K / month): +- [PyPi](https://pypi.org/project/gpt-2-simple) (📥 6.4K / month): ``` pip install gpt-2-simple ```
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finetune (🥉18 · ⭐ 650) - 针对NLP的Scikit风格模型微调。MPL-2.0 - -- [GitHub](https://github.com/IndicoDataSolutions/finetune) (👨‍💻 19 · 🔀 69 · 📦 9 · 📋 140 - 15% open · ⏱️ 01.10.2021): - - ``` - git clone https://github.com/IndicoDataSolutions/finetune - ``` -- [PyPi](https://pypi.org/project/finetune) (📥 100 / month): - ``` - pip install finetune - ``` -
-
flashtext (🥉17 · ⭐ 5K · 💀) - 从句子中提取关键字或替换句子中的关键字。MIT +
fast-bert (🥉18 · ⭐ 1.7K) - Super easy library for BERT based NLP models. Apache-2 -- [GitHub](https://github.com/vi3k6i5/flashtext) (👨‍💻 7 · 🔀 550 · 📦 590 · 📋 94 - 46% open · ⏱️ 03.05.2020): +- [GitHub](https://github.com/utterworks/fast-bert) (👨‍💻 35 · 🔀 320 · 📋 240 - 60% open · ⏱️ 31.08.2021): ``` - git clone https://github.com/vi3k6i5/flashtext + git clone https://github.com/kaushaltrivedi/fast-bert ``` -- [PyPi](https://pypi.org/project/flashtext): +- [PyPi](https://pypi.org/project/fast-bert) (📥 1.9K / month): ``` - pip install flashtext + pip install fast-bert ```
-
textacy (🥉17 · ⭐ 1.8K) - spaCy之前和之后的NLP。❗Unlicensed +
Sockeye (🥉18 · ⭐ 1K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 -- [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 31 · 🔀 220 · 📋 240 - 13% open · ⏱️ 31.05.2021): +- [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 54 · 🔀 280 · 📥 12 · 📋 260 - 1% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/chartbeat-labs/textacy - ``` -- [PyPi](https://pypi.org/project/textacy) (📥 31K / month): - ``` - pip install textacy + git clone https://github.com/awslabs/sockeye ``` -- [Conda](https://anaconda.org/conda-forge/textacy) (📥 99K · ⏱️ 13.04.2021): +- [PyPi](https://pypi.org/project/sockeye) (📥 470 / month): ``` - conda install -c conda-forge textacy + pip install sockeye ```
-
NeuroNER (🥉17 · ⭐ 1.6K · 💀) - 使用神经网络的命名实体识别。MIT +
finetune (🥉18 · ⭐ 660) - Scikit-learn style model finetuning for NLP. MPL-2.0 -- [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 440 · 📦 13 · 📋 150 - 54% open · ⏱️ 02.10.2019): +- [GitHub](https://github.com/IndicoDataSolutions/finetune) (👨‍💻 19 · 🔀 69 · 📦 9 · 📋 140 - 15% open · ⏱️ 18.11.2021): ``` - git clone https://github.com/Franck-Dernoncourt/NeuroNER + git clone https://github.com/IndicoDataSolutions/finetune ``` -- [PyPi](https://pypi.org/project/pyneuroner) (📥 120 / month): +- [PyPi](https://pypi.org/project/finetune) (📥 75 / month): ``` - pip install pyneuroner + pip install finetune ```
-
Camphr (🥉17 · ⭐ 340) - 适用于Transformers，Udify，ELmo等的spaCy插件。Apache-2 spacy +
textpipe (🥉17 · ⭐ 290) - Textpipe: clean and extract metadata from text. MIT -- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (👨‍💻 7 · 🔀 17 · 📋 27 - 7% open · ⏱️ 18.08.2021): +- [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 22 · 📦 8 · 📋 40 - 37% open · ⏱️ 09.06.2021): ``` - git clone https://github.com/PKSHATechnology-Research/camphr + git clone https://github.com/textpipe/textpipe ``` -- [PyPi](https://pypi.org/project/camphr) (📥 580 / month): +- [PyPi](https://pypi.org/project/textpipe) (📥 1.8K / month): ``` - pip install camphr + pip install textpipe ```
-
textpipe (🥉17 · ⭐ 290) - Textpipe：从文本中清理并提取元数据。MIT +
YouTokenToMe (🥉16 · ⭐ 780 · 💤) - Unsupervised text tokenizer focused on computational efficiency. MIT -- [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 22 · 📦 7 · 📋 40 - 37% open · ⏱️ 09.06.2021): +- [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 55 · 📦 180 · 📋 50 - 54% open · ⏱️ 28.01.2021): ``` - git clone https://github.com/textpipe/textpipe + git clone https://github.com/vkcom/youtokentome ``` -- [PyPi](https://pypi.org/project/textpipe) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/youtokentome): ``` - pip install textpipe + pip install youtokentome ```
-
DeepMatcher (🥉16 · ⭐ 370) - 用于实体和文本匹配的Python包。BSD-3 +
DeepMatcher (🥉16 · ⭐ 380) - Python package for performing Entity and Text Matching using.. BSD-3 -- [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 85 · 📦 14 · 📋 76 - 71% open · ⏱️ 13.06.2021): +- [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 88 · 📦 14 · 📋 76 - 71% open · ⏱️ 13.06.2021): ``` git clone https://github.com/anhaidgroup/deepmatcher ``` -- [PyPi](https://pypi.org/project/deepmatcher) (📥 600 / month): +- [PyPi](https://pypi.org/project/deepmatcher) (📥 480 / month): ``` pip install deepmatcher ```
-
Translate (🥉15 · ⭐ 710) - Translate-PyTorch NLP库。BSD-3 +
Camphr (🥉16 · ⭐ 340) - spaCy plugin for Transformers , Udify, ELmo, etc. Apache-2 spacy -- [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 170 · 📋 38 - 28% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/PKSHATechnology-Research/camphr) (👨‍💻 7 · 🔀 17 · 📋 27 - 7% open · ⏱️ 18.08.2021): ``` - git clone https://github.com/pytorch/translate + git clone https://github.com/PKSHATechnology-Research/camphr ``` -- [PyPi](https://pypi.org/project/pytorch-translate) (📥 6 / month): +- [PyPi](https://pypi.org/project/camphr) (📥 200 / month): ``` - pip install pytorch-translate + pip install camphr ```
-
OpenNRE (🥉14 · ⭐ 3.3K) - 神经关系提取（NRE）的开源软件包。MIT +
OpenNRE (🥉15 · ⭐ 3.4K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT -- [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 9 · 🔀 880 · 📋 330 - 3% open · ⏱️ 31.05.2021): +- [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 10 · 🔀 900 · 📋 330 - 3% open · ⏱️ 09.12.2021): ``` git clone https://github.com/thunlp/OpenNRE ```
-
TransferNLP (🥉14 · ⭐ 290 · 💀) - 用于可重复的实验的NLP库。MIT +
Translate (🥉15 · ⭐ 720) - Translate - a PyTorch Language Library. BSD-3 -- [GitHub](https://github.com/feedly/transfer-nlp) (👨‍💻 7 · 🔀 16 · 📋 23 - 13% open · ⏱️ 28.05.2020): +- [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 170 · 📋 38 - 28% open · ⏱️ 06.10.2021): ``` - git clone https://github.com/feedly/transfer-nlp + git clone https://github.com/pytorch/translate ``` -- [PyPi](https://pypi.org/project/transfer-nlp) (📥 140 / month): +- [PyPi](https://pypi.org/project/pytorch-translate): ``` - pip install transfer-nlp + pip install pytorch-translate ```
-
NeuralQA (🥉14 · ⭐ 210 · 💤) - NeuralQA：用于对大型数据集进行问答构建。MIT +
NeuralQA (🥉15 · ⭐ 220 · 💤) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. MIT -- [GitHub](https://github.com/victordibia/neuralqa) (👨‍💻 3 · 🔀 30 · 📦 2 · 📋 28 - 71% open · ⏱️ 16.12.2020): +- [GitHub](https://github.com/victordibia/neuralqa) (👨‍💻 3 · 🔀 31 · 📦 3 · 📋 28 - 71% open · ⏱️ 16.12.2020): ``` git clone https://github.com/victordibia/neuralqa ``` -- [PyPi](https://pypi.org/project/neuralqa) (📥 95 / month): +- [PyPi](https://pypi.org/project/neuralqa) (📥 87 / month): ``` pip install neuralqa ```
-
ONNX-T5 (🥉14 · ⭐ 180 · 💤) - 文本摘要，翻译，情感分析，文本生成等实现。Apache-2 +
ONNX-T5 (🥉15 · ⭐ 190 · 💤) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 -- [GitHub](https://github.com/abelriboulot/onnxt5) (👨‍💻 3 · 🔀 23 · 📋 14 - 42% open · ⏱️ 28.01.2021): +- [GitHub](https://github.com/abelriboulot/onnxt5) (👨‍💻 3 · 🔀 24 · 📋 14 - 42% open · ⏱️ 28.01.2021): ``` git clone https://github.com/abelriboulot/onnxt5 ``` -- [PyPi](https://pypi.org/project/onnxt5) (📥 140 / month): +- [PyPi](https://pypi.org/project/onnxt5) (📥 170 / month): ``` pip install onnxt5 ```
-
textvec (🥉14 · ⭐ 180 · 💤) - 胜过TF-IDF文本向量化工具。MIT +
NeuroNER (🥉14 · ⭐ 1.6K · 💀) - Named-entity recognition using neural networks. Easy-to-use and.. MIT -- [GitHub](https://github.com/textvec/textvec) (👨‍💻 4 · 🔀 21 · 📦 4 · 📋 9 - 33% open · ⏱️ 03.12.2020): +- [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 450 · 📋 150 - 55% open · ⏱️ 02.10.2019): ``` - git clone https://github.com/textvec/textvec + git clone https://github.com/Franck-Dernoncourt/NeuroNER ``` -- [PyPi](https://pypi.org/project/textvec) (📥 260 / month): +- [PyPi](https://pypi.org/project/pyneuroner): ``` - pip install textvec + pip install pyneuroner ```
-
VizSeq (🥉13 · ⭐ 360) - 用于自然语言生成的分析工具包。MIT +
TransferNLP (🥉14 · ⭐ 290 · 💀) - NLP library designed for reproducible experimentation.. MIT -- [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 41 · 📦 2 · 📋 15 - 40% open · ⏱️ 02.09.2021): +- [GitHub](https://github.com/feedly/transfer-nlp) (👨‍💻 7 · 🔀 17 · 📋 23 - 13% open · ⏱️ 28.05.2020): ``` - git clone https://github.com/facebookresearch/vizseq + git clone https://github.com/feedly/transfer-nlp ``` -- [PyPi](https://pypi.org/project/vizseq) (📥 250 / month): +- [PyPi](https://pypi.org/project/transfer-nlp) (📥 81 / month): ``` - pip install vizseq + pip install transfer-nlp ```
-
skift (🥉13 · ⭐ 220 · 💤) - 适用于Python fastText的scikit-learn包装器。❗Unlicensed +
skift (🥉14 · ⭐ 220) - scikit-learn wrappers for Python fastText. ❗Unlicensed -- [GitHub](https://github.com/shaypal5/skift) (👨‍💻 7 · 🔀 20 · 📦 10 · 📋 10 - 20% open · ⏱️ 31.03.2021): +- [GitHub](https://github.com/shaypal5/skift) (👨‍💻 8 · 🔀 21 · 📦 10 · 📋 11 - 18% open · ⏱️ 13.12.2021): ``` git clone https://github.com/shaypal5/skift ``` -- [PyPi](https://pypi.org/project/skift) (📥 540 / month): +- [PyPi](https://pypi.org/project/skift): ``` pip install skift ```
-
Headliner (🥉12 · ⭐ 230 · 💀) - 轻松训练和部署seq2seq模型。❗Unlicensed +
VizSeq (🥉12 · ⭐ 370) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT -- [GitHub](https://github.com/as-ideas/headliner) (👨‍💻 2 · 🔀 40 · 📦 3 · 📋 14 - 7% open · ⏱️ 14.02.2020): +- [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 43 · 📦 3 · 📋 15 - 40% open · ⏱️ 02.09.2021): + + ``` + git clone https://github.com/facebookresearch/vizseq + ``` +- [PyPi](https://pypi.org/project/vizseq) (📥 68 / month): + ``` + pip install vizseq + ``` +
+
textvec (🥉12 · ⭐ 180 · 💤) - Text vectorization tool to outperform TFIDF for classification.. MIT + +- [GitHub](https://github.com/textvec/textvec) (👨‍💻 4 · 🔀 21 · 📦 4 · 📋 9 - 33% open · ⏱️ 03.12.2020): + + ``` + git clone https://github.com/textvec/textvec + ``` +- [PyPi](https://pypi.org/project/textvec): + ``` + pip install textvec + ``` +
+
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): ``` git clone https://github.com/as-ideas/headliner ``` -- [PyPi](https://pypi.org/project/headliner) (📥 150 / month): +- [PyPi](https://pypi.org/project/headliner) (📥 130 / 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._ -
Pillow (🥇40 · ⭐ 9K) - 友好的PIL分支（Python Imaging Library）。❗️PIL +
imgaug (🥇32 · ⭐ 12K · 💀) - Image augmentation for machine learning experiments. MIT -- [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 370 · 🔀 1.6K · 📦 570K · 📋 2.3K - 6% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.2K · 📦 8.4K · 📋 480 - 53% open · ⏱️ 01.06.2020): ``` - git clone https://github.com/python-pillow/Pillow + git clone https://github.com/aleju/imgaug ``` -- [PyPi](https://pypi.org/project/Pillow) (📥 35M / month): +- [PyPi](https://pypi.org/project/imgaug) (📥 260K / month): ``` - pip install Pillow + pip install imgaug ``` -- [Conda](https://anaconda.org/conda-forge/pillow) (📥 11M · ⏱️ 03.09.2021): +- [Conda](https://anaconda.org/conda-forge/imgaug) (📥 59K · ⏱️ 14.02.2020): ``` - conda install -c conda-forge pillow + conda install -c conda-forge imgaug ```
-
Albumentations (🥇32 · ⭐ 8.9K) - 快速的图像增强库和易于使用的包装器。MIT +
Albumentations (🥇32 · ⭐ 9.3K) - Fast image augmentation library and an easy-to-use wrapper.. MIT -- [GitHub](https://github.com/albumentations-team/albumentations) (👨‍💻 95 · 🔀 1.1K · 📦 5.3K · 📋 510 - 38% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/albumentations-team/albumentations) (👨‍💻 98 · 🔀 1.2K · 📦 6K · 📋 540 - 39% open · ⏱️ 14.12.2021): ``` git clone https://github.com/albumentations-team/albumentations ``` -- [PyPi](https://pypi.org/project/albumentations) (📥 170K / month): +- [PyPi](https://pypi.org/project/albumentations) (📥 210K / month): ``` pip install albumentations ``` -- [Conda](https://anaconda.org/conda-forge/albumentations) (📥 26K · ⏱️ 15.07.2021): +- [Conda](https://anaconda.org/conda-forge/albumentations) (📥 29K · ⏱️ 15.07.2021): ``` conda install -c conda-forge albumentations ```
-
MoviePy (🥇32 · ⭐ 8.6K) - 使用Python进行视频编辑。MIT +
MoviePy (🥇32 · ⭐ 8.8K) - Video editing with Python. MIT -- [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 140 · 🔀 1.1K · 📦 11K · 📋 1.1K - 28% open · ⏱️ 19.08.2021): +- [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 140 · 🔀 1.1K · 📦 12K · 📋 1.1K - 29% open · ⏱️ 12.11.2021): ``` git clone https://github.com/Zulko/moviepy ``` -- [PyPi](https://pypi.org/project/moviepy) (📥 1.5M / month): +- [PyPi](https://pypi.org/project/moviepy) (📥 1.4M / month): ``` pip install moviepy ``` -- [Conda](https://anaconda.org/conda-forge/moviepy) (📥 94K · ⏱️ 23.02.2020): +- [Conda](https://anaconda.org/conda-forge/moviepy) (📥 99K · ⏱️ 23.02.2020): ``` conda install -c conda-forge moviepy ```
-
imageio (🥇32 · ⭐ 930) - 用于读取和写入图像数据的Python库。BSD-2 +
PyTorch Image Models (🥇30 · ⭐ 15K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 -- [GitHub](https://github.com/imageio/imageio) (👨‍💻 80 · 🔀 180 · 📦 49K · 📋 380 - 17% open · ⏱️ 08.09.2021): +- [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 62 · 🔀 2.4K · 📥 780K · 📦 1.6K · 📋 420 - 10% open · ⏱️ 14.12.2021): + + ``` + git clone https://github.com/rwightman/pytorch-image-models + ``` +
+
imageio (🥇30 · ⭐ 960) - Python library for reading and writing image data. BSD-2 + +- [GitHub](https://github.com/imageio/imageio) (👨‍💻 83 · 🔀 190 · 📥 45 · 📦 53K · 📋 400 - 17% open · ⏱️ 08.12.2021): ``` git clone https://github.com/imageio/imageio ``` -- [PyPi](https://pypi.org/project/imageio) (📥 16M / month): +- [PyPi](https://pypi.org/project/imageio): ``` pip install imageio ``` -- [Conda](https://anaconda.org/conda-forge/imageio) (📥 2.3M · ⏱️ 06.07.2020): +- [Conda](https://anaconda.org/conda-forge/imageio) (📥 2.4M · ⏱️ 09.12.2021): ``` conda install -c conda-forge imageio ```
-
imgaug (🥇31 · ⭐ 12K · 💀) - 用于机器学习实验的图像增强。MIT +
GluonCV (🥈29 · ⭐ 5K) - Gluon CV Toolkit. Apache-2 -- [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.1K · 📦 7.8K · 📋 460 - 53% open · ⏱️ 01.06.2020): +- [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 110 · 🔀 1.1K · 📦 640 · 📋 790 - 6% open · ⏱️ 14.11.2021): ``` - git clone https://github.com/aleju/imgaug - ``` -- [PyPi](https://pypi.org/project/imgaug) (📥 250K / month): - ``` - pip install imgaug + git clone https://github.com/dmlc/gluon-cv ``` -- [Conda](https://anaconda.org/conda-forge/imgaug) (📥 54K · ⏱️ 14.02.2020): +- [PyPi](https://pypi.org/project/gluoncv) (📥 540K / month): ``` - conda install -c conda-forge imgaug + pip install gluoncv ```
-
Wand (🥇31 · ⭐ 1.1K) - 用于Python的基于ctypes的简单ImageMagick接口。MIT +
scikit-image (🥈29 · ⭐ 4.7K) - Image processing in Python. ❗Unlicensed -- [GitHub](https://github.com/emcconville/wand) (👨‍💻 96 · 🔀 180 · 📥 5.3K · 📦 6.8K · 📋 360 - 3% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 540 · 🔀 1.8K · 📦 88K · 📋 2.2K - 6% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/emcconville/wand + git clone https://github.com/scikit-image/scikit-image ``` -- [PyPi](https://pypi.org/project/wand) (📥 410K / month): +- [PyPi](https://pypi.org/project/scikit-image): ``` - pip install wand + pip install scikit-image ``` -
-
PyTorch Image Models (🥈30 · ⭐ 14K) - PyTorch图像模型，脚本，预训练权重。Apache-2 - -- [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 58 · 🔀 2.1K · 📥 640K · 📦 1.2K · 📋 380 - 8% open · ⏱️ 12.10.2021): - +- [Conda](https://anaconda.org/conda-forge/scikit-image) (📥 3.1M · ⏱️ 10.12.2021): ``` - git clone https://github.com/rwightman/pytorch-image-models + conda install -c conda-forge scikit-image ```
-
torchvision (🥈29 · ⭐ 10K) - 计算机视觉的数据集，转换和模型。BSD-3 +
ImageHash (🥈29 · ⭐ 2.2K) - A Python Perceptual Image Hashing Module. BSD-2 -- [GitHub](https://github.com/pytorch/vision) (👨‍💻 430 · 🔀 5.1K · 📋 1.9K - 21% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 280 · 📦 3.9K · 📋 100 - 10% open · ⏱️ 07.09.2021): ``` - git clone https://github.com/pytorch/vision + git clone https://github.com/JohannesBuchner/imagehash ``` -- [PyPi](https://pypi.org/project/torchvision) (📥 2.7M / month): +- [PyPi](https://pypi.org/project/ImageHash) (📥 1.2M / month): ``` - pip install torchvision + pip install ImageHash ``` -- [Conda](https://anaconda.org/conda-forge/torchvision) (📥 130K · ⏱️ 27.09.2021): +- [Conda](https://anaconda.org/conda-forge/imagehash) (📥 160K · ⏱️ 15.07.2021): ``` - conda install -c conda-forge torchvision + conda install -c conda-forge imagehash ```
-
GluonCV (🥈29 · ⭐ 4.9K) - Gluon CV工具包。Apache-2 +
imutils (🥈28 · ⭐ 3.9K · 💤) - A series of convenience functions to make basic image processing.. MIT -- [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 110 · 🔀 1.1K · 📦 580 · 📋 780 - 6% open · ⏱️ 06.08.2021): +- [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 20 · 🔀 930 · 📦 21K · 📋 160 - 52% open · ⏱️ 15.01.2021): ``` - git clone https://github.com/dmlc/gluon-cv + git clone https://github.com/jrosebr1/imutils ``` -- [PyPi](https://pypi.org/project/gluoncv) (📥 660K / month): +- [PyPi](https://pypi.org/project/imutils) (📥 470K / month): ``` - pip install gluoncv + pip install imutils + ``` +- [Conda](https://anaconda.org/conda-forge/imutils) (📥 74K · ⏱️ 09.12.2021): + ``` + conda install -c conda-forge imutils ```
-
scikit-image (🥈29 · ⭐ 4.5K) - Python中的图像处理。❗Unlicensed +
MMDetection (🥈27 · ⭐ 18K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 -- [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 520 · 🔀 1.8K · 📦 83K · 📋 2.1K - 24% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 290 · 🔀 5.8K · 📦 200 · 📋 4.9K - 7% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/scikit-image/scikit-image - ``` -- [PyPi](https://pypi.org/project/scikit-image): - ``` - pip install scikit-image - ``` -- [Conda](https://anaconda.org/conda-forge/scikit-image) (📥 2.9M · ⏱️ 04.09.2021): - ``` - conda install -c conda-forge scikit-image + git clone https://github.com/open-mmlab/mmdetection ```
-
imutils (🥈28 · ⭐ 3.8K · 💤) - 图像处理库。MIT +
glfw (🥈27 · ⭐ 8.4K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib -- [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 20 · 🔀 920 · 📦 20K · 📋 160 - 52% open · ⏱️ 15.01.2021): +- [GitHub](https://github.com/glfw/glfw) (👨‍💻 180 · 🔀 3K · 📥 2.6M · 📦 1 · 📋 1.5K - 27% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/jrosebr1/imutils + git clone https://github.com/glfw/glfw ``` -- [PyPi](https://pypi.org/project/imutils) (📥 620K / month): +- [PyPi](https://pypi.org/project/glfw) (📥 80K / month): ``` - pip install imutils + pip install glfw ``` -- [Conda](https://anaconda.org/conda-forge/imutils) (📥 68K · ⏱️ 15.01.2021): +- [Conda](https://anaconda.org/conda-forge/glfw) (📥 42K · ⏱️ 10.12.2021): ``` - conda install -c conda-forge imutils + conda install -c conda-forge glfw ```
-
Kornia (🥈27 · ⭐ 5.1K) - PyTorch的开源可微分计算机视觉库。❗Unlicensed +
Kornia (🥈27 · ⭐ 5.6K) - Open Source Differentiable Computer Vision Library for.. ❗Unlicensed -- [GitHub](https://github.com/kornia/kornia) (👨‍💻 130 · 🔀 480 · 📥 130 · 📦 650 · 📋 460 - 20% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/kornia/kornia) (👨‍💻 140 · 🔀 540 · 📥 160 · 📦 830 · 📋 490 - 22% open · ⏱️ 12.12.2021): ``` git clone https://github.com/kornia/kornia ``` -- [PyPi](https://pypi.org/project/kornia) (📥 160K / month): +- [PyPi](https://pypi.org/project/kornia) (📥 180K / month): ``` pip install kornia ```
-
detectron2 (🥈26 · ⭐ 18K) - Detectron2是Facebook FAIR的高级目标检测平台。Apache-2 +
Wand (🥈27 · ⭐ 1.1K) - The ctypes-based simple ImageMagick binding for Python. MIT -- [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 190 · 🔀 4.6K · 📦 360 · 📋 2.7K - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/emcconville/wand) (👨‍💻 97 · 🔀 190 · 📥 5.3K · 📦 7.9K · 📋 360 - 3% open · ⏱️ 20.11.2021): ``` - git clone https://github.com/facebookresearch/detectron2 + git clone https://github.com/emcconville/wand ``` -- [Conda](https://anaconda.org/conda-forge/detectron2) (📥 32K · ⏱️ 30.07.2021): +- [PyPi](https://pypi.org/project/wand): ``` - conda install -c conda-forge detectron2 + pip install wand ```
-
MMDetection (🥈26 · ⭐ 17K) - OpenMMLab检测工具箱。Apache-2 +
detectron2 (🥈26 · ⭐ 19K) - Detectron2 is FAIR's next-generation platform for object.. Apache-2 -- [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 270 · 🔀 5.4K · 📦 140 · 📋 4.5K - 5% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 200 · 🔀 4.9K · 📦 440 · 📋 2.8K - 4% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/open-mmlab/mmdetection + git clone https://github.com/facebookresearch/detectron2 + ``` +- [Conda](https://anaconda.org/conda-forge/detectron2) (📥 36K · ⏱️ 30.07.2021): + ``` + conda install -c conda-forge detectron2 ```
-
InsightFace (🥈26 · ⭐ 10K) - MXNet和PyTorch上的人脸分析项目。MIT +
InsightFace (🥈26 · ⭐ 11K) - Face Analysis Project on MXNet and PyTorch. MIT -- [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 29 · 🔀 3.4K · 📦 100 · 📋 1.7K - 53% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 31 · 🔀 3.5K · 📦 120 · 📋 1.8K - 53% open · ⏱️ 03.12.2021): ``` git clone https://github.com/deepinsight/insightface ``` -- [PyPi](https://pypi.org/project/insightface) (📥 19K / month): +- [PyPi](https://pypi.org/project/insightface) (📥 23K / month): ``` pip install insightface ```
-
glfw (🥈26 · ⭐ 8.2K) - 一个用于OpenGL，Op​​enGL ES，Vulkan，窗口和输入的多平台库。❗️Zlib +
imageai (🥈26 · ⭐ 6.7K · 💤) - A python library built to empower developers to build applications.. MIT -- [GitHub](https://github.com/glfw/glfw) (👨‍💻 170 · 🔀 2.9K · 📥 2.5M · 📋 1.5K - 28% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (👨‍💻 15 · 🔀 1.8K · 📥 680K · 📦 1K · 📋 660 - 35% open · ⏱️ 08.05.2021): ``` - git clone https://github.com/glfw/glfw + git clone https://github.com/OlafenwaMoses/ImageAI ``` -- [PyPi](https://pypi.org/project/glfw) (📥 64K / month): +- [PyPi](https://pypi.org/project/imageai): ``` - pip install glfw + pip install imageai ``` -- [Conda](https://anaconda.org/conda-forge/glfw) (📥 39K · ⏱️ 08.04.2021): +
+
Face Recognition (🥈25 · ⭐ 43K) - The world's simplest facial recognition api for.. MIT + +- [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 47 · 🔀 12K · 📥 450 · 📋 1.2K - 53% open · ⏱️ 14.06.2021): + ``` - conda install -c conda-forge glfw + git clone https://github.com/ageitgey/face_recognition + ``` +- [PyPi](https://pypi.org/project/face_recognition) (📥 52K / month): + ``` + pip install face_recognition ```
-
imageai (🥈26 · ⭐ 6.6K) - python库旨在使开发人员能够构建应用程序。MIT +
Pillow (🥈24 · ⭐ 9.2K · 📉) - The friendly PIL fork (Python Imaging Library). ❗️PIL -- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (👨‍💻 15 · 🔀 1.8K · 📥 650K · 📦 960 · 📋 640 - 34% open · ⏱️ 08.05.2021): +- [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 380 · 🔀 1.6K · 📋 2.4K - 5% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/OlafenwaMoses/ImageAI + git clone https://github.com/python-pillow/Pillow ``` -- [PyPi](https://pypi.org/project/imageai): +- [PyPi](https://pypi.org/project/Pillow): ``` - pip install imageai + pip install Pillow + ``` +- [Conda](https://anaconda.org/conda-forge/pillow) (📥 12M · ⏱️ 10.11.2021): + ``` + conda install -c conda-forge pillow ```
-
Face Recognition (🥈25 · ⭐ 42K) - 简单的面部识别API。MIT +
facenet-pytorch (🥈24 · ⭐ 2.6K) - Pretrained Pytorch face detection (MTCNN) and recognition.. MIT -- [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 47 · 🔀 11K · 📥 450 · 📋 1.2K - 53% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 550 · 📥 180K · 📦 570 · 📋 140 - 36% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/ageitgey/face_recognition + git clone https://github.com/timesler/facenet-pytorch ``` -- [PyPi](https://pypi.org/project/face_recognition) (📥 45K / month): +- [PyPi](https://pypi.org/project/facenet-pytorch): ``` - pip install face_recognition + pip install facenet-pytorch ```
-
ImageHash (🥈25 · ⭐ 2.1K) - Python感知图像哈希模块。BSD-2 +
torchvision (🥈23 · ⭐ 11K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 -- [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 280 · 📦 3.5K · 📋 100 - 8% open · ⏱️ 07.09.2021): +- [GitHub](https://github.com/pytorch/vision) (👨‍💻 440 · 🔀 5.3K · 📋 2K - 23% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/JohannesBuchner/imagehash + git clone https://github.com/pytorch/vision ``` -- [PyPi](https://pypi.org/project/ImageHash): +- [PyPi](https://pypi.org/project/torchvision): ``` - pip install ImageHash + pip install torchvision ``` -- [Conda](https://anaconda.org/conda-forge/imagehash) (📥 160K · ⏱️ 15.07.2021): +- [Conda](https://anaconda.org/conda-forge/torchvision) (📥 160K · ⏱️ 27.09.2021): ``` - conda install -c conda-forge imagehash + conda install -c conda-forge torchvision ```
-
chainercv (🥈25 · ⭐ 1.5K · 💀) - ChainerCV：一个用于计算机视觉深度学习的库。MIT +
mtcnn (🥈23 · ⭐ 1.7K) - MTCNN face detection implementation for TensorFlow, as a PIP package. MIT -- [GitHub](https://github.com/chainer/chainercv) (👨‍💻 39 · 🔀 310 · 📦 260 · 📋 200 - 18% open · ⏱️ 07.01.2020): +- [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 430 · 📦 1.7K · 📋 97 - 61% open · ⏱️ 09.07.2021): ``` - git clone https://github.com/chainer/chainercv + git clone https://github.com/ipazc/mtcnn ``` -- [PyPi](https://pypi.org/project/chainercv) (📥 5.8K / month): +- [PyPi](https://pypi.org/project/mtcnn) (📥 33K / month): ``` - pip install chainercv + pip install mtcnn ```
-
facenet-pytorch (🥉24 · ⭐ 2.4K) - 预训练的Pytorch人脸检测（MTCNN）和识别。MIT +
Image Deduplicator (🥉22 · ⭐ 3.9K · 💀) - Finding duplicate images made easy!. Apache-2 -- [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 520 · 📥 150K · 📦 500 · 📋 140 - 35% open · ⏱️ 23.05.2021): +- [GitHub](https://github.com/idealo/imagededup) (👨‍💻 10 · 🔀 330 · 📦 21 · 📋 87 - 32% open · ⏱️ 23.11.2020): ``` - git clone https://github.com/timesler/facenet-pytorch + git clone https://github.com/idealo/imagededup ``` -- [PyPi](https://pypi.org/project/facenet-pytorch) (📥 12K / month): +- [PyPi](https://pypi.org/project/imagededup) (📥 2.8K / month): ``` - pip install facenet-pytorch + pip install imagededup ```
-
Image Super-Resolution (🥉23 · ⭐ 3.1K) - 图像超精度变换。Apache-2 +
Image Super-Resolution (🥉22 · ⭐ 3.3K) - Super-scale your images and run experiments with.. Apache-2 -- [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 550 · 📦 60 · 📋 180 - 41% open · ⏱️ 02.06.2021): +- [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 570 · 📦 68 · 📋 190 - 42% open · ⏱️ 02.06.2021): ``` git clone https://github.com/idealo/image-super-resolution ``` -- [PyPi](https://pypi.org/project/ISR) (📥 10K / month): +- [PyPi](https://pypi.org/project/ISR) (📥 5.8K / month): ``` pip install ISR ``` -- [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (📥 170 · ⏱️ 01.04.2019): +- [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (📥 190 · ⏱️ 01.04.2019): ``` docker pull idealo/image-super-resolution-gpu ```
-
opencv-python (🥉23 · ⭐ 2.3K) - 自动化的CI工具链可生成预编译的opencv-python。❗Unlicensed +
Torch Points 3D (🥉22 · ⭐ 1.6K) - Pytorch framework for doing deep learning on point clouds. BSD-3 -- [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 33 · 🔀 440 · 📋 470 - 8% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/nicolas-chaulet/torch-points3d) (👨‍💻 29 · 🔀 260 · 📦 4 · 📋 300 - 29% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/skvark/opencv-python + git clone https://github.com/nicolas-chaulet/torch-points3d ``` -- [PyPi](https://pypi.org/project/opencv-python) (📥 4.7M / month): +- [PyPi](https://pypi.org/project/torch-points3d) (📥 1K / month): ``` - pip install opencv-python + pip install torch-points3d ```
-
vit-pytorch (🥉22 · ⭐ 6K) - 实现视觉transformer，一种简单的方法。MIT +
chainercv (🥉22 · ⭐ 1.5K · 💀) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT -- [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 11 · 🔀 820 · 📦 44 · 📋 140 - 46% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/chainer/chainercv) (👨‍💻 39 · 🔀 310 · 📦 270 · 📋 200 - 18% open · ⏱️ 07.01.2020): ``` - git clone https://github.com/lucidrains/vit-pytorch + git clone https://github.com/chainer/chainercv ``` -- [PyPi](https://pypi.org/project/vit-pytorch) (📥 4.4K / month): +- [PyPi](https://pypi.org/project/chainercv): ``` - pip install vit-pytorch + pip install chainercv ```
-
Image Deduplicator (🥉22 · ⭐ 3.8K · 💤) - 图像查重。Apache-2 +
mahotas (🥉22 · ⭐ 720) - Computer Vision in Python. ❗Unlicensed -- [GitHub](https://github.com/idealo/imagededup) (👨‍💻 9 · 🔀 320 · 📦 18 · 📋 82 - 29% open · ⏱️ 23.11.2020): +- [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 32 · 🔀 140 · 📦 720 · 📋 76 - 19% open · ⏱️ 07.12.2021): ``` - git clone https://github.com/idealo/imagededup + git clone https://github.com/luispedro/mahotas ``` -- [PyPi](https://pypi.org/project/imagededup) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/mahotas): ``` - pip install imagededup + pip install mahotas + ``` +- [Conda](https://anaconda.org/conda-forge/mahotas) (📥 310K · ⏱️ 17.11.2021): + ``` + conda install -c conda-forge mahotas ```
-
vidgear (🥉22 · ⭐ 1.9K) - 高性能跨平台视频处理Python框架。Apache-2 +
segmentation_models (🥉21 · ⭐ 3.6K · 💀) - Segmentation models with pretrained backbones. Keras.. MIT -- [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 6 · 🔀 140 · 📥 440 · 📦 140 · 📋 170 - 0% open · ⏱️ 02.09.2021): +- [GitHub](https://github.com/qubvel/segmentation_models) (👨‍💻 14 · 🔀 840 · 📋 450 - 44% open · ⏱️ 17.04.2020): ``` - git clone https://github.com/abhiTronix/vidgear + git clone https://github.com/qubvel/segmentation_models ``` -- [PyPi](https://pypi.org/project/vidgear) (📥 2.4K / month): +- [PyPi](https://pypi.org/project/segmentation_models) (📥 57K / month): ``` - pip install vidgear + pip install segmentation_models ```
-
mtcnn (🥉22 · ⭐ 1.6K) - TensorFlow的MTCNN人脸检测实现。MIT +
PyTorch3D (🥉20 · ⭐ 5.5K) - PyTorch3D is FAIR's library of reusable components for.. ❗Unlicensed -- [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 420 · 📦 1.5K · 📋 96 - 61% open · ⏱️ 09.07.2021): +- [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 75 · 🔀 750 · 📦 130 · 📋 840 - 9% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/ipazc/mtcnn + git clone https://github.com/facebookresearch/pytorch3d ``` -- [PyPi](https://pypi.org/project/mtcnn) (📥 28K / month): +- [PyPi](https://pypi.org/project/pytorch3d): ``` - pip install mtcnn + pip install pytorch3d + ``` +- [Conda](https://anaconda.org/pytorch3d/pytorch3d) (📥 26K · ⏱️ 13.12.2021): + ``` + conda install -c pytorch3d pytorch3d ```
-
lightly (🥉22 · ⭐ 1.2K) - 一个用于对图像进行自监督学习的python库。MIT +
Augmentor (🥉20 · ⭐ 4.6K) - Image augmentation library in Python for machine learning. MIT -- [GitHub](https://github.com/lightly-ai/lightly) (👨‍💻 12 · 🔀 75 · 📦 22 · 📋 240 - 20% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 810 · 📦 390 · 📋 180 - 61% open · ⏱️ 15.10.2021): ``` - git clone https://github.com/lightly-ai/lightly + git clone https://github.com/mdbloice/Augmentor ``` -- [PyPi](https://pypi.org/project/lightly) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/Augmentor): ``` - pip install lightly + pip install Augmentor ```
-
mahotas (🥉22 · ⭐ 720) - Python中的计算机视觉。❗Unlicensed +
vidgear (🥉20 · ⭐ 2K) - High-performance cross-platform Video Processing Python framework.. Apache-2 -- [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 31 · 🔀 130 · 📦 690 · 📋 72 - 19% open · ⏱️ 31.05.2021): +- [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 9 · 🔀 150 · 📥 500 · 📦 160 · 📋 190 - 1% open · ⏱️ 05.12.2021): ``` - git clone https://github.com/luispedro/mahotas - ``` -- [PyPi](https://pypi.org/project/mahotas) (📥 12K / month): - ``` - pip install mahotas + git clone https://github.com/abhiTronix/vidgear ``` -- [Conda](https://anaconda.org/conda-forge/mahotas) (📥 300K · ⏱️ 22.01.2021): +- [PyPi](https://pypi.org/project/vidgear): ``` - conda install -c conda-forge mahotas + pip install vidgear ```
-
pyvips (🥉22 · ⭐ 360) - 使用cffi的libvips的python接口。MIT +
Classy Vision (🥉20 · ⭐ 1.4K) - An end-to-end PyTorch framework for image and video.. MIT -- [GitHub](https://github.com/libvips/pyvips) (👨‍💻 11 · 🔀 30 · 📦 230 · 📋 240 - 35% open · ⏱️ 13.09.2021): +- [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 66 · 🔀 240 · 📋 74 - 17% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/libvips/pyvips + git clone https://github.com/facebookresearch/ClassyVision ``` -- [PyPi](https://pypi.org/project/pyvips) (📥 13K / month): +- [PyPi](https://pypi.org/project/classy_vision) (📥 1.4K / month): ``` - pip install pyvips + pip install classy_vision ``` -- [Conda](https://anaconda.org/conda-forge/pyvips) (📥 12K · ⏱️ 10.09.2021): +- [Conda](https://anaconda.org/conda-forge/classy_vision) (📥 11K · ⏱️ 11.12.2020): ``` - conda install -c conda-forge pyvips + conda install -c conda-forge classy_vision ```
-
PyTorch3D (🥉21 · ⭐ 5.3K) - PyTorch3D是FAIR的深度学习可重用组件库。❗Unlicensed +
CellProfiler (🥉20 · ⭐ 630) - An open-source application for biological image analysis. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 71 · 🔀 690 · 📦 110 · 📋 740 - 7% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 120 · 🔀 290 · 📥 2K · 📦 5 · 📋 3K - 6% open · ⏱️ 05.11.2021): ``` - git clone https://github.com/facebookresearch/pytorch3d - ``` -- [PyPi](https://pypi.org/project/pytorch3d) (📥 7K / month): - ``` - pip install pytorch3d + git clone https://github.com/CellProfiler/CellProfiler ``` -- [Conda](https://anaconda.org/pytorch3d/pytorch3d) (📥 20K · ⏱️ 06.10.2021): +- [PyPi](https://pypi.org/project/cellprofiler): ``` - conda install -c pytorch3d pytorch3d + pip install cellprofiler ```
-
Face Alignment (🥉21 · ⭐ 5.3K) - 使用pytorch构建2D和3D人脸对齐库。BSD-3 +
Caer (🥉20 · ⭐ 580) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT -- [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.1K · 📋 260 - 16% open · ⏱️ 04.08.2021): +- [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 8 · 🔀 63 · 📥 19 · 📋 15 - 13% open · ⏱️ 13.10.2021): ``` - git clone https://github.com/1adrianb/face-alignment + git clone https://github.com/jasmcaus/caer ``` -- [PyPi](https://pypi.org/project/face-alignment) (📥 6.7K / month): +- [PyPi](https://pypi.org/project/caer) (📥 4.1K / month): ``` - pip install face-alignment + pip install caer ```
-
MMF (🥉21 · ⭐ 4.6K) - 来自视觉和语言多模态研究的模块化框架。BSD-3 +
pyvips (🥉20 · ⭐ 370) - python binding for libvips using cffi. MIT -- [GitHub](https://github.com/facebookresearch/mmf) (👨‍💻 79 · 🔀 760 · 📦 9 · 📋 550 - 25% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/libvips/pyvips) (👨‍💻 12 · 🔀 32 · 📦 250 · 📋 260 - 36% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/facebookresearch/mmf + git clone https://github.com/libvips/pyvips ``` -- [PyPi](https://pypi.org/project/mmf) (📥 530 / month): +- [PyPi](https://pypi.org/project/pyvips): ``` - pip install mmf + pip install pyvips + ``` +- [Conda](https://anaconda.org/conda-forge/pyvips) (📥 14K · ⏱️ 22.11.2021): + ``` + conda install -c conda-forge pyvips ```
-
Luminoth (🥉21 · ⭐ 2.4K · 💀) - 用于计算机视觉的深度学习工具包。BSD-3 +
vit-pytorch (🥉19 · ⭐ 7.2K) - Implementation of Vision Transformer, a simple way to.. MIT -- [GitHub](https://github.com/tryolabs/luminoth) (👨‍💻 15 · 🔀 400 · 📥 12K · 📦 35 · 📋 180 - 28% open · ⏱️ 07.01.2020): +- [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 12 · 🔀 1.1K · 📦 59 · 📋 150 - 47% open · ⏱️ 04.12.2021): ``` - git clone https://github.com/tryolabs/luminoth + git clone https://github.com/lucidrains/vit-pytorch ``` -- [PyPi](https://pypi.org/project/luminoth) (📥 990 / month): +- [PyPi](https://pypi.org/project/vit-pytorch): ``` - pip install luminoth + pip install vit-pytorch ```
-
Pillow-SIMD (🥉21 · ⭐ 1.7K · 💀) - 友好的PIL fork。❗️PIL +
PaddleDetection (🥉19 · ⭐ 5.8K) - Object detection and instance segmentation toolkit.. Apache-2 -- [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 310 · 🔀 71 · 📦 460 · 📋 67 - 16% open · ⏱️ 02.06.2020): +- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 75 · 🔀 1.4K · 📦 6 · 📋 2.7K - 28% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/uploadcare/pillow-simd - ``` -- [PyPi](https://pypi.org/project/pillow-simd) (📥 43K / month): - ``` - pip install pillow-simd + git clone https://github.com/PaddlePaddle/PaddleDetection ```
-
CellProfiler (🥉21 · ⭐ 610) - 生物图像分析的开源应用程序。❗Unlicensed +
Face Alignment (🥉19 · ⭐ 5.4K) - 2D and 3D Face alignment library build using pytorch. BSD-3 -- [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 120 · 🔀 290 · 📥 1.6K · 📦 4 · 📋 3K - 6% open · ⏱️ 14.09.2021): +- [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.1K · 📋 260 - 18% open · ⏱️ 04.08.2021): ``` - git clone https://github.com/CellProfiler/CellProfiler + git clone https://github.com/1adrianb/face-alignment ``` -- [PyPi](https://pypi.org/project/cellprofiler) (📥 790 / month): +- [PyPi](https://pypi.org/project/face-alignment): ``` - pip install cellprofiler + pip install face-alignment ```
-
segmentation_models (🥉20 · ⭐ 3.5K · 💀) - Segmentation models with pretrained backbones. Keras.. MIT +
Luminoth (🥉19 · ⭐ 2.4K · 💀) - Deep Learning toolkit for Computer Vision. BSD-3 -- [GitHub](https://github.com/qubvel/segmentation_models) (👨‍💻 14 · 🔀 810 · 📋 440 - 43% open · ⏱️ 17.04.2020): +- [GitHub](https://github.com/tryolabs/luminoth) (👨‍💻 15 · 🔀 400 · 📥 12K · 📦 39 · 📋 180 - 28% open · ⏱️ 07.01.2020): ``` - git clone https://github.com/qubvel/segmentation_models + git clone https://github.com/tryolabs/luminoth ``` -- [PyPi](https://pypi.org/project/segmentation_models) (📥 38K / month): +- [PyPi](https://pypi.org/project/luminoth) (📥 850 / month): ``` - pip install segmentation_models + pip install luminoth ```
-
tensorflow-graphics (🥉20 · ⭐ 2.5K) - TensorFlow图神经网络：可微分的图layerApache-2 +
lightly (🥉19 · ⭐ 1.3K) - A python library for self-supervised learning on images. MIT -- [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 34 · 🔀 310 · 📋 150 - 44% open · ⏱️ 27.09.2021): +- [GitHub](https://github.com/lightly-ai/lightly) (👨‍💻 14 · 🔀 86 · 📦 25 · 📋 290 - 21% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/tensorflow/graphics + git clone https://github.com/lightly-ai/lightly ``` -- [PyPi](https://pypi.org/project/tensorflow-graphics) (📥 2.3K / month): +- [PyPi](https://pypi.org/project/lightly): ``` - pip install tensorflow-graphics + pip install lightly ```
-
Torch Points 3D (🥉20 · ⭐ 1.5K) - 用于在点云上进行深度学习的Pytorch框架。BSD-3 +
MMF (🥉18 · ⭐ 4.7K) - A modular framework for vision & language multimodal research from.. BSD-3 -- [GitHub](https://github.com/nicolas-chaulet/torch-points3d) (👨‍💻 29 · 🔀 240 · 📦 3 · 📋 280 - 28% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/facebookresearch/mmf) (👨‍💻 89 · 🔀 780 · 📦 10 · 📋 570 - 26% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/nicolas-chaulet/torch-points3d + git clone https://github.com/facebookresearch/mmf ``` -- [PyPi](https://pypi.org/project/torch-points3d): +- [PyPi](https://pypi.org/project/mmf): ``` - pip install torch-points3d + pip install mmf ```
-
Classy Vision (🥉20 · ⭐ 1.4K) - 用于图像和视频的端到端PyTorch框架。MIT +
tensorflow-graphics (🥉17 · ⭐ 2.6K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 -- [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 66 · 🔀 230 · 📋 73 - 16% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 34 · 🔀 320 · 📋 160 - 43% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/facebookresearch/ClassyVision - ``` -- [PyPi](https://pypi.org/project/classy_vision) (📥 2.6K / month): - ``` - pip install classy_vision + git clone https://github.com/tensorflow/graphics ``` -- [Conda](https://anaconda.org/conda-forge/classy_vision) (📥 9.8K · ⏱️ 11.12.2020): +- [PyPi](https://pypi.org/project/tensorflow-graphics): ``` - conda install -c conda-forge classy_vision + pip install tensorflow-graphics ```
-
Norfair (🥉20 · ⭐ 1.1K) - 轻量级Python库，用于向其中添加实时2D对象跟踪。BSD-3 +
Norfair (🥉17 · ⭐ 1.2K) - Lightweight Python library for adding real-time 2D object tracking to.. BSD-3 -- [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 9 · 🔀 80 · 📋 36 - 19% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 9 · 🔀 88 · 📋 39 - 20% open · ⏱️ 01.10.2021): ``` git clone https://github.com/tryolabs/norfair ``` -- [PyPi](https://pypi.org/project/norfair) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/norfair): ``` pip install norfair ```
-
Caer (🥉20 · ⭐ 550) - 轻量级的计算机视觉库。MIT +
DE⫶TR (🥉16 · ⭐ 8.1K) - End-to-End Object Detection with Transformers. Apache-2 -- [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 7 · 🔀 60 · 📥 19 · 📋 15 - 20% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/facebookresearch/detr) (👨‍💻 24 · 🔀 1.4K · 📋 400 - 32% open · ⏱️ 18.10.2021): ``` - git clone https://github.com/jasmcaus/caer - ``` -- [PyPi](https://pypi.org/project/caer) (📥 6.3K / month): - ``` - pip install caer + git clone https://github.com/facebookresearch/detr ```
-
PaddleDetection (🥉19 · ⭐ 4.7K) - 对象检测和实例分割工具箱。Apache-2 +
opencv-python (🥉16 · ⭐ 2.4K) - Automated CI toolchain to produce precompiled opencv-.. ❗Unlicensed -- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 65 · 🔀 1.2K · 📦 6 · 📋 2.4K - 24% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 36 · 🔀 470 · 📋 490 - 5% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/PaddlePaddle/PaddleDetection + git clone https://github.com/skvark/opencv-python + ``` +- [PyPi](https://pypi.org/project/opencv-python): + ``` + pip install opencv-python ```
-
Augmentor (🥉19 · ⭐ 4.5K · 💀) - Python中的图像增强库，用于机器学习。MIT +
Pillow-SIMD (🥉16 · ⭐ 1.7K · 💀) - The friendly PIL fork. ❗️PIL -- [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 800 · 📦 370 · 📋 180 - 61% open · ⏱️ 09.03.2020): +- [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 310 · 🔀 70 · 📦 500 · 📋 69 - 17% open · ⏱️ 02.06.2020): ``` - git clone https://github.com/mdbloice/Augmentor + git clone https://github.com/uploadcare/pillow-simd ``` -- [PyPi](https://pypi.org/project/Augmentor): +- [PyPi](https://pypi.org/project/pillow-simd): ``` - pip install Augmentor + pip install pillow-simd ```
-
nude.py (🥉19 · ⭐ 820 · 💤) - 使用Python进行裸露检测。MIT +
nude.py (🥉16 · ⭐ 820 · 💀) - Nudity detection with Python. MIT -- [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 920 · 📋 10 - 70% open · ⏱️ 23.11.2020): +- [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 1.3K · 📋 10 - 70% open · ⏱️ 23.11.2020): ``` git clone https://github.com/hhatto/nude.py ``` -- [PyPi](https://pypi.org/project/nudepy) (📥 6.2K / month): +- [PyPi](https://pypi.org/project/nudepy): ``` pip install nudepy ```
-
image-match (🥉18 · ⭐ 2.6K) - 快速搜索数十亿张图像。❗Unlicensed +
PySlowFast (🥉15 · ⭐ 4.4K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 -- [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 370 · 📋 95 - 49% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 25 · 🔀 820 · 📦 5 · 📋 470 - 49% open · ⏱️ 28.10.2021): ``` - git clone https://github.com/EdjoLabs/image-match - ``` -- [PyPi](https://pypi.org/project/image_match) (📥 1.2K / month): - ``` - pip install image_match + git clone https://github.com/facebookresearch/SlowFast ```
-
PySlowFast (🥉17 · ⭐ 4.2K) - PySlowFast：来自FAIR的视频理解代码库。Apache-2 +
pycls (🥉15 · ⭐ 1.8K) - Codebase for Image Classification Research, written in PyTorch. MIT -- [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 25 · 🔀 800 · 📦 5 · 📋 460 - 49% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 13 · 🔀 200 · 📦 4 · 📋 77 - 28% open · ⏱️ 19.08.2021): ``` - git clone https://github.com/facebookresearch/SlowFast + git clone https://github.com/facebookresearch/pycls ```
-
DE⫶TR (🥉16 · ⭐ 7.7K) - End-to-End Object Detection with Transformers. Apache-2 +
image-match (🥉14 · ⭐ 2.7K) - Quickly search over billions of images. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/detr) (👨‍💻 23 · 🔀 1.3K · 📋 380 - 29% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 370 · 📋 99 - 51% open · ⏱️ 21.09.2021): ``` - git clone https://github.com/facebookresearch/detr + git clone https://github.com/EdjoLabs/image-match ``` -
-
pycls (🥉16 · ⭐ 1.7K) - 用PyTorch编写的图像分类研究代码库。MIT - -- [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 13 · 🔀 190 · 📦 4 · 📋 72 - 26% open · ⏱️ 19.08.2021): - +- [PyPi](https://pypi.org/project/image_match): ``` - git clone https://github.com/facebookresearch/pycls + pip install image_match ```

-## 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 (🥇33 · ⭐ 9.8K) - Python中的网络分析。❗Unlicensed +
networkx (🥇32 · ⭐ 10K) - Network Analysis in Python. ❗Unlicensed -- [GitHub](https://github.com/networkx/networkx) (👨‍💻 550 · 🔀 2.3K · 📥 56 · 📦 87K · 📋 2.6K - 6% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/networkx/networkx) (👨‍💻 560 · 🔀 2.4K · 📥 57 · 📦 93K · 📋 2.6K - 6% open · ⏱️ 13.12.2021): ``` git clone https://github.com/networkx/networkx ``` -- [PyPi](https://pypi.org/project/networkx) (📥 25M / month): +- [PyPi](https://pypi.org/project/networkx) (📥 17M / month): ``` pip install networkx ``` -- [Conda](https://anaconda.org/conda-forge/networkx) (📥 4.7M · ⏱️ 10.09.2021): +- [Conda](https://anaconda.org/conda-forge/networkx) (📥 5.2M · ⏱️ 26.10.2021): ``` conda install -c conda-forge networkx ```
-
dgl (🥇28 · ⭐ 8.1K) - 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 (🥇28 · ⭐ 8.6K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 -- [GitHub](https://github.com/dmlc/dgl) (👨‍💻 160 · 🔀 1.7K · 📋 1.2K - 20% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/dmlc/dgl) (👨‍💻 180 · 🔀 1.9K · 📋 1.3K - 21% open · ⏱️ 15.12.2021): ``` git clone https://github.com/dmlc/dgl ``` -- [PyPi](https://pypi.org/project/dgl) (📥 80K / month): +- [PyPi](https://pypi.org/project/dgl) (📥 68K / month): ``` pip install dgl ```
-
igraph (🥇28 · ⭐ 880) - Igraph的Python接口。❗️GPL-2.0 +
igraph (🥇27 · ⭐ 900) - Python interface for igraph. ❗️GPL-2.0 -- [GitHub](https://github.com/igraph/python-igraph) (👨‍💻 54 · 🔀 200 · 📥 250K · 📦 2K · 📋 330 - 7% open · ⏱️ 09.10.2021): +- [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) (📥 130K / month): +- [PyPi](https://pypi.org/project/python-igraph) (📥 220K / month): ``` pip install python-igraph ``` -- [Conda](https://anaconda.org/conda-forge/igraph) (📥 250K · ⏱️ 16.06.2021): +- [Conda](https://anaconda.org/conda-forge/igraph) (📥 260K · ⏱️ 12.11.2021): ``` conda install -c conda-forge igraph ```
-
PyTorch Geometric (🥈27 · ⭐ 13K) - PyTorch的几何深度学习扩展库。MIT +
PyTorch Geometric (🥈23 · ⭐ 13K) - Geometric Deep Learning Extension Library for PyTorch. MIT -- [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 210 · 🔀 2.1K · 📋 2.2K - 37% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 230 · 🔀 2.3K · 📋 2.3K - 37% open · ⏱️ 16.12.2021): ``` git clone https://github.com/rusty1s/pytorch_geometric ``` -- [PyPi](https://pypi.org/project/torch-geometric) (📥 42K / month): +- [PyPi](https://pypi.org/project/torch-geometric): ``` pip install torch-geometric ```
-
StellarGraph (🥈26 · ⭐ 2.2K) - StellarGraph-图机器学习库。Apache-2 +
Karate Club (🥈23 · ⭐ 1.5K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 -- [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 320 · 📦 91 · 📋 960 - 24% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 13 · 🔀 170 · 📦 65 · 📋 65 - 1% open · ⏱️ 21.11.2021): + + ``` + git clone https://github.com/benedekrozemberczki/karateclub + ``` +- [PyPi](https://pypi.org/project/karateclub) (📥 5.2K / month): + ``` + pip install karateclub + ``` +
+
StellarGraph (🥈22 · ⭐ 2.2K) - StellarGraph - Machine Learning on Graphs. Apache-2 + +- [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 320 · 📦 100 · 📋 980 - 25% open · ⏱️ 29.10.2021): ``` git clone https://github.com/stellargraph/stellargraph ``` -- [PyPi](https://pypi.org/project/stellargraph) (📥 13K / month): +- [PyPi](https://pypi.org/project/stellargraph): ``` pip install stellargraph ```
-
ogb (🥈24 · ⭐ 1.1K) - 用于图机器学习的基准数据集，数据加载器和评估器。MIT +
ogb (🥈22 · ⭐ 1.2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT -- [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 16 · 🔀 220 · 📦 160 · ⏱️ 07.10.2021): +- [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 18 · 🔀 240 · 📦 190 · ⏱️ 06.12.2021): ``` git clone https://github.com/snap-stanford/ogb ``` -- [PyPi](https://pypi.org/project/ogb) (📥 6.8K / month): +- [PyPi](https://pypi.org/project/ogb): ``` pip install ogb ```
-
AmpliGraph (🥈23 · ⭐ 1.6K) - 用于知识表示学习的Python库。Apache-2 +
Spektral (🥈21 · ⭐ 1.9K) - Graph Neural Networks with Keras and Tensorflow 2. MIT -- [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 180 · 📦 16 · 📋 200 - 8% open · ⏱️ 25.05.2021): +- [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 19 · 🔀 260 · 📦 87 · 📋 200 - 18% open · ⏱️ 26.10.2021): ``` - git clone https://github.com/Accenture/AmpliGraph + git clone https://github.com/danielegrattarola/spektral ``` -- [PyPi](https://pypi.org/project/ampligraph) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/spektral) (📥 4.4K / month): ``` - pip install ampligraph + pip install spektral ```
-
pygal (🥈22 · ⭐ 2.4K) - PYthon svg GrAph绘图库。❗️LGPL-3.0 +
Node2Vec (🥈21 · ⭐ 820) - Implementation of the node2vec algorithm. MIT -- [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 380 · 📋 400 - 38% open · ⏱️ 18.08.2021): +- [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 9 · 🔀 180 · 📋 69 - 1% open · ⏱️ 09.10.2021): ``` - git clone https://github.com/Kozea/pygal + git clone https://github.com/eliorc/node2vec ``` -- [PyPi](https://pypi.org/project/pygal) (📥 120K / month): +- [PyPi](https://pypi.org/project/node2vec) (📥 130K / month): ``` - pip install pygal + pip install node2vec ``` -- [Conda](https://anaconda.org/conda-forge/pygal) (📥 8.6K · ⏱️ 04.06.2019): +- [Conda](https://anaconda.org/conda-forge/node2vec) (📥 20K · ⏱️ 25.04.2020): ``` - conda install -c conda-forge pygal + conda install -c conda-forge node2vec ```
-
Spektral (🥈21 · ⭐ 1.9K) - 使用Keras和Tensorflow 2的图神经网络。MIT +
pytorch_geometric_temporal (🥈20 · ⭐ 1.2K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT -- [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 19 · 🔀 250 · 📦 75 · 📋 180 - 16% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (👨‍💻 12 · 🔀 160 · 📋 70 - 2% open · ⏱️ 21.11.2021): ``` - git clone https://github.com/danielegrattarola/spektral + git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal ``` -- [PyPi](https://pypi.org/project/spektral) (📥 7.9K / month): +- [PyPi](https://pypi.org/project/torch-geometric-temporal) (📥 1K / month): ``` - pip install spektral + pip install torch-geometric-temporal ```
-
DeepWalk (🥈20 · ⭐ 2.3K · 💀) - DeepWalk-图的深度学习。❗️GPL-3.0 +
Paddle Graph Learning (🥈20 · ⭐ 1.2K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 -- [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 770 · 📦 44 · 📋 100 - 22% open · ⏱️ 02.04.2020): +- [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 21 · 🔀 190 · 📦 23 · 📋 96 - 35% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/phanein/deepwalk + git clone https://github.com/PaddlePaddle/PGL ``` -- [PyPi](https://pypi.org/project/deepwalk) (📥 3.3K / month): +- [PyPi](https://pypi.org/project/pgl) (📥 980 / month): ``` - pip install deepwalk + pip install pgl ```
-
Karate Club (🥈20 · ⭐ 1.4K) - 面向API的开源Python框架。❗️GPL-3.0 +
PyKEEN (🥈20 · ⭐ 630) - A Python library for learning and evaluating knowledge graph embeddings. MIT -- [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 13 · 🔀 160 · 📦 58 · ⏱️ 29.09.2021): +- [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 24 · 🔀 90 · 📥 92 · 📋 300 - 31% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/benedekrozemberczki/karateclub + git clone https://github.com/pykeen/pykeen ``` -- [PyPi](https://pypi.org/project/karateclub): +- [PyPi](https://pypi.org/project/pykeen) (📥 900 / month): ``` - pip install karateclub + pip install pykeen ```
-
Node2Vec (🥈20 · ⭐ 780) - node2vec算法的实现。MIT +
pygal (🥉19 · ⭐ 2.4K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 -- [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 9 · 🔀 170 · ⏱️ 09.10.2021): +- [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 380 · 📋 400 - 38% open · ⏱️ 24.11.2021): ``` - git clone https://github.com/eliorc/node2vec - ``` -- [PyPi](https://pypi.org/project/node2vec) (📥 32K / month): - ``` - pip install node2vec - ``` -- [Conda](https://anaconda.org/conda-forge/node2vec) (📥 19K · ⏱️ 25.04.2020): - ``` - conda install -c conda-forge node2vec + git clone https://github.com/Kozea/pygal ``` -
-
PyKEEN (🥈20 · ⭐ 550) - 一个用于学习和评估知识图嵌入的Python库。MIT - -- [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 21 · 🔀 78 · 📥 92 · 📋 270 - 35% open · ⏱️ 12.10.2021): - +- [PyPi](https://pypi.org/project/pygal): ``` - git clone https://github.com/pykeen/pykeen + pip install pygal ``` -- [PyPi](https://pypi.org/project/pykeen) (📥 680 / month): +- [Conda](https://anaconda.org/conda-forge/pygal) (📥 9.5K · ⏱️ 04.06.2019): ``` - pip install pykeen + conda install -c conda-forge pygal ```
-
pytorch_geometric_temporal (🥉19 · ⭐ 1.1K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. MIT +
DeepWalk (🥉19 · ⭐ 2.4K · 💀) - DeepWalk - Deep Learning for Graphs. ❗️GPL-3.0 -- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (👨‍💻 12 · 🔀 140 · 📋 59 - 3% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 780 · 📦 46 · 📋 100 - 23% open · ⏱️ 02.04.2020): ``` - git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal + git clone https://github.com/phanein/deepwalk ``` -- [PyPi](https://pypi.org/project/torch-geometric-temporal) (📥 1.3K / month): +- [PyPi](https://pypi.org/project/deepwalk) (📥 2.5K / month): ``` - pip install torch-geometric-temporal + pip install deepwalk ```
-
torch-cluster (🥉19 · ⭐ 420) - 优化图聚类的PyTorch扩展库MIT +
AmpliGraph (🥉18 · ⭐ 1.7K · 💤) - Python library for Representation Learning on Knowledge.. Apache-2 -- [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 19 · 🔀 80 · 📋 88 - 11% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 190 · 📦 16 · 📋 200 - 9% open · ⏱️ 25.05.2021): ``` - git clone https://github.com/rusty1s/pytorch_cluster + git clone https://github.com/Accenture/AmpliGraph ``` -- [PyPi](https://pypi.org/project/torch-cluster) (📥 8.5K / month): +- [PyPi](https://pypi.org/project/ampligraph): ``` - pip install torch-cluster + pip install ampligraph ```
-
Paddle Graph Learning (🥉17 · ⭐ 1.1K) - paddle图机器学习。Apache-2 +
pyRDF2Vec (🥉17 · ⭐ 140) - Python Implementation and Extension of RDF2Vec. MIT -- [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 19 · 🔀 180 · 📦 20 · 📋 88 - 32% open · ⏱️ 23.08.2021): +- [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 5 · 🔀 24 · 📋 44 - 6% open · ⏱️ 08.11.2021): ``` - git clone https://github.com/PaddlePaddle/PGL + git clone https://github.com/IBCNServices/pyRDF2Vec ``` -- [PyPi](https://pypi.org/project/pgl): +- [PyPi](https://pypi.org/project/pyrdf2vec) (📥 170 / month): ``` - pip install pgl + pip install pyrdf2vec ```
-
PyTorch-BigGraph (🥉16 · ⭐ 2.9K) - 从大型图网络结构生成embedding嵌入。❗Unlicensed +
PyTorch-BigGraph (🥉16 · ⭐ 3K) - Generate embeddings from large-scale graph-structured.. ❗Unlicensed -- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 24 · 🔀 390 · 📥 120 · 📋 170 - 29% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 24 · 🔀 400 · 📥 120 · 📋 170 - 30% open · ⏱️ 27.10.2021): ``` git clone https://github.com/facebookresearch/PyTorch-BigGraph ``` -- [PyPi](https://pypi.org/project/torchbiggraph) (📥 710 / month): +- [PyPi](https://pypi.org/project/torchbiggraph) (📥 810 / month): ``` pip install torchbiggraph ```
-
GraphEmbedding (🥉16 · ⭐ 2.3K · 💤) - 图嵌入算法的实现和实验。MIT +
GraphEmbedding (🥉16 · ⭐ 2.5K · 💀) - Implementation and experiments of graph embedding.. MIT -- [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 8 · 🔀 700 · 📦 12 · 📋 52 - 73% open · ⏱️ 18.10.2020): +- [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 8 · 🔀 740 · 📦 12 · 📋 52 - 73% open · ⏱️ 18.10.2020): ``` git clone https://github.com/shenweichen/GraphEmbedding ```
-
kglib (🥉16 · ⭐ 460 · 💤) - Grakn知识图库（ML R＆D）。Apache-2 +
kglib (🥉16 · ⭐ 480) - Grakn Knowledge Graph Library (ML R&D). Apache-2 -- [GitHub](https://github.com/vaticle/kglib) (👨‍💻 7 · 🔀 85 · 📥 210 · 📋 58 - 15% open · ⏱️ 15.01.2021): +- [GitHub](https://github.com/vaticle/kglib) (👨‍💻 7 · 🔀 86 · 📥 210 · 📋 58 - 15% open · ⏱️ 22.10.2021): ``` git clone https://github.com/graknlabs/kglib ``` -- [PyPi](https://pypi.org/project/grakn-kglib) (📥 90 / month): +- [PyPi](https://pypi.org/project/grakn-kglib) (📥 73 / month): ``` pip install grakn-kglib ```
-
graph-nets (🥉15 · ⭐ 5K · 💤) - 在Tensorflow中构建图神经网络。Apache-2 +
torch-cluster (🥉15 · ⭐ 450) - PyTorch Extension Library of Optimized Graph Cluster.. MIT -- [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 750 · 📋 120 - 2% open · ⏱️ 04.12.2020): +- [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 19 · 🔀 84 · 📋 91 - 9% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/deepmind/graph_nets + git clone https://github.com/rusty1s/pytorch_cluster ``` -- [PyPi](https://pypi.org/project/graph-nets) (📥 840 / month): +- [PyPi](https://pypi.org/project/torch-cluster): ``` - pip install graph-nets + pip install torch-cluster ```
-
pyRDF2Vec (🥉15 · ⭐ 130) - RDF2Vec的Python实现和扩展。MIT +
DeepGraph (🥉15 · ⭐ 250) - Analyze Data with Pandas-based Networks. Documentation:. ❗Unlicensed -- [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 5 · 🔀 21 · 📋 41 - 4% open · ⏱️ 05.07.2021): +- [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 36 · 📦 2 · 📋 14 - 64% open · ⏱️ 14.06.2021): ``` - git clone https://github.com/IBCNServices/pyRDF2Vec + git clone https://github.com/deepgraph/deepgraph ``` -- [PyPi](https://pypi.org/project/pyrdf2vec): +- [PyPi](https://pypi.org/project/deepgraph) (📥 300 / month): ``` - pip install pyrdf2vec + pip install deepgraph + ``` +- [Conda](https://anaconda.org/conda-forge/deepgraph) (📥 110K · ⏱️ 08.11.2021): + ``` + conda install -c conda-forge deepgraph ```
-
Euler (🥉14 · ⭐ 2.7K · 💀) - 分布式图深度学习框架。Apache-2 +
Euler (🥉14 · ⭐ 2.7K · 💀) - A distributed graph deep learning framework. Apache-2 -- [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 530 · 📋 320 - 67% open · ⏱️ 29.07.2020): +- [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 540 · 📋 320 - 67% open · ⏱️ 29.07.2020): ``` git clone https://github.com/alibaba/euler ``` -- [PyPi](https://pypi.org/project/euler-gl) (📥 9 / month): +- [PyPi](https://pypi.org/project/euler-gl) (📥 11 / month): ``` pip install euler-gl ```
-
GraphSAGE (🥉14 · ⭐ 2.5K · 💀) - 大型图上的表示学习。MIT +
AutoGL (🥉14 · ⭐ 720) - An autoML framework & toolkit for machine learning on graphs. Apache-2 -- [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 700 · 📋 150 - 59% open · ⏱️ 19.09.2018): +- [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 9 · 🔀 72 · 📋 14 - 21% open · ⏱️ 23.11.2021): ``` - git clone https://github.com/williamleif/GraphSAGE + git clone https://github.com/THUMNLab/AutoGL ``` -
-
OpenNE (🥉14 · ⭐ 1.5K · 💀) - 神经关系提取（NRE）的开源软件包。MIT - -- [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 460 · 📋 95 - 1% open · ⏱️ 12.08.2019): - +- [PyPi](https://pypi.org/project/auto-graph-learning) (📥 28 / month): ``` - git clone https://github.com/thunlp/OpenNE + pip install auto-graph-learning ```
-
AutoGL (🥉14 · ⭐ 690) - 用于图上机器学习的autoML框架和工具包。Apache-2 +
graph-nets (🥉13 · ⭐ 5K · 💤) - Build Graph Nets in Tensorflow. Apache-2 -- [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 9 · 🔀 70 · 📋 9 - 11% open · ⏱️ 12.08.2021): +- [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 760 · 📋 120 - 2% open · ⏱️ 04.12.2020): ``` - git clone https://github.com/THUMNLab/AutoGL + git clone https://github.com/deepmind/graph_nets ``` -- [PyPi](https://pypi.org/project/auto-graph-learning) (📥 27 / month): +- [PyPi](https://pypi.org/project/graph-nets): ``` - pip install auto-graph-learning + pip install graph-nets ```
-
DeepGraph (🥉14 · ⭐ 240) - 使用基于pandas的网络分析数据。❗Unlicensed +
GraphSAGE (🥉13 · ⭐ 2.6K · 💀) - Representation learning on large graphs using stochastic.. MIT -- [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 36 · 📦 1 · 📋 14 - 64% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 720 · 📋 150 - 60% open · ⏱️ 19.09.2018): ``` - git clone https://github.com/deepgraph/deepgraph - ``` -- [PyPi](https://pypi.org/project/deepgraph) (📥 340 / month): - ``` - pip install deepgraph - ``` -- [Conda](https://anaconda.org/conda-forge/deepgraph) (📥 110K · ⏱️ 26.07.2021): - ``` - conda install -c conda-forge deepgraph + git clone https://github.com/williamleif/GraphSAGE ```
-
GraphVite (🥉13 · ⭐ 960 · 💤) - GraphVite：通用的高性能图形嵌入系统。Apache-2 +
OpenNE (🥉13 · ⭐ 1.5K · 💀) - An Open-Source Package for Network Embedding (NE). MIT -- [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 130 · 📋 88 - 36% open · ⏱️ 14.01.2021): +- [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 470 · 📋 96 - 2% open · ⏱️ 12.08.2019): ``` - git clone https://github.com/DeepGraphLearning/graphvite - ``` -- [Conda](https://anaconda.org/milagraph/graphvite) (📥 3.9K · ⏱️ 19.03.2020): - ``` - conda install -c milagraph graphvite + git clone https://github.com/thunlp/OpenNE ```
-
Sematch (🥉13 · ⭐ 360 · 💀) - 知识图的语义相似性框架。Apache-2 +
Sematch (🥉13 · ⭐ 370 · 💀) - semantic similarity framework for knowledge graph. Apache-2 - [GitHub](https://github.com/gsi-upm/sematch) (👨‍💻 5 · 🔀 100 · 📦 29 · 📋 31 - 38% open · ⏱️ 27.03.2019): @@ -3603,9 +3591,21 @@ _用于图数据处理，聚类，图嵌入和机器学习任务的库。_ pip install sematch ```
-
OpenKE (🥉12 · ⭐ 2.7K) - 神经关系提取（NRE）的开源软件包。❗Unlicensed +
GraphVite (🥉12 · ⭐ 980 · 💤) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 + +- [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 130 · 📋 91 - 38% open · ⏱️ 14.01.2021): + + ``` + git clone https://github.com/DeepGraphLearning/graphvite + ``` +- [Conda](https://anaconda.org/milagraph/graphvite) (📥 4.1K · ⏱️ 19.03.2020): + ``` + conda install -c milagraph graphvite + ``` +
+
OpenKE (🥉11 · ⭐ 2.8K · 💤) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed -- [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 820 · 📋 320 - 5% open · ⏱️ 06.04.2021): +- [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 830 · 📋 330 - 5% open · ⏱️ 06.04.2021): ``` git clone https://github.com/thunlp/OpenKE @@ -3613,528 +3613,540 @@ _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 +_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 · ⭐ 19K · 📈) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 -
Pydub (🥇30 · ⭐ 5.6K) - 使用简单易用的高级界面处理音频。MIT +- [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 160 · 🔀 3.2K · 📥 770K · 📦 640 · 📋 2K - 5% open · ⏱️ 17.11.2021): -- [GitHub](https://github.com/jiaaro/pydub) (👨‍💻 90 · 🔀 740 · 📦 9K · 📋 440 - 42% open · ⏱️ 08.06.2021): + ``` + git clone https://github.com/mozilla/DeepSpeech + ``` +- [PyPi](https://pypi.org/project/deepspeech): + ``` + pip install deepspeech + ``` +
+
Pydub (🥇30 · ⭐ 5.8K) - 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): ``` git clone https://github.com/jiaaro/pydub ``` -- [PyPi](https://pypi.org/project/pydub) (📥 930K / month): +- [PyPi](https://pypi.org/project/pydub) (📥 920K / month): ``` pip install pydub ``` -- [Conda](https://anaconda.org/conda-forge/pydub) (📥 18K · ⏱️ 13.03.2021): +- [Conda](https://anaconda.org/conda-forge/pydub) (📥 20K · ⏱️ 13.03.2021): ``` conda install -c conda-forge pydub ```
-
SpeechRecognition (🥇27 · ⭐ 5.9K · 💀) - 适用于Python的语音识别模块。❗Unlicensed +
audioread (🥇27 · ⭐ 380) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding.. MIT -- [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 41 · 🔀 1.9K · 📦 11K · 📋 490 - 42% open · ⏱️ 02.07.2019): +- [GitHub](https://github.com/beetbox/audioread) (👨‍💻 21 · 🔀 89 · 📦 6.9K · 📋 75 - 38% open · ⏱️ 03.12.2021): ``` - git clone https://github.com/Uberi/speech_recognition + git clone https://github.com/beetbox/audioread ``` -- [PyPi](https://pypi.org/project/SpeechRecognition) (📥 270K / month): +- [PyPi](https://pypi.org/project/audioread) (📥 540K / month): ``` - pip install SpeechRecognition + pip install audioread ``` -- [Conda](https://anaconda.org/conda-forge/speechrecognition) (📥 130K · ⏱️ 11.01.2021): +- [Conda](https://anaconda.org/conda-forge/audioread) (📥 370K · ⏱️ 07.11.2021): ``` - conda install -c conda-forge speechrecognition + conda install -c conda-forge audioread ```
-
espnet (🥇27 · ⭐ 4.3K) - 端到端语音处理工具包。Apache-2 +
Magenta (🥈26 · ⭐ 17K) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 -- [GitHub](https://github.com/espnet/espnet) (👨‍💻 190 · 🔀 1.3K · 📥 73 · 📦 24 · 📋 1.5K - 12% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/magenta/magenta) (👨‍💻 150 · 🔀 3.5K · 📦 330 · 📋 860 - 33% open · ⏱️ 30.06.2021): ``` - git clone https://github.com/espnet/espnet + git clone https://github.com/magenta/magenta ``` -- [PyPi](https://pypi.org/project/espnet) (📥 6.2K / month): +- [PyPi](https://pypi.org/project/magenta) (📥 7.5K / month): ``` - pip install espnet + pip install magenta ```
-
Magenta (🥈26 · ⭐ 17K) - 借助机器智能进行音乐和艺术创作。Apache-2 +
aubio (🥈26 · ⭐ 2.6K · 💤) - a library for audio and music analysis. ❗️GPL-3.0 -- [GitHub](https://github.com/magenta/magenta) (👨‍💻 150 · 🔀 3.4K · 📦 310 · 📋 850 - 33% open · ⏱️ 30.06.2021): +- [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 330 · 📦 280 · 📋 300 - 40% open · ⏱️ 19.01.2021): ``` - git clone https://github.com/magenta/magenta + git clone https://github.com/aubio/aubio ``` -- [PyPi](https://pypi.org/project/magenta) (📥 6.2K / month): +- [PyPi](https://pypi.org/project/aubio): ``` - pip install magenta + pip install aubio + ``` +- [Conda](https://anaconda.org/conda-forge/aubio) (📥 480K · ⏱️ 09.11.2021): + ``` + conda install -c conda-forge aubio ```
-
spleeter (🥈25 · ⭐ 18K) - Deezer源分离库，包括预训练的模型。MIT +
torchaudio (🥈25 · ⭐ 1.5K) - Data manipulation and transformation for audio signal.. BSD-2 -- [GitHub](https://github.com/deezer/spleeter) (👨‍💻 18 · 🔀 1.8K · 📥 1.2M · 📋 580 - 16% open · ⏱️ 03.09.2021): +- [GitHub](https://github.com/pytorch/audio) (👨‍💻 140 · 🔀 360 · 📋 550 - 20% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/deezer/spleeter - ``` -- [PyPi](https://pypi.org/project/spleeter) (📥 8.7K / month): - ``` - pip install spleeter + git clone https://github.com/pytorch/audio ``` -- [Conda](https://anaconda.org/conda-forge/spleeter) (📥 59K · ⏱️ 30.06.2020): +- [PyPi](https://pypi.org/project/torchaudio) (📥 380K / month): ``` - conda install -c conda-forge spleeter + pip install torchaudio ```
-
aubio (🥈25 · ⭐ 2.6K · 💤) - 用于音频和音乐分析的库。❗️GPL-3.0 +
spleeter (🥈24 · ⭐ 18K) - Deezer source separation library including pretrained models. MIT -- [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 320 · 📦 250 · 📋 290 - 40% open · ⏱️ 19.01.2021): +- [GitHub](https://github.com/deezer/spleeter) (👨‍💻 18 · 🔀 1.9K · 📥 1.3M · 📋 600 - 17% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/aubio/aubio + git clone https://github.com/deezer/spleeter ``` -- [PyPi](https://pypi.org/project/aubio): +- [PyPi](https://pypi.org/project/spleeter): ``` - pip install aubio + pip install spleeter ``` -- [Conda](https://anaconda.org/conda-forge/aubio) (📥 460K · ⏱️ 19.01.2021): +- [Conda](https://anaconda.org/conda-forge/spleeter) (📥 61K · ⏱️ 30.06.2020): ``` - conda install -c conda-forge aubio + conda install -c conda-forge spleeter ```
-
audioread (🥈25 · ⭐ 370 · 💤) - 跨库（GStreamer + Core Audio + MAD + FFmpeg）音频编解码。MIT +
Essentia (🥈24 · ⭐ 2K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 -- [GitHub](https://github.com/beetbox/audioread) (👨‍💻 20 · 🔀 85 · 📦 6.3K · 📋 71 - 38% open · ⏱️ 20.10.2020): +- [GitHub](https://github.com/MTG/essentia) (👨‍💻 73 · 🔀 420 · 📦 260 · 📋 920 - 34% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/beetbox/audioread - ``` -- [PyPi](https://pypi.org/project/audioread) (📥 460K / month): - ``` - pip install audioread + git clone https://github.com/MTG/essentia ``` -- [Conda](https://anaconda.org/conda-forge/audioread) (📥 350K · ⏱️ 16.03.2021): +- [PyPi](https://pypi.org/project/essentia) (📥 2.3K / month): ``` - conda install -c conda-forge audioread + pip install essentia ```
-
pyAudioAnalysis (🥈24 · ⭐ 4.2K) - Python音频分析库。Apache-2 +
espnet (🥈23 · ⭐ 4.5K) - End-to-End Speech Processing Toolkit. Apache-2 -- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 25 · 🔀 1K · 📦 230 · 📋 270 - 59% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/espnet/espnet) (👨‍💻 210 · 🔀 1.3K · 📥 74 · 📦 25 · 📋 1.6K - 14% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/tyiannak/pyAudioAnalysis + git clone https://github.com/espnet/espnet ``` -- [PyPi](https://pypi.org/project/pyAudioAnalysis) (📥 12K / month): +- [PyPi](https://pypi.org/project/espnet): ``` - pip install pyAudioAnalysis + pip install espnet ```
-
Essentia (🥈24 · ⭐ 1.9K) - C++库，用于音频和音乐分析，描述等。❗️AGPL-3.0 +
kapre (🥈23 · ⭐ 790) - kapre: Keras Audio Preprocessors. MIT -- [GitHub](https://github.com/MTG/essentia) (👨‍💻 71 · 🔀 420 · 📦 230 · 📋 900 - 34% open · ⏱️ 22.09.2021): +- [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 140 · 📥 19 · 📦 1.2K · 📋 93 - 11% open · ⏱️ 14.11.2021): ``` - git clone https://github.com/MTG/essentia + git clone https://github.com/keunwoochoi/kapre ``` -- [PyPi](https://pypi.org/project/essentia) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/kapre) (📥 1.8K / month): ``` - pip install essentia + pip install kapre ```
-
torchaudio (🥈24 · ⭐ 1.4K) - 音频信号的数据处理和转换。BSD-2 +
SpeechRecognition (🥉22 · ⭐ 6K) - Speech recognition module for Python, supporting.. ❗Unlicensed -- [GitHub](https://github.com/pytorch/audio) (👨‍💻 140 · 🔀 340 · 📋 510 - 18% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 41 · 🔀 1.9K · 📋 490 - 43% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/pytorch/audio + git clone https://github.com/Uberi/speech_recognition ``` -- [PyPi](https://pypi.org/project/torchaudio) (📥 330K / month): +- [PyPi](https://pypi.org/project/SpeechRecognition) (📥 240K / month): ``` - pip install torchaudio + pip install SpeechRecognition + ``` +- [Conda](https://anaconda.org/conda-forge/speechrecognition) (📥 130K · ⏱️ 13.12.2021): + ``` + conda install -c conda-forge speechrecognition ```
-
librosa (🥉23 · ⭐ 4.8K) - 用于音频和音乐分析的Python库。ISC +
librosa (🥉22 · ⭐ 4.9K) - Python library for audio and music analysis. ISC -- [GitHub](https://github.com/librosa/librosa) (👨‍💻 91 · 🔀 750 · 📋 900 - 5% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/librosa/librosa) (👨‍💻 92 · 🔀 760 · 📋 920 - 3% open · ⏱️ 13.12.2021): ``` git clone https://github.com/librosa/librosa ``` -- [PyPi](https://pypi.org/project/librosa) (📥 460K / month): +- [PyPi](https://pypi.org/project/librosa) (📥 560K / month): ``` pip install librosa ``` -- [Conda](https://anaconda.org/conda-forge/librosa) (📥 400K · ⏱️ 26.05.2021): +- [Conda](https://anaconda.org/conda-forge/librosa) (📥 420K · ⏱️ 26.05.2021): ``` conda install -c conda-forge librosa ```
-
DDSP (🥉22 · ⭐ 2K) - DDSP：微分数字信号处理。Apache-2 +
python_speech_features (🥉21 · ⭐ 2K · 💤) - This library provides common speech features for ASR.. MIT -- [GitHub](https://github.com/magenta/ddsp) (👨‍💻 27 · 🔀 200 · 📦 15 · 📋 120 - 14% open · ⏱️ 28.08.2021): +- [GitHub](https://github.com/jameslyons/python_speech_features) (👨‍💻 19 · 🔀 570 · 📋 70 - 27% open · ⏱️ 31.12.2020): ``` - git clone https://github.com/magenta/ddsp + git clone https://github.com/jameslyons/python_speech_features ``` -- [PyPi](https://pypi.org/project/ddsp) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/python_speech_features) (📥 130K / month): ``` - pip install ddsp + pip install python_speech_features ```
-
kapre (🥉22 · ⭐ 770 · 💤) - kapre：Keras音频预处理器。MIT +
Madmom (🥉21 · ⭐ 840) - Python audio and music signal processing library. ❗Unlicensed -- [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 130 · 📥 16 · 📦 1.1K · 📋 90 - 11% open · ⏱️ 25.03.2021): +- [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 150 · 📦 170 · 📋 240 - 21% open · ⏱️ 23.08.2021): ``` - git clone https://github.com/keunwoochoi/kapre + git clone https://github.com/CPJKU/madmom ``` -- [PyPi](https://pypi.org/project/kapre) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/madmom) (📥 11K / month): ``` - pip install kapre + pip install madmom ```
-
python-soundfile (🥉21 · ⭐ 410) - SoundFile是基于libsndfile，CFFI等的音频库。BSD-3 +
tinytag (🥉21 · ⭐ 500) - Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and.. MIT -- [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 20 · 🔀 56 · 📥 2.6K · 📦 9K · 📋 160 - 37% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/devsnd/tinytag) (👨‍💻 20 · 🔀 82 · 📦 450 · 📋 85 - 11% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/bastibe/python-soundfile + git clone https://github.com/devsnd/tinytag ``` -- [PyPi](https://pypi.org/project/soundfile): +- [PyPi](https://pypi.org/project/tinytag) (📥 11K / month): ``` - pip install soundfile + pip install tinytag ```
-
Porcupine (🥉20 · ⭐ 2.6K) - 深度学习支持的设备上唤醒词识别。Apache-2 +
pyAudioAnalysis (🥉20 · ⭐ 4.5K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 -- [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 29 · 🔀 360 · 📦 6 · 📋 330 - 1% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 25 · 🔀 1K · 📦 240 · 📋 280 - 58% open · ⏱️ 12.11.2021): ``` - git clone https://github.com/Picovoice/Porcupine + git clone https://github.com/tyiannak/pyAudioAnalysis ``` -- [PyPi](https://pypi.org/project/pvporcupine) (📥 900 / month): +- [PyPi](https://pypi.org/project/pyAudioAnalysis): ``` - pip install pvporcupine + pip install pyAudioAnalysis ```
-
python_speech_features (🥉20 · ⭐ 2K · 💤) - This library provides common speech features for ASR.. MIT +
Porcupine (🥉19 · ⭐ 2.6K) - On-device wake word detection powered by deep learning. Apache-2 -- [GitHub](https://github.com/jameslyons/python_speech_features) (👨‍💻 19 · 🔀 560 · 📋 69 - 27% open · ⏱️ 31.12.2020): +- [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 30 · 🔀 360 · 📦 6 · 📋 340 - 1% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/jameslyons/python_speech_features + git clone https://github.com/Picovoice/Porcupine ``` -- [PyPi](https://pypi.org/project/python_speech_features) (📥 79K / month): +- [PyPi](https://pypi.org/project/pvporcupine): ``` - pip install python_speech_features + pip install pvporcupine ```
-
Madmom (🥉20 · ⭐ 810) - Python音频和音乐信号处理库。❗Unlicensed +
DDSP (🥉19 · ⭐ 2K) - DDSP: Differentiable Digital Signal Processing. Apache-2 -- [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 140 · 📦 150 · 📋 230 - 20% open · ⏱️ 23.08.2021): +- [GitHub](https://github.com/magenta/ddsp) (👨‍💻 29 · 🔀 210 · 📦 18 · 📋 120 - 16% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/CPJKU/madmom + git clone https://github.com/magenta/ddsp ``` -- [PyPi](https://pypi.org/project/madmom) (📥 4.5K / month): +- [PyPi](https://pypi.org/project/ddsp): ``` - pip install madmom + pip install ddsp ```
-
tinytag (🥉20 · ⭐ 490) - 读取音乐元数据和MP3，OGG，OPUS，MP4，M4A，FLAC，WMA等的长度。MIT +
TTS (🥉18 · ⭐ 5.4K · 💤) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 -- [GitHub](https://github.com/devsnd/tinytag) (👨‍💻 20 · 🔀 82 · 📦 410 · 📋 81 - 16% open · ⏱️ 28.08.2021): +- [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 850 · 📥 1.5K · 📋 520 - 2% open · ⏱️ 12.02.2021): ``` - git clone https://github.com/devsnd/tinytag - ``` -- [PyPi](https://pypi.org/project/tinytag) (📥 7.5K / month): - ``` - pip install tinytag + git clone https://github.com/mozilla/TTS ```
-
TTS (🥉19 · ⭐ 5.2K · 💤) - 文本到语音的深度学习。MPL-2.0 +
Muda (🥉18 · ⭐ 200 · 💤) - A library for augmenting annotated audio data. ISC -- [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 820 · 📥 1.3K · 📋 510 - 1% open · ⏱️ 12.02.2021): +- [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 34 · 📦 13 · 📋 49 - 10% open · ⏱️ 03.05.2021): ``` - git clone https://github.com/mozilla/TTS + git clone https://github.com/bmcfee/muda + ``` +- [PyPi](https://pypi.org/project/muda) (📥 160 / month): + ``` + pip install muda ```
-
Dejavu (🥉18 · ⭐ 5.6K · 💀) - Python中的音频指纹识别。MIT +
Dejavu (🥉17 · ⭐ 5.6K · 💀) - Audio fingerprinting and recognition in Python. MIT -- [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 23 · 🔀 1.2K · 📦 18 · 📋 200 - 35% open · ⏱️ 03.06.2020): +- [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 23 · 🔀 1.2K · 📦 19 · 📋 200 - 36% open · ⏱️ 03.06.2020): ``` git clone https://github.com/worldveil/dejavu ``` -- [PyPi](https://pypi.org/project/PyDejavu) (📥 70 / month): +- [PyPi](https://pypi.org/project/PyDejavu): ``` pip install PyDejavu ```
-
Muda (🥉17 · ⭐ 200) - 用于扩充带注释的音频数据的库。ISC +
python-soundfile (🥉16 · ⭐ 430) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 -- [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 34 · 📦 12 · 📋 49 - 10% open · ⏱️ 03.05.2021): +- [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 23 · 🔀 57 · 📥 2.8K · 📋 160 - 37% open · ⏱️ 07.12.2021): ``` - git clone https://github.com/bmcfee/muda + git clone https://github.com/bastibe/python-soundfile ``` -- [PyPi](https://pypi.org/project/muda) (📥 140 / month): +- [PyPi](https://pypi.org/project/soundfile): ``` - pip install muda + pip install soundfile ```
-
Julius (🥉13 · ⭐ 230) - 基于PyTorch的快速DSP，用于音频和一维信号。MIT +
Julius (🥉15 · ⭐ 240) - Fast PyTorch based DSP for audio and 1D signals. MIT -- [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 10 · 📦 37 · 📋 8 - 25% open · ⏱️ 28.07.2021): +- [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 12 · 📦 49 · 📋 9 - 11% open · ⏱️ 20.10.2021): ``` git clone https://github.com/adefossez/julius ``` -- [PyPi](https://pypi.org/project/julius) (📥 5.9K / month): +- [PyPi](https://pypi.org/project/julius) (📥 8.1K / 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 (🥇33 · ⭐ 9K) - WebGL2支持的地理空间可视化图层。MIT +
pydeck (🥇34 · ⭐ 9.3K) - WebGL2 powered geospatial visualization layers. MIT -- [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 180 · 🔀 1.6K · 📦 1.8K · 📋 2.3K - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 180 · 🔀 1.6K · 📦 2.1K · 📋 2.3K - 4% open · ⏱️ 13.12.2021): ``` git clone https://github.com/visgl/deck.gl ``` -- [PyPi](https://pypi.org/project/pydeck): +- [PyPi](https://pypi.org/project/pydeck) (📥 660K / month): ``` pip install pydeck ``` -- [Conda](https://anaconda.org/conda-forge/pydeck) (📥 55K · ⏱️ 27.08.2021): +- [Conda](https://anaconda.org/conda-forge/pydeck) (📥 63K · ⏱️ 26.10.2021): ``` conda install -c conda-forge pydeck ``` -- [NPM](https://www.npmjs.com/package/deck.gl) (📥 230K / month): +- [NPM](https://www.npmjs.com/package/deck.gl) (📥 240K / month): ``` npm install deck.gl ```
-
geopy (🥇33 · ⭐ 3.4K) - 适用于Python的地址解析库。MIT +
geopy (🥇33 · ⭐ 3.5K) - Geocoding library for Python. MIT -- [GitHub](https://github.com/geopy/geopy) (👨‍💻 120 · 🔀 530 · 📦 28K · 📋 250 - 7% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/geopy/geopy) (👨‍💻 120 · 🔀 540 · 📦 30K · 📋 250 - 9% open · ⏱️ 26.09.2021): ``` git clone https://github.com/geopy/geopy ``` -- [PyPi](https://pypi.org/project/geopy) (📥 3.3M / month): +- [PyPi](https://pypi.org/project/geopy) (📥 3.8M / month): ``` pip install geopy ``` -- [Conda](https://anaconda.org/conda-forge/geopy) (📥 610K · ⏱️ 12.07.2021): +- [Conda](https://anaconda.org/conda-forge/geopy) (📥 630K · ⏱️ 12.07.2021): ``` conda install -c conda-forge geopy ```
-
GeoPandas (🥇33 · ⭐ 2.8K) - 用于地理数据的Python工具。BSD-3 +
GeoPandas (🥇33 · ⭐ 2.9K) - Python tools for geographic data. BSD-3 -- [GitHub](https://github.com/geopandas/geopandas) (👨‍💻 150 · 🔀 600 · 📥 1.2K · 📦 10K · 📋 1.1K - 27% open · ⏱️ 12.10.2021): +- [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) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/geopandas) (📥 2M / month): ``` pip install geopandas ``` -- [Conda](https://anaconda.org/conda-forge/geopandas) (📥 1.2M · ⏱️ 08.10.2021): +- [Conda](https://anaconda.org/conda-forge/geopandas) (📥 1.3M · ⏱️ 01.12.2021): ``` conda install -c conda-forge geopandas ```
-
folium (🥈32 · ⭐ 5.5K) - Leaflet.js地图的Python数据。MIT +
Shapely (🥈31 · ⭐ 2.6K) - Manipulation and analysis of geometric objects. BSD-3 -- [GitHub](https://github.com/python-visualization/folium) (👨‍💻 120 · 🔀 2K · 📦 12K · 📋 870 - 18% open · ⏱️ 19.06.2021): +- [GitHub](https://github.com/shapely/shapely) (👨‍💻 130 · 🔀 440 · 📦 25K · 📋 800 - 17% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/python-visualization/folium + git clone https://github.com/Toblerity/Shapely ``` -- [PyPi](https://pypi.org/project/folium) (📥 550K / month): +- [PyPi](https://pypi.org/project/shapely) (📥 6.1M / month): ``` - pip install folium + pip install shapely ``` -- [Conda](https://anaconda.org/conda-forge/folium) (📥 410K · ⏱️ 12.03.2021): +- [Conda](https://anaconda.org/conda-forge/shapely) (📥 3.1M · ⏱️ 20.11.2021): ``` - conda install -c conda-forge folium + conda install -c conda-forge shapely ```
-
pyproj (🥈32 · ⭐ 660) - 与PROJ的Python界面（图形投影和坐标。MIT +
Geocoder (🥈30 · ⭐ 1.4K · 💀) - Python Geocoder. MIT -- [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 43 · 🔀 160 · 📦 11K · 📋 440 - 1% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 74 · 🔀 260 · 📦 4.2K · 📋 290 - 24% open · ⏱️ 12.10.2018): ``` - git clone https://github.com/pyproj4/pyproj + git clone https://github.com/DenisCarriere/geocoder ``` -- [PyPi](https://pypi.org/project/pyproj) (📥 3.3M / month): +- [PyPi](https://pypi.org/project/geocoder) (📥 2.1M / month): ``` - pip install pyproj + pip install geocoder ``` -- [Conda](https://anaconda.org/conda-forge/pyproj) (📥 2.6M · ⏱️ 01.10.2021): +- [Conda](https://anaconda.org/conda-forge/geocoder) (📥 95K · ⏱️ 27.06.2019): ``` - conda install -c conda-forge pyproj + conda install -c conda-forge geocoder ```
-
ipyleaflet (🥈29 · ⭐ 1.2K) - Jupyter-Leaflet.js桥。MIT +
folium (🥈29 · ⭐ 5.5K) - Python Data. Leaflet.js Maps. MIT -- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 69 · 🔀 290 · 📦 1.2K · 📋 440 - 37% open · ⏱️ 13.09.2021): +- [GitHub](https://github.com/python-visualization/folium) (👨‍💻 120 · 🔀 2K · 📦 13K · 📋 890 - 19% open · ⏱️ 30.11.2021): ``` - git clone https://github.com/jupyter-widgets/ipyleaflet - ``` -- [PyPi](https://pypi.org/project/ipyleaflet) (📥 53K / month): - ``` - pip install ipyleaflet + git clone https://github.com/python-visualization/folium ``` -- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (📥 760K · ⏱️ 17.06.2021): +- [PyPi](https://pypi.org/project/folium) (📥 710K / month): ``` - conda install -c conda-forge ipyleaflet + pip install folium ``` -- [NPM](https://www.npmjs.com/package/jupyter-leaflet) (📥 31K / month): +- [Conda](https://anaconda.org/conda-forge/folium) (📥 480K · ⏱️ 03.12.2021): ``` - npm install jupyter-leaflet + conda install -c conda-forge folium ```
-
Geocoder (🥈28 · ⭐ 1.4K · 💀) - Python Geocoder。MIT +
Rasterio (🥈29 · ⭐ 1.6K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed -- [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 74 · 🔀 260 · 📦 3.9K · 📋 290 - 24% open · ⏱️ 12.10.2018): +- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/DenisCarriere/geocoder + git clone https://github.com/mapbox/rasterio ``` -- [PyPi](https://pypi.org/project/geocoder): +- [PyPi](https://pypi.org/project/rasterio) (📥 720K / month): ``` - pip install geocoder + pip install rasterio ``` -- [Conda](https://anaconda.org/conda-forge/geocoder) (📥 93K · ⏱️ 27.06.2019): +- [Conda](https://anaconda.org/conda-forge/rasterio) (📥 1.4M · ⏱️ 03.12.2021): ``` - conda install -c conda-forge geocoder + conda install -c conda-forge rasterio ```
-
Shapely (🥈27 · ⭐ 2.4K) - 操作和分析几何对象。❗Unlicensed +
ipyleaflet (🥈29 · ⭐ 1.2K) - A Jupyter - Leaflet.js bridge. MIT -- [GitHub](https://github.com/Toblerity/Shapely) (👨‍💻 120 · 🔀 420 · 📦 23K · 📋 780 - 17% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 72 · 🔀 300 · 📦 1.3K · 📋 460 - 38% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/Toblerity/Shapely + git clone https://github.com/jupyter-widgets/ipyleaflet ``` -- [PyPi](https://pypi.org/project/shapely): +- [PyPi](https://pypi.org/project/ipyleaflet) (📥 59K / month): ``` - pip install shapely + pip install ipyleaflet ``` -- [Conda](https://anaconda.org/conda-forge/shapely) (📥 2.8M · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (📥 780K · ⏱️ 09.12.2021): ``` - conda install -c conda-forge shapely + conda install -c conda-forge ipyleaflet + ``` +- [NPM](https://www.npmjs.com/package/jupyter-leaflet) (📥 47K / month): + ``` + npm install jupyter-leaflet ```
-
Rasterio (🥈27 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed +
pyproj (🥈29 · ⭐ 690) - Python interface to PROJ (cartographic projections and coordinate.. MIT -- [GitHub](https://github.com/mapbox/rasterio) (👨‍💻 110 · 🔀 430 · 📥 740 · 📦 3.8K · 📋 1.5K - 9% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 44 · 🔀 170 · 📦 12K · 📋 460 - 1% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/mapbox/rasterio + git clone https://github.com/pyproj4/pyproj ``` -- [PyPi](https://pypi.org/project/rasterio) (📥 700K / month): +- [PyPi](https://pypi.org/project/pyproj) (📥 3.9M / month): ``` - pip install rasterio + pip install pyproj ``` -- [Conda](https://anaconda.org/conda-forge/rasterio) (📥 1.3M · ⏱️ 12.10.2021): +- [Conda](https://anaconda.org/conda-forge/pyproj) (📥 2.8M · ⏱️ 18.11.2021): ``` - conda install -c conda-forge rasterio + conda install -c conda-forge pyproj ```
-
Fiona (🥈27 · ⭐ 850) - Fiona读写地理数据文件。❗Unlicensed +
Cartopy (🥉28 · ⭐ 1.6K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed -- [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 65 · 🔀 160 · 📦 6.8K · 📋 640 - 11% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/Toblerity/Fiona + git clone https://github.com/mapbox/rasterio ``` -- [PyPi](https://pypi.org/project/fiona) (📥 1.8M / month): +- [PyPi](https://pypi.org/project/Cartopy) (📥 130K / month): ``` - pip install fiona + pip install Cartopy ``` -- [Conda](https://anaconda.org/conda-forge/fiona) (📥 2.3M · ⏱️ 12.08.2021): +- [Conda](https://anaconda.org/conda-forge/cartopy) (📥 1.9M · ⏱️ 20.11.2021): ``` - conda install -c conda-forge fiona + conda install -c conda-forge cartopy ```
-
geojson (🥈27 · ⭐ 650) - GeoJSON的Python接口。BSD-3 +
Fiona (🥉27 · ⭐ 870) - Fiona reads and writes geographic data files. ❗Unlicensed -- [GitHub](https://github.com/jazzband/geojson) (👨‍💻 44 · 🔀 83 · 📦 7.7K · 📋 77 - 24% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 65 · 🔀 170 · 📦 7.3K · 📋 640 - 11% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/jazzband/geojson + git clone https://github.com/Toblerity/Fiona ``` -- [PyPi](https://pypi.org/project/geojson) (📥 670K / month): +- [PyPi](https://pypi.org/project/fiona) (📥 2.3M / month): ``` - pip install geojson + pip install fiona ``` -- [Conda](https://anaconda.org/conda-forge/geojson) (📥 450K · ⏱️ 11.08.2019): +- [Conda](https://anaconda.org/conda-forge/fiona) (📥 2.4M · ⏱️ 01.12.2021): ``` - conda install -c conda-forge geojson + conda install -c conda-forge fiona ```
-
Cartopy (🥉26 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed +
geojson (🥉27 · ⭐ 680) - Python bindings and utilities for GeoJSON. BSD-3 -- [GitHub](https://github.com/mapbox/rasterio) (👨‍💻 110 · 🔀 430 · 📥 740 · 📦 3.8K · 📋 1.5K - 9% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/jazzband/geojson) (👨‍💻 45 · 🔀 85 · 📦 8.2K · 📋 77 - 24% open · ⏱️ 11.11.2021): ``` - git clone https://github.com/mapbox/rasterio + git clone https://github.com/jazzband/geojson ``` -- [PyPi](https://pypi.org/project/Cartopy) (📥 86K / month): +- [PyPi](https://pypi.org/project/geojson) (📥 690K / month): ``` - pip install Cartopy + pip install geojson ``` -- [Conda](https://anaconda.org/conda-forge/cartopy) (📥 1.8M · ⏱️ 12.10.2021): +- [Conda](https://anaconda.org/conda-forge/geojson) (📥 460K · ⏱️ 11.08.2019): ``` - conda install -c conda-forge cartopy + conda install -c conda-forge geojson ```
-
ArcGIS API (🥉24 · ⭐ 1.1K) - ArcGIS API for Python的文档和示例。Apache-2 +
ArcGIS API (🥉24 · ⭐ 1.2K) - Documentation and samples for ArcGIS API for Python. Apache-2 -- [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 71 · 🔀 800 · 📥 100 · 📋 370 - 26% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 73 · 🔀 820 · 📥 1K · 📋 380 - 24% open · ⏱️ 09.12.2021): ``` git clone https://github.com/Esri/arcgis-python-api ``` -- [PyPi](https://pypi.org/project/arcgis) (📥 48K / month): +- [PyPi](https://pypi.org/project/arcgis) (📥 57K / month): ``` pip install arcgis ``` -- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (📥 5K · ⭐ 33 · ⏱️ 05.10.2021): +- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook) (📥 5.4K · ⭐ 33 · ⏱️ 05.10.2021): ``` docker pull esridocker/arcgis-api-python-notebook ```
-
PySAL (🥉23 · ⭐ 910) - PySAL：Python空间分析库元包。BSD-3 +
PySAL (🥉23 · ⭐ 950) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 -- [GitHub](https://github.com/pysal/pysal) (👨‍💻 72 · 🔀 250 · 📋 600 - 1% open · ⏱️ 03.10.2021): +- [GitHub](https://github.com/pysal/pysal) (👨‍💻 73 · 🔀 250 · 📋 600 - 1% open · ⏱️ 18.10.2021): ``` git clone https://github.com/pysal/pysal ``` -- [PyPi](https://pypi.org/project/pysal) (📥 15K / month): +- [PyPi](https://pypi.org/project/pysal) (📥 22K / month): ``` pip install pysal ``` @@ -4143,198 +4155,226 @@ _用于加载，处理，分析和写入geo地理数据的库，以及用于空 conda install -c conda-forge pysal ```
-
Mapbox GL (🥉23 · ⭐ 580) - 使用Mapbox GL JS可视化Python Jupyter笔记本中的数据。MIT +
Sentinelsat (🥉23 · ⭐ 700) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 -- [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 21 · 🔀 120 · 📦 120 · 📋 97 - 30% open · ⏱️ 19.04.2021): +- [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 42 · 🔀 190 · 📥 230 · 📦 260 · 📋 310 - 2% open · ⏱️ 02.12.2021): ``` - git clone https://github.com/mapbox/mapboxgl-jupyter + git clone https://github.com/sentinelsat/sentinelsat ``` -- [PyPi](https://pypi.org/project/mapboxgl) (📥 10K / month): +- [PyPi](https://pypi.org/project/sentinelsat) (📥 23K / month): ``` - pip install mapboxgl + pip install sentinelsat ```
-
Satpy (🥉21 · ⭐ 760) - 用于地球观测卫星数据处理的Python软件包。❗️GPL-3.0 +
Satpy (🥉21 · ⭐ 780) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 -- [GitHub](https://github.com/pytroll/satpy) (👨‍💻 120 · 🔀 210 · 📦 49 · 📋 670 - 41% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pytroll/satpy) (👨‍💻 120 · 🔀 220 · 📦 54 · 📋 700 - 40% open · ⏱️ 16.12.2021): ``` git clone https://github.com/pytroll/satpy ``` -- [PyPi](https://pypi.org/project/satpy): +- [PyPi](https://pypi.org/project/satpy) (📥 1.7K / month): ``` pip install satpy ``` -- [Conda](https://anaconda.org/conda-forge/satpy) (📥 75K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/satpy) (📥 79K · ⏱️ 11.12.2021): ``` conda install -c conda-forge satpy ```
-
GeoViews (🥉21 · ⭐ 370) - 使用Python进行简单，简洁的地理可视化。BSD-3 +
GeoViews (🥉21 · ⭐ 380) - Simple, concise geographical visualization in Python. BSD-3 -- [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 23 · 🔀 64 · 📋 280 - 34% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 25 · 🔀 65 · 📋 290 - 35% open · ⏱️ 01.12.2021): ``` git clone https://github.com/holoviz/geoviews ``` -- [PyPi](https://pypi.org/project/geoviews) (📥 6.9K / month): +- [PyPi](https://pypi.org/project/geoviews) (📥 8.1K / month): ``` pip install geoviews ``` -- [Conda](https://anaconda.org/conda-forge/geoviews) (📥 81K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/geoviews) (📥 88K · ⏱️ 29.09.2021): ``` conda install -c conda-forge geoviews ```
-
EarthPy (🥉21 · ⭐ 290) - 使用开放源代码处理空间数据。BSD-3 +
EarthPy (🥉21 · ⭐ 310) - A package built to support working with spatial data using open source.. BSD-3 -- [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 120 · 📦 110 · 📋 220 - 6% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 120 · 📦 110 · 📋 220 - 7% open · ⏱️ 11.10.2021): ``` git clone https://github.com/earthlab/earthpy ``` -- [PyPi](https://pypi.org/project/earthpy) (📥 3.9K / month): +- [PyPi](https://pypi.org/project/earthpy) (📥 4.5K / month): ``` pip install earthpy ``` -- [Conda](https://anaconda.org/conda-forge/earthpy) (📥 38K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/earthpy) (📥 40K · ⏱️ 04.10.2021): ``` conda install -c conda-forge earthpy ```
-
geoplotlib (🥉19 · ⭐ 930 · 💀) - python工具箱，用于可视化地理数据和制作地图。MIT +
geoplotlib (🥉20 · ⭐ 940 · 💀) - python toolbox for visualizing geographical data and making maps. MIT -- [GitHub](https://github.com/andrea-cuttone/geoplotlib) (👨‍💻 8 · 🔀 150 · 📦 110 · 📋 43 - 58% open · ⏱️ 06.05.2019): +- [GitHub](https://github.com/andrea-cuttone/geoplotlib) (👨‍💻 8 · 🔀 150 · 📦 120 · 📋 43 - 58% open · ⏱️ 06.05.2019): ``` git clone https://github.com/andrea-cuttone/geoplotlib ``` -- [PyPi](https://pypi.org/project/geoplotlib) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/geoplotlib) (📥 1.5K / month): ``` pip install geoplotlib ```
-
Sentinelsat (🥉19 · ⭐ 670) - 搜索和下载哥白尼前哨卫星图像。❗️GPL-3.0 +
Mapbox GL (🥉19 · ⭐ 590 · 💤) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT -- [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 41 · 🔀 180 · 📥 220 · 📦 230 · 📋 310 - 1% open · ⏱️ 17.09.2021): +- [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 21 · 🔀 120 · 📦 120 · 📋 98 - 31% open · ⏱️ 19.04.2021): ``` - git clone https://github.com/sentinelsat/sentinelsat + git clone https://github.com/mapbox/mapboxgl-jupyter ``` -- [PyPi](https://pypi.org/project/sentinelsat): +- [PyPi](https://pypi.org/project/mapboxgl): ``` - pip install sentinelsat + pip install mapboxgl ```
-
gmaps (🥉18 · ⭐ 720 · 💀) - Google为Jupyter笔记本电脑映射。BSD-3 +
pymap3d (🥉18 · ⭐ 220) - 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) (👨‍💻 10 · 🔀 58 · 📋 32 - 6% open · ⏱️ 28.11.2021): ``` - git clone https://github.com/pbugnion/gmaps - ``` -- [PyPi](https://pypi.org/project/gmaps) (📥 15K / month): - ``` - pip install gmaps + git clone https://github.com/geospace-code/pymap3d ``` -- [Conda](https://anaconda.org/conda-forge/gmaps) (📥 240K · ⏱️ 02.08.2019): +- [PyPi](https://pypi.org/project/pymap3d) (📥 43K / month): ``` - conda install -c conda-forge gmaps + pip install pymap3d ``` -- [NPM](https://www.npmjs.com/package/jupyter-gmaps) (📥 1.8K / month): +- [Conda](https://anaconda.org/conda-forge/pymap3d) (📥 16K · ⏱️ 19.10.2021): ``` - npm install jupyter-gmaps + conda install -c conda-forge pymap3d ```
-
pymap3d (🥉17 · ⭐ 210) - 纯Python实现（Numpy可选）的3D坐标转换。BSD-2 +
gmaps (🥉17 · ⭐ 730 · 💀) - Google maps for Jupyter notebooks. BSD-3 -- [GitHub](https://github.com/geospace-code/pymap3d) (👨‍💻 9 · 🔀 57 · 📋 27 - 11% open · ⏱️ 09.06.2021): +- [GitHub](https://github.com/pbugnion/gmaps) (👨‍💻 16 · 🔀 140 · 📦 1 · 📋 200 - 31% open · ⏱️ 22.07.2019): ``` - git clone https://github.com/geospace-code/pymap3d + git clone https://github.com/pbugnion/gmaps ``` -- [PyPi](https://pypi.org/project/pymap3d) (📥 44K / month): +- [PyPi](https://pypi.org/project/gmaps): ``` - pip install pymap3d + pip install gmaps ``` -- [Conda](https://anaconda.org/conda-forge/pymap3d) (📥 14K · ⏱️ 26.05.2021): +- [Conda](https://anaconda.org/conda-forge/gmaps) (📥 250K · ⏱️ 02.08.2019): ``` - conda install -c conda-forge pymap3d + conda install -c conda-forge gmaps + ``` +- [NPM](https://www.npmjs.com/package/jupyter-gmaps) (📥 1.9K / month): + ``` + npm install jupyter-gmaps ```

-## 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 (🥇28 · ⭐ 15K · 💤) - Zipline，一个Pythonic算法交易库。Apache-2 +
zipline (🥇29 · ⭐ 15K · 💀) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 -- [GitHub](https://github.com/quantopian/zipline) (👨‍💻 150 · 🔀 3.8K · 📦 780 · 📋 960 - 32% open · ⏱️ 14.10.2020): +- [GitHub](https://github.com/quantopian/zipline) (👨‍💻 150 · 🔀 3.9K · 📦 800 · 📋 960 - 32% open · ⏱️ 14.10.2020): ``` git clone https://github.com/quantopian/zipline ``` -- [PyPi](https://pypi.org/project/zipline) (📥 4.6K / month): +- [PyPi](https://pypi.org/project/zipline) (📥 4.3K / month): ``` pip install zipline ```
-
yfinance (🥇28 · ⭐ 5.8K) - Yahoo! 金融市场数据下载器（+更快的Pandas数据加载读取器）。Apache-2 +
yfinance (🥇29 · ⭐ 6.1K) - Yahoo! Finance market data downloader (+faster Pandas Datareader). Apache-2 -- [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 41 · 🔀 1.3K · 📦 7.2K · 📋 650 - 57% open · ⏱️ 10.07.2021): +- [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 49 · 🔀 1.4K · 📦 8.4K · 📋 700 - 54% open · ⏱️ 21.11.2021): ``` git clone https://github.com/ranaroussi/yfinance ``` -- [PyPi](https://pypi.org/project/yfinance) (📥 310K / month): +- [PyPi](https://pypi.org/project/yfinance) (📥 320K / month): ``` pip install yfinance ``` -- [Conda](https://anaconda.org/ranaroussi/yfinance) (📥 12K · ⏱️ 10.07.2021): +- [Conda](https://anaconda.org/ranaroussi/yfinance) (📥 20K · ⏱️ 10.07.2021): ``` conda install -c ranaroussi yfinance ```
-
pyfolio (🥇27 · ⭐ 4.1K · 💀) - Python中的投资组合和风险分析。Apache-2 +
pyfolio (🥇26 · ⭐ 4.2K · 💀) - Portfolio and risk analytics in Python. Apache-2 + +- [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 55 · 🔀 1.3K · 📦 340 · 📋 400 - 33% open · ⏱️ 15.07.2020): + + ``` + git clone https://github.com/quantopian/pyfolio + ``` +- [PyPi](https://pypi.org/project/pyfolio) (📥 5.6K / month): + ``` + pip install pyfolio + ``` +- [Conda](https://anaconda.org/conda-forge/pyfolio) (📥 7.8K · ⏱️ 16.05.2020): + ``` + conda install -c conda-forge pyfolio + ``` +
+
backtrader (🥈25 · ⭐ 7.8K) - Python Backtesting library for trading strategies. ❗️GPL-3.0 + +- [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.3K · 📦 840 · ⏱️ 17.07.2021): + + ``` + git clone https://github.com/mementum/backtrader + ``` +- [PyPi](https://pypi.org/project/backtrader) (📥 15K / month): + ``` + pip install backtrader + ``` +
+
Alphalens (🥈25 · ⭐ 2.1K · 💀) - Performance analysis of predictive (alpha) stock factors. Apache-2 -- [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 55 · 🔀 1.2K · 📦 310 · 📋 400 - 33% open · ⏱️ 15.07.2020): +- [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 790 · 📦 470 · 📋 180 - 20% open · ⏱️ 27.04.2020): ``` - git clone https://github.com/quantopian/pyfolio + git clone https://github.com/quantopian/alphalens ``` -- [PyPi](https://pypi.org/project/pyfolio) (📥 6.3K / month): +- [PyPi](https://pypi.org/project/alphalens) (📥 2.3K / month): ``` - pip install pyfolio + pip install alphalens ``` -- [Conda](https://anaconda.org/conda-forge/pyfolio) (📥 7.4K · ⏱️ 16.05.2020): +- [Conda](https://anaconda.org/conda-forge/alphalens) (📥 14K · ⏱️ 16.05.2020): ``` - conda install -c conda-forge pyfolio + conda install -c conda-forge alphalens ```
-
ta (🥈25 · ⭐ 2.5K · 💤) - 使用Pandas和Numpy的技术分析库。MIT +
bt (🥈24 · ⭐ 1.2K · 💤) - bt - flexible backtesting for Python. MIT -- [GitHub](https://github.com/bukosabino/ta) (👨‍💻 23 · 🔀 600 · 📦 780 · 📋 180 - 51% open · ⏱️ 29.11.2020): +- [GitHub](https://github.com/pmorissette/bt) (👨‍💻 24 · 🔀 290 · 📦 88 · 📋 270 - 17% open · ⏱️ 15.05.2021): ``` - git clone https://github.com/bukosabino/ta + git clone https://github.com/pmorissette/bt ``` -- [PyPi](https://pypi.org/project/ta) (📥 100K / month): +- [PyPi](https://pypi.org/project/bt) (📥 10K / month): ``` - pip install ta + pip install bt ```
-
empyrical (🥈25 · ⭐ 840 · 💤) - 常见的金融风险和绩效指标。Apache-2 +
empyrical (🥈24 · ⭐ 870 · 💀) - Common financial risk and performance metrics. Used by zipline.. Apache-2 -- [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 260 · 📦 710 · 📋 49 - 46% open · ⏱️ 14.10.2020): +- [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 270 · 📦 760 · 📋 49 - 46% open · ⏱️ 14.10.2020): ``` git clone https://github.com/quantopian/empyrical ``` -- [PyPi](https://pypi.org/project/empyrical) (📥 64K / month): +- [PyPi](https://pypi.org/project/empyrical) (📥 33K / month): ``` pip install empyrical ``` @@ -4343,157 +4383,145 @@ _用于算法股票/加密交易，风险分析，回测，技术分析以及其 conda install -c conda-forge empyrical ```
-
Alphalens (🥈24 · ⭐ 2.1K · 💀) - 股票因子预测分析。Apache-2 +
arch (🥈24 · ⭐ 840) - ARCH models in Python. ❗️NCSA -- [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 770 · 📦 450 · 📋 180 - 20% open · ⏱️ 27.04.2020): +- [GitHub](https://github.com/bashtage/arch) (👨‍💻 30 · 🔀 190 · 📦 420 · 📋 160 - 7% open · ⏱️ 19.11.2021): ``` - git clone https://github.com/quantopian/alphalens - ``` -- [PyPi](https://pypi.org/project/alphalens) (📥 2.3K / month): - ``` - pip install alphalens + git clone https://github.com/bashtage/arch ``` -- [Conda](https://anaconda.org/conda-forge/alphalens) (📥 13K · ⏱️ 16.05.2020): +- [PyPi](https://pypi.org/project/arch) (📥 180K / month): ``` - conda install -c conda-forge alphalens + pip install arch ```
-
bt (🥈24 · ⭐ 1.2K) - bt-Python的灵活回测。MIT +
ffn (🥈23 · ⭐ 1K · 💤) - ffn - a financial function library for Python. MIT -- [GitHub](https://github.com/pmorissette/bt) (👨‍💻 24 · 🔀 290 · 📦 76 · 📋 260 - 15% open · ⏱️ 15.05.2021): +- [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 26 · 🔀 190 · 📦 160 · 📋 96 - 16% open · ⏱️ 24.04.2021): ``` - git clone https://github.com/pmorissette/bt + git clone https://github.com/pmorissette/ffn ``` -- [PyPi](https://pypi.org/project/bt) (📥 9.8K / month): +- [PyPi](https://pypi.org/project/ffn) (📥 42K / month): ``` - pip install bt + pip install ffn ```
-
arch (🥈24 · ⭐ 800) - Python中的ARCH模型。❗️NCSA +
Qlib (🥉22 · ⭐ 7.6K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT -- [GitHub](https://github.com/bashtage/arch) (👨‍💻 29 · 🔀 180 · 📦 380 · 📋 160 - 7% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/microsoft/qlib) (👨‍💻 72 · 🔀 1.2K · 📥 270 · 📦 8 · 📋 370 - 33% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/bashtage/arch + git clone https://github.com/microsoft/qlib ``` -- [PyPi](https://pypi.org/project/arch) (📥 210K / month): +- [PyPi](https://pypi.org/project/pyqlib) (📥 3.2K / month): ``` - pip install arch + pip install pyqlib ```
-
TensorTrade (🥈23 · ⭐ 3.5K) - 一个开放源代码的强化学习框架。Apache-2 +
TensorTrade (🥉22 · ⭐ 3.6K) - An open source reinforcement learning framework for training,.. Apache-2 -- [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 55 · 🔀 790 · 📦 23 · 📋 180 - 12% open · ⏱️ 18.09.2021): +- [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 57 · 🔀 820 · 📦 27 · 📋 190 - 11% open · ⏱️ 07.12.2021): ``` git clone https://github.com/tensortrade-org/tensortrade ``` -- [PyPi](https://pypi.org/project/tensortrade) (📥 980 / month): +- [PyPi](https://pypi.org/project/tensortrade) (📥 1K / month): ``` pip install tensortrade ```
-
Alpha Vantage (🥉22 · ⭐ 3.5K) - 用于金融数据的Alpha Vantage API的python包装器。MIT +
PyAlgoTrade (🥉22 · ⭐ 3.6K · 💀) - Python Algorithmic Trading Library. Apache-2 -- [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 620 · 📋 250 - 7% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 98 · 📋 120 - 30% open · ⏱️ 21.08.2018): ``` - git clone https://github.com/RomelTorres/alpha_vantage + git clone https://github.com/gbeced/pyalgotrade ``` -- [PyPi](https://pypi.org/project/alpha_vantage) (📥 22K / month): +- [PyPi](https://pypi.org/project/pyalgotrade) (📥 980 / month): ``` - pip install alpha_vantage + pip install pyalgotrade ```
-
Enigma Catalyst (🥉22 · ⭐ 2.3K) - Python中加密资产的算法交易库。Apache-2 +
Alpha Vantage (🥉22 · ⭐ 3.6K) - A python wrapper for Alpha Vantage API for financial data. MIT -- [GitHub](https://github.com/enigmampc/catalyst) (👨‍💻 150 · 🔀 660 · 📦 23 · 📋 480 - 25% open · ⏱️ 22.09.2021): +- [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 630 · 📋 250 - 1% open · ⏱️ 14.06.2021): ``` - git clone https://github.com/enigmampc/catalyst + git clone https://github.com/RomelTorres/alpha_vantage ``` -- [PyPi](https://pypi.org/project/enigma-catalyst) (📥 2.4K / month): +- [PyPi](https://pypi.org/project/alpha_vantage) (📥 23K / month): ``` - pip install enigma-catalyst + pip install alpha_vantage ```
-
backtrader (🥉21 · ⭐ 7.4K) - 用于交易策略的Python Backtesting库。❗️GPL-3.0 +
FinTA (🥉22 · ⭐ 1.4K) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 -- [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.2K · 📦 780 · ⏱️ 17.07.2021): +- [GitHub](https://github.com/peerchemist/finta) (👨‍💻 27 · 🔀 440 · 📦 140 · 📋 80 - 21% open · ⏱️ 19.10.2021): ``` - git clone https://github.com/mementum/backtrader + git clone https://github.com/peerchemist/finta ``` -- [PyPi](https://pypi.org/project/backtrader): +- [PyPi](https://pypi.org/project/finta) (📥 7.2K / month): ``` - pip install backtrader + pip install finta ```
-
finmarketpy (🥉21 · ⭐ 2.7K) - Python库，用于回测交易策略和分析。Apache-2 +
ta (🥉21 · ⭐ 2.6K) - Technical Analysis Library using Pandas and Numpy. MIT -- [GitHub](https://github.com/cuemacro/finmarketpy) (👨‍💻 14 · 🔀 420 · 📥 40 · 📦 4 · 📋 26 - 88% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/bukosabino/ta) (👨‍💻 24 · 🔀 630 · 📦 900 · 📋 180 - 51% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/cuemacro/finmarketpy + git clone https://github.com/bukosabino/ta ``` -- [PyPi](https://pypi.org/project/finmarketpy) (📥 220 / month): +- [PyPi](https://pypi.org/project/ta): ``` - pip install finmarketpy + pip install ta ```
-
FinTA (🥉21 · ⭐ 1.3K) - 基于pandas实现的通用金融技术指标。❗️LGPL-3.0 +
IB-insync (🥉21 · ⭐ 1.6K) - Python sync/async framework for Interactive Brokers API. BSD-2 -- [GitHub](https://github.com/peerchemist/finta) (👨‍💻 25 · 🔀 410 · 📦 110 · 📋 77 - 18% open · ⏱️ 23.07.2021): +- [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 29 · 🔀 460 · 📋 360 - 2% open · ⏱️ 28.11.2021): ``` - git clone https://github.com/peerchemist/finta - ``` -- [PyPi](https://pypi.org/project/finta) (📥 7.3K / month): - ``` - pip install finta + git clone https://github.com/erdewit/ib_insync ``` -
-
stockstats (🥉21 · ⭐ 860) - 提供StockDataFrame包装器BSD-3 - -- [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 230 · 📦 330 · 📋 63 - 47% open · ⏱️ 03.08.2021): - +- [PyPi](https://pypi.org/project/ib_insync) (📥 8.7K / month): ``` - git clone https://github.com/jealous/stockstats + pip install ib_insync ``` -- [PyPi](https://pypi.org/project/stockstats) (📥 18K / month): +- [Conda](https://anaconda.org/conda-forge/ib-insync) (📥 14K · ⏱️ 29.11.2021): ``` - pip install stockstats + conda install -c conda-forge ib-insync ```
-
Qlib (🥉20 · ⭐ 6.7K) - Qlib是一个面向AI的量化投资平台。MIT +
finmarketpy (🥉20 · ⭐ 2.8K) - Python library for backtesting trading strategies & analyzing.. Apache-2 -- [GitHub](https://github.com/microsoft/qlib) (👨‍💻 67 · 🔀 1.1K · 📥 270 · 📦 5 · 📋 310 - 28% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/cuemacro/finmarketpy) (👨‍💻 14 · 🔀 420 · 📥 40 · 📦 4 · 📋 26 - 88% open · ⏱️ 07.10.2021): ``` - git clone https://github.com/microsoft/qlib + git clone https://github.com/cuemacro/finmarketpy ``` -- [PyPi](https://pypi.org/project/pyqlib) (📥 4.1K / month): +- [PyPi](https://pypi.org/project/finmarketpy) (📥 100 / month): ``` - pip install pyqlib + pip install finmarketpy ```
-
PyAlgoTrade (🥉20 · ⭐ 3.5K · 💀) - Python算法交易库。Apache-2 +
Enigma Catalyst (🥉20 · ⭐ 2.3K) - An Algorithmic Trading Library for Crypto-Assets in Python. Apache-2 -- [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 93 · 📋 120 - 30% open · ⏱️ 21.08.2018): +- [GitHub](https://github.com/scrtlabs/catalyst) (👨‍💻 150 · 🔀 670 · 📦 23 · 📋 480 - 25% open · ⏱️ 22.09.2021): ``` - git clone https://github.com/gbeced/pyalgotrade + git clone https://github.com/enigmampc/catalyst ``` -- [PyPi](https://pypi.org/project/pyalgotrade): +- [PyPi](https://pypi.org/project/enigma-catalyst) (📥 970 / month): ``` - pip install pyalgotrade + pip install enigma-catalyst ```
-
Crypto Signals (🥉19 · ⭐ 3.5K) - CryptoSignal量化交易技术。MIT +
Crypto Signals (🥉19 · ⭐ 3.7K) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT -- [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 910 · 📋 240 - 18% open · ⏱️ 28.06.2021): +- [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 950 · 📋 250 - 19% open · ⏱️ 28.06.2021): ``` git clone https://github.com/CryptoSignal/crypto-signal @@ -4503,61 +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 ```
-
tf-quant-finance (🥉19 · ⭐ 2.8K) - 用于量化投资的高性能TensorFlow库。Apache-2 +
tf-quant-finance (🥉19 · ⭐ 2.9K) - High-performance TensorFlow library for quantitative.. Apache-2 -- [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 36 · 🔀 370 · 📋 30 - 40% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 36 · 🔀 380 · 📋 32 - 43% open · ⏱️ 14.12.2021): ``` git clone https://github.com/google/tf-quant-finance ``` -- [PyPi](https://pypi.org/project/tf-quant-finance) (📥 660 / month): +- [PyPi](https://pypi.org/project/tf-quant-finance) (📥 890 / month): ``` pip install tf-quant-finance ```
-
IB-insync (🥉19 · ⭐ 1.6K) - 用于Interactive Brokers API的Python同步/异步框架。BSD-2 - -- [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 29 · 🔀 440 · 📋 340 - 1% open · ⏱️ 12.10.2021): - - ``` - git clone https://github.com/erdewit/ib_insync - ``` -- [PyPi](https://pypi.org/project/ib_insync): - ``` - pip install ib_insync - ``` -- [Conda](https://anaconda.org/conda-forge/ib-insync) (📥 13K · ⏱️ 12.10.2021): - ``` - conda install -c conda-forge ib-insync - ``` -
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ffn (🥉19 · ⭐ 970) - ffn-Python的金融函数库。MIT +
Backtesting.py (🥉18 · ⭐ 2K) - Backtest trading strategies in Python. ❗️AGPL-3.0 -- [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 26 · 🔀 190 · 📦 140 · 📋 95 - 15% open · ⏱️ 24.04.2021): +- [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 410 · 📋 270 - 14% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/pmorissette/ffn + git clone https://github.com/kernc/backtesting.py ``` -- [PyPi](https://pypi.org/project/ffn): +- [PyPi](https://pypi.org/project/backtesting) (📥 13K / month): ``` - pip install ffn + pip install backtesting ```
-
Backtesting.py (🥉18 · ⭐ 1.8K) - 回溯Python中的交易策略。❗️AGPL-3.0 +
stockstats (🥉17 · ⭐ 910) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 -- [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 380 · 📋 250 - 13% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 240 · 📦 360 · 📋 72 - 41% open · ⏱️ 20.11.2021): ``` - git clone https://github.com/kernc/backtesting.py + git clone https://github.com/jealous/stockstats ``` -- [PyPi](https://pypi.org/project/backtesting) (📥 15K / month): +- [PyPi](https://pypi.org/project/stockstats): ``` - pip install backtesting + pip install stockstats ```
-
surpriver (🥉13 · ⭐ 1.3K · 💀) - 使用机器学习在股票大波动之前找到它。❗️GPL-3.0 +
surpriver (🥉12 · ⭐ 1.4K · 💀) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 -- [GitHub](https://github.com/tradytics/surpriver) (👨‍💻 6 · 🔀 240 · 📋 14 - 57% open · ⏱️ 21.09.2020): +- [GitHub](https://github.com/tradytics/surpriver) (👨‍💻 6 · 🔀 250 · 📋 15 - 60% open · ⏱️ 21.09.2020): ``` git clone https://github.com/tradytics/surpriver @@ -4565,44 +4577,32 @@ _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 - -Back to top - -_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。_ +## Time Series Data -
pmdarima (🥇28 · ⭐ 1K) - 一个统计数据库，旨在填补Python时间序列中的空白。MIT +Back to top -- [GitHub](https://github.com/alkaline-ml/pmdarima) (👨‍💻 19 · 🔀 180 · 📦 1.4K · 📋 250 - 6% open · ⏱️ 05.10.2021): +_Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._ - ``` - git clone https://github.com/alkaline-ml/pmdarima - ``` -- [PyPi](https://pypi.org/project/pmdarima) (📥 1M / month): - ``` - pip install pmdarima - ``` -
-
sktime (🥇26 · ⭐ 4.5K) - 具有时间序列的机器学习的统一框架。BSD-3 +
sktime (🥇26 · ⭐ 4.7K) - A unified framework for machine learning with time series. BSD-3 -- [GitHub](https://github.com/alan-turing-institute/sktime) (👨‍💻 120 · 🔀 640 · 📥 64 · 📦 260 · 📋 660 - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/alan-turing-institute/sktime) (👨‍💻 130 · 🔀 700 · 📥 64 · 📦 310 · 📋 780 - 31% open · ⏱️ 13.12.2021): ``` git clone https://github.com/alan-turing-institute/sktime ``` -- [PyPi](https://pypi.org/project/sktime) (📥 110K / month): +- [PyPi](https://pypi.org/project/sktime) (📥 140K / month): ``` pip install sktime ```
-
tslearn (🥇26 · ⭐ 1.8K) - 专门用于时间序列数据的机器学习工具包。BSD-2 +
tslearn (🥇26 · ⭐ 1.9K) - A machine learning toolkit dedicated to time-series data. BSD-2 -- [GitHub](https://github.com/tslearn-team/tslearn) (👨‍💻 33 · 🔀 240 · 📦 310 · 📋 240 - 27% open · ⏱️ 06.09.2021): +- [GitHub](https://github.com/tslearn-team/tslearn) (👨‍💻 36 · 🔀 250 · 📦 360 · 📋 250 - 27% open · ⏱️ 06.12.2021): ``` git clone https://github.com/tslearn-team/tslearn ``` -- [PyPi](https://pypi.org/project/tslearn) (📥 99K / month): +- [PyPi](https://pypi.org/project/tslearn) (📥 120K / month): ``` pip install tslearn ``` @@ -4611,137 +4611,137 @@ _用于按时间序列和顺序数据进行预测，异常检测，特征提取 conda install -c conda-forge tslearn ```
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Darts (🥈25 · ⭐ 2.9K) - 一个易于操作和预测时间序列的python库。Apache-2 +
Darts (🥈24 · ⭐ 3.2K) - A python library for easy manipulation and forecasting of time series. Apache-2 -- [GitHub](https://github.com/unit8co/darts) (👨‍💻 37 · 🔀 240 · 📦 13 · 📋 160 - 16% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/unit8co/darts) (👨‍💻 41 · 🔀 280 · 📦 22 · 📋 290 - 36% open · ⏱️ 14.12.2021): ``` git clone https://github.com/unit8co/darts ``` -- [PyPi](https://pypi.org/project/u8darts) (📥 13K / month): +- [PyPi](https://pypi.org/project/u8darts) (📥 3.7K / month): ``` pip install u8darts ``` -- [Docker Hub](https://hub.docker.com/r/unit8/darts) (📥 170 · ⏱️ 25.09.2021): +- [Docker Hub](https://hub.docker.com/r/unit8/darts) (📥 230 · ⏱️ 28.11.2021): ``` docker pull unit8/darts ```
-
Prophet (🥈23 · ⭐ 13K) - 产生具有时间序列数据的高质量预测的工具。MIT +
GluonTS (🥈24 · ⭐ 2.4K) - Probabilistic time series modeling in Python. Apache-2 + +- [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 79 · 🔀 480 · 📋 640 - 34% open · ⏱️ 13.12.2021): + + ``` + git clone https://github.com/awslabs/gluon-ts + ``` +- [PyPi](https://pypi.org/project/gluonts) (📥 76K / month): + ``` + pip install gluonts + ``` +
+
Prophet (🥈23 · ⭐ 14K) - Tool for producing high quality forecasts for time series data that has.. MIT -- [GitHub](https://github.com/facebook/prophet) (👨‍💻 140 · 🔀 3.8K · 📥 630 · 📋 1.7K - 8% open · ⏱️ 03.10.2021): +- [GitHub](https://github.com/facebook/prophet) (👨‍💻 140 · 🔀 3.9K · 📥 640 · 📋 1.7K - 9% open · ⏱️ 03.10.2021): ``` git clone https://github.com/facebook/prophet ``` -- [PyPi](https://pypi.org/project/fbprophet) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/fbprophet) (📥 1.2M / month): ``` pip install fbprophet ```
-
tsfresh (🥈23 · ⭐ 6K) - 从时间序列中自动提取相关特征。MIT +
tsfresh (🥈23 · ⭐ 6.1K) - Automatic extraction of relevant features from time series:. MIT -- [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 79 · 🔀 910 · 📋 460 - 7% open · ⏱️ 09.07.2021): +- [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 80 · 🔀 930 · 📋 470 - 8% open · ⏱️ 15.12.2021): ``` git clone https://github.com/blue-yonder/tsfresh ``` -- [PyPi](https://pypi.org/project/tsfresh) (📥 310K / month): +- [PyPi](https://pypi.org/project/tsfresh) (📥 260K / month): ``` pip install tsfresh ``` -- [Conda](https://anaconda.org/conda-forge/tsfresh) (📥 50K · ⏱️ 07.03.2021): +- [Conda](https://anaconda.org/conda-forge/tsfresh) (📥 71K · ⏱️ 07.03.2021): ``` conda install -c conda-forge tsfresh ```
-
GluonTS (🥈23 · ⭐ 2.2K) - Python中的概率时间序列建模。Apache-2 +
STUMPY (🥈22 · ⭐ 2K) - STUMPY is a powerful and scalable Python library for computing a Matrix.. BSD-3 -- [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 79 · 🔀 450 · 📋 620 - 32% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 26 · 🔀 190 · 📋 270 - 10% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/awslabs/gluon-ts - ``` -- [PyPi](https://pypi.org/project/gluonts) (📥 55K / month): - ``` - pip install gluonts + git clone https://github.com/TDAmeritrade/stumpy ``` -
-
pytorch-forecasting (🥈23 · ⭐ 1.4K) - 使用PyTorch进行时间序列预测。MIT - -- [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 22 · 🔀 190 · 📋 320 - 32% open · ⏱️ 26.09.2021): - +- [PyPi](https://pypi.org/project/stumpy) (📥 320K / month): ``` - git clone https://github.com/jdb78/pytorch-forecasting + pip install stumpy ``` -- [PyPi](https://pypi.org/project/pytorch-forecasting) (📥 23K / month): +- [Conda](https://anaconda.org/conda-forge/stumpy) (📥 34K · ⏱️ 15.12.2021): ``` - pip install pytorch-forecasting + conda install -c conda-forge stumpy ```
-
PyFlux (🥉21 · ⭐ 1.9K · 💀) - 适用于Python的开源时间序列库。BSD-3 +
pmdarima (🥈22 · ⭐ 1.1K) - A statistical library designed to fill the void in Python's time series.. MIT -- [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 200 · 📋 140 - 55% open · ⏱️ 16.12.2018): +- [GitHub](https://github.com/alkaline-ml/pmdarima) (👨‍💻 19 · 🔀 190 · 📦 1.6K · 📋 260 - 7% open · ⏱️ 28.11.2021): ``` - git clone https://github.com/RJT1990/pyflux + git clone https://github.com/alkaline-ml/pmdarima ``` -- [PyPi](https://pypi.org/project/pyflux) (📥 50K / month): +- [PyPi](https://pypi.org/project/pmdarima): ``` - pip install pyflux + pip install pmdarima ```
-
pyts (🥉20 · ⭐ 1.1K) - 用于时间序列分类的Python软件包。BSD-3 +
Streamz (🥉21 · ⭐ 1K) - Real-time stream processing for python. ❗Unlicensed -- [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 9 · 🔀 110 · 📦 140 · 📋 52 - 59% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 44 · 🔀 130 · 📦 250 · 📋 240 - 38% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/johannfaouzi/pyts + git clone https://github.com/python-streamz/streamz ``` -- [PyPi](https://pypi.org/project/pyts) (📥 8.4K / month): +- [PyPi](https://pypi.org/project/streamz) (📥 10K / month): ``` - pip install pyts + pip install streamz ``` -- [Conda](https://anaconda.org/conda-forge/pyts) (📥 9.1K · ⏱️ 21.03.2020): +- [Conda](https://anaconda.org/conda-forge/streamz) (📥 230K · ⏱️ 04.10.2021): ``` - conda install -c conda-forge pyts + conda install -c conda-forge streamz ```
-
Streamz (🥉20 · ⭐ 990) - python的实时流处理。❗Unlicensed +
pytorch-forecasting (🥉20 · ⭐ 1.6K) - Time series forecasting with PyTorch. MIT -- [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 41 · 🔀 120 · 📦 230 · 📋 230 - 40% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 27 · 🔀 230 · 📋 360 - 36% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/python-streamz/streamz - ``` -- [PyPi](https://pypi.org/project/streamz): - ``` - pip install streamz + git clone https://github.com/jdb78/pytorch-forecasting ``` -- [Conda](https://anaconda.org/conda-forge/streamz) (📥 210K · ⏱️ 04.10.2021): +- [PyPi](https://pypi.org/project/pytorch-forecasting): ``` - conda install -c conda-forge streamz + pip install pytorch-forecasting ```
-
STUMPY (🥉19 · ⭐ 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 (🥉20 · ⭐ 1.1K) - A Python package for time series classification. BSD-3 -- [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 26 · 🔀 190 · 📋 260 - 10% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 10 · 🔀 110 · 📦 160 · 📋 56 - 57% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/TDAmeritrade/stumpy + git clone https://github.com/johannfaouzi/pyts ``` -- [PyPi](https://pypi.org/project/stumpy): +- [PyPi](https://pypi.org/project/pyts): ``` - pip install stumpy + pip install pyts ``` -- [Conda](https://anaconda.org/conda-forge/stumpy) (📥 31K · ⏱️ 28.07.2021): +- [Conda](https://anaconda.org/conda-forge/pyts) (📥 9.7K · ⏱️ 31.10.2021): ``` - conda install -c conda-forge stumpy + conda install -c conda-forge pyts ```
-
luminol (🥉19 · ⭐ 970 · 💀) - 异常检测和相关库。Apache-2 +
luminol (🥉19 · ⭐ 980 · 💀) - Anomaly Detection and Correlation library. Apache-2 -- [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 190 · 📦 43 · 📋 36 - 66% open · ⏱️ 09.01.2018): +- [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 190 · 📦 47 · 📋 36 - 66% open · ⏱️ 09.01.2018): ``` git clone https://github.com/linkedin/luminol @@ -4751,279 +4751,279 @@ _用于按时间序列和顺序数据进行预测，异常检测，特征提取 pip install luminol ```
-
ADTK (🥉18 · ⭐ 730 · 💀) - 一个Python工具包，用于基于规则的/无监督的异常检测。MPL-2.0 +
tick (🥉18 · ⭐ 360 · 💀) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 -- [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 90 · 📋 60 - 43% open · ⏱️ 17.04.2020): +- [GitHub](https://github.com/X-DataInitiative/tick) (👨‍💻 16 · 🔀 81 · 📥 190 · 📦 46 · 📋 220 - 24% open · ⏱️ 15.06.2020): ``` - git clone https://github.com/arundo/adtk + git clone https://github.com/X-DataInitiative/tick ``` -- [PyPi](https://pypi.org/project/adtk) (📥 80K / month): +- [PyPi](https://pypi.org/project/tick) (📥 890 / month): ``` - pip install adtk + pip install tick ```
-
pydlm (🥉18 · ⭐ 400 · 💀) - 用于贝叶斯时间序列建模的python库。BSD-3 +
PyFlux (🥉17 · ⭐ 1.9K · 💀) - Open source time series library for Python. BSD-3 -- [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 86 · 📦 23 · 📋 43 - 81% open · ⏱️ 22.10.2019): +- [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 210 · 📋 150 - 55% open · ⏱️ 16.12.2018): ``` - git clone https://github.com/wwrechard/pydlm + git clone https://github.com/RJT1990/pyflux ``` -- [PyPi](https://pypi.org/project/pydlm) (📥 15K / month): +- [PyPi](https://pypi.org/project/pyflux): ``` - pip install pydlm + pip install pyflux ```
-
tick (🥉18 · ⭐ 360 · 💀) - 统计学习模块。BSD-3 +
ADTK (🥉17 · ⭐ 760 · 💀) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 -- [GitHub](https://github.com/X-DataInitiative/tick) (👨‍💻 16 · 🔀 80 · 📥 190 · 📦 41 · 📋 220 - 25% open · ⏱️ 15.06.2020): +- [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 94 · 📋 60 - 43% open · ⏱️ 17.04.2020): ``` - git clone https://github.com/X-DataInitiative/tick + git clone https://github.com/arundo/adtk ``` -- [PyPi](https://pypi.org/project/tick) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/adtk) (📥 55K / month): ``` - pip install tick + pip install adtk ```
-
matrixprofile-ts (🥉17 · ⭐ 660 · 💀) - 一个用于检测模式和异常的Python库。Apache-2 +
seglearn (🥉17 · ⭐ 480 · 💤) - Python module for machine learning time series:. BSD-3 -- [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 93 · 📦 17 · 📋 53 - 35% open · ⏱️ 25.04.2020): +- [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 13 · 🔀 52 · 📦 11 · 📋 28 - 17% open · ⏱️ 12.03.2021): ``` - git clone https://github.com/target/matrixprofile-ts + git clone https://github.com/dmbee/seglearn ``` -- [PyPi](https://pypi.org/project/matrixprofile-ts) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/seglearn) (📥 1.5K / month): ``` - pip install matrixprofile-ts + pip install seglearn ```
-
Auto TS (🥉16 · ⭐ 310) - 自动实现ARIMA，SARIMAX，VAR，FB Prophet和XGBoost等模型时序建模。Apache-2 +
Auto TS (🥉17 · ⭐ 350) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 -- [GitHub](https://github.com/AutoViML/Auto_TS) (👨‍💻 6 · 🔀 59 · 📋 51 - 15% open · ⏱️ 27.08.2021): +- [GitHub](https://github.com/AutoViML/Auto_TS) (👨‍💻 6 · 🔀 65 · 📋 57 - 14% open · ⏱️ 07.12.2021): ``` git clone https://github.com/AutoViML/Auto_TS ``` -- [PyPi](https://pypi.org/project/auto-ts) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/auto-ts) (📥 2.6K / month): ``` pip install auto-ts ```
-
seglearn (🥉14 · ⭐ 480 · 💤) - 机器学习时间序列的Python模块。BSD-3 +
matrixprofile-ts (🥉14 · ⭐ 670 · 💀) - A Python library for detecting patterns and anomalies.. Apache-2 -- [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 13 · 🔀 51 · 📦 10 · 📋 28 - 17% open · ⏱️ 12.03.2021): +- [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 92 · 📦 17 · 📋 53 - 35% open · ⏱️ 25.04.2020): ``` - git clone https://github.com/dmbee/seglearn + git clone https://github.com/target/matrixprofile-ts ``` -- [PyPi](https://pypi.org/project/seglearn): +- [PyPi](https://pypi.org/project/matrixprofile-ts): ``` - pip install seglearn + pip install matrixprofile-ts + ``` +
+
pydlm (🥉14 · ⭐ 400 · 💀) - A python library for Bayesian time series modeling. BSD-3 + +- [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 87 · 📦 24 · 📋 43 - 81% open · ⏱️ 22.10.2019): + + ``` + git clone https://github.com/wwrechard/pydlm + ``` +- [PyPi](https://pypi.org/project/pydlm): + ``` + pip install pydlm ```
-
atspy (🥉14 · ⭐ 380) - AtsPy：Python中的自动时间序列模型。❗Unlicensed +
atspy (🥉10 · ⭐ 400) - AtsPy: Automated Time Series Models in Python (by @firmai). ❗Unlicensed -- [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 75 · 📦 3 · 📋 20 - 90% open · ⏱️ 30.08.2021): +- [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 78 · 📦 3 · 📋 20 - 90% open · ⏱️ 30.08.2021): ``` git clone https://github.com/firmai/atspy ``` -- [PyPi](https://pypi.org/project/atspy) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/atspy): ``` 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 · ⭐ 1.7K) - Python中的生存分析。MIT +
Lifelines (🥇29 · ⭐ 1.8K) - Survival analysis in Python. MIT -- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 98 · 🔀 430 · 📦 690 · 📋 820 - 24% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 98 · 🔀 440 · 📦 730 · 📋 830 - 25% open · ⏱️ 30.11.2021): ``` git clone https://github.com/CamDavidsonPilon/lifelines ``` -- [PyPi](https://pypi.org/project/lifelines) (📥 270K / month): +- [PyPi](https://pypi.org/project/lifelines) (📥 320K / month): ``` pip install lifelines ``` -- [Conda](https://anaconda.org/conda-forge/lifelines) (📥 170K · ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/conda-forge/lifelines) (📥 180K · ⏱️ 01.12.2021): ``` conda install -c conda-forge lifelines ```
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NIPYPE (🥇28 · ⭐ 590) - 神经影像软件包的工作流程和接口。Apache-2 +
NIPYPE (🥇29 · ⭐ 600) - Workflows and interfaces for neuroimaging packages. Apache-2 -- [GitHub](https://github.com/nipy/nipype) (👨‍💻 220 · 🔀 440 · 📦 740 · 📋 1.2K - 27% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/nipy/nipype) (👨‍💻 230 · 🔀 440 · 📦 810 · 📋 1.2K - 27% open · ⏱️ 15.12.2021): ``` git clone https://github.com/nipy/nipype ``` -- [PyPi](https://pypi.org/project/nipype) (📥 27K / month): +- [PyPi](https://pypi.org/project/nipype) (📥 32K / month): ``` pip install nipype ``` -- [Conda](https://anaconda.org/conda-forge/nipype) (📥 440K · ⏱️ 13.07.2021): +- [Conda](https://anaconda.org/conda-forge/nipype) (📥 460K · ⏱️ 20.10.2021): ``` conda install -c conda-forge nipype ```
-
MNE (🥈27 · ⭐ 1.7K) - MNE：Python中的磁脑图（MEG）和脑电图（EEG）。BSD-3 +
MNE (🥈27 · ⭐ 1.8K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 -- [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 270 · 🔀 930 · 📦 1.2K · 📋 3.8K - 8% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 280 · 🔀 940 · 📦 1.3K · 📋 3.9K - 8% open · ⏱️ 16.12.2021): ``` git clone https://github.com/mne-tools/mne-python ``` -- [PyPi](https://pypi.org/project/mne) (📥 29K / month): +- [PyPi](https://pypi.org/project/mne) (📥 37K / month): ``` pip install mne ``` -- [Conda](https://anaconda.org/conda-forge/mne) (📥 170K · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/mne) (📥 180K · ⏱️ 02.12.2021): ``` conda install -c conda-forge mne ```
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Hail (🥈26 · ⭐ 750) - 可扩展的基因组数据分析。MIT - -- [GitHub](https://github.com/hail-is/hail) (👨‍💻 74 · 🔀 190 · 📦 44 · 📋 2K - 1% open · ⏱️ 12.10.2021): - - ``` - git clone https://github.com/hail-is/hail - ``` -- [PyPi](https://pypi.org/project/hail) (📥 45K / month): - ``` - pip install hail - ``` -
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NiBabel (🥈25 · ⭐ 440) - Python软件包，用于访问神经影像文件格式。❗Unlicensed +
NiBabel (🥈27 · ⭐ 450) - Python package to access a cacophony of neuro-imaging file formats. ❗Unlicensed -- [GitHub](https://github.com/nipy/nibabel) (👨‍💻 93 · 🔀 210 · 📦 5.4K · 📋 410 - 25% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/nipy/nibabel) (👨‍💻 93 · 🔀 220 · 📦 5.9K · 📋 410 - 25% open · ⏱️ 30.09.2021): ``` git clone https://github.com/nipy/nibabel ``` -- [PyPi](https://pypi.org/project/nibabel): +- [PyPi](https://pypi.org/project/nibabel) (📥 150K / month): ``` pip install nibabel ``` -- [Conda](https://anaconda.org/conda-forge/nibabel) (📥 380K · ⏱️ 29.11.2020): +- [Conda](https://anaconda.org/conda-forge/nibabel) (📥 400K · ⏱️ 29.11.2020): ``` conda install -c conda-forge nibabel ```
-
MONAI (🥈24 · ⭐ 2.4K) - 用于医疗成像的AI工具包。Apache-2 +
Hail (🥈26 · ⭐ 770) - Scalable genomic data analysis. MIT -- [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 78 · 🔀 440 · 📦 120 · 📋 1.2K - 8% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/hail-is/hail) (👨‍💻 76 · 🔀 200 · 📦 45 · 📋 2K - 1% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/Project-MONAI/MONAI + git clone https://github.com/hail-is/hail ``` -- [PyPi](https://pypi.org/project/monai) (📥 18K / month): +- [PyPi](https://pypi.org/project/hail) (📥 20K / month): ``` - pip install monai + pip install hail ```
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Nilearn (🥈24 · ⭐ 780) - Python中NeuroImaging的机器学习。❗Unlicensed +
Nilearn (🥈24 · ⭐ 790) - Machine learning for NeuroImaging in Python. ❗Unlicensed -- [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 170 · 🔀 420 · 📥 9 · 📦 1.2K · 📋 1.5K - 14% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 180 · 🔀 420 · 📥 14 · 📦 1.3K · 📋 1.5K - 15% open · ⏱️ 16.12.2021): ``` git clone https://github.com/nilearn/nilearn ``` -- [PyPi](https://pypi.org/project/nilearn) (📥 30K / month): +- [PyPi](https://pypi.org/project/nilearn) (📥 21K / month): ``` pip install nilearn ``` -- [Conda](https://anaconda.org/conda-forge/nilearn) (📥 120K · ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/conda-forge/nilearn) (📥 130K · ⏱️ 16.09.2021): ``` conda install -c conda-forge nilearn ```
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DIPY (🥈24 · ⭐ 470) - DIPY是Python中的Paragon 3D/4D +影像库。❗Unlicensed +
DIPY (🥈24 · ⭐ 480) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed -- [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 310 · 📦 440 · 📋 720 - 12% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 320 · 📦 480 · 📋 740 - 13% open · ⏱️ 03.12.2021): ``` git clone https://github.com/dipy/dipy ``` -- [PyPi](https://pypi.org/project/dipy) (📥 8.5K / month): +- [PyPi](https://pypi.org/project/dipy) (📥 8.6K / month): ``` pip install dipy ``` -- [Conda](https://anaconda.org/conda-forge/dipy) (📥 260K · ⏱️ 06.05.2021): +- [Conda](https://anaconda.org/conda-forge/dipy) (📥 270K · ⏱️ 06.05.2021): ``` conda install -c conda-forge dipy ```
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NiftyNet (🥉22 · ⭐ 1.3K · 💀) - 开源医疗卷积神经网络工具库。Apache-2 +
DeepVariant (🥈22 · ⭐ 2.4K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 -- [GitHub](https://github.com/NifTK/NiftyNet) (👨‍💻 58 · 🔀 390 · 📦 37 · 📋 320 - 30% open · ⏱️ 21.04.2020): +- [GitHub](https://github.com/google/deepvariant) (👨‍💻 21 · 🔀 580 · 📥 3.7K · 📋 450 - 0% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/NifTK/NiftyNet + git clone https://github.com/google/deepvariant ``` -- [PyPi](https://pypi.org/project/niftynet) (📥 180 / month): +- [Conda](https://anaconda.org/bioconda/deepvariant) (📥 36K · ⏱️ 16.12.2021): ``` - pip install niftynet + conda install -c bioconda deepvariant ```
-
DeepVariant (🥉21 · ⭐ 2.4K) - DeepVariant是使用深度神经网络的分析管道。BSD-3 +
NiftyNet (🥈22 · ⭐ 1.3K · 💀) - [unmaintained] An open-source convolutional neural.. Apache-2 -- [GitHub](https://github.com/google/deepvariant) (👨‍💻 20 · 🔀 570 · 📥 3.5K · 📋 440 - 0% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/NifTK/NiftyNet) (👨‍💻 58 · 🔀 390 · 📦 37 · 📋 320 - 30% open · ⏱️ 21.04.2020): ``` - git clone https://github.com/google/deepvariant + git clone https://github.com/NifTK/NiftyNet ``` -- [Conda](https://anaconda.org/bioconda/deepvariant) (📥 34K · ⏱️ 30.07.2021): +- [PyPi](https://pypi.org/project/niftynet) (📥 380 / month): ``` - conda install -c bioconda deepvariant + pip install niftynet ```
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MedPy (🥉21 · ⭐ 370 · 💀) - Python中的医学图像处理。❗️GPL-3.0 +
MedPy (🥉21 · ⭐ 380 · 💀) - Medical image processing in Python. ❗️GPL-3.0 -- [GitHub](https://github.com/loli/medpy) (👨‍💻 13 · 🔀 110 · 📦 400 · 📋 78 - 14% open · ⏱️ 01.05.2020): +- [GitHub](https://github.com/loli/medpy) (👨‍💻 13 · 🔀 110 · 📦 450 · 📋 78 - 14% open · ⏱️ 01.05.2020): ``` git clone https://github.com/loli/medpy ``` -- [PyPi](https://pypi.org/project/MedPy) (📥 9.2K / month): +- [PyPi](https://pypi.org/project/MedPy) (📥 10K / month): ``` pip install MedPy ```
-
Glow (🥉20 · ⭐ 180) - 一个用于大规模基因组分析的开源工具包。Apache-2 +
MONAI (🥉20 · ⭐ 2.6K) - AI Toolkit for Healthcare Imaging. Apache-2 -- [GitHub](https://github.com/projectglow/glow) (👨‍💻 16 · 🔀 50 · 📋 110 - 34% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 84 · 🔀 480 · 📦 160 · 📋 1.3K - 8% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/projectglow/glow + git clone https://github.com/Project-MONAI/MONAI ``` -- [PyPi](https://pypi.org/project/glow.py) (📥 47K / month): +- [PyPi](https://pypi.org/project/monai): ``` - pip install glow.py + pip install monai ```
-
DLTK (🥉19 · ⭐ 1.3K · 💀) - 用于医学图像分析的深度学习工具包。Apache-2 +
Glow (🥉20 · ⭐ 180) - An open-source toolkit for large-scale genomic analysis. Apache-2 -- [GitHub](https://github.com/DLTK/DLTK) (👨‍💻 9 · 🔀 390 · 📦 21 · 📋 31 - 22% open · ⏱️ 21.01.2019): +- [GitHub](https://github.com/projectglow/glow) (👨‍💻 18 · 🔀 55 · 📋 120 - 36% open · ⏱️ 01.12.2021): ``` - git clone https://github.com/DLTK/DLTK + git clone https://github.com/projectglow/glow ``` -- [PyPi](https://pypi.org/project/dltk) (📥 160 / month): +- [PyPi](https://pypi.org/project/glow.py) (📥 27K / month): ``` - pip install dltk + pip install glow.py ```
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NIPY (🥉18 · ⭐ 310 · 💤) - Python FMRI分析软件包中的Neuroimaging。BSD-3 +
NIPY (🥉19 · ⭐ 310 · 💤) - Neuroimaging in Python FMRI analysis package. BSD-3 - [GitHub](https://github.com/nipy/nipy) (👨‍💻 63 · 🔀 130 · 📋 150 - 25% open · ⏱️ 29.03.2021): @@ -5034,48 +5034,60 @@ _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) (📥 88K · ⏱️ 04.05.2020): +- [Conda](https://anaconda.org/conda-forge/nipy) (📥 89K · ⏱️ 04.05.2020): ``` conda install -c conda-forge nipy ```
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Brainiak (🥉17 · ⭐ 250) - 脑成像分析套件。Apache-2 +
Brainiak (🥉18 · ⭐ 260 · 💤) - Brain Imaging Analysis Kit. Apache-2 -- [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 33 · 🔀 120 · 📦 14 · 📋 190 - 35% open · ⏱️ 28.05.2021): +- [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 33 · 🔀 120 · 📦 15 · 📋 190 - 35% open · ⏱️ 28.05.2021): ``` git clone https://github.com/brainiak/brainiak ``` -- [PyPi](https://pypi.org/project/brainiak) (📥 180 / month): +- [PyPi](https://pypi.org/project/brainiak) (📥 190 / month): ``` pip install brainiak ``` -- [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (📥 640 · ⭐ 1 · ⏱️ 15.10.2020): +- [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (📥 680 · ⭐ 1 · ⏱️ 15.10.2020): ``` docker pull brainiak/brainiak ```
-
MedicalTorch (🥉15 · ⭐ 750) - Pytorch的医学成像框架。Apache-2 +
DLTK (🥉16 · ⭐ 1.3K · 💀) - Deep Learning Toolkit for Medical Image Analysis. 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 · 💤) - A medical imaging framework for Pytorch. Apache-2 - [GitHub](https://github.com/perone/medicaltorch) (👨‍💻 8 · 🔀 110 · 📦 11 · 📋 22 - 59% open · ⏱️ 16.04.2021): ``` git clone https://github.com/perone/medicaltorch ``` -- [PyPi](https://pypi.org/project/medicaltorch) (📥 160 / month): +- [PyPi](https://pypi.org/project/medicaltorch) (📥 200 / month): ``` pip install medicaltorch ```
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MedicalNet (🥉14 · ⭐ 1.2K · 💀) - Transfer Learning for 3D Medical Image Analysis的论文实现。MIT +
MedicalNet (🥉13 · ⭐ 1.3K · 💀) - Many studies have shown that the performance on deep learning is.. MIT -- [GitHub](https://github.com/Tencent/MedicalNet) (🔀 330 · 📋 60 - 76% open · ⏱️ 27.08.2020): +- [GitHub](https://github.com/Tencent/MedicalNet) (🔀 330 · 📋 62 - 77% open · ⏱️ 27.08.2020): ``` git clone https://github.com/Tencent/MedicalNet ```
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Medical Detection Toolkit (🥉13 · ⭐ 1K) - Medical Detection Toolkit包含2D + 3D。Apache-2 +
Medical Detection Toolkit (🥉12 · ⭐ 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): @@ -5083,157 +5095,157 @@ _用于处理和分析MRI，EEG，基因组数据和其他医学成像格式等 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 (🥉12 · ⭐ 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) (📥 35 / month): +- [PyPi](https://pypi.org/project/deepneuro) (📥 33 / 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 (🥇29 · ⭐ 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 (🥇30 · ⭐ 13K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 -- [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 89 · 🔀 1.6K · 📥 620K · 📦 570 · 📋 420 - 26% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 90 · 🔀 1.7K · 📥 870K · 📦 750 · 📋 470 - 29% open · ⏱️ 15.10.2021): ``` git clone https://github.com/JaidedAI/EasyOCR ``` -- [PyPi](https://pypi.org/project/easyocr): +- [PyPi](https://pypi.org/project/easyocr) (📥 120K / month): ``` pip install easyocr ```
-
tesserocr (🥇28 · ⭐ 1.5K) - 用于tesseract-ocr API的Python包装器。MIT +
PaddleOCR (🥇26 · ⭐ 18K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 -- [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 200 · 📦 560 · 📋 220 - 31% open · ⏱️ 14.09.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 58 · 🔀 3.6K · 📦 450 · 📋 3.5K - 25% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/sirfz/tesserocr - ``` -- [PyPi](https://pypi.org/project/tesserocr) (📥 78K / month): - ``` - pip install tesserocr + git clone https://github.com/PaddlePaddle/PaddleOCR ``` -- [Conda](https://anaconda.org/conda-forge/tesserocr) (📥 59K · ⏱️ 13.01.2021): +- [PyPi](https://pypi.org/project/paddleocr) (📥 38K / month): ``` - conda install -c conda-forge tesserocr + pip install paddleocr ```
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PaddleOCR (🥈27 · ⭐ 17K) - 基于PaddlePaddle的多语言OCR工具包。Apache-2 +
tesserocr (🥈25 · ⭐ 1.6K) - A Python wrapper for the tesseract-ocr API. MIT -- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 53 · 🔀 3.3K · 📦 340 · 📋 3.1K - 27% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 200 · 📦 580 · 📋 230 - 31% open · ⏱️ 09.11.2021): ``` - git clone https://github.com/PaddlePaddle/PaddleOCR + git clone https://github.com/sirfz/tesserocr ``` -- [PyPi](https://pypi.org/project/paddleocr) (📥 31K / month): +- [PyPi](https://pypi.org/project/tesserocr): ``` - pip install paddleocr + pip install tesserocr + ``` +- [Conda](https://anaconda.org/conda-forge/tesserocr) (📥 62K · ⏱️ 13.01.2021): + ``` + conda install -c conda-forge tesserocr ```
-
Tesseract (🥈25 · ⭐ 3.8K) - Python-tesseract是一种光学字符识别（OCR）工具。Apache-2 +
Tesseract (🥈24 · ⭐ 3.9K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 -- [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 38 · 🔀 550 · 📋 280 - 3% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 38 · 🔀 550 · 📋 280 - 3% open · ⏱️ 08.12.2021): ``` git clone https://github.com/madmaze/pytesseract ``` -- [PyPi](https://pypi.org/project/pytesseract) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/pytesseract) (📥 850K / month): ``` pip install pytesseract ``` -- [Conda](https://anaconda.org/conda-forge/pytesseract) (📥 470K · ⏱️ 05.06.2021): +- [Conda](https://anaconda.org/conda-forge/pytesseract) (📥 480K · ⏱️ 05.06.2021): ``` conda install -c conda-forge pytesseract ```
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keras-ocr (🥈19 · ⭐ 920) - CRAFT文本检测器。MIT +
OCRmyPDF (🥈22 · ⭐ 5.5K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 -- [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 11 · 🔀 220 · 📥 150K · 📋 150 - 31% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 58 · 🔀 510 · 📋 780 - 11% open · ⏱️ 11.12.2021): ``` - git clone https://github.com/faustomorales/keras-ocr + git clone https://github.com/jbarlow83/OCRmyPDF ``` -- [PyPi](https://pypi.org/project/keras-ocr) (📥 4.7K / month): +- [PyPi](https://pypi.org/project/ocrmypdf) (📥 21K / month): ``` - pip install keras-ocr + pip install ocrmypdf ```
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calamari (🥈19 · ⭐ 860) - 基于OCRopy的基于行的ATR引擎。Apache-2 +
attention-ocr (🥉21 · ⭐ 880) - A Tensorflow model for text recognition (CNN + seq2seq with.. MIT -- [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 180 · 📋 220 - 15% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 18 · 📋 150 - 14% open · ⏱️ 29.10.2021): ``` - git clone https://github.com/Calamari-OCR/calamari + git clone https://github.com/emedvedev/attention-ocr ``` -- [PyPi](https://pypi.org/project/calamari_ocr) (📥 930 / month): +- [PyPi](https://pypi.org/project/aocr) (📥 280 / month): ``` - pip install calamari_ocr + pip install aocr ```
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OCRmyPDF (🥉18 · ⭐ 4.9K) - OCRmyPDF将OCR文本层添加到扫描的PDF文件中使用。MPL-2.0 +
keras-ocr (🥉19 · ⭐ 960) - A packaged and flexible version of the CRAFT text detector and.. MIT -- [GitHub](https://github.com/jbarlow83/OCRmyPDF) (👨‍💻 56 · 🔀 470 · 📋 750 - 11% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 12 · 🔀 240 · 📥 200K · 📋 150 - 30% open · ⏱️ 24.11.2021): ``` - git clone https://github.com/jbarlow83/OCRmyPDF + git clone https://github.com/faustomorales/keras-ocr ``` -- [PyPi](https://pypi.org/project/ocrmypdf): +- [PyPi](https://pypi.org/project/keras-ocr) (📥 4.9K / month): ``` - pip install ocrmypdf + pip install keras-ocr ```
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attention-ocr (🥉18 · ⭐ 870 · 💤) - 用于文本识别的Tensorflow模型。MIT +
doc2text (🥉17 · ⭐ 1.3K · 💤) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT -- [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 18 · 📋 150 - 14% open · ⏱️ 31.10.2020): +- [GitHub](https://github.com/jlsutherland/doc2text) (👨‍💻 5 · 🔀 94 · 📦 50 · 📋 21 - 57% open · ⏱️ 01.12.2020): ``` - git clone https://github.com/emedvedev/attention-ocr + git clone https://github.com/jlsutherland/doc2text ``` -- [PyPi](https://pypi.org/project/aocr): +- [PyPi](https://pypi.org/project/doc2text) (📥 380 / month): ``` - pip install aocr + pip install doc2text ```
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pdftabextract (🥉17 · ⭐ 2K · 💀) - 一组用于从PDF文件提取表格的工具。Apache-2 +
calamari (🥉17 · ⭐ 880) - Line based ATR Engine based on OCRopy. Apache-2 -- [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 2 · 🔀 340 · 📦 37 · 📋 21 - 14% open · ⏱️ 26.10.2018): +- [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 180 · 📋 230 - 16% open · ⏱️ 02.10.2021): ``` - git clone https://github.com/WZBSocialScienceCenter/pdftabextract + git clone https://github.com/Calamari-OCR/calamari ``` -- [PyPi](https://pypi.org/project/pdftabextract) (📥 340 / month): +- [PyPi](https://pypi.org/project/calamari_ocr): ``` - pip install pdftabextract + pip install calamari_ocr ```
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doc2text (🥉15 · ⭐ 1.2K · 💤) - 批量检测文本块和OCR扫描不良的PDF。MIT +
pdftabextract (🥉15 · ⭐ 2K · 💀) - A set of tools for extracting tables from PDF files.. Apache-2 -- [GitHub](https://github.com/jlsutherland/doc2text) (👨‍💻 5 · 🔀 94 · 📦 47 · 📋 21 - 57% open · ⏱️ 01.12.2020): +- [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 2 · 🔀 340 · 📦 37 · 📋 21 - 14% open · ⏱️ 26.10.2018): ``` - git clone https://github.com/jlsutherland/doc2text + git clone https://github.com/WZBSocialScienceCenter/pdftabextract ``` -- [PyPi](https://pypi.org/project/doc2text): +- [PyPi](https://pypi.org/project/pdftabextract): ``` - pip install doc2text + pip install pdftabextract ```
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Mozart (🥉10 · ⭐ 300) - 光学音乐识别（OMR）系统。Apache-2 +
Mozart (🥉10 · ⭐ 340 · 💤) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 -- [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 45 · 📋 6 - 33% open · ⏱️ 05.05.2021): +- [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 47 · 📋 9 - 33% open · ⏱️ 05.05.2021): ``` git clone https://github.com/aashrafh/Mozart @@ -5241,399 +5253,387 @@ _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 · ⭐ 31K) - 灵活而强大的数据分析/操作库。BSD-3 +
pandas (🥇43 · ⭐ 32K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 -- [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 2.8K · 🔀 13K · 📥 120K · 📦 550K · 📋 21K - 15% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 2.9K · 🔀 13K · 📥 130K · 📦 600K · 📋 22K - 15% open · ⏱️ 16.12.2021): ``` git clone https://github.com/pandas-dev/pandas ``` -- [PyPi](https://pypi.org/project/pandas) (📥 91M / month): +- [PyPi](https://pypi.org/project/pandas) (📥 71M / month): ``` pip install pandas ``` -- [Conda](https://anaconda.org/conda-forge/pandas) (📥 20M · ⏱️ 12.09.2021): +- [Conda](https://anaconda.org/conda-forge/pandas) (📥 22M · ⏱️ 13.12.2021): ``` conda install -c conda-forge pandas ```
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numpy (🥇38 · ⭐ 18K) - 使用Python进行科学计算的基本软件包。BSD-3 +
numpy (🥇38 · ⭐ 19K) - The fundamental package for scientific computing with Python. BSD-3 -- [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.3K · 🔀 5.8K · 📥 400K · 📦 850K · 📋 10K - 21% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.4K · 🔀 6.1K · 📥 430K · 📦 910K · 📋 10K - 20% open · ⏱️ 16.12.2021): ``` git clone https://github.com/numpy/numpy ``` -- [PyPi](https://pypi.org/project/numpy) (📥 89M / month): +- [PyPi](https://pypi.org/project/numpy) (📥 90M / month): ``` pip install numpy ``` -- [Conda](https://anaconda.org/conda-forge/numpy) (📥 24M · ⏱️ 16.08.2021): +- [Conda](https://anaconda.org/conda-forge/numpy) (📥 27M · ⏱️ 05.11.2021): ``` conda install -c conda-forge numpy ```
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h5py (🥇36 · ⭐ 1.6K) - 适用于Python的HDF5-h5py软件包，HDF5的Pythonic接口。BSD-3 +
h5py (🥇34 · ⭐ 1.6K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 -- [GitHub](https://github.com/h5py/h5py) (👨‍💻 170 · 🔀 410 · 📥 1.5K · 📦 130K · 📋 1.2K - 16% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/h5py/h5py) (👨‍💻 170 · 🔀 420 · 📥 1.6K · 📦 140K · 📋 1.3K - 16% open · ⏱️ 11.12.2021): ``` git clone https://github.com/h5py/h5py ``` -- [PyPi](https://pypi.org/project/h5py) (📥 10M / month): +- [PyPi](https://pypi.org/project/h5py): ``` pip install h5py ``` -- [Conda](https://anaconda.org/conda-forge/h5py) (📥 6.3M · ⏱️ 13.09.2021): +- [Conda](https://anaconda.org/conda-forge/h5py) (📥 6.8M · ⏱️ 26.11.2021): ``` conda install -c conda-forge h5py ```
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Arrow (🥈33 · ⭐ 8.5K) - Apache Arrow定义了一种在内存中表示tabular data的格式。Apache-2 +
Arrow (🥈33 · ⭐ 8.8K) - Apache Arrow is a cross-language development platform for in-.. Apache-2 -- [GitHub](https://github.com/apache/arrow) (👨‍💻 740 · 🔀 2K · 📦 54 · 📋 660 - 1% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/apache/arrow) (👨‍💻 780 · 🔀 2K · 📦 57 · 📋 700 - 1% open · ⏱️ 15.12.2021): ``` git clone https://github.com/apache/arrow ``` -- [PyPi](https://pypi.org/project/pyarrow) (📥 36M / month): +- [PyPi](https://pypi.org/project/pyarrow) (📥 32M / month): ``` pip install pyarrow ``` -- [Conda](https://anaconda.org/conda-forge/arrow) (📥 790K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/arrow) (📥 840K · ⏱️ 26.10.2021): ``` conda install -c conda-forge arrow ```
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xarray (🥈30 · ⭐ 2.3K) - Python中带有N-D标签的数组和数据集。Apache-2 +
xarray (🥈30 · ⭐ 2.4K) - N-D labeled arrays and datasets in Python. Apache-2 -- [GitHub](https://github.com/pydata/xarray) (👨‍💻 340 · 🔀 710 · 📦 7.8K · 📋 2.9K - 26% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/pydata/xarray) (👨‍💻 350 · 🔀 740 · 📦 8.5K · 📋 3K - 27% open · ⏱️ 13.12.2021): ``` git clone https://github.com/pydata/xarray ``` -- [PyPi](https://pypi.org/project/xarray) (📥 940K / month): +- [PyPi](https://pypi.org/project/xarray) (📥 1.2M / month): ``` pip install xarray ``` -- [Conda](https://anaconda.org/conda-forge/xarray) (📥 4M · ⏱️ 26.07.2021): +- [Conda](https://anaconda.org/conda-forge/xarray) (📥 4.4M · ⏱️ 10.12.2021): ``` conda install -c conda-forge xarray ```
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Koalas (🥈29 · ⭐ 3K) - Apache Spark上的pandas API。Apache-2 +
Koalas (🥈29 · ⭐ 3K) - Koalas: pandas API on Apache Spark. Apache-2 -- [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 320 · 📥 1K · 📦 120 · 📋 560 - 14% open · ⏱️ 26.08.2021): +- [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 320 · 📥 1K · 📦 160 · 📋 570 - 15% open · ⏱️ 21.10.2021): ``` git clone https://github.com/databricks/koalas ``` -- [PyPi](https://pypi.org/project/koalas) (📥 2.9M / month): +- [PyPi](https://pypi.org/project/koalas) (📥 2.3M / month): ``` pip install koalas ``` -- [Conda](https://anaconda.org/conda-forge/koalas) (📥 100K · ⏱️ 18.06.2021): +- [Conda](https://anaconda.org/conda-forge/koalas) (📥 110K · ⏱️ 20.10.2021): ``` conda install -c conda-forge koalas ```
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Bottleneck (🥈29 · ⭐ 650 · 💤) - 用C编写的快速NumPy数组函数。BSD-2 +
sklearn-pandas (🥈28 · ⭐ 2.5K · 💤) - Pandas integration with sklearn. ❗️Zlib -- [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 21 · 🔀 70 · 📦 27K · 📋 210 - 16% open · ⏱️ 24.01.2021): +- [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 37 · 🔀 370 · 📦 3.2K · 📋 150 - 13% open · ⏱️ 08.05.2021): ``` - git clone https://github.com/pydata/bottleneck - ``` -- [PyPi](https://pypi.org/project/Bottleneck) (📥 580K / month): - ``` - pip install Bottleneck + git clone https://github.com/scikit-learn-contrib/sklearn-pandas ``` -- [Conda](https://anaconda.org/conda-forge/bottleneck) (📥 1.7M · ⏱️ 24.08.2021): +- [PyPi](https://pypi.org/project/sklearn-pandas) (📥 490K / month): ``` - conda install -c conda-forge bottleneck + pip install sklearn-pandas ```
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zarr (🥈28 · ⭐ 780) - Python的分块，压缩N维数组的实现。MIT +
zarr (🥈27 · ⭐ 820) - An implementation of chunked, compressed, N-dimensional arrays for Python. MIT -- [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 48 · 🔀 120 · 📦 880 · 📋 430 - 38% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 52 · 🔀 130 · 📦 970 · 📋 440 - 37% open · ⏱️ 14.12.2021): ``` git clone https://github.com/zarr-developers/zarr-python ``` -- [PyPi](https://pypi.org/project/zarr) (📥 56K / month): +- [PyPi](https://pypi.org/project/zarr): ``` pip install zarr ``` -- [Conda](https://anaconda.org/conda-forge/zarr) (📥 1M · ⏱️ 30.09.2021): +- [Conda](https://anaconda.org/conda-forge/zarr) (📥 1.2M · ⏱️ 19.11.2021): ``` conda install -c conda-forge zarr ```
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Modin (🥈27 · ⭐ 6.5K) - Modin：通过更改一行来加快Pandas工作流程。❗Unlicensed +
Bottleneck (🥈27 · ⭐ 680 · 💤) - Fast NumPy array functions written in C. BSD-2 -- [GitHub](https://github.com/modin-project/modin) (👨‍💻 81 · 🔀 450 · 📥 200K · 📦 470 · 📋 2K - 28% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 21 · 🔀 74 · 📦 29K · 📋 220 - 17% open · ⏱️ 24.01.2021): ``` - git clone https://github.com/modin-project/modin - ``` -- [PyPi](https://pypi.org/project/modin) (📥 140K / month): - ``` - pip install modin + git clone https://github.com/pydata/bottleneck ``` -
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sklearn-pandas (🥈27 · ⭐ 2.5K) - pandas与sklearn集成。❗️Zlib - -- [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 37 · 🔀 370 · 📦 2.9K · 📋 140 - 12% open · ⏱️ 08.05.2021): - +- [PyPi](https://pypi.org/project/Bottleneck): ``` - git clone https://github.com/scikit-learn-contrib/sklearn-pandas + pip install Bottleneck ``` -- [PyPi](https://pypi.org/project/sklearn-pandas) (📥 320K / month): +- [Conda](https://anaconda.org/conda-forge/bottleneck) (📥 1.8M · ⏱️ 04.11.2021): ``` - pip install sklearn-pandas + conda install -c conda-forge bottleneck ```
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Blaze (🥈26 · ⭐ 3K · 💀) - NumPy和Pandas连接到大数据。❗Unlicensed +
Blaze (🥈26 · ⭐ 3K · 💀) - NumPy and Pandas interface to Big Data. ❗Unlicensed -- [GitHub](https://github.com/blaze/blaze) (👨‍💻 64 · 🔀 350 · 📦 7.9K · 📋 750 - 33% open · ⏱️ 15.08.2019): +- [GitHub](https://github.com/blaze/blaze) (👨‍💻 64 · 🔀 360 · 📦 8K · 📋 750 - 33% open · ⏱️ 15.08.2019): ``` git clone https://github.com/blaze/blaze ``` -- [PyPi](https://pypi.org/project/blaze) (📥 14K / month): +- [PyPi](https://pypi.org/project/blaze) (📥 13K / month): ``` pip install blaze ``` -- [Conda](https://anaconda.org/conda-forge/blaze) (📥 190K · ⏱️ 15.07.2018): +- [Conda](https://anaconda.org/conda-forge/blaze) (📥 200K · ⏱️ 15.07.2018): ``` conda install -c conda-forge blaze ```
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datasketch (🥈26 · ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog等实现。MIT +
Modin (🥈25 · ⭐ 6.6K) - Modin: Speed up your Pandas workflows by changing a single.. ❗Unlicensed -- [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 18 · 🔀 220 · 📥 18 · 📦 320 · 📋 120 - 20% open · ⏱️ 02.06.2021): +- [GitHub](https://github.com/modin-project/modin) (👨‍💻 85 · 🔀 460 · 📥 200K · 📦 520 · 📋 2.2K - 28% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/ekzhu/datasketch + git clone https://github.com/modin-project/modin ``` -- [PyPi](https://pypi.org/project/datasketch) (📥 320K / month): +- [PyPi](https://pypi.org/project/modin): ``` - pip install datasketch + pip install modin ```
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Pandaral·lel (🥉25 · ⭐ 1.8K) - A simple and efficient tool to parallelize Pandas.. BSD-3 +
bcolz (🥉23 · ⭐ 940 · 💀) - A columnar data container that can be compressed. ❗Unlicensed -- [GitHub](https://github.com/nalepae/pandarallel) (👨‍💻 15 · 🔀 120 · 📦 300 · 📋 140 - 56% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 120 · 📦 1.7K · 📋 240 - 50% open · ⏱️ 10.09.2020): ``` - git clone https://github.com/nalepae/pandarallel + git clone https://github.com/Blosc/bcolz ``` -- [PyPi](https://pypi.org/project/pandarallel) (📥 110K / month): +- [PyPi](https://pypi.org/project/bcolz) (📥 14K / month): ``` - pip install pandarallel + pip install bcolz + ``` +- [Conda](https://anaconda.org/conda-forge/bcolz) (📥 280K · ⏱️ 05.11.2019): + ``` + conda install -c conda-forge bcolz ```
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TinyDB (🥉24 · ⭐ 4.6K) - TinyDB：轻型面向文档的数据库。MIT +
Vaex (🥉22 · ⭐ 6.8K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and.. MIT -- [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 68 · 🔀 400 · 📋 270 - 3% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/vaexio/vaex) (👨‍💻 62 · 🔀 520 · 📥 220 · 📋 890 - 31% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/msiemens/tinydb + git clone https://github.com/vaexio/vaex ``` -- [PyPi](https://pypi.org/project/tinydb) (📥 420K / month): +- [PyPi](https://pypi.org/project/vaex) (📥 22K / month): ``` - pip install tinydb + pip install vaex ``` -- [Conda](https://anaconda.org/conda-forge/tinydb) (📥 140K · ⏱️ 23.09.2021): +- [Conda](https://anaconda.org/conda-forge/vaex) (📥 120K · ⏱️ 30.11.2021): ``` - conda install -c conda-forge tinydb + conda install -c conda-forge vaex ```
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swifter (🥉24 · ⭐ 1.8K) - 一个可以对pandas Dataframe或者series做高效function映射的工具库。MIT +
TinyDB (🥉22 · ⭐ 4.7K) - TinyDB is a lightweight document oriented database optimized for your.. MIT -- [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 14 · 🔀 83 · 📦 400 · 📋 100 - 20% open · ⏱️ 25.06.2021): +- [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 70 · 🔀 410 · 📋 270 - 2% open · ⏱️ 04.12.2021): ``` - git clone https://github.com/jmcarpenter2/swifter + git clone https://github.com/msiemens/tinydb ``` -- [PyPi](https://pypi.org/project/swifter) (📥 130K / month): +- [PyPi](https://pypi.org/project/tinydb): ``` - pip install swifter + pip install tinydb ``` -- [Conda](https://anaconda.org/conda-forge/swifter) (📥 120K · ⏱️ 26.06.2021): +- [Conda](https://anaconda.org/conda-forge/tinydb) (📥 150K · ⏱️ 23.09.2021): ``` - conda install -c conda-forge swifter + conda install -c conda-forge tinydb ```
-
numexpr (🥉24 · ⭐ 1.7K · 💤) - 适用于Python，NumPy，PyTables等的快速数值数组表达式评估器。MIT +
Arctic (🥉22 · ⭐ 2.5K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 -- [GitHub](https://github.com/pydata/numexpr) (👨‍💻 58 · 🔀 160 · 📋 310 - 18% open · ⏱️ 03.03.2021): +- [GitHub](https://github.com/man-group/arctic) (👨‍💻 72 · 🔀 490 · 📥 180 · 📦 140 · 📋 520 - 15% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/pydata/numexpr + git clone https://github.com/man-group/arctic ``` -- [PyPi](https://pypi.org/project/numexpr) (📥 1.6M / month): +- [PyPi](https://pypi.org/project/arctic): ``` - pip install numexpr + pip install arctic ``` -- [Conda](https://anaconda.org/conda-forge/numexpr) (📥 3.1M · ⏱️ 02.09.2021): +- [Conda](https://anaconda.org/conda-forge/arctic) (📥 17K · ⏱️ 16.12.2019): ``` - conda install -c conda-forge numexpr + conda install -c conda-forge arctic ```
-
PyTables (🥉24 · ⭐ 1.1K) - 一个Python包，用于管理大量数据。BSD-3 +
swifter (🥉22 · ⭐ 1.8K) - A package which efficiently applies any function to a pandas.. MIT -- [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 99 · 🔀 200 · 📥 160 · 📋 620 - 26% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 14 · 🔀 84 · 📦 440 · 📋 110 - 21% open · ⏱️ 25.06.2021): ``` - git clone https://github.com/PyTables/PyTables + git clone https://github.com/jmcarpenter2/swifter ``` -- [PyPi](https://pypi.org/project/tables) (📥 920K / month): +- [PyPi](https://pypi.org/project/swifter): ``` - pip install tables + pip install swifter ``` -- [Conda](https://anaconda.org/conda-forge/pytables) (📥 3.2M · ⏱️ 03.09.2021): +- [Conda](https://anaconda.org/conda-forge/swifter) (📥 130K · ⏱️ 26.06.2021): ``` - conda install -c conda-forge pytables + conda install -c conda-forge swifter ```
-
bcolz (🥉24 · ⭐ 940 · 💀) - 可以压缩的列式数据容器。❗Unlicensed +
numexpr (🥉22 · ⭐ 1.7K) - Fast numerical array expression evaluator for Python, NumPy, PyTables,.. MIT -- [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 120 · 📦 1.6K · 📋 240 - 49% open · ⏱️ 10.09.2020): +- [GitHub](https://github.com/pydata/numexpr) (👨‍💻 59 · 🔀 160 · 📋 310 - 17% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/Blosc/bcolz + git clone https://github.com/pydata/numexpr ``` -- [PyPi](https://pypi.org/project/bcolz) (📥 16K / month): +- [PyPi](https://pypi.org/project/numexpr): ``` - pip install bcolz + pip install numexpr ``` -- [Conda](https://anaconda.org/conda-forge/bcolz) (📥 270K · ⏱️ 05.11.2019): +- [Conda](https://anaconda.org/conda-forge/numexpr) (📥 3.4M · ⏱️ 09.12.2021): ``` - conda install -c conda-forge bcolz + conda install -c conda-forge numexpr ```
-
Arctic (🥉23 · ⭐ 2.4K) - Arctic是用于数字数据的高性能数据存储。❗️LGPL-2.1 +
datasketch (🥉22 · ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT -- [GitHub](https://github.com/man-group/arctic) (👨‍💻 71 · 🔀 470 · 📥 170 · 📦 140 · 📋 520 - 15% open · ⏱️ 23.07.2021): +- [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 20 · 🔀 230 · 📥 18 · 📦 330 · 📋 120 - 21% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/man-group/arctic - ``` -- [PyPi](https://pypi.org/project/arctic) (📥 4.7K / month): - ``` - pip install arctic + git clone https://github.com/ekzhu/datasketch ``` -- [Conda](https://anaconda.org/conda-forge/arctic) (📥 16K · ⏱️ 16.12.2019): +- [PyPi](https://pypi.org/project/datasketch): ``` - conda install -c conda-forge arctic + pip install datasketch ```
-
Vaex (🥉22 · ⭐ 6.6K) - 用于Python，ML的核外混合Apache Arrow / NumPy DataFrame可视化等实现。MIT +
PyTables (🥉22 · ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 -- [GitHub](https://github.com/vaexio/vaex) (👨‍💻 57 · 🔀 510 · 📥 220 · 📋 840 - 35% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 100 · 🔀 200 · 📥 160 · 📋 630 - 26% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/vaexio/vaex + git clone https://github.com/PyTables/PyTables ``` -- [PyPi](https://pypi.org/project/vaex) (📥 20K / month): +- [PyPi](https://pypi.org/project/tables): ``` - pip install vaex + pip install tables ``` -- [Conda](https://anaconda.org/conda-forge/vaex) (📥 120K · ⏱️ 27.09.2021): +- [Conda](https://anaconda.org/conda-forge/pytables) (📥 3.6M · ⏱️ 29.11.2021): ``` - conda install -c conda-forge vaex + conda install -c conda-forge pytables ```
-
pandasql (🥉22 · ⭐ 1K · 💀) - pandas的sqldf。MIT +
pandasql (🥉22 · ⭐ 1.1K · 💀) - sqldf for pandas. MIT -- [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 940 · 📋 64 - 64% open · ⏱️ 01.02.2017): +- [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 1K · 📋 65 - 64% open · ⏱️ 01.02.2017): ``` git clone https://github.com/yhat/pandasql ``` -- [PyPi](https://pypi.org/project/pandasql) (📥 580K / month): +- [PyPi](https://pypi.org/project/pandasql) (📥 1.1M / month): ``` pip install pandasql ```
-
StaticFrame (🥉21 · ⭐ 240) - 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 · ⭐ 260) - Immutable and grow-only Pandas-like DataFrames with a more explicit.. MIT -- [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 16 · 🔀 23 · 📦 9 · 📋 330 - 10% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 16 · 🔀 23 · 📦 10 · 📋 360 - 10% open · ⏱️ 16.12.2021): ``` git clone https://github.com/InvestmentSystems/static-frame ``` -- [PyPi](https://pypi.org/project/static-frame) (📥 1.6K / month): +- [PyPi](https://pypi.org/project/static-frame): ``` pip install static-frame ``` -- [Conda](https://anaconda.org/conda-forge/static-frame) (📥 120K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/static-frame) (📥 130K · ⏱️ 01.12.2021): ``` conda install -c conda-forge static-frame ```
-
datatable (🥉20 · ⭐ 1.4K) - 一个用于处理二维表格数据的Python包。MPL-2.0 +
Pandaral·lel (🥉20 · ⭐ 1.9K) - A simple and efficient tool to parallelize Pandas.. BSD-3 -- [GitHub](https://github.com/h2oai/datatable) (👨‍💻 30 · 🔀 120 · 📥 1.1K · 📋 1.4K - 10% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/nalepae/pandarallel) (👨‍💻 18 · 🔀 120 · 📦 360 · 📋 140 - 54% open · ⏱️ 17.10.2021): ``` - git clone https://github.com/h2oai/datatable + git clone https://github.com/nalepae/pandarallel ``` -- [PyPi](https://pypi.org/project/datatable) (📥 48K / month): +- [PyPi](https://pypi.org/project/pandarallel): ``` - pip install datatable + pip install pandarallel ```
-
Pandas Summary (🥉19 · ⭐ 370 · 💀) - pandas Dataframe的describe函数功能扩展。MIT +
fletcher (🥉19 · ⭐ 220 · 💤) - Pandas ExtensionDType/Array backed by Apache Arrow. MIT -- [GitHub](https://github.com/mouradmourafiq/pandas-summary) (👨‍💻 6 · 🔀 35 · 📦 670 · 📋 13 - 61% open · ⏱️ 24.08.2019): +- [GitHub](https://github.com/xhochy/fletcher) (👨‍💻 24 · 🔀 34 · 📥 13 · 📦 3 · 📋 73 - 45% open · ⏱️ 18.02.2021): ``` - git clone https://github.com/mouradmourafiq/pandas-summary + git clone https://github.com/xhochy/fletcher ``` -- [PyPi](https://pypi.org/project/pandas-summary) (📥 45K / month): +- [PyPi](https://pypi.org/project/fletcher): ``` - pip install pandas-summary + pip install fletcher + ``` +- [Conda](https://anaconda.org/conda-forge/fletcher) (📥 35K · ⏱️ 04.11.2021): + ``` + conda install -c conda-forge fletcher ```
-
fletcher (🥉19 · ⭐ 220 · 💤) - 由Apache Arrow支持的Pandas ExtensionDType/Array。MIT +
datatable (🥉17 · ⭐ 1.4K) - A Python package for manipulating 2-dimensional tabular data.. MPL-2.0 -- [GitHub](https://github.com/xhochy/fletcher) (👨‍💻 24 · 🔀 34 · 📥 13 · 📦 3 · 📋 73 - 45% open · ⏱️ 18.02.2021): +- [GitHub](https://github.com/h2oai/datatable) (👨‍💻 32 · 🔀 120 · 📥 1.2K · 📋 1.4K - 9% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/xhochy/fletcher - ``` -- [PyPi](https://pypi.org/project/fletcher) (📥 310 / month): - ``` - pip install fletcher + git clone https://github.com/h2oai/datatable ``` -- [Conda](https://anaconda.org/conda-forge/fletcher) (📥 32K · ⏱️ 17.01.2021): +- [PyPi](https://pypi.org/project/datatable): ``` - conda install -c conda-forge fletcher + pip install datatable ```
-
Bounter (🥉18 · ⭐ 920) - 使用有限内存的高效计数器。MIT +
Bounter (🥉16 · ⭐ 930 · 💤) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT -- [GitHub](https://github.com/RaRe-Technologies/bounter) (👨‍💻 8 · 🔀 47 · 📦 25 · 📋 23 - 60% open · ⏱️ 24.05.2021): +- [GitHub](https://github.com/RaRe-Technologies/bounter) (👨‍💻 8 · 🔀 45 · 📦 25 · 📋 23 - 60% open · ⏱️ 24.05.2021): ``` git clone https://github.com/RaRe-Technologies/bounter ``` -- [PyPi](https://pypi.org/project/bounter) (📥 92 / month): +- [PyPi](https://pypi.org/project/bounter): ``` pip install bounter ```
-
pickleDB (🥉15 · ⭐ 610 · 💀) - pickleDB是使用Python的json的开源键值存储。BSD-3 +
pickleDB (🥉16 · ⭐ 620 · 💀) - pickleDB is an open source key-value store using Python's json.. BSD-3 -- [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 100 · 📦 710 · 📋 53 - 26% open · ⏱️ 15.11.2019): +- [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 100 · 📦 790 · 📋 54 - 27% open · ⏱️ 15.11.2019): ``` git clone https://github.com/patx/pickledb @@ -5643,198 +5643,210 @@ _通用数据容器和结构以及pandas的实用程序和扩展。_ pip install pickledb ```
-
PandaPy (🥉11 · ⭐ 480) - PandaPy：具有NumPy的速度，性能高于pandas的表格数据实现。❗Unlicensed +
Pandas Summary (🥉13 · ⭐ 370) - An extension to pandas dataframes describe function. Apache-2 + +- [GitHub](https://github.com/polyaxon/datatile) (👨‍💻 7 · 🔀 37 · 📦 3 · 📋 13 - 53% open · ⏱️ 02.12.2021): + + ``` + git clone https://github.com/mouradmourafiq/pandas-summary + ``` +- [PyPi](https://pypi.org/project/pandas-summary): + ``` + pip install pandas-summary + ``` +
+
PandaPy (🥉11 · ⭐ 490) - PandaPy has the speed of NumPy and the usability of Pandas.. ❗Unlicensed -- [GitHub](https://github.com/firmai/pandapy) (👨‍💻 3 · 🔀 54 · 📦 1 · 📋 2 - 50% open · ⏱️ 30.08.2021): +- [GitHub](https://github.com/firmai/pandapy) (👨‍💻 3 · 🔀 56 · 📦 1 · 📋 2 - 50% open · ⏱️ 20.10.2021): ``` git clone https://github.com/firmai/pandapy ``` -- [PyPi](https://pypi.org/project/pandapy) (📥 62 / month): +- [PyPi](https://pypi.org/project/pandapy) (📥 67 / 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 · ⭐ 13K) - Faker is a Python package that generates fake data for you. MIT -- [GitHub](https://github.com/joke2k/faker) (👨‍💻 430 · 🔀 1.5K · 📦 40K · 📋 520 - 25% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/joke2k/faker) (👨‍💻 430 · 🔀 1.5K · 📦 45K · 📋 530 - 24% open · ⏱️ 07.12.2021): ``` git clone https://github.com/joke2k/faker ``` -- [PyPi](https://pypi.org/project/Faker) (📥 4.7M / month): +- [PyPi](https://pypi.org/project/Faker) (📥 5.3M / month): ``` pip install Faker ``` -- [Conda](https://anaconda.org/conda-forge/faker) (📥 500K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/faker) (📥 530K · ⏱️ 07.12.2021): ``` conda install -c conda-forge faker ```
-
Datasets (🥇34 · ⭐ 10K) - 具有ML模型的最大的即用型NLP数据集合。Apache-2 +
Datasets (🥇34 · ⭐ 12K) - The largest hub of ready-to-use NLP datasets for ML models with.. Apache-2 -- [GitHub](https://github.com/huggingface/datasets) (👨‍💻 320 · 🔀 1.2K · 📦 1.8K · 📋 1K - 33% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/huggingface/datasets) (👨‍💻 360 · 🔀 1.3K · 📦 2.4K · 📋 1.2K - 34% open · ⏱️ 14.12.2021): ``` git clone https://github.com/huggingface/datasets ``` -- [PyPi](https://pypi.org/project/datasets) (📥 490K / month): +- [PyPi](https://pypi.org/project/datasets) (📥 540K / month): ``` pip install datasets ```
-
Tablib (🥇31 · ⭐ 4K) - 用于XLS，CSV，JSON，YAML和＆c中表格数据集的Python模块。MIT +
xmltodict (🥇31 · ⭐ 4.6K · 💀) - Python module that makes working with XML feel like you are.. MIT -- [GitHub](https://github.com/jazzband/tablib) (👨‍💻 110 · 🔀 550 · 📦 12K · 📋 230 - 12% open · ⏱️ 04.09.2021): +- [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 41 · 🔀 420 · 📦 34K · 📋 200 - 32% open · ⏱️ 26.04.2020): ``` - git clone https://github.com/jazzband/tablib + git clone https://github.com/martinblech/xmltodict ``` -- [PyPi](https://pypi.org/project/tablib) (📥 840K / month): +- [PyPi](https://pypi.org/project/xmltodict) (📥 15M / month): ``` - pip install tablib + pip install xmltodict ``` -- [Conda](https://anaconda.org/conda-forge/tablib) (📥 67K · ⏱️ 05.12.2020): +- [Conda](https://anaconda.org/conda-forge/xmltodict) (📥 1.3M · ⏱️ 11.02.2019): ``` - conda install -c conda-forge tablib + conda install -c conda-forge xmltodict ```
-
xmltodict (🥈30 · ⭐ 4.6K · 💀) - 像处理JSON一样处理XML。MIT +
Tablib (🥈29 · ⭐ 4.1K) - Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c. MIT -- [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 41 · 🔀 420 · 📦 31K · 📋 200 - 32% open · ⏱️ 26.04.2020): +- [GitHub](https://github.com/jazzband/tablib) (👨‍💻 120 · 🔀 550 · 📦 13K · 📋 240 - 11% open · ⏱️ 04.11.2021): ``` - git clone https://github.com/martinblech/xmltodict + git clone https://github.com/jazzband/tablib ``` -- [PyPi](https://pypi.org/project/xmltodict) (📥 13M / month): +- [PyPi](https://pypi.org/project/tablib): ``` - pip install xmltodict + pip install tablib ``` -- [Conda](https://anaconda.org/conda-forge/xmltodict) (📥 1.2M · ⏱️ 11.02.2019): +- [Conda](https://anaconda.org/conda-forge/tablib) (📥 69K · ⏱️ 26.10.2021): ``` - conda install -c conda-forge xmltodict + conda install -c conda-forge tablib ```
-
xlrd (🥈30 · ⭐ 1.9K) - xlrd是python语言中用于读取excel表格内容的库。❗Unlicensed +
xlrd (🥈29 · ⭐ 2K) - Please use openpyxl where you can... ❗Unlicensed -- [GitHub](https://github.com/python-excel/xlrd) (👨‍💻 51 · 🔀 410 · 📦 83K · ⏱️ 21.08.2021): +- [GitHub](https://github.com/python-excel/xlrd) (👨‍💻 51 · 🔀 410 · 📦 86K · ⏱️ 21.08.2021): ``` git clone https://github.com/python-excel/xlrd ``` -- [PyPi](https://pypi.org/project/xlrd) (📥 11M / month): +- [PyPi](https://pypi.org/project/xlrd) (📥 12M / month): ``` pip install xlrd ``` -- [Conda](https://anaconda.org/conda-forge/xlrd) (📥 1.7M · ⏱️ 09.01.2021): +- [Conda](https://anaconda.org/conda-forge/xlrd) (📥 2M · ⏱️ 09.01.2021): ``` conda install -c conda-forge xlrd ```
-
TensorFlow Datasets (🥈28 · ⭐ 3K) - TFDS是一个高级数据集合。Apache-2 +
TensorFlow Datasets (🥈28 · ⭐ 3.1K) - TFDS is a collection of datasets ready to use with.. Apache-2 -- [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 220 · 🔀 1.1K · 📋 890 - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 240 · 🔀 1.1K · 📋 910 - 33% open · ⏱️ 16.12.2021): ``` git clone https://github.com/tensorflow/datasets ``` -- [PyPi](https://pypi.org/project/tensorflow-datasets) (📥 1.8M / month): +- [PyPi](https://pypi.org/project/tensorflow-datasets) (📥 1.9M / month): ``` pip install tensorflow-datasets ```
-
python-magic (🥈28 · ⭐ 2K) - 用于libmagic的python包装器。❗Unlicensed +
snorkel (🥈27 · ⭐ 5K) - A system for quickly generating training data with weak supervision. Apache-2 -- [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 52 · 🔀 220 · 📦 19K · 📋 160 - 15% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/snorkel-team/snorkel) (👨‍💻 74 · 🔀 780 · 📥 900 · 📦 140 · 📋 960 - 1% open · ⏱️ 04.12.2021): ``` - git clone https://github.com/ahupp/python-magic + git clone https://github.com/snorkel-team/snorkel ``` -- [PyPi](https://pypi.org/project/python-magic) (📥 3.2M / month): +- [PyPi](https://pypi.org/project/snorkel) (📥 58K / month): ``` - pip install python-magic + pip install snorkel ``` -- [Conda](https://anaconda.org/conda-forge/python-magic) (📥 100K · ⏱️ 08.06.2021): +- [Conda](https://anaconda.org/conda-forge/snorkel) (📥 24K · ⏱️ 23.11.2021): ``` - conda install -c conda-forge python-magic + conda install -c conda-forge snorkel ```
-
csvkit (🥈27 · ⭐ 4.7K) - 一套实用工具，可转换为CSV并操作。MIT +
csvkit (🥈27 · ⭐ 4.8K) - A suite of utilities for converting to and working with CSV, the king of.. MIT -- [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 540 · 📦 950 · 📋 830 - 6% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 540 · 📦 970 · 📋 830 - 7% open · ⏱️ 08.10.2021): ``` git clone https://github.com/wireservice/csvkit ``` -- [PyPi](https://pypi.org/project/csvkit) (📥 49K / month): +- [PyPi](https://pypi.org/project/csvkit) (📥 54K / month): ``` pip install csvkit ``` -- [Conda](https://anaconda.org/conda-forge/csvkit) (📥 56K · ⏱️ 13.07.2021): +- [Conda](https://anaconda.org/conda-forge/csvkit) (📥 58K · ⏱️ 13.07.2021): ``` conda install -c conda-forge csvkit ```
-
snorkel (🥈26 · ⭐ 4.9K) - 在弱监督环境下快速生成训练数据的系统。Apache-2 +
PDFMiner (🥈26 · ⭐ 4.7K · 💀) - Python PDF Parser (Not actively maintained). Check out pdfminer.six. MIT -- [GitHub](https://github.com/snorkel-team/snorkel) (👨‍💻 70 · 🔀 770 · 📥 700 · 📦 120 · 📋 960 - 2% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 960 · 📦 2.7K · 📋 230 - 82% open · ⏱️ 18.01.2020): ``` - git clone https://github.com/snorkel-team/snorkel + git clone https://github.com/euske/pdfminer ``` -- [PyPi](https://pypi.org/project/snorkel) (📥 58K / month): +- [PyPi](https://pypi.org/project/pdfminer) (📥 150K / month): ``` - pip install snorkel + pip install pdfminer ``` -- [Conda](https://anaconda.org/conda-forge/snorkel) (📥 23K · ⏱️ 30.04.2021): +- [Conda](https://anaconda.org/conda-forge/pdfminer) (📥 20K · ⏱️ 15.02.2021): ``` - conda install -c conda-forge snorkel + conda install -c conda-forge pdfminer ```
-
PDFMiner (🥈26 · ⭐ 4.7K · 💀) - Python PDF解析器。MIT +
smart-open (🥈26 · ⭐ 2.3K) - Utils for streaming large files (S3, HDFS, gzip, bz2...). MIT -- [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 950 · 📦 2.6K · 📋 230 - 82% open · ⏱️ 18.01.2020): +- [GitHub](https://github.com/RaRe-Technologies/smart_open) (👨‍💻 89 · 🔀 290 · 📋 330 - 18% open · ⏱️ 02.12.2021): ``` - git clone https://github.com/euske/pdfminer - ``` -- [PyPi](https://pypi.org/project/pdfminer) (📥 150K / month): - ``` - pip install pdfminer + git clone https://github.com/RaRe-Technologies/smart_open ``` -- [Conda](https://anaconda.org/conda-forge/pdfminer) (📥 19K · ⏱️ 15.02.2021): +- [PyPi](https://pypi.org/project/smart-open) (📥 16M / month): ``` - conda install -c conda-forge pdfminer + pip install smart-open ```
-
smart-open (🥈26 · ⭐ 2.2K) - 用于大文件（S3，HDFS，gzip，bz2 ...）流传输的实用程序。MIT +
python-magic (🥉25 · ⭐ 2K) - A python wrapper for libmagic. ❗Unlicensed -- [GitHub](https://github.com/RaRe-Technologies/smart_open) (👨‍💻 87 · 🔀 280 · 📋 320 - 16% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 53 · 🔀 220 · 📦 21K · 📋 160 - 14% open · ⏱️ 23.10.2021): ``` - git clone https://github.com/RaRe-Technologies/smart_open + git clone https://github.com/ahupp/python-magic ``` -- [PyPi](https://pypi.org/project/smart-open) (📥 17M / month): +- [PyPi](https://pypi.org/project/python-magic): ``` - pip install smart-open + pip install python-magic + ``` +- [Conda](https://anaconda.org/conda-forge/python-magic) (📥 110K · ⏱️ 05.11.2021): + ``` + conda install -c conda-forge python-magic ```
-
textract (🥉24 · ⭐ 3.1K) - 从任何文档中提取文本。MIT +
textract (🥉24 · ⭐ 3.2K) - extract text from any document. no muss. no fuss. MIT -- [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 39 · 🔀 430 · 📋 200 - 37% open · ⏱️ 21.08.2021): +- [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 39 · 🔀 440 · 📋 200 - 37% open · ⏱️ 21.08.2021): ``` git clone https://github.com/deanmalmgren/textract ``` -- [PyPi](https://pypi.org/project/textract) (📥 75K / month): +- [PyPi](https://pypi.org/project/textract) (📥 74K / month): ``` pip install textract ``` @@ -5843,9 +5855,9 @@ _用于从各种数据源和格式加载，收集和提取数据的库。_ conda install -c conda-forge textract ```
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Intake (🥉24 · ⭐ 630) - Intake是一个轻量级的程序包，用于查找，调查，加载等。BSD-2 +
Intake (🥉24 · ⭐ 660) - Intake is a lightweight package for finding, investigating, loading and.. BSD-2 -- [GitHub](https://github.com/intake/intake) (👨‍💻 64 · 🔀 110 · 📦 300 · 📋 280 - 24% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/intake/intake) (👨‍💻 67 · 🔀 110 · 📦 320 · 📋 280 - 25% open · ⏱️ 01.12.2021): ``` git clone https://github.com/intake/intake @@ -5854,134 +5866,134 @@ _用于从各种数据源和格式加载，收集和提取数据的库。_ ``` pip install intake ``` -- [Conda](https://anaconda.org/conda-forge/intake) (📥 100K · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/intake) (📥 120K · ⏱️ 11.10.2021): ``` conda install -c conda-forge intake ```
-
SDV (🥉23 · ⭐ 520) - 用于表格，关系和时间序列数据的综合数据生成。MIT +
SDV (🥉23 · ⭐ 600) - Synthetic Data Generation for tabular, relational and time series data. MIT -- [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 38 · 🔀 94 · 📦 35 · 📋 370 - 32% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 39 · 🔀 100 · 📦 41 · 📋 410 - 33% open · ⏱️ 15.12.2021): ``` git clone https://github.com/sdv-dev/SDV ``` -- [PyPi](https://pypi.org/project/sdv) (📥 12K / month): +- [PyPi](https://pypi.org/project/sdv) (📥 23K / month): ``` pip install sdv ```
-
tabulator-py (🥉22 · ⭐ 210 · 💤) - 用于读取和写入图像数据的Python库。MIT +
tabulator-py (🥉22 · ⭐ 220 · 💤) - Python library for reading and writing tabular data via streams. MIT -- [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 630 · ⏱️ 22.03.2021): +- [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 670 · ⏱️ 22.03.2021): ``` git clone https://github.com/frictionlessdata/tabulator-py ``` -- [PyPi](https://pypi.org/project/tabulator) (📥 290K / month): +- [PyPi](https://pypi.org/project/tabulator) (📥 370K / month): ``` pip install tabulator ``` -- [Conda](https://anaconda.org/conda-forge/tabulator-py) (📥 45K · ⏱️ 24.07.2018): +- [Conda](https://anaconda.org/conda-forge/tabulator-py) (📥 46K · ⏱️ 24.07.2018): ``` conda install -c conda-forge tabulator-py ```
-
pandas-datareader (🥉20 · ⭐ 2.1K) - 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 · 🔀 540 · 📋 480 - 18% open · ⏱️ 07.08.2021): +- [GitHub](https://github.com/okfn/messytables) (👨‍💻 44 · 🔀 100 · 📦 220 · 📋 85 - 35% open · ⏱️ 13.11.2019): ``` - git clone https://github.com/pydata/pandas-datareader - ``` -- [PyPi](https://pypi.org/project/pandas-datareader) (📥 310K / month): - ``` - pip install pandas-datareader + git clone https://github.com/okfn/messytables ``` -- [Conda](https://anaconda.org/conda-forge/pandas-datareader) (📥 150K · ⏱️ 14.07.2021): +- [PyPi](https://pypi.org/project/messytables) (📥 9.2K / month): ``` - conda install -c conda-forge pandas-datareader + pip install messytables ```
-
rows (🥉20 · ⭐ 770) - 通用美观的表格数据界面。❗️LGPL-3.0 +
pandas-datareader (🥉20 · ⭐ 2.2K) - Extract data from a wide range of Internet sources.. ❗Unlicensed -- [GitHub](https://github.com/turicas/rows) (👨‍💻 30 · 🔀 130 · 📥 37 · 📦 130 · 📋 290 - 48% open · ⏱️ 22.05.2021): +- [GitHub](https://github.com/pydata/pandas-datareader) (👨‍💻 83 · 🔀 550 · 📋 480 - 19% open · ⏱️ 07.08.2021): ``` - git clone https://github.com/turicas/rows - ``` -- [PyPi](https://pypi.org/project/rows) (📥 1.8K / month): - ``` - pip install rows + git clone https://github.com/pydata/pandas-datareader ``` -
-
messytables (🥉20 · ⭐ 380 · 💀) - 解析混乱的表格数据的工具。❗Unlicensed - -- [GitHub](https://github.com/okfn/messytables) (👨‍💻 44 · 🔀 100 · 📦 210 · 📋 85 - 35% open · ⏱️ 13.11.2019): - +- [PyPi](https://pypi.org/project/pandas-datareader) (📥 240K / month): ``` - git clone https://github.com/okfn/messytables + pip install pandas-datareader ``` -- [PyPi](https://pypi.org/project/messytables) (📥 10K / month): +- [Conda](https://anaconda.org/conda-forge/pandas-datareader) (📥 160K · ⏱️ 14.07.2021): ``` - pip install messytables + conda install -c conda-forge pandas-datareader ```
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pyexcel-xlsx (🥉20 · ⭐ 92 · 💤) - 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 +
pyexcel-xlsx (🥉20 · ⭐ 95 · 💀) - A wrapper library to read, manipulate and write data in.. ❗Unlicensed -- [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 16 · 📥 51 · 📦 1.4K · 📋 32 - 37% open · ⏱️ 28.11.2020): +- [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 17 · 📥 51 · 📦 1.4K · 📋 33 - 39% open · ⏱️ 28.11.2020): ``` git clone https://github.com/pyexcel/pyexcel-xlsx ``` -- [PyPi](https://pypi.org/project/pyexcel-xlsx) (📥 79K / month): +- [PyPi](https://pypi.org/project/pyexcel-xlsx) (📥 110K / month): ``` pip install pyexcel-xlsx ``` -- [Conda](https://anaconda.org/conda-forge/pyexcel-xlsx) (📥 18K · ⏱️ 10.10.2020): +- [Conda](https://anaconda.org/conda-forge/pyexcel-xlsx) (📥 19K · ⏱️ 10.10.2020): ``` conda install -c conda-forge pyexcel-xlsx ```
-
datatest (🥉19 · ⭐ 240) - 用于测试驱动的数据整理和数据验证的工具。❗Unlicensed +
Camelot (🥉19 · ⭐ 3.1K · 💀) - Camelot: PDF Table Extraction for Humans. ❗Unlicensed -- [GitHub](https://github.com/shawnbrown/datatest) (👨‍💻 6 · 🔀 11 · 📦 48 · 📋 52 - 19% open · ⏱️ 26.04.2021): +- [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 330 · 📋 350 - 21% open · ⏱️ 15.10.2019): ``` - git clone https://github.com/shawnbrown/datatest + git clone https://github.com/atlanhq/camelot ``` -- [PyPi](https://pypi.org/project/datatest) (📥 18K / month): +- [PyPi](https://pypi.org/project/camelot-py) (📥 43K / month): ``` - pip install datatest + pip install camelot-py ```
-
Camelot (🥉18 · ⭐ 3.1K · 💀) - Camelot：简单的PDF表提取。❗Unlicensed +
datatest (🥉19 · ⭐ 250) - Tools for test driven data-wrangling and data validation. ❗Unlicensed -- [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 320 · 📋 350 - 20% open · ⏱️ 15.10.2019): +- [GitHub](https://github.com/shawnbrown/datatest) (👨‍💻 7 · 🔀 12 · 📦 59 · 📋 52 - 19% open · ⏱️ 05.12.2021): ``` - git clone https://github.com/atlanhq/camelot + git clone https://github.com/shawnbrown/datatest ``` -- [PyPi](https://pypi.org/project/camelot-py) (📥 34K / month): +- [PyPi](https://pypi.org/project/datatest) (📥 5.6K / month): ``` - pip install camelot-py + pip install datatest ```
-
Singer (🥉17 · ⭐ 870) - 在数据库，Web API，文件，队列等之间移动数据的标准。❗️AGPL-3.0 +
Singer (🥉18 · ⭐ 910 · 💤) - Standard for moving data between databases, web APIs, files,.. ❗️AGPL-3.0 - [GitHub](https://github.com/singer-io/getting-started) (👨‍💻 26 · 🔀 120 · 📋 37 - 51% open · ⏱️ 29.04.2021): ``` git clone https://github.com/singer-io/getting-started ``` -- [PyPi](https://pypi.org/project/singer-python) (📥 110K / month): +- [PyPi](https://pypi.org/project/singer-python) (📥 130K / month): ``` pip install singer-python ```
-
openpyxl (🥉15 · ⭐ 27) - 一个用于读取/写入Excel 2010 xlsx/xlsm文件的Python库。MIT +
rows (🥉18 · ⭐ 780) - A common, beautiful interface to tabular data, no matter the format. ❗️LGPL-3.0 + +- [GitHub](https://github.com/turicas/rows) (👨‍💻 30 · 🔀 130 · 📥 37 · 📦 130 · 📋 290 - 48% open · ⏱️ 13.12.2021): + + ``` + git clone https://github.com/turicas/rows + ``` +- [PyPi](https://pypi.org/project/rows): + ``` + pip install rows + ``` +
+
openpyxl (🥉15 · ⭐ 31) - A Python library to read/write Excel 2010 xlsx/xlsm files. MIT -- [PyPi](https://pypi.org/project/openpyxl) (📥 17M / month): +- [PyPi](https://pypi.org/project/openpyxl) (📥 20M / month): ``` pip install openpyxl ``` @@ -5990,7 +6002,7 @@ _用于从各种数据源和格式加载，收集和提取数据的库。_ ``` git clone https://foss.heptapod.net/openpyxl/openpyxl ``` -- [Conda](https://anaconda.org/anaconda/openpyxl) (📥 59K · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/anaconda/openpyxl) (📥 63K · ⏱️ 05.10.2021): ``` conda install -c anaconda openpyxl ``` @@ -6001,25 +6013,25 @@ _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 ( ⭐ 1.3K) - Collection of web-scraping and crawling libraries. +🔗 Python Web Scraping ( ⭐ 1.4K) - 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 (🥇37 · ⭐ 18K) - Asynchronous task queue/job queue based on distributed message.. ❗Unlicensed -- [GitHub](https://github.com/celery/celery) (👨‍💻 1.2K · 🔀 4K · 📦 59K · 📋 4.6K - 10% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/celery/celery) (👨‍💻 1.2K · 🔀 4K · 📦 62K · 📋 4.6K - 9% open · ⏱️ 16.12.2021): ``` git clone https://github.com/celery/celery @@ -6028,270 +6040,270 @@ _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 celery ``` -- [Conda](https://anaconda.org/conda-forge/celery) (📥 670K · ⏱️ 29.06.2021): +- [Conda](https://anaconda.org/conda-forge/celery) (📥 760K · ⏱️ 29.06.2021): ``` conda install -c conda-forge celery ```
-
luigi (🥇33 · ⭐ 15K) - Luigi是一个Python模块，可帮助您构建复杂的批处理管道。Apache-2 +
joblib (🥇34 · ⭐ 2.6K) - Computing with Python functions. BSD-3 -- [GitHub](https://github.com/spotify/luigi) (👨‍💻 560 · 🔀 2.2K · 📦 1.6K · 📋 910 - 7% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 300 · 📦 150K · 📋 660 - 43% open · ⏱️ 08.11.2021): ``` - git clone https://github.com/spotify/luigi + git clone https://github.com/joblib/joblib ``` -- [PyPi](https://pypi.org/project/luigi) (📥 700K / month): +- [PyPi](https://pypi.org/project/joblib) (📥 27M / month): ``` - pip install luigi + pip install joblib ``` -- [Conda](https://anaconda.org/anaconda/luigi) (📥 8.2K · ⏱️ 17.04.2021): +- [Conda](https://anaconda.org/conda-forge/joblib) (📥 6.5M · ⏱️ 07.10.2021): ``` - conda install -c anaconda luigi + conda install -c conda-forge joblib ```
-
rq (🥇31 · ⭐ 7.9K) - 适用于Python的简单作业队列。❗Unlicensed +
Dagster (🥇31 · ⭐ 4.1K) - A data orchestrator for machine learning, analytics, and ETL. Apache-2 -- [GitHub](https://github.com/rq/rq) (👨‍💻 250 · 🔀 1.2K · 📦 8.9K · 📋 900 - 16% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/dagster-io/dagster) (👨‍💻 180 · 🔀 480 · 📦 270 · 📋 3.5K - 22% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/rq/rq + git clone https://github.com/dagster-io/dagster ``` -- [PyPi](https://pypi.org/project/rq) (📥 500K / month): +- [PyPi](https://pypi.org/project/dagster) (📥 190K / month): ``` - pip install rq + pip install dagster ``` -- [Conda](https://anaconda.org/conda-forge/rq) (📥 62K · ⏱️ 30.06.2021): +- [Conda](https://anaconda.org/conda-forge/dagster) (📥 420K · ⏱️ 10.12.2021): ``` - conda install -c conda-forge rq + conda install -c conda-forge dagster ```
-
Prefect (🥇31 · ⭐ 7.5K) - 自动化数据的最简单方法。Apache-2 +
Airflow (🥇29 · ⭐ 24K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 -- [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 250 · 🔀 690 · 📦 460 · 📋 1.9K - 19% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/apache/airflow) (👨‍💻 2.2K · 🔀 9.4K · 📥 220K · 📋 4.6K - 17% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/PrefectHQ/prefect + git clone https://github.com/apache/airflow ``` -- [PyPi](https://pypi.org/project/prefect) (📥 160K / month): +- [PyPi](https://pypi.org/project/apache-airflow) (📥 4.3M / month): ``` - pip install prefect + pip install apache-airflow ``` -- [Conda](https://anaconda.org/conda-forge/prefect) (📥 210K · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/airflow) (📥 510K · ⏱️ 15.11.2021): ``` - conda install -c conda-forge prefect + conda install -c conda-forge airflow + ``` +- [Docker Hub](https://hub.docker.com/r/apache/airflow) (📥 55M · ⭐ 310 · ⏱️ 15.12.2021): + ``` + docker pull apache/airflow ```
-
Dagster (🥇31 · ⭐ 3.9K) - 用于机器学习，分析和ETL的数据协调器。Apache-2 +
Prefect (🥇29 · ⭐ 7.9K) - The easiest way to automate your data. Apache-2 -- [GitHub](https://github.com/dagster-io/dagster) (👨‍💻 160 · 🔀 440 · 📦 240 · 📋 3.3K - 22% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 280 · 🔀 730 · 📦 530 · 📋 2K - 18% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/dagster-io/dagster + git clone https://github.com/PrefectHQ/prefect ``` -- [PyPi](https://pypi.org/project/dagster) (📥 160K / month): +- [PyPi](https://pypi.org/project/prefect): ``` - pip install dagster + pip install prefect ``` -- [Conda](https://anaconda.org/conda-forge/dagster) (📥 380K · ⏱️ 07.10.2021): +- [Conda](https://anaconda.org/conda-forge/prefect) (📥 230K · ⏱️ 01.12.2021): ``` - conda install -c conda-forge dagster + conda install -c conda-forge prefect ```
-
dbt (🥇31 · ⭐ 3.6K) - 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 +
Beam (🥇29 · ⭐ 5.1K) - Unified programming model to define and execute data processing.. ❗Unlicensed -- [GitHub](https://github.com/dbt-labs/dbt) (👨‍💻 180 · 🔀 660 · 📦 420 · 📋 2.2K - 14% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/apache/beam) (👨‍💻 1.2K · 🔀 3.2K · ⏱️ 16.12.2021): ``` - git clone https://github.com/fishtown-analytics/dbt - ``` -- [PyPi](https://pypi.org/project/dbt) (📥 660K / month): - ``` - pip install dbt + git clone https://github.com/apache/beam ``` -- [Conda](https://anaconda.org/conda-forge/dbt) (📥 180K · ⏱️ 04.05.2021): +- [PyPi](https://pypi.org/project/apache-beam) (📥 3.8M / month): ``` - conda install -c conda-forge dbt + pip install apache-beam ```
-
joblib (🥇31 · ⭐ 2.6K) - 使用Python函数进行计算。BSD-3 +
luigi (🥈28 · ⭐ 15K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 -- [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 300 · 📦 130K · 📋 660 - 43% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/spotify/luigi) (👨‍💻 570 · 🔀 2.2K · 📦 1.6K · 📋 920 - 7% open · ⏱️ 27.11.2021): ``` - git clone https://github.com/joblib/joblib + git clone https://github.com/spotify/luigi ``` -- [PyPi](https://pypi.org/project/joblib): +- [PyPi](https://pypi.org/project/luigi): ``` - pip install joblib + pip install luigi ``` -- [Conda](https://anaconda.org/conda-forge/joblib) (📥 5.5M · ⏱️ 07.10.2021): +- [Conda](https://anaconda.org/anaconda/luigi) (📥 8.5K · ⏱️ 17.04.2021): ``` - conda install -c conda-forge joblib + conda install -c anaconda luigi ```
-
Airflow (🥈28 · ⭐ 24K) - 代码实现的创建，安排和监视工作流的平台。Apache-2 +
rq (🥈28 · ⭐ 8.1K) - Simple job queues for Python. ❗Unlicensed -- [GitHub](https://github.com/apache/airflow) (👨‍💻 2.1K · 🔀 9K · 📥 190K · 📋 4.2K - 18% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/rq/rq) (👨‍💻 250 · 🔀 1.2K · 📦 9.2K · 📋 930 - 16% open · ⏱️ 11.12.2021): ``` - git clone https://github.com/apache/airflow - ``` -- [PyPi](https://pypi.org/project/apache-airflow) (📥 2.4M / month): - ``` - pip install apache-airflow + git clone https://github.com/rq/rq ``` -- [Conda](https://anaconda.org/conda-forge/airflow) (📥 410K · ⏱️ 12.10.2021): +- [PyPi](https://pypi.org/project/rq): ``` - conda install -c conda-forge airflow + pip install rq ``` -- [Docker Hub](https://hub.docker.com/r/apache/airflow) (📥 44M · ⭐ 290 · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/rq) (📥 66K · ⏱️ 30.06.2021): ``` - docker pull apache/airflow + conda install -c conda-forge rq ```
-
Beam (🥈28 · ⭐ 5K) - 统一的编程模型，用于定义和执行数据处理。❗Unlicensed +
dbt (🥈28 · ⭐ 3.9K) - dbt (data build tool) enables data analysts and engineers to transform.. Apache-2 -- [GitHub](https://github.com/apache/beam) (👨‍💻 1.1K · 🔀 3.1K · ⏱️ 13.10.2021): +- [GitHub](https://github.com/dbt-labs/dbt-core) (👨‍💻 190 · 🔀 700 · 📥 21 · 📦 230 · 📋 2.4K - 11% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/apache/beam + git clone https://github.com/fishtown-analytics/dbt ``` -- [PyPi](https://pypi.org/project/apache-beam) (📥 2.8M / month): +- [PyPi](https://pypi.org/project/dbt): ``` - pip install apache-beam + pip install dbt + ``` +- [Conda](https://anaconda.org/conda-forge/dbt) (📥 190K · ⏱️ 09.12.2021): + ``` + conda install -c conda-forge dbt ```
-
Kedro (🥈27 · ⭐ 4.5K) - 用于创建可重现，可维护和模块化的Python框架。❗Unlicensed +
mrjob (🥈27 · ⭐ 2.6K · 💀) - Run MapReduce jobs on Hadoop or Amazon Web Services. Apache-2 -- [GitHub](https://github.com/quantumblacklabs/kedro) (👨‍💻 120 · 🔀 500 · 📦 570 · 📋 540 - 7% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 570 · 📦 900 · 📋 1.3K - 15% open · ⏱️ 16.11.2020): ``` - git clone https://github.com/quantumblacklabs/kedro + git clone https://github.com/Yelp/mrjob ``` -- [PyPi](https://pypi.org/project/kedro) (📥 210K / month): +- [PyPi](https://pypi.org/project/mrjob): ``` - pip install kedro + pip install mrjob + ``` +- [Conda](https://anaconda.org/conda-forge/mrjob) (📥 420K · ⏱️ 24.12.2020): + ``` + conda install -c conda-forge mrjob ```
-
Hub (🥈27 · ⭐ 3.6K) - TensorFlow/PyTorch最快的非结构化数据集管理。MPL-2.0 +
petl (🥈27 · ⭐ 950) - Python Extract Transform and Load Tables of Data. MIT -- [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 85 · 🔀 290 · 📦 130 · 📋 300 - 13% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/petl-developers/petl) (👨‍💻 51 · 🔀 160 · 📦 580 · 📋 420 - 17% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/activeloopai/Hub + git clone https://github.com/petl-developers/petl ``` -- [PyPi](https://pypi.org/project/hub) (📥 17K / month): +- [PyPi](https://pypi.org/project/petl) (📥 46K / month): ``` - pip install hub + pip install petl + ``` +- [Conda](https://anaconda.org/conda-forge/petl) (📥 54K · ⏱️ 05.04.2021): + ``` + conda install -c conda-forge petl ```
-
mrjob (🥈27 · ⭐ 2.6K · 💤) - 在Hadoop或Amazon Web Services上运行MapReduce作业。Apache-2 +
faust (🥈26 · ⭐ 5.9K · 💀) - Python Stream Processing. ❗Unlicensed -- [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 570 · 📦 850 · 📋 1.3K - 15% open · ⏱️ 16.11.2020): +- [GitHub](https://github.com/robinhood/faust) (👨‍💻 93 · 🔀 490 · 📦 900 · 📋 460 - 48% open · ⏱️ 09.10.2020): ``` - git clone https://github.com/Yelp/mrjob - ``` -- [PyPi](https://pypi.org/project/mrjob) (📥 100K / month): - ``` - pip install mrjob + git clone https://github.com/robinhood/faust ``` -- [Conda](https://anaconda.org/conda-forge/mrjob) (📥 400K · ⏱️ 24.12.2020): +- [PyPi](https://pypi.org/project/faust) (📥 420K / month): ``` - conda install -c conda-forge mrjob + pip install faust ```
-
faust (🥈26 · ⭐ 5.8K · 💤) - Python流处理。❗Unlicensed +
Kedro (🥈26 · ⭐ 4.8K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 -- [GitHub](https://github.com/robinhood/faust) (👨‍💻 91 · 🔀 480 · 📦 860 · 📋 450 - 47% open · ⏱️ 09.10.2020): +- [GitHub](https://github.com/quantumblacklabs/kedro) (👨‍💻 130 · 🔀 530 · 📦 640 · 📋 590 - 7% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/robinhood/faust + git clone https://github.com/quantumblacklabs/kedro ``` -- [PyPi](https://pypi.org/project/faust) (📥 510K / month): +- [PyPi](https://pypi.org/project/kedro) (📥 230K / month): ``` - pip install faust + pip install kedro ```
-
PyFunctional (🥈26 · ⭐ 1.9K) - 用于创建具有链功能的数据管道的Python库。MIT +
Hub (🥈26 · ⭐ 4K) - Fastest unstructured dataset management for TensorFlow/PyTorch... MPL-2.0 -- [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 24 · 🔀 100 · 📦 340 · 📋 120 - 2% open · ⏱️ 06.07.2021): +- [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 88 · 🔀 320 · 📦 140 · 📋 310 - 14% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/EntilZha/PyFunctional + git clone https://github.com/activeloopai/Hub ``` -- [PyPi](https://pypi.org/project/pyfunctional) (📥 74K / month): +- [PyPi](https://pypi.org/project/hub) (📥 2.2K / month): ``` - pip install pyfunctional + pip install hub ```
-
TFX (🥈26 · ⭐ 1.6K) - TFX是用于部署机器学习生产流水线的端到端平台。Apache-2 +
Great Expectations (🥈24 · ⭐ 5.8K) - Always know what to expect from your data. Apache-2 -- [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 120 · 🔀 480 · 📋 680 - 33% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 250 · 🔀 780 · 📋 1.1K - 11% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/tensorflow/tfx + git clone https://github.com/great-expectations/great_expectations ``` -- [PyPi](https://pypi.org/project/tfx) (📥 780K / month): +- [PyPi](https://pypi.org/project/great_expectations) (📥 2.6M / month): ``` - pip install tfx + pip install great_expectations ```
-
petl (🥈26 · ⭐ 930) - Python提取转换并加载数据表。MIT +
TaskTiger (🥉22 · ⭐ 1.1K) - Python task queue using Redis. MIT -- [GitHub](https://github.com/petl-developers/petl) (👨‍💻 49 · 🔀 160 · 📦 520 · 📋 420 - 17% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 24 · 🔀 59 · 📦 21 · 📋 57 - 38% open · ⏱️ 02.12.2021): ``` - git clone https://github.com/petl-developers/petl - ``` -- [PyPi](https://pypi.org/project/petl) (📥 35K / month): - ``` - pip install petl + git clone https://github.com/closeio/tasktiger ``` -- [Conda](https://anaconda.org/conda-forge/petl) (📥 31K · ⏱️ 05.04.2021): +- [PyPi](https://pypi.org/project/tasktiger) (📥 2.2K / month): ``` - conda install -c conda-forge petl + pip install tasktiger ```
-
Great Expectations (🥉24 · ⭐ 5.5K) - 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 +
PyFunctional (🥉21 · ⭐ 1.9K) - Python library for creating data pipelines with chain functional.. MIT -- [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 230 · 🔀 720 · 📋 1K - 13% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 25 · 🔀 100 · 📦 370 · 📋 120 - 4% open · ⏱️ 05.11.2021): ``` - git clone https://github.com/great-expectations/great_expectations + git clone https://github.com/EntilZha/PyFunctional ``` -- [PyPi](https://pypi.org/project/great_expectations) (📥 1.8M / month): +- [PyPi](https://pypi.org/project/pyfunctional): ``` - pip install great_expectations + pip install pyfunctional ```
-
bonobo (🥉21 · ⭐ 1.5K · 💤) - 提取适用于Python 3.5+的Transform Load。Apache-2 +
bonobo (🥉21 · ⭐ 1.5K · 💤) - Extract Transform Load for Python 3.5+. Apache-2 -- [GitHub](https://github.com/python-bonobo/bonobo) (👨‍💻 37 · 🔀 120 · 📦 120 · 📋 180 - 38% open · ⏱️ 10.03.2021): +- [GitHub](https://github.com/python-bonobo/bonobo) (👨‍💻 37 · 🔀 120 · 📦 130 · 📋 180 - 38% open · ⏱️ 10.03.2021): ``` git clone https://github.com/python-bonobo/bonobo ``` -- [PyPi](https://pypi.org/project/bonobo) (📥 3.7K / month): +- [PyPi](https://pypi.org/project/bonobo) (📥 4.3K / month): ``` pip install bonobo ```
-
streamparse (🥉21 · ⭐ 1.4K · 💤) - 在Apache Storm拓扑中运行Python。 Pythonic API，CLI 等。❗Unlicensed +
streamparse (🥉21 · ⭐ 1.4K · 💤) - Run Python in Apache Storm topologies. Pythonic API,.. ❗Unlicensed -- [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 41 · 🔀 210 · 📦 50 · 📋 320 - 19% open · ⏱️ 18.12.2020): +- [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 41 · 🔀 210 · 📦 52 · 📋 320 - 19% open · ⏱️ 18.12.2020): ``` git clone https://github.com/Parsely/streamparse ``` -- [PyPi](https://pypi.org/project/streamparse) (📥 3.5K / month): +- [PyPi](https://pypi.org/project/streamparse) (📥 5.6K / month): ``` pip install streamparse ```
-
pysparkling (🥉21 · ⭐ 240 · 💤) - Apache Spark的RDD和DStream的纯Python实现。❗Unlicensed +
pysparkling (🥉21 · ⭐ 240 · 💤) - A pure Python implementation of Apache Spark's RDD and.. ❗Unlicensed -- [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 39 · 📦 72 · 📋 27 - 22% open · ⏱️ 22.02.2021): +- [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 41 · 📦 81 · 📋 27 - 22% open · ⏱️ 22.02.2021): ``` git clone https://github.com/svenkreiss/pysparkling @@ -6301,101 +6313,89 @@ _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 pysparkling ```
-
dpark (🥉20 · ⭐ 2.7K · 💤) - dpark是Python中与MapReduce相似的框架。BSD-3 +
dpark (🥉20 · ⭐ 2.7K · 💤) - Python clone of Spark, a MapReduce alike framework in Python. BSD-3 -- [GitHub](https://github.com/douban/dpark) (👨‍💻 35 · 🔀 540 · 📦 3 · ⏱️ 25.12.2020): +- [GitHub](https://github.com/douban/dpark) (👨‍💻 35 · 🔀 540 · 📦 4 · ⏱️ 25.12.2020): ``` git clone https://github.com/douban/dpark ``` -- [PyPi](https://pypi.org/project/dpark) (📥 91 / month): +- [PyPi](https://pypi.org/project/dpark) (📥 82 / month): ``` pip install dpark ```
-
TaskTiger (🥉20 · ⭐ 1.1K) - 使用Redis的Python任务队列。MIT - -- [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 23 · 🔀 59 · 📦 20 · 📋 57 - 38% open · ⏱️ 07.10.2021): - - ``` - git clone https://github.com/closeio/tasktiger - ``` -- [PyPi](https://pypi.org/project/tasktiger) (📥 4.3K / month): - ``` - pip install tasktiger - ``` -
-
Pypeline (🥉19 · ⭐ 1.3K) - Python中的并发数据管道。MIT +
TFX (🥉20 · ⭐ 1.7K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 -- [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 10 · 🔀 74 · 📋 52 - 26% open · ⏱️ 13.04.2021): +- [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 120 · 🔀 510 · 📋 710 - 32% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/cgarciae/pypeln + git clone https://github.com/tensorflow/tfx ``` -- [PyPi](https://pypi.org/project/pypeln) (📥 9.6K / month): +- [PyPi](https://pypi.org/project/tfx): ``` - pip install pypeln + pip install tfx ```
-
mrq (🥉19 · ⭐ 850 · 💤) - Mr. Queue - 使用Redis和gevent的Python中的分布式worker任务队列。MIT +
mrq (🥉20 · ⭐ 860 · 💤) - Mr. Queue - A distributed worker task queue in Python using Redis & gevent. MIT -- [GitHub](https://github.com/pricingassistant/mrq) (👨‍💻 37 · 🔀 110 · 📦 25 · 📋 170 - 30% open · ⏱️ 13.12.2020): +- [GitHub](https://github.com/pricingassistant/mrq) (👨‍💻 37 · 🔀 110 · 📦 27 · 📋 170 - 30% open · ⏱️ 13.12.2020): ``` git clone https://github.com/pricingassistant/mrq ``` -- [PyPi](https://pypi.org/project/mrq) (📥 380 / month): +- [PyPi](https://pypi.org/project/mrq) (📥 260 / month): ``` pip install mrq ```
-
pdpipe (🥉19 · ⭐ 620) - pandas DataFrames的简单管道。❗Unlicensed +
ploomber (🥉20 · ⭐ 790) - Lean Data Science workflows: develop and test locally. Deploy to.. Apache-2 -- [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 8 · 🔀 28 · 📦 36 · 📋 24 - 33% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 23 · 🔀 64 · 📦 22 · 📋 400 - 19% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/pdpipe/pdpipe + git clone https://github.com/ploomber/ploomber ``` -- [PyPi](https://pypi.org/project/pdpipe) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/ploomber) (📥 2.7K / month): ``` - pip install pdpipe + pip install ploomber ```
-
spark-deep-learning (🥉18 · ⭐ 1.9K) - 适用于Apache Spark的深度学习管道。Apache-2 +
zenml (🥉18 · ⭐ 1.5K) - ZenML : MLOps framework to create reproducible ML pipelines for.. Apache-2 -- [GitHub](https://github.com/databricks/spark-deep-learning) (👨‍💻 16 · 🔀 460 · 📦 18 · 📋 100 - 73% open · ⏱️ 19.08.2021): +- [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 21 · 🔀 83 · 📋 49 - 8% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/databricks/spark-deep-learning + git clone https://github.com/maiot-io/zenml + ``` +- [PyPi](https://pypi.org/project/zenml) (📥 460 / 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 +
Optimus (🥉18 · ⭐ 1.1K) - Agile Data Preparation Workflows madeeasy with pandas, dask,.. Apache-2 -- [GitHub](https://github.com/hi-primus/optimus) (👨‍💻 23 · 🔀 200 · 📋 220 - 15% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/hi-primus/optimus) (👨‍💻 23 · 🔀 200 · 📋 220 - 13% open · ⏱️ 09.12.2021): ``` git clone https://github.com/ironmussa/Optimus ``` -- [PyPi](https://pypi.org/project/optimuspyspark) (📥 7.6K / month): +- [PyPi](https://pypi.org/project/optimuspyspark) (📥 7.4K / month): ``` pip install optimuspyspark ```
-
ploomber (🥉18 · ⭐ 600) - 精益数据科学工作流程。Apache-2 +
spark-deep-learning (🥉17 · ⭐ 1.9K) - Deep Learning Pipelines for Apache Spark. Apache-2 -- [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 10 · 🔀 20 · 📦 14 · 📋 340 - 15% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/databricks/spark-deep-learning) (👨‍💻 16 · 🔀 460 · 📦 19 · 📋 100 - 73% open · ⏱️ 19.08.2021): ``` - git clone https://github.com/ploomber/ploomber - ``` -- [PyPi](https://pypi.org/project/ploomber) (📥 3.1K / month): - ``` - pip install ploomber + git clone https://github.com/databricks/spark-deep-learning ```
-
BatchFlow (🥉18 · ⭐ 160) - 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 +
BatchFlow (🥉17 · ⭐ 170) - BatchFlow helps you conveniently work with random or sequential.. Apache-2 -- [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 30 · 🔀 37 · 📋 100 - 33% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 30 · 🔀 37 · 📋 100 - 33% open · ⏱️ 14.12.2021): ``` git clone https://github.com/analysiscenter/batchflow @@ -6405,81 +6405,81 @@ _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 batchflow ```
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Mara Pipelines (🥉17 · ⭐ 1.8K) - 一个轻量级的ETL框架。MIT +
Mara Pipelines (🥉16 · ⭐ 1.8K) - A lightweight opinionated ETL framework, halfway between plain.. MIT -- [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 16 · 🔀 84 · 📦 7 · 📋 18 - 33% open · ⏱️ 18.09.2021): +- [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 16 · 🔀 85 · 📦 8 · 📋 18 - 33% open · ⏱️ 18.09.2021): ``` git clone https://github.com/mara/mara-pipelines ``` -- [PyPi](https://pypi.org/project/mara-pipelines) (📥 69 / month): +- [PyPi](https://pypi.org/project/mara-pipelines): ``` pip install mara-pipelines ```
-
zenml (🥉17 · ⭐ 1.3K) - ZenML：MLOps框架。Apache-2 +
riko (🥉16 · ⭐ 1.6K · 💀) - A Python stream processing engine modeled after Yahoo! Pipes. MIT -- [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 17 · 🔀 72 · 📋 47 - 10% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 67 · 📋 29 - 72% open · ⏱️ 14.08.2020): ``` - git clone https://github.com/maiot-io/zenml + git clone https://github.com/nerevu/riko ``` -- [PyPi](https://pypi.org/project/zenml) (📥 680 / month): +- [PyPi](https://pypi.org/project/riko) (📥 270 / month): ``` - pip install zenml + pip install riko ```
-
Databolt Flow (🥉17 · ⭐ 930) - Python库，用于构建高效的数据科学工作流程。MIT +
pdpipe (🥉16 · ⭐ 630) - Easy pipelines for pandas DataFrames. ❗Unlicensed -- [GitHub](https://github.com/d6t/d6tflow) (👨‍💻 12 · 🔀 68 · 📦 16 · 📋 22 - 40% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 9 · 🔀 29 · 📦 38 · 📋 38 - 39% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/d6t/d6tflow + git clone https://github.com/pdpipe/pdpipe ``` -- [PyPi](https://pypi.org/project/d6tflow) (📥 300 / month): +- [PyPi](https://pypi.org/project/pdpipe): ``` - pip install d6tflow + pip install pdpipe ```
-
riko (🥉16 · ⭐ 1.6K · 💀) - 一个模仿Yahoo!的Python流处理引擎。MIT +
Pypeline (🥉15 · ⭐ 1.3K · 💤) - Concurrent data pipelines in Python . MIT -- [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 66 · 📋 29 - 72% open · ⏱️ 14.08.2020): +- [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 10 · 🔀 73 · 📋 52 - 26% open · ⏱️ 13.04.2021): ``` - git clone https://github.com/nerevu/riko + git clone https://github.com/cgarciae/pypeln ``` -- [PyPi](https://pypi.org/project/riko) (📥 250 / month): +- [PyPi](https://pypi.org/project/pypeln): ``` - pip install riko + pip install pypeln ```
-
flupy (🥉15 · ⭐ 160) - python中的流利数据管道。❗Unlicensed +
Databolt Flow (🥉15 · ⭐ 940) - Python library for building highly effective data science workflows. MIT -- [GitHub](https://github.com/olirice/flupy) (👨‍💻 5 · 🔀 10 · 📋 8 - 12% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/d6t/d6tflow) (👨‍💻 12 · 🔀 68 · 📦 17 · 📋 22 - 40% open · ⏱️ 28.09.2021): ``` - git clone https://github.com/olirice/flupy + git clone https://github.com/d6t/d6tflow ``` -- [PyPi](https://pypi.org/project/flupy) (📥 85K / month): +- [PyPi](https://pypi.org/project/d6tflow): ``` - pip install flupy + pip install d6tflow ```
-
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 +
flupy (🥉14 · ⭐ 170) - Fluent data pipelines for python and your shell. ❗Unlicensed -- [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 99 · 📦 1 · 📋 4 - 50% open · ⏱️ 23.05.2019): +- [GitHub](https://github.com/olirice/flupy) (👨‍💻 6 · 🔀 12 · ⏱️ 05.11.2021): ``` - git clone https://github.com/kkyon/botflow + git clone https://github.com/olirice/flupy ``` -- [PyPi](https://pypi.org/project/botflow) (📥 40 / month): +- [PyPi](https://pypi.org/project/flupy) (📥 36K / month): ``` - pip install botflow + pip install flupy ```
-
bodywork-core (🥉12 · ⭐ 300) - MLOps工具，用于将机器学习项目部署到Kubernetes。❗️AGPL-3.0 +
bodywork-core (🥉12 · ⭐ 310) - MLOps tool for deploying machine learning projects to.. ❗️AGPL-3.0 -- [GitHub](https://github.com/bodywork-ml/bodywork-core) (👨‍💻 4 · 🔀 12 · 📦 7 · 📋 55 - 21% open · ⏱️ 05.07.2021): +- [GitHub](https://github.com/bodywork-ml/bodywork-core) (👨‍💻 4 · 🔀 14 · 📦 9 · 📋 55 - 21% open · ⏱️ 05.07.2021): ``` git clone https://github.com/bodywork-ml/bodywork-core @@ -6489,318 +6489,330 @@ _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 · 💀) - Python Fast Dataflow programming framework for Data pipeline.. ❗Unlicensed + +- [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 100 · 📦 1 · 📋 4 - 50% open · ⏱️ 23.05.2019): + + ``` + git clone https://github.com/kkyon/botflow + ``` +- [PyPi](https://pypi.org/project/botflow): + ``` + 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 · ⭐ 8.9K) - 具有任务调度的并行计算。BSD-3 +
dask (🥇32 · ⭐ 9.3K) - Parallel computing with task scheduling. BSD-3 -- [GitHub](https://github.com/dask/dask) (👨‍💻 480 · 🔀 1.3K · 📦 31K · 📋 3.9K - 16% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/dask/dask) (👨‍💻 490 · 🔀 1.4K · 📦 32K · 📋 4K - 16% open · ⏱️ 15.12.2021): ``` git clone https://github.com/dask/dask ``` -- [PyPi](https://pypi.org/project/dask) (📥 7.2M / month): +- [PyPi](https://pypi.org/project/dask) (📥 5.7M / month): ``` pip install dask ``` -- [Conda](https://anaconda.org/conda-forge/dask) (📥 4.3M · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/dask) (📥 4.7M · ⏱️ 11.12.2021): ``` conda install -c conda-forge dask ```
-
Ray (🥇29 · ⭐ 18K) - 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 +
Ray (🥇28 · ⭐ 19K) - An open source framework that provides a simple, universal API for.. Apache-2 -- [GitHub](https://github.com/ray-project/ray) (👨‍💻 570 · 🔀 2.9K · 📋 8K - 21% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/ray-project/ray) (👨‍💻 600 · 🔀 3K · 📦 3.5K · 📋 8.6K - 21% open · ⏱️ 16.12.2021): ``` git clone https://github.com/ray-project/ray ``` -- [PyPi](https://pypi.org/project/ray) (📥 570K / month): +- [PyPi](https://pypi.org/project/ray): ``` pip install ray ```
-
dask.distributed (🥇28 · ⭐ 1.3K) - Dask的分布式任务调度规划程序。❗Unlicensed +
dask.distributed (🥇28 · ⭐ 1.3K) - A distributed task scheduler for Dask. ❗Unlicensed -- [GitHub](https://github.com/dask/distributed) (👨‍💻 250 · 🔀 540 · 📦 20K · 📋 2.3K - 34% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/dask/distributed) (👨‍💻 260 · 🔀 560 · 📦 21K · 📋 2.4K - 29% open · ⏱️ 14.12.2021): ``` git clone https://github.com/dask/distributed ``` -- [PyPi](https://pypi.org/project/distributed) (📥 6.8M / month): +- [PyPi](https://pypi.org/project/distributed) (📥 7M / month): ``` pip install distributed ``` -- [Conda](https://anaconda.org/conda-forge/distributed) (📥 5.4M · ⏱️ 22.09.2021): +- [Conda](https://anaconda.org/conda-forge/distributed) (📥 5.9M · ⏱️ 11.12.2021): ``` conda install -c conda-forge distributed ```
-
Mesh (🥇28 · ⭐ 1.1K) - Mesh TensorFlow：简化模型并行化。Apache-2 +
DEAP (🥈27 · ⭐ 4.5K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 -- [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 44 · 🔀 180 · 📦 580 · 📋 74 - 81% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/DEAP/deap) (👨‍💻 76 · 🔀 920 · 📦 2.3K · 📋 430 - 42% open · ⏱️ 21.11.2021): ``` - git clone https://github.com/tensorflow/mesh + git clone https://github.com/deap/deap ``` -- [PyPi](https://pypi.org/project/mesh-tensorflow) (📥 450K / month): +- [PyPi](https://pypi.org/project/deap) (📥 190K / month): ``` - pip install mesh-tensorflow + pip install deap + ``` +- [Conda](https://anaconda.org/conda-forge/deap) (📥 160K · ⏱️ 07.11.2021): + ``` + conda install -c conda-forge deap ```
-
horovod (🥈27 · ⭐ 12K) - 基于TensorFlow，Keras，PyTorch，MXNet等的分布式训练框架。❗Unlicensed +
Mesh (🥈27 · ⭐ 1.2K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 -- [GitHub](https://github.com/horovod/horovod) (👨‍💻 140 · 🔀 1.9K · 📦 440 · 📋 1.9K - 13% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 44 · 🔀 200 · 📦 610 · 📋 75 - 81% open · ⏱️ 18.10.2021): ``` - git clone https://github.com/horovod/horovod + git clone https://github.com/tensorflow/mesh ``` -- [PyPi](https://pypi.org/project/horovod) (📥 48K / month): +- [PyPi](https://pypi.org/project/mesh-tensorflow) (📥 400K / month): ``` - pip install horovod + pip install mesh-tensorflow ```
-
DEAP (🥈27 · ⭐ 4.4K) - Python中的分布式进化算法。❗️LGPL-3.0 +
BigDL (🥈26 · ⭐ 3.8K) - BigDL: Distributed Deep Learning Framework for Apache Spark. Apache-2 -- [GitHub](https://github.com/DEAP/deap) (👨‍💻 68 · 🔀 910 · 📦 2.1K · 📋 420 - 45% open · ⏱️ 08.05.2021): +- [GitHub](https://github.com/intel-analytics/BigDL) (👨‍💻 130 · 🔀 890 · 📦 31 · 📋 1K - 25% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/deap/deap + git clone https://github.com/intel-analytics/BigDL ``` -- [PyPi](https://pypi.org/project/deap) (📥 180K / month): +- [PyPi](https://pypi.org/project/bigdl) (📥 16K / month): ``` - pip install deap + pip install bigdl ``` -- [Conda](https://anaconda.org/conda-forge/deap) (📥 150K · ⏱️ 01.08.2021): +- [Maven](https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4): ``` - conda install -c conda-forge deap + + com.intel.analytics.bigdl + bigdl-SPARK_2.4 + [VERSION] + ```
-
Elephas (🥈27 · ⭐ 1.5K) - 使用Keras和Spark进行分布式深度学习。MIT keras +
analytics-zoo (🥈25 · ⭐ 2.4K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 -- [GitHub](https://github.com/maxpumperla/elephas) (👨‍💻 27 · 🔀 290 · 📦 47 · 📋 150 - 15% open · ⏱️ 17.08.2021): +- [GitHub](https://github.com/intel-analytics/analytics-zoo) (👨‍💻 100 · 🔀 690 · 📦 3 · 📋 1.3K - 33% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/maxpumperla/elephas + git clone https://github.com/intel-analytics/analytics-zoo ``` -- [PyPi](https://pypi.org/project/elephas) (📥 63K / month): +- [PyPi](https://pypi.org/project/analytics-zoo) (📥 13K / month): ``` - pip install elephas + pip install analytics-zoo ```
-
petastorm (🥈27 · ⭐ 1.2K) - Petastorm库单机或分布式训练。Apache-2 +
horovod (🥈24 · ⭐ 12K) - Distributed training framework for TensorFlow, Keras, PyTorch,.. ❗Unlicensed -- [GitHub](https://github.com/uber/petastorm) (👨‍💻 41 · 🔀 210 · 📥 310 · 📦 43 · 📋 250 - 48% open · ⏱️ 03.09.2021): +- [GitHub](https://github.com/horovod/horovod) (👨‍💻 140 · 🔀 1.9K · 📦 480 · 📋 1.9K - 13% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/uber/petastorm + git clone https://github.com/horovod/horovod ``` -- [PyPi](https://pypi.org/project/petastorm) (📥 150K / month): +- [PyPi](https://pypi.org/project/horovod): ``` - pip install petastorm + pip install horovod ```
-
DeepSpeed (🥈26 · ⭐ 5.7K) - DeepSpeed是一个深度学习优化库。MIT +
DeepSpeed (🥈24 · ⭐ 6K) - DeepSpeed is a deep learning optimization library that makes.. MIT -- [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 71 · 🔀 600 · 📦 100 · 📋 640 - 48% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 86 · 🔀 640 · 📦 130 · 📋 720 - 47% open · ⏱️ 15.12.2021): ``` git clone https://github.com/microsoft/DeepSpeed ``` -- [PyPi](https://pypi.org/project/deepspeed) (📥 45K / month): +- [PyPi](https://pypi.org/project/deepspeed): ``` pip install deepspeed ``` -- [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (📥 11K · ⭐ 3 · ⏱️ 05.05.2021): +- [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (📥 12K · ⭐ 3 · ⏱️ 05.05.2021): ``` docker pull deepspeed/deepspeed ```
-
BigDL (🥈25 · ⭐ 3.8K) - BigDL：适用于Apache Spark的分布式深度学习框架。Apache-2 +
MMLSpark (🥈23 · ⭐ 2.9K) - Microsoft Machine Learning for Apache Spark. MIT -- [GitHub](https://github.com/intel-analytics/BigDL) (👨‍💻 74 · 🔀 870 · 📦 27 · 📋 890 - 18% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 78 · 🔀 590 · 📋 480 - 40% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/intel-analytics/BigDL - ``` -- [PyPi](https://pypi.org/project/bigdl) (📥 2.8K / month): - ``` - pip install bigdl + git clone https://github.com/Azure/mmlspark ``` -- [Maven](https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4): +- [PyPi](https://pypi.org/project/mmlspark) (📥 53K / month): ``` - - com.intel.analytics.bigdl - bigdl-SPARK_2.4 - [VERSION] - + pip install mmlspark ```
-
TensorFlowOnSpark (🥈23 · ⭐ 3.7K) - TensorFlowOnSpark将TensorFlow程序引入Spark。Apache-2 +
dask-ml (🥈23 · ⭐ 770) - Scalable Machine Learning with Dask. BSD-3 -- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 33 · 🔀 920 · 📋 360 - 1% open · ⏱️ 07.07.2021): +- [GitHub](https://github.com/dask/dask-ml) (👨‍💻 69 · 🔀 210 · 📦 530 · 📋 420 - 44% open · ⏱️ 30.11.2021): ``` - git clone https://github.com/yahoo/TensorFlowOnSpark + git clone https://github.com/dask/dask-ml ``` -- [PyPi](https://pypi.org/project/tensorflowonspark) (📥 250K / month): +- [PyPi](https://pypi.org/project/dask-ml): ``` - pip install tensorflowonspark + pip install dask-ml + ``` +- [Conda](https://anaconda.org/conda-forge/dask-ml) (📥 260K · ⏱️ 30.11.2021): + ``` + conda install -c conda-forge dask-ml ```
-
MMLSpark (🥈23 · ⭐ 2.4K) - 适用于Apache Spark的Microsoft机器学习。MIT +
Elephas (🥉22 · ⭐ 1.5K) - Distributed Deep learning with Keras & Spark. MIT keras -- [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 70 · 🔀 550 · 📋 440 - 42% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/maxpumperla/elephas) (👨‍💻 27 · 🔀 290 · 📦 51 · 📋 150 - 10% open · ⏱️ 17.08.2021): ``` - git clone https://github.com/Azure/mmlspark + git clone https://github.com/maxpumperla/elephas ``` -- [PyPi](https://pypi.org/project/mmlspark) (📥 38K / month): +- [PyPi](https://pypi.org/project/elephas): ``` - pip install mmlspark + pip install elephas ```
-
FairScale (🥈23 · ⭐ 1.4K) - PyTorch扩展用于高性能和大规模训练。BSD-3 +
petastorm (🥉22 · ⭐ 1.3K) - Petastorm library enables single machine or distributed training.. Apache-2 -- [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 44 · 🔀 120 · 📦 86 · 📋 220 - 22% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/uber/petastorm) (👨‍💻 43 · 🔀 220 · 📥 310 · 📦 53 · 📋 260 - 49% open · ⏱️ 27.10.2021): ``` - git clone https://github.com/facebookresearch/fairscale + git clone https://github.com/uber/petastorm ``` -- [PyPi](https://pypi.org/project/fairscale) (📥 44K / month): +- [PyPi](https://pypi.org/project/petastorm): ``` - pip install fairscale + pip install petastorm ```
-
ipyparallel (🥉22 · ⭐ 2.1K) - Python中的交互式并行计算。❗Unlicensed +
ipyparallel (🥉21 · ⭐ 2.1K) - Interactive Parallel Computing in Python. ❗Unlicensed -- [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 100 · 🔀 800 · 📦 1.7K · 📋 300 - 16% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 100 · 🔀 810 · 📦 1.8K · 📋 310 - 15% open · ⏱️ 08.12.2021): ``` git clone https://github.com/ipython/ipyparallel ``` -- [PyPi](https://pypi.org/project/ipyparallel) (📥 47K / month): +- [PyPi](https://pypi.org/project/ipyparallel): ``` pip install ipyparallel ``` -- [Conda](https://anaconda.org/conda-forge/ipyparallel) (📥 510K · ⏱️ 30.09.2021): +- [Conda](https://anaconda.org/conda-forge/ipyparallel) (📥 540K · ⏱️ 02.12.2021): ``` conda install -c conda-forge ipyparallel ```
-
dask-ml (🥉22 · ⭐ 750) - 使用Dask进行可扩展的机器学习。BSD-3 +
mpi4py (🥉21 · ⭐ 480) - Python bindings for MPI. BSD-2 -- [GitHub](https://github.com/dask/dask-ml) (👨‍💻 67 · 🔀 200 · 📦 480 · 📋 410 - 44% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 20 · 🔀 74 · 📥 2.7K · 📋 54 - 24% open · ⏱️ 25.11.2021): ``` - git clone https://github.com/dask/dask-ml + git clone https://github.com/mpi4py/mpi4py ``` -- [PyPi](https://pypi.org/project/dask-ml) (📥 37K / month): +- [PyPi](https://pypi.org/project/mpi4py): ``` - pip install dask-ml + pip install mpi4py ``` -- [Conda](https://anaconda.org/conda-forge/dask-ml) (📥 240K · ⏱️ 03.05.2021): +- [Conda](https://anaconda.org/conda-forge/mpi4py) (📥 860K · ⏱️ 25.11.2021): ``` - conda install -c conda-forge dask-ml + conda install -c conda-forge mpi4py ```
-
analytics-zoo (🥉20 · ⭐ 2.4K) - Apache上的分布式Tensorflow，Keras和PyTorch。Apache-2 +
Apache Singa (🥉19 · ⭐ 2.4K) - a distributed deep learning platform. Apache-2 -- [GitHub](https://github.com/intel-analytics/analytics-zoo) (👨‍💻 100 · 🔀 680 · 📦 2 · 📋 1.2K - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/apache/singa) (👨‍💻 76 · 🔀 720 · 📦 1 · 📋 67 - 26% open · ⏱️ 10.08.2021): ``` - git clone https://github.com/intel-analytics/analytics-zoo + git clone https://github.com/apache/singa ``` -- [PyPi](https://pypi.org/project/analytics-zoo): +- [Conda](https://anaconda.org/nusdbsystem/singa) (📥 390 · ⏱️ 09.08.2021): ``` - pip install analytics-zoo + conda install -c nusdbsystem singa + ``` +- [Docker Hub](https://hub.docker.com/r/apache/singa) (📥 210 · ⭐ 4 · ⏱️ 04.06.2019): + ``` + docker pull apache/singa ```
-
TensorFrames (🥉20 · ⭐ 760 · 💀) - 用于DataFrames的Tensorflow包装器。Apache-2 +
FairScale (🥉19 · ⭐ 1.5K) - PyTorch extensions for high performance and large scale training. BSD-3 -- [GitHub](https://github.com/databricks/tensorframes) (👨‍💻 16 · 🔀 160 · 📋 91 - 52% open · ⏱️ 15.11.2019): +- [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 51 · 🔀 140 · 📦 120 · 📋 250 - 21% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/databricks/tensorframes + git clone https://github.com/facebookresearch/fairscale ``` -- [PyPi](https://pypi.org/project/tensorframes) (📥 20K / month): +- [PyPi](https://pypi.org/project/fairscale): ``` - pip install tensorframes + pip install fairscale ```
-
Submit it (🥉20 · ⭐ 480) - 用于将作业提交到Slurm的Python工具箱。MIT +
TensorFrames (🥉19 · ⭐ 760 · 💀) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. Apache-2 -- [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 16 · 🔀 40 · 📦 240 · 📋 46 - 39% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/databricks/tensorframes) (👨‍💻 16 · 🔀 160 · 📋 91 - 52% open · ⏱️ 15.11.2019): ``` - git clone https://github.com/facebookincubator/submitit - ``` -- [PyPi](https://pypi.org/project/submitit) (📥 6.8K / month): - ``` - pip install submitit + git clone https://github.com/databricks/tensorframes ``` -- [Conda](https://anaconda.org/conda-forge/submitit) (📥 4.5K · ⏱️ 10.02.2021): +- [PyPi](https://pypi.org/project/tensorframes) (📥 21K / month): ``` - conda install -c conda-forge submitit + pip install tensorframes ```
-
mpi4py (🥉20 · ⭐ 460) - MPI的Python接口。❗Unlicensed +
somoclu (🥉19 · ⭐ 230) - Massively parallel self-organizing maps: accelerate training on.. MIT -- [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 19 · 🔀 71 · 📥 1.9K · 📋 45 - 20% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 61 · 📥 1.5K · 📋 130 - 18% open · ⏱️ 31.10.2021): ``` - git clone https://github.com/mpi4py/mpi4py + git clone https://github.com/peterwittek/somoclu ``` -- [PyPi](https://pypi.org/project/mpi4py) (📥 120K / month): +- [PyPi](https://pypi.org/project/somoclu) (📥 2.1K / month): ``` - pip install mpi4py + pip install somoclu ``` -- [Conda](https://anaconda.org/conda-forge/mpi4py) (📥 790K · ⏱️ 15.08.2021): +- [Conda](https://anaconda.org/conda-forge/somoclu) (📥 57K · ⏱️ 15.11.2021): ``` - conda install -c conda-forge mpi4py + conda install -c conda-forge somoclu ```
-
Apache Singa (🥉19 · ⭐ 2.4K) - 分布式深度学习平台。Apache-2 +
TensorFlowOnSpark (🥉18 · ⭐ 3.7K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 -- [GitHub](https://github.com/apache/singa) (👨‍💻 76 · 🔀 670 · 📦 1 · 📋 62 - 25% open · ⏱️ 10.08.2021): +- [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 33 · 🔀 920 · 📋 360 - 1% open · ⏱️ 15.10.2021): ``` - git clone https://github.com/apache/singa - ``` -- [Conda](https://anaconda.org/nusdbsystem/singa) (📥 310 · ⏱️ 09.08.2021): - ``` - conda install -c nusdbsystem singa + git clone https://github.com/yahoo/TensorFlowOnSpark ``` -- [Docker Hub](https://hub.docker.com/r/apache/singa) (📥 200 · ⭐ 4 · ⏱️ 04.06.2019): +- [PyPi](https://pypi.org/project/tensorflowonspark): ``` - docker pull apache/singa + pip install tensorflowonspark ```
-
Hivemind (🥉18 · ⭐ 840) - PyTorch中的分布式深度学习。专为训练模型而设计。MIT +
Hivemind (🥉17 · ⭐ 880) - Decentralized deep learning in PyTorch. Built to train models on.. MIT -- [GitHub](https://github.com/learning-at-home/hivemind) (👨‍💻 17 · 🔀 48 · 📦 3 · 📋 100 - 39% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/learning-at-home/hivemind) (👨‍💻 19 · 🔀 57 · 📦 4 · 📋 110 - 34% open · ⏱️ 16.12.2021): ``` git clone https://github.com/learning-at-home/hivemind ``` -- [PyPi](https://pypi.org/project/hivemind) (📥 130 / month): +- [PyPi](https://pypi.org/project/hivemind): ``` pip install hivemind ```
-
BytePS (🥉17 · ⭐ 3K) - 分布式DNN训练的高性能通用框架。Apache-2 +
BytePS (🥉16 · ⭐ 3K) - A high performance and generic framework for distributed DNN training. Apache-2 -- [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 410 · 📋 240 - 37% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 420 · 📋 250 - 37% open · ⏱️ 12.10.2021): ``` git clone https://github.com/bytedance/byteps ``` -- [PyPi](https://pypi.org/project/byteps) (📥 220 / month): +- [PyPi](https://pypi.org/project/byteps): ``` pip install byteps ``` @@ -6809,209 +6821,209 @@ _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 docker pull bytepsimage/tensorflow ```
-
somoclu (🥉17 · ⭐ 230) - 大规模并行的自组织图：加速训练。MIT +
Fiber (🥉16 · ⭐ 950 · 💤) - Distributed Computing for AI Made Simple. Apache-2 -- [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 61 · 📥 1.5K · 📋 130 - 19% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 100 · 📦 30 · 📋 24 - 66% open · ⏱️ 15.03.2021): ``` - git clone https://github.com/peterwittek/somoclu - ``` -- [PyPi](https://pypi.org/project/somoclu) (📥 970 / month): - ``` - pip install somoclu + git clone https://github.com/uber/fiber ``` -- [Conda](https://anaconda.org/conda-forge/somoclu) (📥 55K · ⏱️ 13.10.2020): +- [PyPi](https://pypi.org/project/fiber) (📥 1.8K / month): ``` - conda install -c conda-forge somoclu + pip install fiber ```
-
Fiber (🥉16 · ⭐ 930 · 💤) - 简化了AI的分布式计算。Apache-2 +
Submit it (🥉15 · ⭐ 510) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT -- [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 100 · 📦 29 · 📋 24 - 66% open · ⏱️ 15.03.2021): +- [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 17 · 🔀 48 · 📋 53 - 41% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/uber/fiber + git clone https://github.com/facebookincubator/submitit ``` -- [PyPi](https://pypi.org/project/fiber) (📥 2.7K / month): +- [PyPi](https://pypi.org/project/submitit): ``` - pip install fiber + pip install submitit + ``` +- [Conda](https://anaconda.org/conda-forge/submitit) (📥 5.1K · ⏱️ 10.02.2021): + ``` + conda install -c conda-forge submitit ```
-
sk-dist (🥉16 · ⭐ 270) - PySpark中的分布式scikit学习元估计器。Apache-2 +
sk-dist (🥉12 · ⭐ 270) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 - [GitHub](https://github.com/Ibotta/sk-dist) (👨‍💻 7 · 🔀 46 · 📦 8 · 📋 17 - 41% open · ⏱️ 07.07.2021): ``` git clone https://github.com/Ibotta/sk-dist ``` -- [PyPi](https://pypi.org/project/sk-dist) (📥 14K / month): +- [PyPi](https://pypi.org/project/sk-dist): ``` pip install sk-dist ```
-
LazyCluster (🥉12 · ⭐ 44) - 分布式机器学习框架。Apache-2 +
LazyCluster (🥉10 · ⭐ 43) - Distributed machine learning made simple. Apache-2 - [GitHub](https://github.com/ml-tooling/lazycluster) (👨‍💻 2 · 🔀 8 · 📦 7 · ⏱️ 19.08.2021): ``` git clone https://github.com/ml-tooling/lazycluster ``` -- [PyPi](https://pypi.org/project/lazycluster) (📥 71 / month): +- [PyPi](https://pypi.org/project/lazycluster): ``` 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 · ⭐ 5.3K) - 超参数优化框架。MIT +
Optuna (🥇33 · ⭐ 5.7K) - A hyperparameter optimization framework. MIT -- [GitHub](https://github.com/optuna/optuna) (👨‍💻 150 · 🔀 570 · 📦 2K · 📋 940 - 12% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/optuna/optuna) (👨‍💻 170 · 🔀 620 · 📦 2.3K · 📋 1K - 11% open · ⏱️ 16.12.2021): ``` git clone https://github.com/optuna/optuna ``` -- [PyPi](https://pypi.org/project/optuna) (📥 840K / month): +- [PyPi](https://pypi.org/project/optuna) (📥 820K / month): ``` pip install optuna ``` -- [Conda](https://anaconda.org/conda-forge/optuna) (📥 43K · ⏱️ 04.10.2021): +- [Conda](https://anaconda.org/conda-forge/optuna) (📥 48K · ⏱️ 04.10.2021): ``` conda install -c conda-forge optuna ```
-
scikit-optimize (🥇31 · ⭐ 2.2K) - SMBO模型优化实现。BSD-3 +
scikit-optimize (🥇31 · ⭐ 2.3K) - Sequential model-based optimization with a `scipy.optimize`.. BSD-3 -- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 75 · 🔀 390 · 📦 2K · 📋 580 - 33% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 75 · 🔀 410 · 📦 2.2K · 📋 580 - 34% open · ⏱️ 12.10.2021): ``` git clone https://github.com/scikit-optimize/scikit-optimize ``` -- [PyPi](https://pypi.org/project/scikit-optimize) (📥 1M / month): +- [PyPi](https://pypi.org/project/scikit-optimize) (📥 500K / month): ``` pip install scikit-optimize ``` -- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (📥 440K · ⏱️ 04.09.2020): +- [Conda](https://anaconda.org/conda-forge/scikit-optimize) (📥 520K · ⏱️ 15.12.2021): ``` conda install -c conda-forge scikit-optimize ```
-
AutoKeras (🥇30 · ⭐ 8.2K) - 用于深度学习的AutoML库。Apache-2 +
Keras Tuner (🥇30 · ⭐ 2.4K · 📈) - Hyperparameter tuning for humans. Apache-2 -- [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 130 · 🔀 1.3K · 📥 790 · 📦 240 · 📋 780 - 6% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 41 · 🔀 310 · 📦 1K · 📋 360 - 45% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/keras-team/autokeras + git clone https://github.com/keras-team/keras-tuner ``` -- [PyPi](https://pypi.org/project/autokeras) (📥 30K / month): +- [PyPi](https://pypi.org/project/keras-tuner) (📥 970K / month): ``` - pip install autokeras + pip install keras-tuner ```
-
NNI (🥇29 · ⭐ 10K) - 一个开源AutoML工具箱，用于自动化机器学习生命周期。MIT +
Bayesian Optimization (🥇29 · ⭐ 5.6K · 💤) - A Python implementation of global optimization with.. MIT -- [GitHub](https://github.com/microsoft/nni) (👨‍💻 150 · 🔀 1.4K · 📦 150 · 📋 1.4K - 14% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 27 · 🔀 1.2K · 📥 70 · 📦 990 · 📋 220 - 20% open · ⏱️ 19.12.2020): ``` - git clone https://github.com/microsoft/nni + git clone https://github.com/fmfn/BayesianOptimization ``` -- [PyPi](https://pypi.org/project/nni) (📥 13K / month): +- [PyPi](https://pypi.org/project/bayesian-optimization) (📥 190K / month): ``` - pip install nni + pip install bayesian-optimization ```
-
Bayesian Optimization (🥇29 · ⭐ 5.4K · 💤) - 全局优化的Python实现。MIT +
Hyperopt (🥇28 · ⭐ 6K) - Distributed Asynchronous Hyperparameter Optimization in Python. ❗Unlicensed -- [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 27 · 🔀 1.2K · 📥 67 · 📦 900 · 📋 210 - 19% open · ⏱️ 19.12.2020): +- [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 93 · 🔀 810 · 📦 5.4K · 📋 590 - 60% open · ⏱️ 29.11.2021): ``` - git clone https://github.com/fmfn/BayesianOptimization + git clone https://github.com/hyperopt/hyperopt ``` -- [PyPi](https://pypi.org/project/bayesian-optimization) (📥 130K / month): +- [PyPi](https://pypi.org/project/hyperopt) (📥 1.9M / month): ``` - pip install bayesian-optimization + pip install hyperopt + ``` +- [Conda](https://anaconda.org/conda-forge/hyperopt) (📥 310K · ⏱️ 14.10.2020): + ``` + conda install -c conda-forge hyperopt ```
-
TPOT (🥈28 · ⭐ 8.3K · 💤) - Python自动化机器学习工具。❗️LGPL-3.0 +
featuretools (🥇28 · ⭐ 5.9K) - An open source python library for automated feature engineering. BSD-3 -- [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.4K · 📦 1.2K · 📋 830 - 27% open · ⏱️ 06.01.2021): +- [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 57 · 🔀 750 · 📦 890 · 📋 700 - 21% open · ⏱️ 12.12.2021): ``` - git clone https://github.com/EpistasisLab/tpot + git clone https://github.com/alteryx/featuretools ``` -- [PyPi](https://pypi.org/project/tpot) (📥 29K / month): +- [PyPi](https://pypi.org/project/featuretools) (📥 1.1M / month): ``` - pip install tpot + pip install featuretools ``` -- [Conda](https://anaconda.org/conda-forge/tpot) (📥 130K · ⏱️ 05.03.2021): +- [Conda](https://anaconda.org/conda-forge/featuretools) (📥 74K · ⏱️ 03.12.2021): ``` - conda install -c conda-forge tpot + conda install -c conda-forge featuretools ```
-
Hyperopt (🥈28 · ⭐ 5.9K) - Python中的分布式异步超参数优化。❗Unlicensed +
TPOT (🥈27 · ⭐ 8.4K · 💤) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 -- [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 90 · 🔀 790 · 📦 4.9K · 📋 580 - 60% open · ⏱️ 15.09.2021): +- [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.4K · 📦 1.2K · 📋 830 - 27% open · ⏱️ 06.01.2021): ``` - git clone https://github.com/hyperopt/hyperopt + git clone https://github.com/EpistasisLab/tpot ``` -- [PyPi](https://pypi.org/project/hyperopt) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/tpot): ``` - pip install hyperopt + pip install tpot ``` -- [Conda](https://anaconda.org/conda-forge/hyperopt) (📥 270K · ⏱️ 14.10.2020): +- [Conda](https://anaconda.org/conda-forge/tpot) (📥 140K · ⏱️ 05.03.2021): ``` - conda install -c conda-forge hyperopt + conda install -c conda-forge tpot ```
-
auto-sklearn (🥈28 · ⭐ 5.8K) - 使用scikit-learn的自动化机器学习。BSD-3 +
AutoKeras (🥈26 · ⭐ 8.3K) - AutoML library for deep learning. Apache-2 -- [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 76 · 🔀 1.1K · 📦 200 · 📋 770 - 13% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 130 · 🔀 1.3K · 📥 1.7K · 📦 260 · 📋 790 - 7% open · ⏱️ 04.12.2021): ``` - git clone https://github.com/automl/auto-sklearn + git clone https://github.com/keras-team/autokeras ``` -- [PyPi](https://pypi.org/project/auto-sklearn) (📥 26K / month): +- [PyPi](https://pypi.org/project/autokeras): ``` - pip install auto-sklearn + pip install autokeras ```
-
featuretools (🥈27 · ⭐ 5.8K) - 一个用于自动化特征工程的开源python库。BSD-3 +
AutoGluon (🥈26 · ⭐ 3.9K) - AutoGluon: AutoML for Text, Image, and Tabular Data. Apache-2 -- [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 56 · 🔀 740 · 📦 850 · 📋 670 - 20% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 62 · 🔀 500 · 📦 86 · 📋 560 - 22% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/alteryx/featuretools - ``` -- [PyPi](https://pypi.org/project/featuretools) (📥 830K / month): - ``` - pip install featuretools + git clone https://github.com/awslabs/autogluon ``` -- [Conda](https://anaconda.org/conda-forge/featuretools) (📥 67K · ⏱️ 21.09.2021): +- [PyPi](https://pypi.org/project/autogluon) (📥 19K / month): ``` - conda install -c conda-forge featuretools + pip install autogluon ```
-
AutoGluon (🥈26 · ⭐ 3.7K) - AutoGluon：用于文本，图像和表格数据的AutoML。Apache-2 +
BoTorch (🥈26 · ⭐ 2.1K) - Bayesian optimization in PyTorch. MIT -- [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 62 · 🔀 470 · 📦 66 · 📋 530 - 20% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/pytorch/botorch) (👨‍💻 64 · 🔀 230 · 📦 190 · 📋 230 - 21% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/awslabs/autogluon + git clone https://github.com/pytorch/botorch ``` -- [PyPi](https://pypi.org/project/autogluon) (📥 20K / month): +- [PyPi](https://pypi.org/project/botorch) (📥 130K / month): ``` - pip install autogluon + pip install botorch ```
-
Ax (🥈26 · ⭐ 1.6K) - 自适应实验平台。MIT +
Ax (🥈26 · ⭐ 1.7K) - Adaptive Experimentation Platform. MIT -- [GitHub](https://github.com/facebook/Ax) (👨‍💻 100 · 🔀 170 · 📦 200 · 📋 280 - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/facebook/Ax) (👨‍💻 110 · 🔀 170 · 📦 220 · 📋 320 - 6% open · ⏱️ 16.12.2021): ``` git clone https://github.com/facebook/Ax @@ -7021,229 +7033,253 @@ _用于超参数优化，自动机器学习和神经体系结构搜索的库。_ pip install ax-platform ```
-
BoTorch (🥈25 · ⭐ 2.1K) - PyTorch中的贝叶斯优化。MIT +
NNI (🥈25 · ⭐ 11K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT -- [GitHub](https://github.com/pytorch/botorch) (👨‍💻 61 · 🔀 210 · 📦 160 · 📋 210 - 21% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/microsoft/nni) (👨‍💻 150 · 🔀 1.5K · 📦 160 · 📋 1.4K - 15% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/pytorch/botorch + git clone https://github.com/microsoft/nni ``` -- [PyPi](https://pypi.org/project/botorch) (📥 120K / month): +- [PyPi](https://pypi.org/project/nni): ``` - pip install botorch + pip install nni ```
-
mljar-supervised (🥈25 · ⭐ 1.6K) - 使用scikit-learn的自动化机器学习。MIT +
auto-sklearn (🥈24 · ⭐ 5.9K) - Automated Machine Learning with scikit-learn. BSD-3 -- [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 13 · 🔀 210 · 📦 23 · 📋 420 - 12% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 77 · 🔀 1.1K · 📦 240 · 📋 810 - 11% open · ⏱️ 09.11.2021): ``` - git clone https://github.com/mljar/mljar-supervised + git clone https://github.com/automl/auto-sklearn ``` -- [PyPi](https://pypi.org/project/mljar-supervised) (📥 130K / month): +- [PyPi](https://pypi.org/project/auto-sklearn): ``` - pip install mljar-supervised + pip install auto-sklearn ```
-
Keras Tuner (🥈24 · ⭐ 2.4K) - 简单易用的超参数调整。Apache-2 +
Hyperas (🥈24 · ⭐ 2.1K) - Keras + Hyperopt: A very simple wrapper for convenient.. MIT -- [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 39 · 🔀 300 · 📦 890 · 📋 350 - 43% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/maxpumperla/hyperas) (👨‍💻 21 · 🔀 300 · 📦 220 · 📋 250 - 36% open · ⏱️ 19.11.2021): ``` - git clone https://github.com/keras-team/keras-tuner + git clone https://github.com/maxpumperla/hyperas ``` -- [PyPi](https://pypi.org/project/keras-tuner): +- [PyPi](https://pypi.org/project/hyperas) (📥 12K / month): ``` - pip install keras-tuner + pip install hyperas ```
-
nevergrad (🥈23 · ⭐ 3.2K) - 用于执行无梯度优化(gradient-free optimization)的Python工具箱。MIT +
nevergrad (🥈23 · ⭐ 3.2K) - A Python toolbox for performing gradient-free optimization. MIT -- [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 46 · 🔀 290 · 📦 240 · 📋 210 - 32% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 46 · 🔀 300 · 📦 270 · 📋 210 - 27% open · ⏱️ 15.12.2021): ``` git clone https://github.com/facebookresearch/nevergrad ``` -- [PyPi](https://pypi.org/project/nevergrad) (📥 37K / month): +- [PyPi](https://pypi.org/project/nevergrad) (📥 32K / month): ``` pip install nevergrad ``` -- [Conda](https://anaconda.org/conda-forge/nevergrad) (📥 16K · ⏱️ 14.06.2021): +- [Conda](https://anaconda.org/conda-forge/nevergrad) (📥 20K · ⏱️ 14.06.2021): ``` conda install -c conda-forge nevergrad ```
-
Hyperas (🥈23 · ⭐ 2.1K · 💤) - Keras + Hyperopt：一个非常简单的包装，方便使用。MIT +
GPyOpt (🥈23 · ⭐ 780 · 💀) - Gaussian Process Optimization using GPy. BSD-3 -- [GitHub](https://github.com/maxpumperla/hyperas) (👨‍💻 21 · 🔀 300 · 📦 220 · 📋 250 - 35% open · ⏱️ 22.12.2020): +- [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 240 · 📦 230 · 📋 280 - 34% open · ⏱️ 05.11.2020): ``` - git clone https://github.com/maxpumperla/hyperas + git clone https://github.com/SheffieldML/GPyOpt ``` -- [PyPi](https://pypi.org/project/hyperas) (📥 20K / month): +- [PyPi](https://pypi.org/project/gpyopt) (📥 18K / month): ``` - pip install hyperas + pip install gpyopt ```
-
GPyOpt (🥈23 · ⭐ 760 · 💤) - 使用GPy进行高斯过程优化。BSD-3 +
SMAC3 (🥈21 · ⭐ 640) - Sequential Model-based Algorithm Configuration. ❗Unlicensed -- [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 230 · 📦 220 · 📋 280 - 34% open · ⏱️ 05.11.2020): +- [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 160 · 📋 350 - 18% open · ⏱️ 05.11.2021): ``` - git clone https://github.com/SheffieldML/GPyOpt + git clone https://github.com/automl/SMAC3 ``` -- [PyPi](https://pypi.org/project/gpyopt) (📥 14K / month): +- [PyPi](https://pypi.org/project/smac) (📥 30K / month): ``` - pip install gpyopt + pip install smac + ``` +
+
mljar-supervised (🥈20 · ⭐ 1.7K) - Automated Machine Learning Pipeline with Feature Engineering.. MIT + +- [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 14 · 🔀 240 · 📦 33 · 📋 450 - 16% open · ⏱️ 06.12.2021): + + ``` + git clone https://github.com/mljar/mljar-supervised + ``` +- [PyPi](https://pypi.org/project/mljar-supervised): + ``` + pip install mljar-supervised ```
-
AdaNet (🥈22 · ⭐ 3.3K) - 具有学习保证的快速灵活的AutoML。Apache-2 +
auto_ml (🥈20 · ⭐ 1.6K · 💀) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT -- [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 39 · 📋 110 - 58% open · ⏱️ 30.08.2021): +- [GitHub](https://github.com/ClimbsRocks/auto_ml) (👨‍💻 13 · 🔀 300 · 📥 38 · 📋 390 - 45% open · ⏱️ 25.03.2018): ``` - git clone https://github.com/tensorflow/adanet + git clone https://github.com/ClimbsRocks/auto_ml ``` -- [PyPi](https://pypi.org/project/adanet) (📥 910 / month): +- [PyPi](https://pypi.org/project/auto_ml) (📥 1.4K / month): ``` - pip install adanet + pip install auto_ml ```
-
Talos (🥉21 · ⭐ 1.4K) - TensorFlow，Keras和PyTorch的超参数优化。MIT +
Talos (🥈20 · ⭐ 1.5K · 💤) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT -- [GitHub](https://github.com/autonomio/talos) (👨‍💻 19 · 🔀 240 · 📦 130 · 📋 390 - 9% open · ⏱️ 27.05.2021): +- [GitHub](https://github.com/autonomio/talos) (👨‍💻 19 · 🔀 250 · 📦 130 · 📋 390 - 8% open · ⏱️ 27.05.2021): ``` git clone https://github.com/autonomio/talos ``` -- [PyPi](https://pypi.org/project/talos) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/talos) (📥 810 / month): ``` pip install talos ```
-
MLBox (🥉21 · ⭐ 1.3K · 💀) - MLBox是功能强大的自动机器学习python库。❗Unlicensed +
MLBox (🥈20 · ⭐ 1.3K · 💀) - MLBox is a powerful Automated Machine Learning python library. ❗Unlicensed -- [GitHub](https://github.com/AxeldeRomblay/MLBox) (👨‍💻 9 · 🔀 260 · 📦 26 · 📋 89 - 16% open · ⏱️ 25.08.2020): +- [GitHub](https://github.com/AxeldeRomblay/MLBox) (👨‍💻 9 · 🔀 260 · 📦 28 · 📋 90 - 17% open · ⏱️ 25.08.2020): ``` git clone https://github.com/AxeldeRomblay/MLBox ``` -- [PyPi](https://pypi.org/project/mlbox) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/mlbox) (📥 2.8K / month): ``` pip install mlbox ```
-
SMAC3 (🥉21 · ⭐ 620) - Sequential Model-based算法的配置。❗Unlicensed +
lazypredict (🥈20 · ⭐ 270) - Lazy Predict help build a lot of basic models without much code.. MIT -- [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 160 · 📋 340 - 18% open · ⏱️ 06.08.2021): +- [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 16 · 🔀 36 · 📦 210 · 📋 59 - 49% open · ⏱️ 18.10.2021): ``` - git clone https://github.com/automl/SMAC3 + git clone https://github.com/shankarpandala/lazypredict ``` -- [PyPi](https://pypi.org/project/smac) (📥 23K / month): +- [PyPi](https://pypi.org/project/lazypredict) (📥 7.9K / month): ``` - pip install smac + pip install lazypredict ```
-
optunity (🥉21 · ⭐ 380 · 💀) - 超参数优化的优化例程。BSD-3 +
AdaNet (🥉19 · ⭐ 3.3K) - Fast and flexible AutoML with learning guarantees. Apache-2 -- [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 73 · 📥 67 · 📦 66 · 📋 95 - 49% open · ⏱️ 11.05.2020): +- [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 41 · 📋 110 - 58% open · ⏱️ 30.08.2021): ``` - git clone https://github.com/claesenm/optunity + git clone https://github.com/tensorflow/adanet ``` -- [PyPi](https://pypi.org/project/optunity) (📥 15K / month): +- [PyPi](https://pypi.org/project/adanet): ``` - pip install optunity + pip install adanet ```
-
auto_ml (🥉20 · ⭐ 1.6K · 💀) - [UNMAINTAINED] Automated machine learning for analytics & production. MIT +
sklearn-deap (🥉19 · ⭐ 670) - Use evolutionary algorithms instead of gridsearch in.. MIT -- [GitHub](https://github.com/ClimbsRocks/auto_ml) (👨‍💻 13 · 🔀 300 · 📥 38 · 📋 390 - 45% open · ⏱️ 25.03.2018): +- [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 110 · 📦 30 · 📋 50 - 32% open · ⏱️ 30.07.2021): ``` - git clone https://github.com/ClimbsRocks/auto_ml + git clone https://github.com/rsteca/sklearn-deap ``` -- [PyPi](https://pypi.org/project/auto_ml) (📥 3K / month): +- [PyPi](https://pypi.org/project/sklearn-deap) (📥 1K / month): ``` - pip install auto_ml + pip install sklearn-deap + ``` +
+
HpBandSter (🥉19 · ⭐ 500 · 💀) - a distributed Hyperband implementation on Steroids. BSD-3 + +- [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 110 · 📦 190 · 📋 86 - 59% open · ⏱️ 26.03.2019): + + ``` + git clone https://github.com/automl/HpBandSter + ``` +- [PyPi](https://pypi.org/project/hpbandster) (📥 25K / month): + ``` + pip install hpbandster ```
-
Neuraxle (🥉20 · ⭐ 450) - 类似于Sklearn的超参数调整和AutoML输入框架。Apache-2 +
Neuraxle (🥉19 · ⭐ 490) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 -- [GitHub](https://github.com/Neuraxio/Neuraxle) (👨‍💻 7 · 🔀 51 · 📦 24 · 📋 300 - 46% open · ⏱️ 26.07.2021): +- [GitHub](https://github.com/Neuraxio/Neuraxle) (👨‍💻 7 · 🔀 52 · 📦 24 · 📋 310 - 41% open · ⏱️ 01.11.2021): ``` git clone https://github.com/Neuraxio/Neuraxle ``` -- [PyPi](https://pypi.org/project/neuraxle) (📥 280 / month): +- [PyPi](https://pypi.org/project/neuraxle): ``` pip install neuraxle ```
-
Orion (🥉20 · ⭐ 200) - 异步分布式超参数优化。❗Unlicensed +
Test Tube (🥉18 · ⭐ 700 · 💀) - Python library to easily log experiments and parallelize.. MIT -- [GitHub](https://github.com/Epistimio/orion) (👨‍💻 24 · 🔀 41 · 📦 44 · 📋 190 - 27% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/williamFalcon/test-tube) (👨‍💻 16 · 🔀 64 · 📥 10 · 📋 44 - 52% open · ⏱️ 17.03.2020): ``` - git clone https://github.com/Epistimio/orion + git clone https://github.com/williamFalcon/test-tube ``` -- [PyPi](https://pypi.org/project/orion) (📥 2.8K / month): +- [PyPi](https://pypi.org/project/test_tube) (📥 13K / month): ``` - pip install orion + pip install test_tube ```
-
sklearn-deap (🥉19 · ⭐ 650) - 使用进化算法而非gridsearch的超参数优化。MIT +
AlphaPy (🥉18 · ⭐ 680) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 -- [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 110 · 📦 29 · 📋 49 - 30% open · ⏱️ 30.07.2021): +- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 140 · 📦 3 · 📋 40 - 27% open · ⏱️ 23.10.2021): ``` - git clone https://github.com/rsteca/sklearn-deap + git clone https://github.com/ScottfreeLLC/AlphaPy ``` -- [PyPi](https://pypi.org/project/sklearn-deap) (📥 830 / month): +- [PyPi](https://pypi.org/project/alphapy) (📥 180 / month): ``` - pip install sklearn-deap + pip install alphapy ```
-
lazypredict (🥉19 · ⭐ 240) - Lazy Predict帮助您无需大量代码即可构建许多基本模型。MIT +
Dragonfly (🥉17 · ⭐ 610 · 💀) - An open source python library for scalable Bayesian optimisation. MIT -- [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 14 · 🔀 31 · 📦 170 · 📋 56 - 46% open · ⏱️ 13.07.2021): +- [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 12 · 🔀 200 · 📋 49 - 63% open · ⏱️ 03.07.2020): ``` - git clone https://github.com/shankarpandala/lazypredict + git clone https://github.com/dragonfly/dragonfly ``` -- [PyPi](https://pypi.org/project/lazypredict) (📥 5.5K / month): +- [PyPi](https://pypi.org/project/dragonfly-opt) (📥 34K / month): ``` - pip install lazypredict + pip install dragonfly-opt ```
-
AlphaPy (🥉18 · ⭐ 640 · 💤) - 使用scikit-learn的自动化机器学习。Apache-2 +
optunity (🥉17 · ⭐ 380 · 💀) - optimization routines for hyperparameter tuning. BSD-3 -- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 140 · 📦 3 · 📋 38 - 23% open · ⏱️ 08.02.2021): +- [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 73 · 📥 67 · 📦 68 · 📋 95 - 49% open · ⏱️ 11.05.2020): ``` - git clone https://github.com/ScottfreeLLC/AlphaPy + git clone https://github.com/claesenm/optunity ``` -- [PyPi](https://pypi.org/project/alphapy) (📥 160 / month): +- [PyPi](https://pypi.org/project/optunity): ``` - pip install alphapy + pip install optunity ```
-
Test Tube (🥉17 · ⭐ 700 · 💀) - 可轻松记录实验并进行并行化的Python库。MIT +
Auto ViML (🥉17 · ⭐ 310) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 -- [GitHub](https://github.com/williamFalcon/test-tube) (👨‍💻 16 · 🔀 65 · 📥 10 · 📋 44 - 52% open · ⏱️ 17.03.2020): +- [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 69 · 📦 15 · 📋 18 - 22% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/williamFalcon/test-tube + git clone https://github.com/AutoViML/Auto_ViML ``` -- [PyPi](https://pypi.org/project/test_tube) (📥 11K / month): +- [PyPi](https://pypi.org/project/autoviml) (📥 930 / month): ``` - pip install test_tube + pip install autoviml ```
-
Sherpa (🥉17 · ⭐ 300 · 💤) - 超参数优化库。❗Unlicensed +
Sherpa (🥉17 · ⭐ 310 · 💀) - Hyperparameter optimization that enables researchers to.. ❗Unlicensed -- [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 46 · 📦 15 · 📋 54 - 24% open · ⏱️ 18.10.2020): +- [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 48 · 📦 17 · 📋 56 - 26% open · ⏱️ 18.10.2020): ``` git clone https://github.com/sherpa-ai/sherpa @@ -7253,62 +7289,62 @@ _用于超参数优化，自动机器学习和神经体系结构搜索的库。_ pip install parameter-sherpa ```
-
Auto ViML (🥉17 · ⭐ 300) - 用单行代码自动构建多个ML模型。Apache-2 +
Orion (🥉17 · ⭐ 210) - Asynchronous Distributed Hyperparameter Optimization. ❗Unlicensed -- [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 69 · 📦 15 · 📋 18 - 22% open · ⏱️ 25.07.2021): +- [GitHub](https://github.com/Epistimio/orion) (👨‍💻 24 · 🔀 41 · 📦 47 · 📋 200 - 29% open · ⏱️ 01.12.2021): ``` - git clone https://github.com/AutoViML/Auto_ViML + git clone https://github.com/Epistimio/orion ``` -- [PyPi](https://pypi.org/project/autoviml) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/orion): ``` - pip install autoviml + pip install orion ```
-
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 +
Auto Tune Models (🥉16 · ⭐ 510 · 💀) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT -- [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 26 · 📋 29 - 79% open · ⏱️ 05.04.2019): +- [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 8 · 📋 88 - 19% open · ⏱️ 21.02.2020): ``` - git clone https://github.com/minimaxir/automl-gs + git clone https://github.com/HDI-Project/ATM ``` -- [PyPi](https://pypi.org/project/automl_gs) (📥 43 / month): +- [PyPi](https://pypi.org/project/atm) (📥 97 / month): ``` - pip install automl_gs + pip install atm ```
-
Xcessiv (🥉16 · ⭐ 1.3K · 💀) - 基于Web的应用程序，高效、可扩展且自动化。Apache-2 +
featurewiz (🥉16 · ⭐ 99) - Use advanced feature engineering strategies and select the.. Apache-2 -- [GitHub](https://github.com/reiinakano/xcessiv) (👨‍💻 6 · 🔀 100 · 📦 1 · 📋 34 - 61% open · ⏱️ 21.08.2017): +- [GitHub](https://github.com/AutoViML/featurewiz) (👨‍💻 3 · 🔀 27 · 📦 3 · 📋 7 - 71% open · ⏱️ 10.12.2021): ``` - git clone https://github.com/reiinakano/xcessiv + git clone https://github.com/AutoViML/featurewiz ``` -- [PyPi](https://pypi.org/project/xcessiv) (📥 71 / month): +- [PyPi](https://pypi.org/project/featurewiz) (📥 120K / month): ``` - pip install xcessiv + pip install featurewiz ```
-
Auto Tune Models (🥉16 · ⭐ 510 · 💀) - 自动调整模型。MIT +
automl-gs (🥉15 · ⭐ 1.8K · 💀) - Provide an input CSV and a target field to predict, generate a.. MIT -- [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 6 · 📋 88 - 19% open · ⏱️ 21.02.2020): +- [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 27 · 📋 30 - 80% open · ⏱️ 05.04.2019): ``` - git clone https://github.com/HDI-Project/ATM + git clone https://github.com/minimaxir/automl-gs ``` -- [PyPi](https://pypi.org/project/atm) (📥 130 / month): +- [PyPi](https://pypi.org/project/automl_gs) (📥 19 / month): ``` - pip install atm + pip install automl_gs ```
-
Advisor (🥉15 · ⭐ 1.4K · 💀) - Google Vizier的超参数开源实现。Apache-2 +
Advisor (🥉15 · ⭐ 1.4K · 💀) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 -- [GitHub](https://github.com/tobegit3hub/advisor) (👨‍💻 11 · 🔀 250 · 📋 32 - 59% open · ⏱️ 11.11.2019): +- [GitHub](https://github.com/tobegit3hub/advisor) (👨‍💻 11 · 🔀 260 · 📋 32 - 59% open · ⏱️ 11.11.2019): ``` git clone https://github.com/tobegit3hub/advisor ``` -- [PyPi](https://pypi.org/project/advisor) (📥 71 / month): +- [PyPi](https://pypi.org/project/advisor) (📥 62 / month): ``` pip install advisor ``` @@ -7317,43 +7353,43 @@ _用于超参数优化，自动机器学习和神经体系结构搜索的库。_ docker pull tobegit3hub/advisor ```
-
HyperparameterHunter (🥉15 · ⭐ 670 · 💤) - 轻松进行超参数优化和自动结果评估。MIT +
Xcessiv (🥉15 · ⭐ 1.3K · 💀) - A web-based application for quick, scalable, and automated.. Apache-2 -- [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (👨‍💻 4 · 🔀 87 · 📥 330 · 📋 120 - 27% open · ⏱️ 20.01.2021): +- [GitHub](https://github.com/reiinakano/xcessiv) (👨‍💻 6 · 🔀 110 · 📦 1 · 📋 34 - 61% open · ⏱️ 21.08.2017): ``` - git clone https://github.com/HunterMcGushion/hyperparameter_hunter + git clone https://github.com/reiinakano/xcessiv ``` -- [PyPi](https://pypi.org/project/hyperparameter-hunter) (📥 92 / month): +- [PyPi](https://pypi.org/project/xcessiv): ``` - pip install hyperparameter-hunter + pip install xcessiv ```
-
HpBandSter (🥉15 · ⭐ 490 · 💀) - 分布式自动化机器学习库。BSD-3 +
Parfit (🥉15 · ⭐ 200 · 💀) - A package for parallelizing the fit and flexibly scoring of.. MIT -- [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 100 · 📦 170 · 📋 85 - 58% open · ⏱️ 26.03.2019): +- [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 2 · 🔀 25 · 📦 9 · 📋 11 - 54% open · ⏱️ 04.04.2020): ``` - git clone https://github.com/automl/HpBandSter + git clone https://github.com/jmcarpenter2/parfit ``` -- [PyPi](https://pypi.org/project/hpbandster): +- [PyPi](https://pypi.org/project/parfit) (📥 16K / month): ``` - pip install hpbandster + pip install parfit ```
-
Parfit (🥉15 · ⭐ 200 · 💀) - 并行化拟合与评估工具库。MIT +
HyperparameterHunter (🥉14 · ⭐ 680 · 💤) - Easy hyperparameter optimization and automatic result.. MIT -- [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 2 · 🔀 25 · 📦 9 · 📋 11 - 54% open · ⏱️ 04.04.2020): +- [GitHub](https://github.com/HunterMcGushion/hyperparameter_hunter) (👨‍💻 4 · 🔀 87 · 📥 330 · 📋 120 - 27% open · ⏱️ 20.01.2021): ``` - git clone https://github.com/jmcarpenter2/parfit + git clone https://github.com/HunterMcGushion/hyperparameter_hunter ``` -- [PyPi](https://pypi.org/project/parfit) (📥 16K / month): +- [PyPi](https://pypi.org/project/hyperparameter-hunter): ``` - pip install parfit + pip install hyperparameter-hunter ```
-
ENAS (🥉13 · ⭐ 2.5K · 💀) - Efficient Neural Architecture Search的Pytorch实现。Apache-2 +
ENAS (🥉13 · ⭐ 2.5K · 💀) - 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): @@ -7361,55 +7397,31 @@ _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/carpedm20/ENAS-pytorch ```
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Auptimizer (🥉13 · ⭐ 180 · 💤) - 自动ML模型优化工具。❗️GPL-3.0 +
Auptimizer (🥉13 · ⭐ 180 · 💤) - An automatic ML model optimization tool. ❗️GPL-3.0 - [GitHub](https://github.com/LGE-ARC-AdvancedAI/auptimizer) (👨‍💻 11 · 🔀 21 · ⏱️ 03.03.2021): ``` git clone https://github.com/LGE-ARC-AdvancedAI/auptimizer ``` -- [PyPi](https://pypi.org/project/auptimizer) (📥 59 / month): +- [PyPi](https://pypi.org/project/auptimizer) (📥 33 / month): ``` pip install auptimizer ```
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Dragonfly (🥉12 · ⭐ 600 · 💀) - 一个用于自动化特征工程的开源python库。MIT - -- [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 12 · 🔀 83 · 📋 47 - 61% open · ⏱️ 03.07.2020): - - ``` - git clone https://github.com/dragonfly/dragonfly - ``` -- [PyPi](https://pypi.org/project/dragonfly-opt): - ``` - pip install dragonfly-opt - ``` -
-
Hypermax (🥉12 · ⭐ 97 · 💀) - 更好更快的超参数优化。BSD-3 +
Hypermax (🥉12 · ⭐ 97 · 💀) - Better, faster hyper-parameter optimization. BSD-3 -- [GitHub](https://github.com/electricbrainio/hypermax) (👨‍💻 9 · 🔀 14 · 📦 4 · 📋 4 - 75% open · ⏱️ 02.08.2020): +- [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) (📥 34 / month): +- [PyPi](https://pypi.org/project/hypermax) (📥 31 / month): ``` pip install hypermax ```
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featurewiz (🥉12 · ⭐ 81) - 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) (👨‍💻 2 · 🔀 26 · 📦 3 · 📋 6 - 83% open · ⏱️ 08.07.2021): - - ``` - git clone https://github.com/AutoViML/featurewiz - ``` -- [PyPi](https://pypi.org/project/featurewiz) (📥 1.8K / month): - ``` - pip install featurewiz - ``` -
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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): @@ -7417,278 +7429,274 @@ _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 (🥉11 · ⭐ 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) (📥 23 / month): +- [PyPi](https://pypi.org/project/hypertunity) (📥 25 / 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 · ⭐ 25K) - 开发和比较强化学习的工具包。MIT +
OpenAI Gym (🥇36 · ⭐ 26K) - A toolkit for developing and comparing reinforcement learning.. MIT -- [GitHub](https://github.com/openai/gym) (👨‍💻 320 · 🔀 6.8K · 📦 23K · 📋 1.4K - 6% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/openai/gym) (👨‍💻 330 · 🔀 7K · 📦 25K · 📋 1.4K - 6% open · ⏱️ 16.12.2021): ``` git clone https://github.com/openai/gym ``` -- [PyPi](https://pypi.org/project/gym) (📥 890K / month): +- [PyPi](https://pypi.org/project/gym) (📥 930K / month): ``` pip install gym ```
-
baselines (🥇25 · ⭐ 12K · 💀) - OpenAI基线：强化学习的高质量实现。MIT +
ViZDoom (🥇23 · ⭐ 1.3K) - Doom-based AI Research Platform for Reinforcement Learning from.. ❗Unlicensed + +- [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 45 · 🔀 300 · 📥 11K · 📦 120 · 📋 420 - 19% open · ⏱️ 13.12.2021): + + ``` + git clone https://github.com/mwydmuch/ViZDoom + ``` +- [PyPi](https://pypi.org/project/vizdoom): + ``` + pip install vizdoom + ``` +
+
baselines (🥈22 · ⭐ 12K · 💀) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT -- [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.3K · 📦 340 · 📋 820 - 47% open · ⏱️ 31.01.2020): +- [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.3K · 📦 360 · 📋 820 - 47% open · ⏱️ 31.01.2020): ``` git clone https://github.com/openai/baselines ``` -- [PyPi](https://pypi.org/project/baselines) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/baselines): ``` pip install baselines ```
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keras-rl (🥇25 · ⭐ 5.1K · 💀) - Keras的深度强化学习。MIT +
keras-rl (🥈22 · ⭐ 5.2K · 💀) - Deep Reinforcement Learning for Keras. MIT -- [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 520 · 📋 230 - 4% open · ⏱️ 11.11.2019): +- [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 540 · 📋 230 - 4% open · ⏱️ 11.11.2019): ``` git clone https://github.com/keras-rl/keras-rl ``` -- [PyPi](https://pypi.org/project/keras-rl) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/keras-rl): ``` pip install keras-rl ```
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Acme (🥇25 · ⭐ 2.3K) - 强化学习组件和代理库。Apache-2 +
Acme (🥈22 · ⭐ 2.4K) - A library of reinforcement learning components and agents. Apache-2 -- [GitHub](https://github.com/deepmind/acme) (👨‍💻 49 · 🔀 270 · 📦 44 · 📋 130 - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/deepmind/acme) (👨‍💻 53 · 🔀 290 · 📦 47 · 📋 140 - 27% open · ⏱️ 13.12.2021): ``` git clone https://github.com/deepmind/acme ``` -- [PyPi](https://pypi.org/project/dm-acme) (📥 1.5K / month): +- [PyPi](https://pypi.org/project/dm-acme): ``` pip install dm-acme ```
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TF-Agents (🥇25 · ⭐ 2.1K) - TF-Agents：可靠，可扩展且易于使用的TensorFlow的强化学习库。Apache-2 +
TF-Agents (🥈21 · ⭐ 2.1K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 -- [GitHub](https://github.com/tensorflow/agents) (👨‍💻 110 · 🔀 540 · 📦 590 · 📋 500 - 18% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tensorflow/agents) (👨‍💻 110 · 🔀 560 · 📦 650 · 📋 510 - 19% open · ⏱️ 10.12.2021): ``` git clone https://github.com/tensorflow/agents ``` -- [PyPi](https://pypi.org/project/tf-agents) (📥 20K / month): +- [PyPi](https://pypi.org/project/tf-agents): ``` pip install tf-agents ```
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Dopamine (🥈24 · ⭐ 9.6K) - 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 +
PFRL (🥈21 · ⭐ 750) - PFRL: a PyTorch-based deep reinforcement learning library. MIT -- [GitHub](https://github.com/google/dopamine) (👨‍💻 14 · 🔀 1.3K · 📋 140 - 42% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 15 · 🔀 98 · 📦 27 · 📋 56 - 41% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/google/dopamine + git clone https://github.com/pfnet/pfrl ``` -- [PyPi](https://pypi.org/project/dopamine-rl) (📥 1.2M / month): +- [PyPi](https://pypi.org/project/pfrl) (📥 1.8K / month): ``` - pip install dopamine-rl + pip install pfrl ```
-
TensorForce (🥈23 · ⭐ 3K) - Tensorforce：一个基于TensorFlow的强化学习库。Apache-2 +
TensorForce (🥈20 · ⭐ 3.1K) - Tensorforce: a TensorFlow library for applied.. Apache-2 -- [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 80 · 🔀 490 · 📋 610 - 1% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 81 · 🔀 490 · 📋 620 - 0% open · ⏱️ 10.11.2021): ``` git clone https://github.com/tensorforce/tensorforce ``` -- [PyPi](https://pypi.org/project/tensorforce) (📥 1.4K / month): +- [PyPi](https://pypi.org/project/tensorforce): ``` pip install tensorforce ```
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ViZDoom (🥈23 · ⭐ 1.3K) - 人工智能强化学习工具库。❗Unlicensed +
garage (🥈20 · ⭐ 1.4K) - A toolkit for reproducible reinforcement learning research. MIT -- [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 45 · 🔀 300 · 📥 11K · 📦 120 · 📋 420 - 21% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 78 · 🔀 240 · 📦 23 · 📋 990 - 19% open · ⏱️ 20.10.2021): ``` - git clone https://github.com/mwydmuch/ViZDoom + git clone https://github.com/rlworkgroup/garage ``` -- [PyPi](https://pypi.org/project/vizdoom) (📥 810 / month): +- [PyPi](https://pypi.org/project/garage): ``` - pip install vizdoom + pip install garage ```
-
ChainerRL (🥈23 · ⭐ 1K) - ChainerRL是建立在Chainer之上的深度强化学习库。MIT +
ChainerRL (🥈20 · ⭐ 1K · 💤) - ChainerRL is a deep reinforcement learning library built on top of.. MIT -- [GitHub](https://github.com/chainer/chainerrl) (👨‍💻 29 · 🔀 210 · 📦 100 · 📋 200 - 25% open · ⏱️ 17.04.2021): +- [GitHub](https://github.com/chainer/chainerrl) (👨‍💻 29 · 🔀 210 · 📦 110 · 📋 200 - 25% open · ⏱️ 17.04.2021): ``` git clone https://github.com/chainer/chainerrl ``` -- [PyPi](https://pypi.org/project/chainerrl) (📥 470 / month): +- [PyPi](https://pypi.org/project/chainerrl): ``` pip install chainerrl ```
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Stable Baselines (🥉22 · ⭐ 3.3K) - OpenAI Baselines的一个分支，强化学习的实现。MIT - -- [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 640 · 📋 890 - 11% open · ⏱️ 25.08.2021): - - ``` - git clone https://github.com/hill-a/stable-baselines - ``` -- [PyPi](https://pypi.org/project/stable-baselines) (📥 8.8K / month): - ``` - pip install stable-baselines - ``` -
-
garage (🥉22 · ⭐ 1.3K) - 用于可重复的强化学习研究的工具包。MIT +
Dopamine (🥉18 · ⭐ 9.7K) - Dopamine is a research framework for fast prototyping of.. Apache-2 -- [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 77 · 🔀 230 · 📦 19 · 📋 980 - 18% open · ⏱️ 22.06.2021): +- [GitHub](https://github.com/google/dopamine) (👨‍💻 14 · 🔀 1.3K · 📋 140 - 42% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/rlworkgroup/garage + git clone https://github.com/google/dopamine ``` -- [PyPi](https://pypi.org/project/garage) (📥 480 / month): +- [PyPi](https://pypi.org/project/dopamine-rl): ``` - pip install garage + pip install dopamine-rl ```
-
TensorLayer (🥉21 · ⭐ 6.7K) - 深度学习和强化学习库。❗Unlicensed +
TensorLayer (🥉18 · ⭐ 6.8K) - Deep Learning and Reinforcement Learning Library for.. ❗Unlicensed -- [GitHub](https://github.com/tensorlayer/tensorlayer) (👨‍💻 130 · 🔀 1.5K · 📥 1.3K · 📋 450 - 4% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/tensorlayer/TensorLayer) (👨‍💻 130 · 🔀 1.5K · 📥 1.3K · 📋 460 - 3% open · ⏱️ 29.10.2021): ``` git clone https://github.com/tensorlayer/tensorlayer ``` -- [PyPi](https://pypi.org/project/tensorlayer) (📥 2.2K / month): +- [PyPi](https://pypi.org/project/tensorlayer): ``` pip install tensorlayer ```
-
PARL (🥉21 · ⭐ 2.2K) - 强化学习高性能分布式训练框架。Apache-2 +
PARL (🥉18 · ⭐ 2.3K) - A high-performance distributed training framework for Reinforcement.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 27 · 🔀 560 · 📦 78 · 📋 250 - 18% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 28 · 🔀 590 · 📦 84 · 📋 280 - 21% open · ⏱️ 15.12.2021): ``` git clone https://github.com/PaddlePaddle/PARL ``` -- [PyPi](https://pypi.org/project/parl) (📥 840 / month): +- [PyPi](https://pypi.org/project/parl): ``` pip install parl ```
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TRFL (🥉20 · ⭐ 3.1K) - TensorFlow强化学习。Apache-2 +
Stable Baselines (🥉17 · ⭐ 3.4K) - A fork of OpenAI Baselines, implementations of reinforcement.. MIT -- [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 370 · 📦 62 · 📋 20 - 20% open · ⏱️ 16.08.2021): +- [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 650 · 📋 900 - 11% open · ⏱️ 25.08.2021): ``` - git clone https://github.com/deepmind/trfl + git clone https://github.com/hill-a/stable-baselines ``` -- [PyPi](https://pypi.org/project/trfl) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/stable-baselines): ``` - pip install trfl + pip install stable-baselines ```
-
Coach (🥉20 · ⭐ 2.1K) - 英特尔AI实验室的强化学习训练器。Apache-2 +
ReAgent (🥉17 · ⭐ 3.1K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 -- [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 400 · 📋 260 - 29% open · ⏱️ 28.06.2021): +- [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 120 · 🔀 420 · 📋 97 - 22% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/IntelLabs/coach - ``` -- [PyPi](https://pypi.org/project/rl_coach) (📥 300 / month): - ``` - pip install rl_coach + git clone https://github.com/facebookresearch/ReAgent ```
-
PFRL (🥉20 · ⭐ 710) - PFRL：基于PyTorch的深度强化学习库。MIT +
Coach (🥉17 · ⭐ 2.1K) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 -- [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 15 · 🔀 93 · 📦 24 · 📋 54 - 40% open · ⏱️ 07.09.2021): +- [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 410 · 📋 260 - 29% open · ⏱️ 28.06.2021): ``` - git clone https://github.com/pfnet/pfrl + git clone https://github.com/IntelLabs/coach ``` -- [PyPi](https://pypi.org/project/pfrl) (📥 880 / month): +- [PyPi](https://pypi.org/project/rl_coach): ``` - pip install pfrl + pip install rl_coach ```
-
RLax (🥉19 · ⭐ 680) - 强化学习组件和代理库。Apache-2 jax +
RLax (🥉17 · ⭐ 720) - A library of reinforcement learning building blocks in JAX. Apache-2 jax -- [GitHub](https://github.com/deepmind/rlax) (👨‍💻 15 · 🔀 53 · 📦 25 · 📋 11 - 36% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/deepmind/rlax) (👨‍💻 16 · 🔀 56 · 📦 32 · 📋 12 - 25% open · ⏱️ 02.12.2021): ``` git clone https://github.com/deepmind/rlax ``` -- [PyPi](https://pypi.org/project/rlax) (📥 1.8K / month): +- [PyPi](https://pypi.org/project/rlax): ``` pip install rlax ```
-
ReAgent (🥉17 · ⭐ 3K) - 推理系统平台。BSD-3 +
DeepMind Lab (🥉16 · ⭐ 6.6K) - A customisable 3D platform for agent-based AI research. ❗️GPL-2.0 -- [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 120 · 🔀 420 · 📋 97 - 22% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/deepmind/lab) (👨‍💻 7 · 🔀 1.3K · 📋 210 - 23% open · ⏱️ 21.07.2021): ``` - git clone https://github.com/facebookresearch/ReAgent + git clone https://github.com/deepmind/lab ```
-
DeepMind Lab (🥉16 · ⭐ 6.5K · 📈) - 可定制的3D平台，用于agent-based AI研究。❗️GPL-2.0 +
TRFL (🥉16 · ⭐ 3.1K) - TensorFlow Reinforcement Learning. Apache-2 -- [GitHub](https://github.com/deepmind/lab) (👨‍💻 7 · 🔀 1.3K · 📋 200 - 22% open · ⏱️ 21.07.2021): +- [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 370 · 📦 68 · 📋 20 - 20% open · ⏱️ 16.08.2021): ``` - git clone https://github.com/deepmind/lab + git clone https://github.com/deepmind/trfl + ``` +- [PyPi](https://pypi.org/project/trfl): + ``` + pip install trfl ```

-## 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._ -
scikit-surprise (🥇26 · ⭐ 5K · 💀) - 用于构建和分析推荐算法的Python scikit工具库。BSD-3 +
TF Recommenders (🥇25 · ⭐ 1.1K) - TensorFlow Recommenders is a library for building.. Apache-2 -- [GitHub](https://github.com/NicolasHug/Surprise) (👨‍💻 38 · 🔀 880 · 📦 1.3K · 📋 330 - 12% open · ⏱️ 05.08.2020): +- [GitHub](https://github.com/tensorflow/recommenders) (👨‍💻 29 · 🔀 150 · 📦 61 · 📋 200 - 53% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/NicolasHug/Surprise - ``` -- [PyPi](https://pypi.org/project/scikit-surprise) (📥 71K / month): - ``` - pip install scikit-surprise + git clone https://github.com/tensorflow/recommenders ``` -- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (📥 200K · ⏱️ 13.10.2020): +- [PyPi](https://pypi.org/project/tensorflow-recommenders) (📥 250K / month): ``` - conda install -c conda-forge scikit-surprise + pip install tensorflow-recommenders ```
-
lightfm (🥇25 · ⭐ 3.8K · 💤) - 全局优化的Python实现。Apache-2 +
lightfm (🥇24 · ⭐ 3.9K · 💤) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 -- [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 600 · 📦 560 · 📋 430 - 19% open · ⏱️ 07.02.2021): +- [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 610 · 📦 610 · 📋 430 - 20% open · ⏱️ 07.02.2021): ``` git clone https://github.com/lyst/lightfm ``` -- [PyPi](https://pypi.org/project/lightfm) (📥 190K / month): +- [PyPi](https://pypi.org/project/lightfm): ``` pip install lightfm ``` @@ -7697,25 +7705,25 @@ _用于建立和评估推荐系统的库。_ conda install -c conda-forge lightfm ```
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implicit (🥈24 · ⭐ 2.5K) - 隐式反馈数据集的快速Python协同过滤。MIT +
implicit (🥇24 · ⭐ 2.6K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT -- [GitHub](https://github.com/benfred/implicit) (👨‍💻 30 · 🔀 500 · 📦 480 · 📋 360 - 22% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/benfred/implicit) (👨‍💻 30 · 🔀 500 · 📦 520 · 📋 370 - 22% open · ⏱️ 02.10.2021): ``` git clone https://github.com/benfred/implicit ``` -- [PyPi](https://pypi.org/project/implicit) (📥 130K / month): +- [PyPi](https://pypi.org/project/implicit) (📥 120K / month): ``` pip install implicit ``` -- [Conda](https://anaconda.org/conda-forge/implicit) (📥 300K · ⏱️ 29.08.2021): +- [Conda](https://anaconda.org/conda-forge/implicit) (📥 320K · ⏱️ 29.08.2021): ``` conda install -c conda-forge implicit ```
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Cornac (🥈24 · ⭐ 440) - 多模态推荐系统的比较框架。Apache-2 +
Cornac (🥇24 · ⭐ 490) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 -- [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 13 · 🔀 76 · 📦 62 · 📋 63 - 1% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 13 · 🔀 81 · 📦 68 · 📋 74 - 1% open · ⏱️ 30.09.2021): ``` git clone https://github.com/PreferredAI/cornac @@ -7724,84 +7732,100 @@ _用于建立和评估推荐系统的库。_ ``` pip install cornac ``` -- [Conda](https://anaconda.org/conda-forge/cornac) (📥 180K · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/cornac) (📥 190K · ⏱️ 15.11.2021): ``` conda install -c conda-forge cornac ```
-
TF Recommenders (🥈23 · ⭐ 1K) - TensorFlow Recommenders是一个用于构建推荐系统的工具库。Apache-2 +
scikit-surprise (🥈22 · ⭐ 5.1K · 💀) - A Python scikit for building and analyzing recommender.. BSD-3 -- [GitHub](https://github.com/tensorflow/recommenders) (👨‍💻 28 · 🔀 140 · 📦 43 · 📋 190 - 53% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/NicolasHug/Surprise) (👨‍💻 38 · 🔀 890 · 📋 330 - 12% open · ⏱️ 05.08.2020): ``` - git clone https://github.com/tensorflow/recommenders + git clone https://github.com/NicolasHug/Surprise ``` -- [PyPi](https://pypi.org/project/tensorflow-recommenders) (📥 120K / month): +- [PyPi](https://pypi.org/project/scikit-surprise) (📥 72K / month): ``` - pip install tensorflow-recommenders + pip install scikit-surprise + ``` +- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (📥 200K · ⏱️ 18.11.2021): + ``` + conda install -c conda-forge scikit-surprise ```
-
RecBole (🥉22 · ⭐ 1.3K) - 统一，全面，高效的推荐库。MIT +
RecBole (🥉21 · ⭐ 1.5K) - A unified, comprehensive and efficient recommendation library. MIT -- [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 40 · 🔀 210 · 📋 190 - 19% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 41 · 🔀 250 · 📋 260 - 16% open · ⏱️ 09.12.2021): ``` git clone https://github.com/RUCAIBox/RecBole ``` -- [PyPi](https://pypi.org/project/recbole) (📥 670 / month): +- [PyPi](https://pypi.org/project/recbole): ``` pip install recbole ``` -- [Conda](https://anaconda.org/aibox/recbole) (📥 710 · ⏱️ 16.09.2021): +- [Conda](https://anaconda.org/aibox/recbole) (📥 910 · ⏱️ 16.09.2021): ``` conda install -c aibox recbole ```
-
TF Ranking (🥉21 · ⭐ 2.3K) - 在TensorFlow中学习推荐排序。Apache-2 +
Recommenders (🥉19 · ⭐ 12K) - Best Practices on Recommendation Systems. MIT + +- [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 100 · 🔀 2K · 📥 85 · 📦 5 · 📋 630 - 23% open · ⏱️ 23.09.2021): + + ``` + git clone https://github.com/microsoft/recommenders + ``` +
+
TF Ranking (🥉19 · ⭐ 2.4K) - Learning to Rank in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/ranking) (👨‍💻 20 · 🔀 390 · 📋 260 - 12% open · ⏱️ 22.07.2021): +- [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) (📥 34K / month): +- [PyPi](https://pypi.org/project/tensorflow_ranking): ``` pip install tensorflow_ranking ```
-
tensorrec (🥉19 · ⭐ 1.2K · 💀) - TensorFlow推荐算法和框架。Apache-2 +
Case Recommender (🥉19 · ⭐ 370) - Case Recommender: A Flexible and Extensible Python.. MIT -- [GitHub](https://github.com/jfkirk/tensorrec) (👨‍💻 9 · 🔀 220 · 📦 26 · 📋 120 - 28% open · ⏱️ 04.02.2020): +- [GitHub](https://github.com/caserec/CaseRecommender) (👨‍💻 11 · 🔀 77 · 📦 9 · 📋 24 - 16% open · ⏱️ 25.11.2021): ``` - git clone https://github.com/jfkirk/tensorrec + git clone https://github.com/caserec/CaseRecommender ``` -- [PyPi](https://pypi.org/project/tensorrec) (📥 940 / month): +- [PyPi](https://pypi.org/project/caserecommender) (📥 820 / month): ``` - pip install tensorrec + pip install caserecommender ```
-
Recommenders (🥉18 · ⭐ 11K) - 推荐系统最佳实践。MIT +
tensorrec (🥉18 · ⭐ 1.2K · 💀) - A TensorFlow recommendation algorithm and framework in.. Apache-2 -- [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 100 · 🔀 1.9K · 📥 58 · 📦 1 · 📋 620 - 23% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/jfkirk/tensorrec) (👨‍💻 9 · 🔀 220 · 📦 26 · 📋 120 - 28% open · ⏱️ 04.02.2020): ``` - git clone https://github.com/microsoft/recommenders + git clone https://github.com/jfkirk/tensorrec + ``` +- [PyPi](https://pypi.org/project/tensorrec) (📥 310 / month): + ``` + pip install tensorrec ```
-
fastFM (🥉18 · ⭐ 940 · 💤) - fastFM：用于分解机的工具库。❗Unlicensed +
recmetrics (🥉18 · ⭐ 330) - A library of metrics for evaluating recommender systems. MIT -- [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 190 · 📥 400 · 📦 88 · 📋 110 - 43% open · ⏱️ 24.03.2021): +- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 13 · 🔀 74 · 📦 20 · 📋 16 - 37% open · ⏱️ 27.10.2021): ``` - git clone https://github.com/ibayer/fastFM + git clone https://github.com/statisticianinstilettos/recmetrics ``` -- [PyPi](https://pypi.org/project/fastfm) (📥 630 / month): +- [PyPi](https://pypi.org/project/recmetrics) (📥 1.1K / month): ``` - pip install fastfm + pip install recmetrics ```
-
Spotlight (🥉17 · ⭐ 2.6K · 💀) - 使用PyTorch的深度推荐系统模型实现。MIT +
Spotlight (🥉17 · ⭐ 2.6K · 💀) - Deep recommender models using PyTorch. MIT - [GitHub](https://github.com/maciejkula/spotlight) (👨‍💻 11 · 🔀 390 · 📋 110 - 55% open · ⏱️ 09.02.2020): @@ -7813,693 +7837,681 @@ _用于建立和评估推荐系统的库。_ conda install -c maciejkula spotlight ```
-
recmetrics (🥉17 · ⭐ 300) - 用于评估推荐系统的度量标准库。MIT - -- [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 12 · 🔀 69 · 📦 20 · 📋 14 - 35% open · ⏱️ 23.09.2021): - - ``` - git clone https://github.com/statisticianinstilettos/recmetrics - ``` -- [PyPi](https://pypi.org/project/recmetrics) (📥 650 / month): - ``` - pip install recmetrics - ``` -
-
Case Recommender (🥉16 · ⭐ 360) - Case Recommender：灵活且可扩展的Python推荐系统工具库。MIT +
fastFM (🥉17 · ⭐ 960 · 💤) - fastFM: A Library for Factorization Machines. ❗Unlicensed -- [GitHub](https://github.com/caserec/CaseRecommender) (👨‍💻 11 · 🔀 76 · 📦 9 · 📋 24 - 29% open · ⏱️ 17.06.2021): +- [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 190 · 📥 420 · 📦 91 · 📋 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) (📥 360 / month): +- [PyPi](https://pypi.org/project/fastfm): ``` - pip install caserecommender + pip install fastfm ```

-## 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 · ⭐ 7.6K) - 基于内部数据自动化回答问题的工具库。Apache-2 +
PySyft (🥇26 · ⭐ 7.8K) - A library for answering questions using data you cannot see. Apache-2 -- [GitHub](https://github.com/OpenMined/PySyft) (👨‍💻 420 · 🔀 1.7K · 📋 3K - 9% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/OpenMined/PySyft) (👨‍💻 430 · 🔀 1.7K · 📋 3K - 9% open · ⏱️ 10.12.2021): ``` git clone https://github.com/OpenMined/PySyft ``` -- [PyPi](https://pypi.org/project/syft) (📥 3.1K / month): +- [PyPi](https://pypi.org/project/syft) (📥 4.7K / month): ``` pip install syft ```
-
TensorFlow Privacy (🥈23 · ⭐ 1.5K) - 用于训练机器学习模型的库。Apache-2 +
TensorFlow Privacy (🥈23 · ⭐ 1.5K) - Library for training machine learning models with.. Apache-2 -- [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 43 · 🔀 310 · 📥 51 · 📋 140 - 40% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 43 · 🔀 330 · 📥 59 · 📋 140 - 39% open · ⏱️ 14.12.2021): ``` git clone https://github.com/tensorflow/privacy ``` -- [PyPi](https://pypi.org/project/tensorflow-privacy) (📥 17K / month): +- [PyPi](https://pypi.org/project/tensorflow-privacy) (📥 23K / month): ``` pip install tensorflow-privacy ```
-
Opacus (🥈22 · ⭐ 910) - 使用不同的隐私训练PyTorch模型。Apache-2 +
FATE (🥈22 · ⭐ 3.8K) - An Industrial Grade Federated Learning Framework. Apache-2 -- [GitHub](https://github.com/pytorch/opacus) (👨‍💻 33 · 🔀 140 · 📥 40 · 📦 53 · 📋 92 - 11% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 68 · 🔀 1.1K · 📋 1K - 33% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/pytorch/opacus - ``` -- [PyPi](https://pypi.org/project/opacus) (📥 27K / month): - ``` - pip install opacus + git clone https://github.com/FederatedAI/FATE ```
-
FATE (🥉20 · ⭐ 3.5K) - 工业级联邦学习框架。Apache-2 +
Opacus (🥈22 · ⭐ 1K) - Training PyTorch models with differential privacy. Apache-2 -- [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 62 · 🔀 1K · 📋 950 - 34% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/pytorch/opacus) (👨‍💻 40 · 🔀 160 · 📥 40 · 📦 69 · 📋 110 - 15% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/FederatedAI/FATE + git clone https://github.com/pytorch/opacus + ``` +- [PyPi](https://pypi.org/project/opacus) (📥 4K / month): + ``` + pip install opacus ```
-
TFEncrypted (🥉19 · ⭐ 940 · 💀) - TensorFlow中的加密机器学习框架。Apache-2 +
TFEncrypted (🥉19 · ⭐ 960 · 💀) - A Framework for Encrypted Machine Learning in TensorFlow. Apache-2 -- [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 170 · 📦 57 · 📋 410 - 42% open · ⏱️ 19.08.2020): +- [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 170 · 📦 58 · 📋 410 - 42% open · ⏱️ 19.08.2020): ``` git clone https://github.com/tf-encrypted/tf-encrypted ``` -- [PyPi](https://pypi.org/project/tf-encrypted) (📥 720 / month): +- [PyPi](https://pypi.org/project/tf-encrypted) (📥 570 / month): ``` pip install tf-encrypted ```
-
CrypTen (🥉16 · ⭐ 920) - 隐私保护的机器学习框架。MIT +
CrypTen (🥉17 · ⭐ 970) - A framework for Privacy Preserving Machine Learning. MIT -- [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 25 · 🔀 140 · 📦 11 · 📋 97 - 17% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 25 · 🔀 160 · 📦 12 · 📋 110 - 16% open · ⏱️ 15.12.2021): ``` git clone https://github.com/facebookresearch/CrypTen ``` -- [PyPi](https://pypi.org/project/crypten) (📥 830 / month): +- [PyPi](https://pypi.org/project/crypten) (📥 310 / month): ``` pip install crypten ```

-## 工作流程和实验跟踪 +## Workflow & Experiment Tracking -Back to top +Back to top -_图书馆组织，跟踪和可视化机器学习实验。_ +_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 · ⭐ 5.7K) - TensorFlow's Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 270 · 🔀 1.4K · 📦 81K · 📋 1.6K - 33% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 270 · 🔀 1.4K · 📦 88K · 📋 1.6K - 32% open · ⏱️ 16.12.2021): ``` git clone https://github.com/tensorflow/tensorboard ``` -- [PyPi](https://pypi.org/project/tensorboard) (📥 11M / month): +- [PyPi](https://pypi.org/project/tensorboard) (📥 13M / month): ``` pip install tensorboard ``` -- [Conda](https://anaconda.org/conda-forge/tensorboard) (📥 2.5M · ⏱️ 23.08.2021): +- [Conda](https://anaconda.org/conda-forge/tensorboard) (📥 2.7M · ⏱️ 10.11.2021): ``` 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 (🥇32 · ⭐ 1.5K) - A library for training and deploying machine learning.. Apache-2 -- [GitHub](https://github.com/aws/sagemaker-python-sdk) (👨‍💻 220 · 🔀 670 · 📦 880 · 📋 900 - 29% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/aws/sagemaker-python-sdk) (👨‍💻 240 · 🔀 700 · 📦 980 · 📋 930 - 31% open · ⏱️ 15.12.2021): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` -- [PyPi](https://pypi.org/project/sagemaker) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/sagemaker) (📥 2.3M / month): ``` pip install sagemaker ```
-
mlflow (🥇30 · ⭐ 10K) - 机器学习生命周期的开源平台。Apache-2 +
tensorboardX (🥇30 · ⭐ 7.2K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT -- [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 320 · 🔀 2.2K · 📋 1.9K - 39% open · ⏱️ 13.10.2021): - - ``` - git clone https://github.com/mlflow/mlflow - ``` -- [PyPi](https://pypi.org/project/mlflow) (📥 18M / month): - ``` - pip install mlflow - ``` -- [Conda](https://anaconda.org/conda-forge/mlflow) (📥 410K · ⏱️ 27.09.2021): - ``` - conda install -c conda-forge mlflow - ``` -
-
tensorboardX (🥇30 · ⭐ 7.1K) - pytorch（和链接器，mxnet，numpy，...）的张量板。MIT - -- [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 67 · 🔀 820 · 📥 340 · 📦 15K · 📋 420 - 14% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 67 · 🔀 830 · 📥 340 · 📦 16K · 📋 420 - 14% open · ⏱️ 12.09.2021): ``` git clone https://github.com/lanpa/tensorboardX ``` -- [PyPi](https://pypi.org/project/tensorboardX) (📥 790K / month): +- [PyPi](https://pypi.org/project/tensorboardX) (📥 680K / month): ``` pip install tensorboardX ``` -- [Conda](https://anaconda.org/conda-forge/tensorboardx) (📥 530K · ⏱️ 10.08.2021): +- [Conda](https://anaconda.org/conda-forge/tensorboardx) (📥 630K · ⏱️ 10.08.2021): ``` conda install -c conda-forge tensorboardx ```
-
PyCaret (🥇30 · ⭐ 4.1K) - Python中的开源代码，低代码机器学习库。MIT +
mlflow (🥇27 · ⭐ 11K) - Open source platform for the machine learning lifecycle. Apache-2 -- [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 62 · 🔀 930 · 📥 460 · 📦 1.4K · 📋 1.1K - 15% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 340 · 🔀 2.3K · 📋 2K - 40% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/pycaret/pycaret - ``` -- [PyPi](https://pypi.org/project/pycaret) (📥 200K / month): - ``` - pip install pycaret + git clone https://github.com/mlflow/mlflow ``` -
-
sacred (🥈28 · ⭐ 3.6K) - 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) (👨‍💻 94 · 🔀 320 · 📦 1.1K · 📋 520 - 17% open · ⏱️ 08.10.2021): - +- [PyPi](https://pypi.org/project/mlflow): ``` - git clone https://github.com/IDSIA/sacred + pip install mlflow ``` -- [PyPi](https://pypi.org/project/sacred) (📥 23K / month): +- [Conda](https://anaconda.org/conda-forge/mlflow) (📥 460K · ⏱️ 08.12.2021): ``` - pip install sacred + conda install -c conda-forge mlflow ```
-
DVC (🥈27 · ⭐ 8.7K · 📉) - 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 +
Catalyst (🥇27 · ⭐ 2.8K) - Accelerated deep learning R&D. Apache-2 -- [GitHub](https://github.com/iterative/dvc) (👨‍💻 240 · 🔀 820 · 📥 39K · 📋 3.3K - 15% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 350 · 📦 450 · 📋 320 - 1% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/iterative/dvc - ``` -- [PyPi](https://pypi.org/project/dvc) (📥 310K / month): - ``` - pip install dvc + git clone https://github.com/catalyst-team/catalyst ``` -- [Conda](https://anaconda.org/conda-forge/dvc) (📥 890K · ⏱️ 13.10.2021): +- [PyPi](https://pypi.org/project/catalyst) (📥 11K / month): ``` - conda install -c conda-forge dvc + pip install catalyst ```
-
Metaflow (🥈27 · ⭐ 4.7K) - 轻松构建和管理现实生活中的数据科学项目。Apache-2 +
Metaflow (🥈26 · ⭐ 5.1K) - Build and manage real-life data science projects with ease. Apache-2 -- [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 41 · 🔀 400 · 📦 210 · 📋 320 - 44% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 42 · 🔀 420 · 📦 230 · 📋 350 - 45% open · ⏱️ 16.12.2021): ``` git clone https://github.com/Netflix/metaflow ``` -- [PyPi](https://pypi.org/project/metaflow) (📥 20K / month): +- [PyPi](https://pypi.org/project/metaflow): ``` pip install metaflow ``` -- [Conda](https://anaconda.org/conda-forge/metaflow) (📥 25K · ⏱️ 05.10.2021): +- [Conda](https://anaconda.org/conda-forge/metaflow) (📥 29K · ⏱️ 09.12.2021): ``` conda install -c conda-forge metaflow ```
-
kaggle (🥈27 · ⭐ 4.4K · 💤) - 官方Kaggle API。Apache-2 - -- [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 850 · 📦 6.7K · 📋 310 - 55% open · ⏱️ 15.03.2021): - - ``` - git clone https://github.com/Kaggle/kaggle-api - ``` -- [PyPi](https://pypi.org/project/kaggle) (📥 280K / month): - ``` - pip install kaggle - ``` -- [Conda](https://anaconda.org/conda-forge/kaggle) (📥 71K · ⏱️ 16.03.2021): - ``` - conda install -c conda-forge kaggle - ``` -
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ClearML (🥈27 · ⭐ 2.7K) - ClearML-自动精简工具套件。Apache-2 +
PyCaret (🥈26 · ⭐ 4.6K) - An open-source, low-code machine learning library in Python. MIT -- [GitHub](https://github.com/allegroai/clearml) (👨‍💻 39 · 🔀 370 · 📥 370 · 📦 120 · 📋 390 - 31% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 68 · 🔀 1K · 📥 500 · 📦 1.6K · 📋 1.2K - 15% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/allegroai/clearml - ``` -- [PyPi](https://pypi.org/project/clearml) (📥 38K / month): - ``` - pip install clearml + git clone https://github.com/pycaret/pycaret ``` -- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (📥 30K · ⏱️ 05.10.2020): +- [PyPi](https://pypi.org/project/pycaret): ``` - docker pull allegroai/trains + pip install pycaret ```
-
Catalyst (🥈27 · ⭐ 2.7K) - 加快深度学习研发。Apache-2 +
wandb client (🥈26 · ⭐ 3.6K) - A tool for visualizing and tracking your machine learning.. MIT -- [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 340 · 📦 420 · 📋 320 - 3% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/wandb/client) (👨‍💻 97 · 🔀 280 · 📋 1.4K - 17% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/catalyst-team/catalyst + git clone https://github.com/wandb/client ``` -- [PyPi](https://pypi.org/project/catalyst) (📥 12K / month): +- [PyPi](https://pypi.org/project/wandb) (📥 540K / month): ``` - pip install catalyst + pip install wandb ```
-
snakemake (🥈27 · ⭐ 1.1K) - 工作流管理系统snakemake。MIT +
snakemake (🥈26 · ⭐ 1.2K) - This is the development home of the workflow management system.. MIT -- [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 220 · 🔀 260 · 📦 930 · 📋 740 - 62% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 230 · 🔀 270 · 📦 990 · 📋 790 - 62% open · ⏱️ 09.12.2021): ``` git clone https://github.com/snakemake/snakemake ``` -- [PyPi](https://pypi.org/project/snakemake) (📥 22K / month): +- [PyPi](https://pypi.org/project/snakemake): ``` pip install snakemake ``` -- [Conda](https://anaconda.org/bioconda/snakemake) (📥 340K · ⏱️ 30.09.2021): +- [Conda](https://anaconda.org/bioconda/snakemake) (📥 360K · ⏱️ 09.12.2021): ``` conda install -c bioconda snakemake ```
-
wandb client (🥈26 · ⭐ 3.4K) - 用于可视化和跟踪机器学习的工具。MIT +
VisualDL (🥈25 · ⭐ 4.3K) - Deep Learning Visualization Toolkit. Apache-2 -- [GitHub](https://github.com/wandb/client) (👨‍💻 93 · 🔀 260 · 📋 1.3K - 25% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 31 · 🔀 570 · 📥 160 · 📦 840 · 📋 390 - 14% open · ⏱️ 26.11.2021): ``` - git clone https://github.com/wandb/client + git clone https://github.com/PaddlePaddle/VisualDL ``` -- [PyPi](https://pypi.org/project/wandb) (📥 470K / month): +- [PyPi](https://pypi.org/project/visualdl) (📥 53K / month): ``` - pip install wandb + pip install visualdl ```
-
VisualDL (🥈25 · ⭐ 4.2K) - 深度学习可视化工具包。Apache-2 +
ClearML (🥈25 · ⭐ 2.9K) - ClearML - Auto-Magical Suite of tools to streamline your ML.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 31 · 🔀 570 · 📥 150 · 📦 700 · 📋 380 - 13% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/allegroai/clearml) (👨‍💻 42 · 🔀 380 · 📥 380 · 📦 170 · 📋 420 - 32% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/PaddlePaddle/VisualDL + git clone https://github.com/allegroai/clearml ``` -- [PyPi](https://pypi.org/project/visualdl) (📥 24K / month): +- [PyPi](https://pypi.org/project/clearml): ``` - pip install visualdl + pip install clearml + ``` +- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (📥 30K · ⏱️ 05.10.2020): + ``` + docker pull allegroai/trains ```
-
AzureML SDK (🥈25 · ⭐ 2.7K) - 带有ML的Python笔记本和带有Azure的深度学习示例。MIT +
AzureML SDK (🥈25 · ⭐ 2.8K) - Python notebooks with ML and deep learning examples with Azure.. MIT -- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 57 · 🔀 1.9K · 📥 430 · 📋 1.2K - 14% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 57 · 🔀 1.9K · 📥 430 · 📋 1.2K - 16% open · ⏱️ 13.12.2021): ``` git clone https://github.com/Azure/MachineLearningNotebooks ``` -- [PyPi](https://pypi.org/project/azureml-sdk) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/azureml-sdk) (📥 1.9M / month): ``` pip install azureml-sdk ```
-
ml-metadata (🥈25 · ⭐ 390) - 用于记录和检索与ML相关的元数据。Apache-2 +
DVC (🥈24 · ⭐ 9K) - Data Version Control | Git for Data & Models. Apache-2 -- [GitHub](https://github.com/google/ml-metadata) (👨‍💻 13 · 🔀 67 · 📥 1.5K · 📦 150 · 📋 70 - 24% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/iterative/dvc) (👨‍💻 250 · 🔀 850 · 📥 48K · 📋 3.4K - 16% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/google/ml-metadata + git clone https://github.com/iterative/dvc ``` -- [PyPi](https://pypi.org/project/ml-metadata) (📥 880K / month): +- [PyPi](https://pypi.org/project/dvc) (📥 360K / month): ``` - pip install ml-metadata + pip install dvc + ``` +- [Conda](https://anaconda.org/conda-forge/dvc) (📥 950K · ⏱️ 14.12.2021): + ``` + conda install -c conda-forge dvc + ``` +
+
sacred (🥈24 · ⭐ 3.7K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT + +- [GitHub](https://github.com/IDSIA/sacred) (👨‍💻 95 · 🔀 340 · 📦 1.1K · 📋 520 - 17% open · ⏱️ 05.11.2021): + + ``` + git clone https://github.com/IDSIA/sacred + ``` +- [PyPi](https://pypi.org/project/sacred): + ``` + pip install sacred ```
-
livelossplot (🥉23 · ⭐ 1.1K) - Jupyter Notebook for Keras的实时训练loss图。MIT +
livelossplot (🥉23 · ⭐ 1.1K) - Live training loss plot in Jupyter Notebook for Keras,.. MIT -- [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 650 · 📋 73 - 4% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 690 · 📋 73 - 4% open · ⏱️ 12.10.2021): ``` git clone https://github.com/stared/livelossplot ``` -- [PyPi](https://pypi.org/project/livelossplot) (📥 76K / month): +- [PyPi](https://pypi.org/project/livelossplot) (📥 79K / month): ``` pip install livelossplot ```
-
knockknock (🥉22 · ⭐ 2.2K · 💀) - 当您的训练结束后通知您。MIT +
knockknock (🥉20 · ⭐ 2.3K · 💀) - Knock Knock: Get notified when your training ends with only two.. MIT -- [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 190 · 📦 210 · 📋 37 - 37% open · ⏱️ 16.03.2020): +- [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 190 · 📦 230 · 📋 37 - 37% open · ⏱️ 16.03.2020): ``` git clone https://github.com/huggingface/knockknock ``` -- [PyPi](https://pypi.org/project/knockknock) (📥 1K / month): +- [PyPi](https://pypi.org/project/knockknock): ``` pip install knockknock ``` -- [Conda](https://anaconda.org/conda-forge/knockknock) (📥 7.9K · ⏱️ 17.03.2020): +- [Conda](https://anaconda.org/conda-forge/knockknock) (📥 8.3K · ⏱️ 17.03.2020): ``` conda install -c conda-forge knockknock ```
-
Labml (🥉21 · ⭐ 760) - 从您的手机监控深度学习模型训练和硬件使用情况。MIT +
hiddenlayer (🥉20 · ⭐ 1.6K · 💀) - Neural network graphs and training metrics for.. MIT -- [GitHub](https://github.com/labmlai/labml) (🔀 52 · 📦 35 · 📋 24 - 62% open · ⏱️ 06.09.2021): +- [GitHub](https://github.com/waleedka/hiddenlayer) (👨‍💻 6 · 🔀 220 · 📦 88 · 📋 80 - 57% open · ⏱️ 24.04.2020): ``` - git clone https://github.com/lab-ml/labml + git clone https://github.com/waleedka/hiddenlayer ``` -- [PyPi](https://pypi.org/project/labml) (📥 800 / month): +- [PyPi](https://pypi.org/project/hiddenlayer) (📥 1.9K / month): ``` - pip install labml + pip install hiddenlayer + ``` +
+
lore (🥉20 · ⭐ 1.5K · 💀) - Lore makes machine learning approachable for Software Engineers and.. MIT + +- [GitHub](https://github.com/instacart/lore) (👨‍💻 22 · 🔀 120 · 📦 17 · 📋 34 - 47% open · ⏱️ 11.05.2020): + + ``` + git clone https://github.com/instacart/lore + ``` +- [PyPi](https://pypi.org/project/lore) (📥 650 / month): + ``` + pip install lore ```
-
TNT (🥉20 · ⭐ 1.3K · 💤) - 用于记录和可视化，加载和训练的简单工具。BSD-3 +
TNT (🥉20 · ⭐ 1.4K · 💤) - Simple tools for logging and visualizing, loading and training. BSD-3 - [GitHub](https://github.com/pytorch/tnt) (👨‍💻 35 · 🔀 190 · 📋 58 - 39% open · ⏱️ 05.01.2021): ``` git clone https://github.com/pytorch/tnt ``` -- [PyPi](https://pypi.org/project/torchnet) (📥 13K / month): +- [PyPi](https://pypi.org/project/torchnet) (📥 17K / month): ``` pip install torchnet ```
-
TensorWatch (🥉19 · ⭐ 3.2K · 💤) - Python机器学习的调试，监视和可视化。MIT +
ml-metadata (🥉20 · ⭐ 410) - For recording and retrieving metadata associated with ML.. Apache-2 -- [GitHub](https://github.com/microsoft/tensorwatch) (👨‍💻 13 · 🔀 340 · 📦 60 · 📋 65 - 76% open · ⏱️ 15.01.2021): +- [GitHub](https://github.com/google/ml-metadata) (👨‍💻 13 · 🔀 75 · 📥 1.7K · 📦 170 · 📋 74 - 24% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/microsoft/tensorwatch + git clone https://github.com/google/ml-metadata ``` -- [PyPi](https://pypi.org/project/tensorwatch) (📥 3.6K / month): +- [PyPi](https://pypi.org/project/ml-metadata): ``` - pip install tensorwatch + pip install ml-metadata ```
-
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 +
kaggle (🥉19 · ⭐ 4.5K · 💤) - Official Kaggle API. Apache-2 -- [GitHub](https://github.com/instacart/lore) (👨‍💻 22 · 🔀 120 · 📦 16 · 📋 34 - 47% open · ⏱️ 11.05.2020): +- [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 870 · 📋 320 - 54% open · ⏱️ 15.03.2021): ``` - git clone https://github.com/instacart/lore + git clone https://github.com/Kaggle/kaggle-api ``` -- [PyPi](https://pypi.org/project/lore) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/kaggle): ``` - pip install lore + pip install kaggle + ``` +- [Conda](https://anaconda.org/conda-forge/kaggle) (📥 75K · ⏱️ 15.11.2021): + ``` + conda install -c conda-forge kaggle ```
-
hiddenlayer (🥉19 · ⭐ 1.5K · 💀) - 神经网络图和训练指标。MIT +
TensorWatch (🥉19 · ⭐ 3.2K · 💤) - Debugging, monitoring and visualization for Python Machine.. MIT -- [GitHub](https://github.com/waleedka/hiddenlayer) (👨‍💻 6 · 🔀 220 · 📦 84 · 📋 80 - 57% open · ⏱️ 24.04.2020): +- [GitHub](https://github.com/microsoft/tensorwatch) (👨‍💻 13 · 🔀 340 · 📦 65 · 📋 65 - 76% open · ⏱️ 15.01.2021): ``` - git clone https://github.com/waleedka/hiddenlayer + git clone https://github.com/microsoft/tensorwatch ``` -- [PyPi](https://pypi.org/project/hiddenlayer) (📥 2.8K / month): +- [PyPi](https://pypi.org/project/tensorwatch) (📥 6.1K / month): ``` - pip install hiddenlayer + pip install tensorwatch ```
-
Guild AI (🥉19 · ⭐ 630) - 实验跟踪，ML开发人员工具库。Apache-2 +
Guild AI (🥉19 · ⭐ 640) - Experiment tracking, ML developer tools. Apache-2 -- [GitHub](https://github.com/guildai/guildai) (👨‍💻 18 · 🔀 46 · 📦 38 · 📋 280 - 39% open · ⏱️ 12.10.2021): +- [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) (📥 5.3K / month): +- [PyPi](https://pypi.org/project/guildai) (📥 2.8K / month): ``` pip install guildai ```
-
gokart (🥉19 · ⭐ 220) - 数据管道库luigi的包装。MIT +
MXBoard (🥉19 · ⭐ 330 · 💀) - Logging MXNet data for visualization in TensorBoard. Apache-2 -- [GitHub](https://github.com/m3dev/gokart) (👨‍💻 28 · 🔀 36 · 📋 59 - 22% open · ⏱️ 17.09.2021): +- [GitHub](https://github.com/awslabs/mxboard) (👨‍💻 9 · 🔀 47 · 📦 130 · 📋 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) (📥 620 / month): +- [PyPi](https://pypi.org/project/mxboard) (📥 5.2K / month): ``` - pip install gokart + pip install mxboard ```
-
Studio.ml (🥉18 · ⭐ 370) - Studio：简化和加快模型构建过程。Apache-2 +
Labml (🥉18 · ⭐ 890) - Monitor deep learning model training and hardware usage from your mobile.. MIT -- [GitHub](https://github.com/studioml/studio) (👨‍💻 21 · 🔀 51 · 📦 5 · 📋 250 - 22% open · ⏱️ 14.09.2021): +- [GitHub](https://github.com/labmlai/labml) (👨‍💻 6 · 🔀 58 · 📦 39 · 📋 25 - 60% open · ⏱️ 06.09.2021): ``` - git clone https://github.com/studioml/studio + git clone https://github.com/lab-ml/labml ``` -- [PyPi](https://pypi.org/project/studioml): +- [PyPi](https://pypi.org/project/labml): ``` - pip install studioml + pip install labml ```
-
MXBoard (🥉18 · ⭐ 330 · 💀) - MXNet日志记录器，以在TensorBoard中进行可视化。Apache-2 +
Studio.ml (🥉17 · ⭐ 370) - Studio: Simplify and expedite model building process. Apache-2 -- [GitHub](https://github.com/awslabs/mxboard) (👨‍💻 9 · 🔀 45 · 📦 120 · 📋 31 - 51% open · ⏱️ 24.01.2020): +- [GitHub](https://github.com/studioml/studio) (👨‍💻 21 · 🔀 51 · 📦 5 · 📋 250 - 22% open · ⏱️ 14.09.2021): ``` - git clone https://github.com/awslabs/mxboard + git clone https://github.com/studioml/studio ``` -- [PyPi](https://pypi.org/project/mxboard) (📥 2K / month): +- [PyPi](https://pypi.org/project/studioml): ``` - pip install mxboard + pip install studioml ```
-
aim (🥉17 · ⭐ 1.4K) - 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 +
gokart (🥉17 · ⭐ 230) - A wrapper of the data pipeline library luigi. MIT -- [GitHub](https://github.com/aimhubio/aim) (👨‍💻 20 · 🔀 84 · 📦 37 · 📋 190 - 51% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/m3dev/gokart) (👨‍💻 29 · 🔀 38 · 📋 62 - 17% open · ⏱️ 16.11.2021): ``` - git clone https://github.com/aimhubio/aim + git clone https://github.com/m3dev/gokart ``` -- [PyPi](https://pypi.org/project/aim) (📥 4.9K / month): +- [PyPi](https://pypi.org/project/gokart): ``` - pip install aim + pip install gokart ```
-
TensorBoard Logger (🥉15 · ⭐ 610 · 💀) - 简易TensorBoard日志记录库。MIT +
aim (🥉16 · ⭐ 1.9K) - Aim a super-easy way to record, search and compare 1000s of ML training.. Apache-2 -- [GitHub](https://github.com/TeamHG-Memex/tensorboard_logger) (👨‍💻 5 · 🔀 50 · 📋 23 - 34% open · ⏱️ 21.10.2019): +- [GitHub](https://github.com/aimhubio/aim) (👨‍💻 22 · 🔀 110 · 📦 44 · 📋 260 - 33% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/TeamHG-Memex/tensorboard_logger + git clone https://github.com/aimhubio/aim ``` -- [PyPi](https://pypi.org/project/tensorboard_logger) (📥 51K / month): +- [PyPi](https://pypi.org/project/aim): ``` - pip install tensorboard_logger + pip install aim ```
-
quinn (🥉15 · ⭐ 280 · 💤) - pyspark方法可提高开发人员的工作效率。❗Unlicensed +
quinn (🥉16 · ⭐ 300 · 💤) - pyspark methods to enhance developer productivity. ❗Unlicensed -- [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 33 · 📋 23 - 60% open · ⏱️ 09.02.2021): +- [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 40 · 📋 23 - 60% open · ⏱️ 09.02.2021): ``` git clone https://github.com/MrPowers/quinn ``` -- [PyPi](https://pypi.org/project/quinn) (📥 400K / month): +- [PyPi](https://pypi.org/project/quinn) (📥 460K / month): ``` pip install quinn ```
-
steppy (🥉15 · ⭐ 130 · 💀) - 轻量级的Python库，可进行快速且可重复的实验。MIT +
SKLL (🥉15 · ⭐ 530) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗Unlicensed -- [GitHub](https://github.com/minerva-ml/steppy) (👨‍💻 5 · 🔀 33 · 📦 40 · 📋 63 - 20% open · ⏱️ 23.11.2018): +- [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 36 · 🔀 63 · 📥 11 · 📦 34 · 📋 390 - 8% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/minerva-ml/steppy + git clone https://github.com/EducationalTestingService/skll ``` -- [PyPi](https://pypi.org/project/steppy) (📥 63 / month): +- [PyPi](https://pypi.org/project/skll) (📥 400 / month): ``` - pip install steppy + pip install skll ```
-
SKLL (🥉14 · ⭐ 520) - SciKit学习实验室（SKLL）使机器学习易于操作。❗Unlicensed +
steppy (🥉14 · ⭐ 130 · 💀) - Lightweight, Python library for fast and reproducible experimentation. MIT -- [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 35 · 🔀 62 · 📥 11 · 📦 31 · 📋 390 - 10% open · ⏱️ 30.04.2021): +- [GitHub](https://github.com/minerva-ml/steppy) (👨‍💻 5 · 🔀 33 · 📦 42 · 📋 63 - 20% open · ⏱️ 23.11.2018): ``` - git clone https://github.com/EducationalTestingService/skll + git clone https://github.com/minerva-ml/steppy ``` -- [PyPi](https://pypi.org/project/skll) (📥 490 / month): +- [PyPi](https://pypi.org/project/steppy): ``` - pip install skll + pip install steppy ```
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datmo (🥉14 · ⭐ 340 · 💀) - 面向数据科学家的开源生产模型管理工具。MIT +
datmo (🥉13 · ⭐ 340 · 💀) - Open source production model management tool for data scientists. MIT -- [GitHub](https://github.com/datmo/datmo) (👨‍💻 6 · 🔀 27 · 📦 5 · 📋 180 - 15% open · ⏱️ 29.11.2019): +- [GitHub](https://github.com/datmo/datmo) (👨‍💻 6 · 🔀 28 · 📦 5 · 📋 180 - 15% open · ⏱️ 29.11.2019): ``` git clone https://github.com/datmo/datmo ``` -- [PyPi](https://pypi.org/project/datmo) (📥 130 / month): +- [PyPi](https://pypi.org/project/datmo): ``` pip install datmo ```
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ModelChimp (🥉14 · ⭐ 120) - 机器和深度学习项目的实验跟踪。BSD-2 +
ModelChimp (🥉13 · ⭐ 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) (📥 83 / month): +- [PyPi](https://pypi.org/project/modelchimp): ``` pip install modelchimp ``` -- [Docker Hub](https://hub.docker.com/r/modelchimp/modelchimp-server) (📥 640 · ⏱️ 09.04.2019): +- [Docker Hub](https://hub.docker.com/r/modelchimp/modelchimp-server) (📥 650 · ⏱️ 09.04.2019): ``` docker pull modelchimp/modelchimp-server ```
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traintool (🥉7 · ⭐ 9 · 💤) - 一站式训练现成的机器学习模型。Apache-2 +
TensorBoard Logger (🥉12 · ⭐ 620 · 💀) - Log TensorBoard events without touching TensorFlow. 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 + ``` +
+
traintool (🥉7 · ⭐ 9 · 💤) - Train off-the-shelf machine learning models in one.. Apache-2 - [GitHub](https://github.com/jrieke/traintool) (🔀 1 · ⏱️ 12.03.2021): ``` git clone https://github.com/jrieke/traintool ``` -- [PyPi](https://pypi.org/project/traintool) (📥 17 / month): +- [PyPi](https://pypi.org/project/traintool) (📥 20 / 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 · ⭐ 11K) - 机器学习互操作性的开放标准。Apache-2 +
onnx (🥇35 · ⭐ 12K) - Open standard for machine learning interoperability. Apache-2 -- [GitHub](https://github.com/onnx/onnx) (👨‍💻 210 · 🔀 2.1K · 📥 17K · 📦 4.3K · 📋 1.6K - 25% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/onnx/onnx) (👨‍💻 220 · 🔀 2.2K · 📥 17K · 📦 5K · 📋 1.7K - 23% open · ⏱️ 15.12.2021): ``` git clone https://github.com/onnx/onnx ``` -- [PyPi](https://pypi.org/project/onnx) (📥 1.5M / month): +- [PyPi](https://pypi.org/project/onnx) (📥 1.2M / month): ``` pip install onnx ``` -- [Conda](https://anaconda.org/conda-forge/onnx) (📥 290K · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/onnx) (📥 330K · ⏱️ 14.12.2021): ``` conda install -c conda-forge onnx ```
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Core ML Tools (🥇24 · ⭐ 2.4K) - 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 · ⭐ 2.5K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 -- [GitHub](https://github.com/apple/coremltools) (👨‍💻 120 · 🔀 360 · 📥 3.5K · 📦 640 · 📋 790 - 43% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/apple/coremltools) (👨‍💻 120 · 🔀 370 · 📥 3.8K · 📦 700 · 📋 830 - 38% open · ⏱️ 14.12.2021): ``` git clone https://github.com/apple/coremltools ``` -- [PyPi](https://pypi.org/project/coremltools) (📥 53K / month): +- [PyPi](https://pypi.org/project/coremltools) (📥 77K / month): ``` pip install coremltools ```
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TorchServe (🥇24 · ⭐ 2.1K) - 在PyTorch上进行模型服务。Apache-2 +
TorchServe (🥈24 · ⭐ 2.3K) - Model Serving on PyTorch. Apache-2 -- [GitHub](https://github.com/pytorch/serve) (👨‍💻 81 · 🔀 380 · 📥 660 · 📋 690 - 14% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/pytorch/serve) (👨‍💻 94 · 🔀 420 · 📥 720 · 📋 740 - 14% open · ⏱️ 15.12.2021): ``` git clone https://github.com/pytorch/serve ``` -- [PyPi](https://pypi.org/project/torchserve) (📥 11K / month): +- [PyPi](https://pypi.org/project/torchserve): ``` pip install torchserve ``` -- [Conda](https://anaconda.org/pytorch/torchserve) (📥 14K · ⏱️ 02.08.2021): +- [Conda](https://anaconda.org/pytorch/torchserve) (📥 17K · ⏱️ 19.11.2021): ``` conda install -c pytorch torchserve ``` -- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (📥 930K · ⭐ 8 · ⏱️ 02.08.2021): +- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (📥 950K · ⭐ 9 · ⏱️ 22.11.2021): ``` docker pull pytorch/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 +
cortex (🥈23 · ⭐ 7.6K) - Cost-effective serverless computing at scale. Apache-2 -- [GitHub](https://github.com/cortexlabs/cortex) (👨‍💻 22 · 🔀 570 · 📋 1.1K - 9% open · ⏱️ 05.08.2021): +- [GitHub](https://github.com/cortexlabs/cortex) (👨‍💻 23 · 🔀 580 · 📋 1.1K - 9% open · ⏱️ 14.12.2021): ``` git clone https://github.com/cortexlabs/cortex ``` -- [PyPi](https://pypi.org/project/cortex) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/cortex) (📥 1.2K / month): ``` pip install cortex ```
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mmdnn (🥈22 · ⭐ 5.4K · 💀) - 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 · ⭐ 5.5K · 💀) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT -- [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 940 · 📥 3.5K · 📦 66 · 📋 600 - 52% open · ⏱️ 14.08.2020): +- [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 950 · 📥 3.5K · 📦 66 · 📋 610 - 52% open · ⏱️ 14.08.2020): ``` git clone https://github.com/Microsoft/MMdnn ``` -- [PyPi](https://pypi.org/project/mmdnn) (📥 440 / month): +- [PyPi](https://pypi.org/project/mmdnn) (📥 1.1K / month): ``` pip install mmdnn ```
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Hummingbird (🥈22 · ⭐ 2.6K) - 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 +
Hummingbird (🥉22 · ⭐ 2.7K) - Hummingbird compiles trained ML models into tensor computation for.. MIT -- [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 25 · 🔀 200 · 📥 140 · 📦 19 · 📋 220 - 21% open · ⏱️ 27.09.2021): +- [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 27 · 🔀 200 · 📥 150 · 📦 20 · 📋 230 - 21% open · ⏱️ 16.12.2021): ``` git clone https://github.com/microsoft/hummingbird ``` -- [PyPi](https://pypi.org/project/hummingbird-ml) (📥 3.9K / month): +- [PyPi](https://pypi.org/project/hummingbird-ml) (📥 3.1K / month): ``` pip install hummingbird-ml ```
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m2cgen (🥈22 · ⭐ 1.9K) - 将ML模型转换成本机代码（Java，C，Python，Go，JavaScript）等。MIT +
m2cgen (🥉22 · ⭐ 2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT -- [GitHub](https://github.com/BayesWitnesses/m2cgen) (👨‍💻 12 · 🔀 160 · 📦 6 · 📋 79 - 40% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/BayesWitnesses/m2cgen) (👨‍💻 12 · 🔀 160 · 📦 7 · 📋 82 - 41% open · ⏱️ 25.11.2021): ``` git clone https://github.com/BayesWitnesses/m2cgen ``` -- [PyPi](https://pypi.org/project/m2cgen) (📥 45K / month): +- [PyPi](https://pypi.org/project/m2cgen) (📥 54K / month): ``` pip install m2cgen ```
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pytorch2keras (🥉17 · ⭐ 750) - PyTorch到Keras模型转换器。MIT +
sklearn-porter (🥉18 · ⭐ 1.1K · 💀) - Transpile trained scikit-learn estimators to C, Java,.. MIT -- [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 130 · 📦 24 · 📋 120 - 41% open · ⏱️ 06.08.2021): +- [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 11 · 🔀 140 · 📋 67 - 56% open · ⏱️ 18.12.2019): ``` - git clone https://github.com/nerox8664/pytorch2keras + git clone https://github.com/nok/sklearn-porter ``` -- [PyPi](https://pypi.org/project/pytorch2keras) (📥 640 / month): +- [PyPi](https://pypi.org/project/sklearn-porter) (📥 520 / month): ``` - pip install pytorch2keras + pip install sklearn-porter ```
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Larq Compute Engine (🥉17 · ⭐ 170) - 高度优化的二值化推理引擎。Apache-2 +
Larq Compute Engine (🥉17 · ⭐ 180) - Highly optimized inference engine for Binarized.. Apache-2 -- [GitHub](https://github.com/larq/compute-engine) (👨‍💻 17 · 🔀 26 · 📥 300 · 📦 4 · 📋 120 - 18% open · ⏱️ 08.09.2021): +- [GitHub](https://github.com/larq/compute-engine) (👨‍💻 18 · 🔀 28 · 📥 330 · 📦 4 · 📋 130 - 9% open · ⏱️ 15.12.2021): ``` git clone https://github.com/larq/compute-engine @@ -8509,413 +8521,401 @@ _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 pip install larq-compute-engine ```
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sklearn-porter (🥉16 · ⭐ 1.1K · 💀) - 将经过训练的scikit-learn估计器转换为C，Java等。MIT +
pytorch2keras (🥉16 · ⭐ 760) - PyTorch to Keras model convertor. MIT -- [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 11 · 🔀 140 · 📋 67 - 56% open · ⏱️ 18.12.2019): +- [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 130 · 📦 26 · 📋 120 - 42% open · ⏱️ 06.08.2021): ``` - git clone https://github.com/nok/sklearn-porter + git clone https://github.com/nerox8664/pytorch2keras ``` -- [PyPi](https://pypi.org/project/sklearn-porter) (📥 550 / month): +- [PyPi](https://pypi.org/project/pytorch2keras) (📥 710 / month): ``` - pip install sklearn-porter + pip install pytorch2keras ```
-
tfdeploy (🥉15 · ⭐ 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 +
tfdeploy (🥉14 · ⭐ 340 · 💤) - 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): ``` git clone https://github.com/riga/tfdeploy ``` -- [PyPi](https://pypi.org/project/tfdeploy) (📥 140 / month): +- [PyPi](https://pypi.org/project/tfdeploy): ``` 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 (🥇34 · ⭐ 14K) - 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 · ⭐ 15K) - A game theoretic approach to explain the output of any machine learning model. MIT -- [GitHub](https://github.com/slundberg/shap) (👨‍💻 160 · 🔀 2.1K · 📦 3.5K · 📋 1.7K - 67% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/slundberg/shap) (👨‍💻 160 · 🔀 2.2K · 📦 4K · 📋 1.8K - 68% open · ⏱️ 04.12.2021): ``` git clone https://github.com/slundberg/shap ``` -- [PyPi](https://pypi.org/project/shap) (📥 4M / month): +- [PyPi](https://pypi.org/project/shap) (📥 4.3M / month): ``` pip install shap ``` -- [Conda](https://anaconda.org/conda-forge/shap) (📥 650K · ⏱️ 29.04.2021): +- [Conda](https://anaconda.org/conda-forge/shap) (📥 720K · ⏱️ 24.10.2021): ``` conda install -c conda-forge shap ```
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Lime (🥇29 · ⭐ 9.2K) - Lime：解释任何机器学习分类器的预测。BSD-2 +
Lime (🥇30 · ⭐ 9.4K) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 -- [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.5K · 📦 1.6K · 📋 540 - 2% open · ⏱️ 29.07.2021): +- [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.5K · 📦 1.8K · 📋 550 - 3% open · ⏱️ 29.07.2021): ``` git clone https://github.com/marcotcr/lime ``` -- [PyPi](https://pypi.org/project/lime) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/lime) (📥 1.3M / month): ``` pip install lime ``` -- [Conda](https://anaconda.org/conda-forge/lime) (📥 83K · ⏱️ 28.06.2020): +- [Conda](https://anaconda.org/conda-forge/lime) (📥 89K · ⏱️ 28.06.2020): ``` conda install -c conda-forge lime ```
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InterpretML (🥇28 · ⭐ 4.1K) - 拟合可解释的模型。对机器学习黑匣子进行解释。MIT +
pyLDAvis (🥇29 · ⭐ 1.6K · 💤) - Python library for interactive topic model visualization... BSD-3 -- [GitHub](https://github.com/interpretml/interpret) (👨‍💻 27 · 🔀 510 · 📦 120 · 📋 240 - 33% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/bmabey/pyLDAvis) (👨‍💻 32 · 🔀 320 · 📦 2.9K · 📋 160 - 51% open · ⏱️ 24.03.2021): ``` - git clone https://github.com/interpretml/interpret + git clone https://github.com/bmabey/pyLDAvis ``` -- [PyPi](https://pypi.org/project/interpret) (📥 70K / month): +- [PyPi](https://pypi.org/project/pyldavis) (📥 590K / month): ``` - pip install interpret + pip install pyldavis + ``` +- [Conda](https://anaconda.org/conda-forge/pyldavis) (📥 32K · ⏱️ 24.03.2021): + ``` + conda install -c conda-forge pyldavis ```
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Captum (🥇27 · ⭐ 2.7K) - PyTorch的模型可解释性和理解。BSD-3 +
InterpretML (🥇27 · ⭐ 4.4K) - Fit interpretable models. Explain blackbox machine learning. MIT -- [GitHub](https://github.com/pytorch/captum) (👨‍💻 77 · 🔀 280 · 📦 280 · 📋 280 - 23% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/interpretml/interpret) (👨‍💻 28 · 🔀 540 · 📦 140 · 📋 260 - 31% open · ⏱️ 11.12.2021): ``` - git clone https://github.com/pytorch/captum + git clone https://github.com/interpretml/interpret ``` -- [PyPi](https://pypi.org/project/captum) (📥 30K / month): +- [PyPi](https://pypi.org/project/interpret) (📥 54K / month): ``` - pip install captum + pip install interpret ```
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dtreeviz (🥇27 · ⭐ 1.8K) - 用于决策树可视化和模型解释的python库。MIT +
Captum (🥇27 · ⭐ 2.8K) - Model interpretability and understanding for PyTorch. BSD-3 -- [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 16 · 🔀 220 · 📦 240 · 📋 100 - 17% open · ⏱️ 10.09.2021): +- [GitHub](https://github.com/pytorch/captum) (👨‍💻 77 · 🔀 290 · 📦 340 · 📋 300 - 21% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/parrt/dtreeviz + git clone https://github.com/pytorch/captum ``` -- [PyPi](https://pypi.org/project/dtreeviz) (📥 180K / month): +- [PyPi](https://pypi.org/project/captum) (📥 37K / month): ``` - pip install dtreeviz + pip install captum ```
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pyLDAvis (🥇27 · ⭐ 1.5K · 💤) - 用于交互式主题模型可视化的Python库。BSD-3 +
Model Analysis (🥈26 · ⭐ 1.1K) - Model analysis tools for TensorFlow. Apache-2 -- [GitHub](https://github.com/bmabey/pyLDAvis) (👨‍💻 32 · 🔀 310 · 📦 2.7K · 📋 160 - 50% open · ⏱️ 24.03.2021): +- [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 36 · 🔀 220 · 📋 61 - 22% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/bmabey/pyLDAvis - ``` -- [PyPi](https://pypi.org/project/pyldavis) (📥 420K / month): - ``` - pip install pyldavis + git clone https://github.com/tensorflow/model-analysis ``` -- [Conda](https://anaconda.org/conda-forge/pyldavis) (📥 30K · ⏱️ 24.03.2021): +- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (📥 7M / month): ``` - conda install -c conda-forge pyldavis + pip install tensorflow-model-analysis ```
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arviz (🥇27 · ⭐ 1.1K) - 使用Python探索性分析贝叶斯模型。Apache-2 +
arviz (🥈26 · ⭐ 1.1K) - Exploratory analysis of Bayesian models with Python. Apache-2 -- [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 95 · 🔀 240 · 📥 110 · 📦 1.4K · 📋 670 - 23% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 110 · 🔀 250 · 📥 110 · 📦 1.7K · 📋 690 - 19% open · ⏱️ 15.12.2021): ``` git clone https://github.com/arviz-devs/arviz ``` -- [PyPi](https://pypi.org/project/arviz) (📥 290K / month): +- [PyPi](https://pypi.org/project/arviz): ``` pip install arviz ``` -- [Conda](https://anaconda.org/conda-forge/arviz) (📥 510K · ⏱️ 03.10.2021): +- [Conda](https://anaconda.org/conda-forge/arviz) (📥 580K · ⏱️ 03.10.2021): ``` conda install -c conda-forge arviz ```
-
scikit-plot (🥈26 · ⭐ 2.1K · 💀) - 一个直观的库，可向其中添加绘图功能。MIT +
scikit-plot (🥈25 · ⭐ 2.2K · 💀) - An intuitive library to add plotting functionality to.. MIT -- [GitHub](https://github.com/reiinakano/scikit-plot) (👨‍💻 13 · 🔀 250 · 📦 1.4K · 📋 58 - 32% open · ⏱️ 19.08.2018): +- [GitHub](https://github.com/reiinakano/scikit-plot) (👨‍💻 13 · 🔀 260 · 📦 1.5K · 📋 58 - 32% open · ⏱️ 19.08.2018): ``` git clone https://github.com/reiinakano/scikit-plot ``` -- [PyPi](https://pypi.org/project/scikit-plot) (📥 410K / month): +- [PyPi](https://pypi.org/project/scikit-plot) (📥 390K / month): ``` pip install scikit-plot ``` -- [Conda](https://anaconda.org/conda-forge/scikit-plot) (📥 99K · ⏱️ 05.06.2019): +- [Conda](https://anaconda.org/conda-forge/scikit-plot) (📥 100K · ⏱️ 05.06.2019): ``` conda install -c conda-forge scikit-plot ```
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Model Analysis (🥈26 · ⭐ 1.1K) - TensorFlow的模型分析工具。Apache-2 +
Alibi (🥈25 · ⭐ 1.4K) - Algorithms for monitoring and explaining machine learning models. Apache-2 -- [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 35 · 🔀 220 · 📋 61 - 22% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 18 · 🔀 160 · 📦 120 · 📋 240 - 39% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/tensorflow/model-analysis + git clone https://github.com/SeldonIO/alibi ``` -- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (📥 11M / month): +- [PyPi](https://pypi.org/project/alibi) (📥 15K / month): ``` - pip install tensorflow-model-analysis + pip install alibi ```
-
Alibi (🥈25 · ⭐ 1.3K) - 监视和解释机器学习模型的算法。Apache-2 +
Fairness 360 (🥈24 · ⭐ 1.6K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 -- [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 16 · 🔀 150 · 📦 100 · 📋 220 - 39% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 46 · 🔀 500 · 📦 130 · 📋 110 - 47% open · ⏱️ 18.11.2021): ``` - git clone https://github.com/SeldonIO/alibi + git clone https://github.com/Trusted-AI/AIF360 ``` -- [PyPi](https://pypi.org/project/alibi) (📥 13K / month): +- [PyPi](https://pypi.org/project/aif360) (📥 7.3K / month): ``` - pip install alibi + pip install aif360 ```
-
DoWhy (🥈24 · ⭐ 3.3K) - DoWhy是用于因果推断的Python库。MIT +
Lucid (🥈23 · ⭐ 4.3K · 💤) - A collection of infrastructure and tools for research in.. Apache-2 -- [GitHub](https://github.com/microsoft/dowhy) (👨‍💻 44 · 🔀 490 · 📥 24 · 📦 64 · 📋 140 - 25% open · ⏱️ 19.09.2021): +- [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 580 · 📦 590 · 📋 170 - 41% open · ⏱️ 19.03.2021): ``` - git clone https://github.com/Microsoft/dowhy - ``` -- [PyPi](https://pypi.org/project/dowhy) (📥 48K / month): - ``` - pip install dowhy + git clone https://github.com/tensorflow/lucid ``` -- [Conda](https://anaconda.org/conda-forge/dowhy) (📥 3.6K · ⏱️ 28.04.2021): +- [PyPi](https://pypi.org/project/lucid) (📥 1K / month): ``` - conda install -c conda-forge dowhy + pip install lucid ```
-
Fairness 360 (🥈24 · ⭐ 1.5K) - 一整套用于数据集的公平度量标准。Apache-2 +
keras-vis (🥈23 · ⭐ 2.9K · 💀) - Neural network visualization toolkit for keras. MIT -- [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 46 · 🔀 470 · 📦 120 · 📋 110 - 48% open · ⏱️ 18.09.2021): +- [GitHub](https://github.com/raghakot/keras-vis) (👨‍💻 10 · 🔀 610 · 📦 1.5K · 📋 210 - 53% open · ⏱️ 20.04.2020): ``` - git clone https://github.com/Trusted-AI/AIF360 + git clone https://github.com/raghakot/keras-vis ``` -- [PyPi](https://pypi.org/project/aif360) (📥 7.6K / month): +- [PyPi](https://pypi.org/project/keras-vis) (📥 3.6K / month): ``` - pip install aif360 + pip install keras-vis ```
-
keras-vis (🥈23 · ⭐ 2.9K · 💀) - 用于Keras的神经网络可视化工具包。MIT +
CausalNex (🥈23 · ⭐ 1.4K) - A Python library that helps data scientists to infer.. Apache-2 -- [GitHub](https://github.com/raghakot/keras-vis) (👨‍💻 10 · 🔀 600 · 📦 1.3K · 📋 210 - 53% open · ⏱️ 20.04.2020): +- [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 150 · 📦 33 · 📋 100 - 13% open · ⏱️ 11.11.2021): ``` - git clone https://github.com/raghakot/keras-vis + git clone https://github.com/quantumblacklabs/causalnex ``` -- [PyPi](https://pypi.org/project/keras-vis) (📥 3.8K / month): +- [PyPi](https://pypi.org/project/causalnex) (📥 4.4K / month): ``` - pip install keras-vis + pip install causalnex ```
-
keract (🥈23 · ⭐ 930) - 在Keras中分层输出和渐变。MIT +
DoWhy (🥈22 · ⭐ 3.5K) - DoWhy is a Python library for causal inference that supports explicit.. MIT -- [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 99 · 📋 83 - 2% open · ⏱️ 28.07.2021): +- [GitHub](https://github.com/microsoft/dowhy) (👨‍💻 45 · 🔀 520 · 📥 24 · 📦 78 · 📋 160 - 29% open · ⏱️ 05.12.2021): ``` - git clone https://github.com/philipperemy/keract + git clone https://github.com/Microsoft/dowhy ``` -- [PyPi](https://pypi.org/project/keract) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/dowhy): ``` - pip install keract + pip install dowhy + ``` +- [Conda](https://anaconda.org/conda-forge/dowhy) (📥 4.1K · ⏱️ 28.04.2021): + ``` + conda install -c conda-forge dowhy ```
-
eli5 (🥈22 · ⭐ 2.5K · 💀) - 一个用于调试/检查机器学习分类器的库。MIT +
eli5 (🥈22 · ⭐ 2.5K · 💀) - A library for debugging/inspecting machine learning classifiers and.. MIT -- [GitHub](https://github.com/TeamHG-Memex/eli5) (👨‍💻 14 · 🔀 300 · 📋 240 - 54% open · ⏱️ 22.01.2020): +- [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) (📥 1.1M / month): +- [PyPi](https://pypi.org/project/eli5) (📥 1.6M / month): ``` pip install eli5 ``` -- [Conda](https://anaconda.org/conda-forge/eli5) (📥 100K · ⏱️ 25.01.2021): +- [Conda](https://anaconda.org/conda-forge/eli5) (📥 110K · ⏱️ 25.01.2021): ``` conda install -c conda-forge eli5 ```
-
CausalNex (🥈22 · ⭐ 1.3K) - 一个可帮助数据科学家进行因果推断的Python库。Apache-2 +
dtreeviz (🥈22 · ⭐ 1.9K) - A python library for decision tree visualization and model interpretation. MIT -- [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 140 · 📦 27 · 📋 96 - 11% open · ⏱️ 15.09.2021): +- [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 17 · 🔀 240 · 📦 270 · 📋 110 - 16% open · ⏱️ 03.12.2021): ``` - git clone https://github.com/quantumblacklabs/causalnex + git clone https://github.com/parrt/dtreeviz ``` -- [PyPi](https://pypi.org/project/causalnex) (📥 2.7K / month): +- [PyPi](https://pypi.org/project/dtreeviz): ``` - pip install causalnex + pip install dtreeviz ```
-
Explainability 360 (🥈22 · ⭐ 960) - 数据和机器学习的可解释性。Apache-2 +
Explainability 360 (🥈22 · ⭐ 1K) - Interpretability and explainability of data and machine.. Apache-2 -- [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 29 · 🔀 190 · 📦 34 · 📋 53 - 56% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 29 · 🔀 210 · 📦 36 · 📋 56 - 55% open · ⏱️ 12.10.2021): ``` git clone https://github.com/Trusted-AI/AIX360 ``` -- [PyPi](https://pypi.org/project/aix360) (📥 1.3K / month): +- [PyPi](https://pypi.org/project/aix360) (📥 1.4K / month): ``` pip install aix360 ```
-
explainerdashboard (🥈22 · ⭐ 640) - 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) (👨‍💻 12 · 🔀 81 · 📦 38 · 📋 120 - 11% open · ⏱️ 08.07.2021): - - ``` - git clone https://github.com/oegedijk/explainerdashboard - ``` -- [PyPi](https://pypi.org/project/explainerdashboard) (📥 8.2K / month): - ``` - pip install explainerdashboard - ``` -
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Lucid (🥈21 · ⭐ 4.3K · 💤) - 用于神经科学研究的基础设施和工具的集合。Apache-2 +
tf-explain (🥈22 · ⭐ 890) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT -- [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 580 · 📦 580 · 📋 170 - 40% open · ⏱️ 19.03.2021): +- [GitHub](https://github.com/sicara/tf-explain) (👨‍💻 16 · 🔀 89 · 📦 92 · 📋 86 - 43% open · ⏱️ 30.11.2021): ``` - git clone https://github.com/tensorflow/lucid + git clone https://github.com/sicara/tf-explain ``` -- [PyPi](https://pypi.org/project/lucid): +- [PyPi](https://pypi.org/project/tf-explain) (📥 2.3K / month): ``` - pip install lucid + pip install tf-explain ```
-
random-forest-importances (🥈21 · ⭐ 480 · 💤) - 随机森林特征重要度计算。MIT +
checklist (🥈21 · ⭐ 1.5K) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT -- [GitHub](https://github.com/parrt/random-forest-importances) (👨‍💻 14 · 🔀 100 · 📦 85 · 📋 32 - 12% open · ⏱️ 30.01.2021): +- [GitHub](https://github.com/marcotcr/checklist) (👨‍💻 12 · 🔀 150 · 📦 58 · 📋 80 - 1% open · ⏱️ 28.09.2021): ``` - git clone https://github.com/parrt/random-forest-importances + git clone https://github.com/marcotcr/checklist ``` -- [PyPi](https://pypi.org/project/rfpimp) (📥 19K / month): +- [PyPi](https://pypi.org/project/checklist) (📥 14K / month): ``` - pip install rfpimp + pip install checklist ```
-
yellowbrick (🥉20 · ⭐ 3.4K) - 可视化分析和诊断工具，方便机器使用。Apache-2 +
keract (🥈21 · ⭐ 940) - Layers Outputs and Gradients in Keras. Made easy. MIT -- [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 100 · 🔀 480 · 📋 620 - 12% open · ⏱️ 25.09.2021): +- [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 110 · 📋 83 - 2% open · ⏱️ 28.07.2021): ``` - git clone https://github.com/DistrictDataLabs/yellowbrick + git clone https://github.com/philipperemy/keract ``` -- [PyPi](https://pypi.org/project/yellowbrick) (📥 310K / month): +- [PyPi](https://pypi.org/project/keract) (📥 1.3K / month): ``` - pip install yellowbrick + pip install keract ```
-
checklist (🥉20 · ⭐ 1.5K) - 超越准确性：使用CheckList对NLP模型进行行为测试。MIT +
imodels (🥈21 · ⭐ 400) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT -- [GitHub](https://github.com/marcotcr/checklist) (👨‍💻 12 · 🔀 140 · 📦 37 · ⏱️ 28.09.2021): +- [GitHub](https://github.com/csinva/imodels) (👨‍💻 7 · 🔀 40 · 📦 10 · 📋 17 - 17% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/marcotcr/checklist + git clone https://github.com/csinva/imodels ``` -- [PyPi](https://pypi.org/project/checklist) (📥 14K / month): +- [PyPi](https://pypi.org/project/imodels) (📥 1.6K / month): ``` - pip install checklist + pip install imodels ```
-
fairlearn (🥉20 · ⭐ 1.1K) - 一个用于评估和改善机器公平性的Python程序包。MIT +
yellowbrick (🥉20 · ⭐ 3.4K) - Visual analysis and diagnostic tools to facilitate machine.. Apache-2 -- [GitHub](https://github.com/fairlearn/fairlearn) (👨‍💻 58 · 🔀 260 · 📋 300 - 41% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 100 · 🔀 490 · 📋 630 - 13% open · ⏱️ 10.11.2021): ``` - git clone https://github.com/fairlearn/fairlearn - ``` -- [PyPi](https://pypi.org/project/fairlearn) (📥 33K / month): - ``` - pip install fairlearn + git clone https://github.com/DistrictDataLabs/yellowbrick ``` -- [Conda](https://anaconda.org/conda-forge/fairlearn) (📥 15K · ⏱️ 07.07.2021): +- [PyPi](https://pypi.org/project/yellowbrick) (📥 330K / month): ``` - conda install -c conda-forge fairlearn + pip install yellowbrick ```
-
Skater (🥉20 · ⭐ 1K · 💀) - 用于模型解释/说明的Python库。❗️UPL-1.0 +
Skater (🥉20 · ⭐ 1K · 💀) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 - [GitHub](https://github.com/oracle/Skater) (👨‍💻 34 · 🔀 160 · 📋 160 - 40% open · ⏱️ 29.06.2020): ``` git clone https://github.com/oracle/Skater ``` -- [PyPi](https://pypi.org/project/skater) (📥 7.9K / month): +- [PyPi](https://pypi.org/project/skater) (📥 2.4K / month): ``` pip install skater ``` -- [Conda](https://anaconda.org/conda-forge/skater) (📥 44K · ⏱️ 01.11.2020): +- [Conda](https://anaconda.org/conda-forge/skater) (📥 46K · ⏱️ 15.11.2021): ``` conda install -c conda-forge skater ```
-
DALEX (🥉20 · ⭐ 910) - 用于模型探索和扩展的模块。❗️GPL-3.0 +
DALEX (🥉20 · ⭐ 970) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 -- [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 120 · 📦 20 · 📋 320 - 4% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 120 · 📦 26 · 📋 330 - 4% open · ⏱️ 08.11.2021): ``` git clone https://github.com/ModelOriented/DALEX ``` -- [PyPi](https://pypi.org/project/dalex) (📥 8.4K / month): +- [PyPi](https://pypi.org/project/dalex) (📥 11K / month): ``` pip install dalex ```
-
tf-explain (🥉20 · ⭐ 860) - 使用Tensorflow 2.x的tf.keras模型的可解释性方法。MIT +
explainerdashboard (🥉20 · ⭐ 770) - Quickly build Explainable AI dashboards that show the inner.. MIT -- [GitHub](https://github.com/sicara/tf-explain) (👨‍💻 15 · 🔀 84 · 📦 90 · 📋 84 - 42% open · ⏱️ 22.06.2021): +- [GitHub](https://github.com/oegedijk/explainerdashboard) (👨‍💻 12 · 🔀 91 · 📦 46 · 📋 130 - 15% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/sicara/tf-explain + git clone https://github.com/oegedijk/explainerdashboard ``` -- [PyPi](https://pypi.org/project/tf-explain) (📥 2.3K / month): +- [PyPi](https://pypi.org/project/explainerdashboard): ``` - pip install tf-explain + pip install explainerdashboard ```
-
DiCE (🥉20 · ⭐ 660) - 生成任何机器学习的各种反事实说明。MIT +
fairlearn (🥉19 · ⭐ 1.1K) - A Python package to assess and improve fairness of machine.. MIT -- [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 12 · 🔀 85 · 📋 86 - 43% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/fairlearn/fairlearn) (👨‍💻 61 · 🔀 270 · 📋 320 - 37% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/interpretml/DiCE + git clone https://github.com/fairlearn/fairlearn ``` -- [PyPi](https://pypi.org/project/dice-ml) (📥 19K / month): +- [PyPi](https://pypi.org/project/fairlearn): ``` - pip install dice-ml + pip install fairlearn + ``` +- [Conda](https://anaconda.org/conda-forge/fairlearn) (📥 16K · ⏱️ 07.07.2021): + ``` + conda install -c conda-forge fairlearn ```
-
TreeInterpreter (🥉19 · ⭐ 680 · 💤) - 解释scikit-learn决策树的程序包。BSD-3 +
TreeInterpreter (🥉19 · ⭐ 690 · 💤) - Package for interpreting scikit-learn's decision tree.. BSD-3 -- [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 130 · 📦 160 · 📋 23 - 82% open · ⏱️ 28.02.2021): +- [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 130 · 📦 180 · 📋 23 - 82% open · ⏱️ 28.02.2021): ``` git clone https://github.com/andosa/treeinterpreter ``` -- [PyPi](https://pypi.org/project/treeinterpreter) (📥 240K / month): +- [PyPi](https://pypi.org/project/treeinterpreter) (📥 200K / month): ``` pip install treeinterpreter ```
-
What-If Tool (🥉19 · ⭐ 580) - What-If工具的源代码/网页/演示。Apache-2 +
What-If Tool (🥉19 · ⭐ 610) - Source code/webpage/demos for the What-If Tool. Apache-2 -- [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 19 · 🔀 110 · 📋 90 - 51% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 20 · 🔀 120 · 📋 94 - 51% open · ⏱️ 01.11.2021): ``` git clone https://github.com/PAIR-code/what-if-tool @@ -8924,304 +8924,316 @@ _用于可视化，解释，调试，评估和解释机器学习模型的库。_ ``` pip install witwidget ``` -- [NPM](https://www.npmjs.com/package/wit-widget) (📥 2.9K / month): +- [NPM](https://www.npmjs.com/package/wit-widget) (📥 4.3K / month): ``` npm install wit-widget ```
-
sklearn-evaluation (🥉19 · ⭐ 310) - 机器学习模型评估变得容易。MIT +
deeplift (🥉19 · ⭐ 600) - Public facing deeplift repo. MIT -- [GitHub](https://github.com/edublancas/sklearn-evaluation) (👨‍💻 6 · 🔀 25 · 📦 31 · 📋 37 - 21% open · ⏱️ 10.07.2021): +- [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 130 · 📦 52 · 📋 81 - 40% open · ⏱️ 11.11.2021): ``` - git clone https://github.com/edublancas/sklearn-evaluation + git clone https://github.com/kundajelab/deeplift ``` -- [PyPi](https://pypi.org/project/sklearn-evaluation) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/deeplift) (📥 520 / month): ``` - pip install sklearn-evaluation + pip install deeplift ```
-
imodels (🥉19 · ⭐ 280) - 可解释的ML包，用于简洁，透明和准确的预测。MIT +
sklearn-evaluation (🥉19 · ⭐ 320) - Machine learning model evaluation made easy: plots,.. MIT -- [GitHub](https://github.com/csinva/imodels) (👨‍💻 5 · 🔀 26 · 📦 9 · 📋 15 - 6% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/edublancas/sklearn-evaluation) (👨‍💻 6 · 🔀 25 · 📦 33 · 📋 37 - 21% open · ⏱️ 17.10.2021): ``` - git clone https://github.com/csinva/imodels + git clone https://github.com/edublancas/sklearn-evaluation ``` -- [PyPi](https://pypi.org/project/imodels) (📥 500 / month): +- [PyPi](https://pypi.org/project/sklearn-evaluation) (📥 910 / month): ``` - pip install imodels + pip install sklearn-evaluation ```
-
fairness-indicators (🥉19 · ⭐ 220) - Tensorflow的公平性评估和可视化。Apache-2 +
aequitas (🥉18 · ⭐ 440 · 💤) - Bias and Fairness Audit Toolkit. MIT -- [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 23 · 🔀 61 · 📋 10 - 30% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 84 · 📦 87 · 📋 58 - 63% open · ⏱️ 27.05.2021): ``` - git clone https://github.com/tensorflow/fairness-indicators + git clone https://github.com/dssg/aequitas ``` -- [PyPi](https://pypi.org/project/fairness-indicators) (📥 780 / month): +- [PyPi](https://pypi.org/project/aequitas) (📥 1.2K / month): ``` - pip install fairness-indicators + pip install aequitas ```
-
deeplift (🥉18 · ⭐ 570 · 💤) - Public facing deeplift repo。MIT +
random-forest-importances (🥉17 · ⭐ 490 · 💤) - Code to compute permutation and drop-column.. MIT -- [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 130 · 📦 50 · 📋 79 - 40% open · ⏱️ 11.11.2020): +- [GitHub](https://github.com/parrt/random-forest-importances) (👨‍💻 14 · 🔀 110 · 📦 88 · 📋 34 - 17% open · ⏱️ 30.01.2021): ``` - git clone https://github.com/kundajelab/deeplift + git clone https://github.com/parrt/random-forest-importances ``` -- [PyPi](https://pypi.org/project/deeplift) (📥 470 / month): +- [PyPi](https://pypi.org/project/rfpimp): ``` - pip install deeplift + pip install rfpimp ```
-
model-card-toolkit (🥉18 · ⭐ 220) - 模型解释与分析卡片工具库。Apache-2 +
model-card-toolkit (🥉17 · ⭐ 240) - a tool that leverages rich metadata and lineage.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 11 · 🔀 33 · 📦 4 · 📋 6 - 66% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 11 · 🔀 41 · 📦 5 · 📋 6 - 66% open · ⏱️ 10.12.2021): ``` git clone https://github.com/tensorflow/model-card-toolkit ``` -- [PyPi](https://pypi.org/project/model-card-toolkit) (📥 380 / month): +- [PyPi](https://pypi.org/project/model-card-toolkit): ``` pip install model-card-toolkit ```
-
aequitas (🥉17 · ⭐ 420) - 偏差和公平审计工具包。MIT +
fairness-indicators (🥉17 · ⭐ 240) - Tensorflow's Fairness Evaluation and Visualization.. Apache-2 -- [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 78 · 📦 82 · 📋 55 - 61% open · ⏱️ 27.05.2021): +- [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 25 · 🔀 66 · 📋 10 - 20% open · ⏱️ 03.12.2021): ``` - git clone https://github.com/dssg/aequitas + git clone https://github.com/tensorflow/fairness-indicators + ``` +- [PyPi](https://pypi.org/project/fairness-indicators): + ``` + pip install fairness-indicators + ``` +
+
LIT (🥉16 · ⭐ 2.7K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 + +- [GitHub](https://github.com/PAIR-code/lit) (👨‍💻 17 · 🔀 270 · 📦 7 · 📋 86 - 29% open · ⏱️ 14.11.2021): + + ``` + git clone https://github.com/PAIR-code/lit + ``` +- [PyPi](https://pypi.org/project/lit-nlp): + ``` + pip install lit-nlp + ``` +
+
XAI (🥉16 · ⭐ 740) - XAI - An eXplainability toolbox for machine learning. MIT + +- [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 110 · 📦 11 · 📋 8 - 12% open · ⏱️ 30.10.2021): + + ``` + git clone https://github.com/EthicalML/xai ``` -- [PyPi](https://pypi.org/project/aequitas) (📥 970 / month): +- [PyPi](https://pypi.org/project/xai): ``` - pip install aequitas + pip install xai ```
-
iNNvestigate (🥉16 · ⭐ 900) - 神经网络预估分析工具箱。BSD-2 +
DiCE (🥉16 · ⭐ 730) - Generate Diverse Counterfactual Explanations for any machine.. MIT -- [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 190 · 📋 220 - 29% open · ⏱️ 03.08.2021): +- [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 12 · 🔀 96 · 📋 90 - 44% open · ⏱️ 11.12.2021): ``` - git clone https://github.com/albermax/innvestigate + git clone https://github.com/interpretml/DiCE ``` -- [PyPi](https://pypi.org/project/innvestigate) (📥 340 / month): +- [PyPi](https://pypi.org/project/dice-ml): ``` - pip install innvestigate + pip install dice-ml ```
-
tcav (🥉16 · ⭐ 490) - TCAV ML可解释性项目的代码。Apache-2 +
tcav (🥉16 · ⭐ 500) - Code for the TCAV ML interpretability project. Apache-2 -- [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 110 · 📦 9 · 📋 55 - 5% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 120 · 📦 11 · 📋 55 - 5% open · ⏱️ 16.09.2021): ``` git clone https://github.com/tensorflow/tcav ``` -- [PyPi](https://pypi.org/project/tcav) (📥 86 / month): +- [PyPi](https://pypi.org/project/tcav): ``` pip install tcav ```
-
ExplainX.ai (🥉16 · ⭐ 230 · 💤) - 适用于数据科学家的可解释AI框架。MIT +
iNNvestigate (🥉15 · ⭐ 920) - A toolbox to iNNvestigate neural networks' predictions!. BSD-2 -- [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 37 · 📥 2 · 📋 24 - 29% open · ⏱️ 02.02.2021): +- [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 200 · 📋 230 - 28% open · ⏱️ 03.08.2021): ``` - git clone https://github.com/explainX/explainx + git clone https://github.com/albermax/innvestigate ``` -- [PyPi](https://pypi.org/project/explainx) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/innvestigate) (📥 450 / month): ``` - pip install explainx + pip install innvestigate ```
-
LIT (🥉15 · ⭐ 2.7K) - 语言可解释性工具：交互式分析NLP模型。Apache-2 +
Anchor (🥉15 · ⭐ 680) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 -- [GitHub](https://github.com/PAIR-code/lit) (👨‍💻 14 · 🔀 260 · 📦 7 · 📋 80 - 45% open · ⏱️ 05.04.2021): +- [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 10 · 🔀 93 · 📋 67 - 23% open · ⏱️ 17.11.2021): ``` - git clone https://github.com/PAIR-code/lit + git clone https://github.com/marcotcr/anchor ``` -- [PyPi](https://pypi.org/project/lit-nlp): +- [PyPi](https://pypi.org/project/anchor_exp) (📥 1.8K / month): ``` - pip install lit-nlp + pip install anchor_exp ```
-
XAI (🥉15 · ⭐ 710) - XAI-用于机器学习的可解释性工具箱。MIT +
LOFO (🥉15 · ⭐ 420) - Leave One Feature Out Importance. MIT -- [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 110 · 📦 11 · 📋 8 - 62% open · ⏱️ 23.04.2021): +- [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 50 · 📦 6 · 📋 17 - 23% open · ⏱️ 04.10.2021): ``` - git clone https://github.com/EthicalML/xai + git clone https://github.com/aerdem4/lofo-importance ``` -- [PyPi](https://pypi.org/project/xai) (📥 250 / month): +- [PyPi](https://pypi.org/project/lofo-importance) (📥 330 / month): ``` - pip install xai + pip install lofo-importance ```
-
FlashTorch (🥉15 · ⭐ 620) - PyTorch中用于神经网络的可视化工具包。MIT +
ExplainX.ai (🥉15 · ⭐ 250 · 💤) - Explainable AI framework for data scientists. Explain & debug any.. MIT -- [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 73 · 📦 7 · 📋 28 - 21% open · ⏱️ 27.04.2021): +- [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 36 · 📥 2 · 📋 24 - 29% open · ⏱️ 02.02.2021): ``` - git clone https://github.com/MisaOgura/flashtorch + git clone https://github.com/explainX/explainx ``` -- [PyPi](https://pypi.org/project/flashtorch) (📥 300 / month): +- [PyPi](https://pypi.org/project/explainx) (📥 600 / month): ``` - pip install flashtorch + pip install explainx ```
-
LOFO (🥉15 · ⭐ 380) - Leave One Feature Out特征重要度。MIT +
FlashTorch (🥉13 · ⭐ 640 · 💤) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT -- [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 43 · 📦 6 · 📋 13 - 23% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 77 · 📦 8 · 📋 29 - 24% open · ⏱️ 27.04.2021): ``` - git clone https://github.com/aerdem4/lofo-importance + git clone https://github.com/MisaOgura/flashtorch ``` -- [PyPi](https://pypi.org/project/lofo-importance) (📥 700 / month): +- [PyPi](https://pypi.org/project/flashtorch): ``` - pip install lofo-importance + pip install flashtorch ```
-
Anchor (🥉14 · ⭐ 670) - High-Precision Model-Agnostic Explanations论文代码。BSD-2 +
Attribution Priors (🥉12 · ⭐ 90 · 💤) - Tools for training explainable models using.. MIT -- [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 8 · 🔀 91 · 📋 66 - 27% open · ⏱️ 19.04.2021): +- [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 10 · 📦 3 · 📋 4 - 25% open · ⏱️ 19.03.2021): ``` - git clone https://github.com/marcotcr/anchor + git clone https://github.com/suinleelab/attributionpriors ``` -- [PyPi](https://pypi.org/project/anchor_exp) (📥 800 / month): +- [PyPi](https://pypi.org/project/attributionpriors) (📥 27 / month): ``` - pip install anchor_exp + pip install attributionpriors ```
-
contextual-ai (🥉13 · ⭐ 72) - AI 模型可解释性工具。Apache-2 +
contextual-ai (🥉12 · ⭐ 74) - Contextual AI adds explainability to different stages of.. Apache-2 -- [GitHub](https://github.com/SAP/contextual-ai) (👨‍💻 11 · 🔀 10 · 📋 12 - 58% open · ⏱️ 15.09.2021): +- [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) (📥 140 / month): +- [PyPi](https://pypi.org/project/contextual-ai): ``` pip install contextual-ai ```
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Attribution Priors (🥉12 · ⭐ 86 · 💤) - 训练可解释模型的工具。MIT - -- [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 9 · 📦 3 · 📋 4 - 25% open · ⏱️ 19.03.2021): - - ``` - git clone https://github.com/suinleelab/attributionpriors - ``` -- [PyPi](https://pypi.org/project/attributionpriors) (📥 33 / month): - ``` - pip install attributionpriors - ``` -
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bias-detector (🥉11 · ⭐ 34) - Bias Detector是用于检测机器偏差的python软件包。MIT +
bias-detector (🥉12 · ⭐ 36) - Bias Detector is a python package for detecting bias in machine.. MIT -- [GitHub](https://github.com/intuit/bias-detector) (👨‍💻 4 · 🔀 7 · ⏱️ 01.06.2021): +- [GitHub](https://github.com/intuit/bias-detector) (👨‍💻 4 · 🔀 9 · ⏱️ 27.10.2021): ``` git clone https://github.com/intuit/bias-detector ``` -- [PyPi](https://pypi.org/project/bias-detector) (📥 81 / month): +- [PyPi](https://pypi.org/project/bias-detector) (📥 40 / 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 ( ⭐ 2.5K) - Benchmarks of approximate nearest neighbor libraries in Python. +🔗 ANN Benchmarks ( ⭐ 2.7K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Annoy (🥇30 · ⭐ 9.1K) - 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) (👨‍💻 73 · 🔀 940 · 📦 1.8K · 📋 330 - 10% open · ⏱️ 22.09.2021): - - ``` - git clone https://github.com/spotify/annoy - ``` -- [PyPi](https://pypi.org/project/annoy) (📥 930K / month): - ``` - pip install annoy - ``` -
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NMSLIB (🥇28 · ⭐ 2.6K) - 非度量空间库（NMSLIB）：一种有效的相似度搜索。Apache-2 +
Milvus (🥇27 · ⭐ 9K) - An open source embedding vector similarity search engine powered by.. Apache-2 -- [GitHub](https://github.com/nmslib/nmslib) (👨‍💻 45 · 🔀 360 · 📦 480 · 📋 380 - 13% open · ⏱️ 19.09.2021): +- [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 180 · 🔀 1.3K · 📥 6.1K · 📋 4.1K - 4% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/nmslib/nmslib + git clone https://github.com/milvus-io/milvus ``` -- [PyPi](https://pypi.org/project/nmslib) (📥 94K / month): +- [PyPi](https://pypi.org/project/pymilvus): ``` - pip install nmslib + pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/nmslib) (📥 42K · ⏱️ 08.01.2021): +- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (📥 660K · ⭐ 16 · ⏱️ 26.11.2021): ``` - conda install -c conda-forge nmslib + docker pull milvusdb/milvus ```
-
Faiss (🥈27 · ⭐ 15K) - 一个用于高效相似性搜索和密集向量聚类的库。MIT +
Faiss (🥇26 · ⭐ 16K) - A library for efficient similarity search and clustering of dense vectors. MIT -- [GitHub](https://github.com/facebookresearch/faiss) (👨‍💻 89 · 🔀 2.3K · 📦 470 · 📋 1.6K - 12% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/facebookresearch/faiss) (👨‍💻 90 · 🔀 2.4K · 📦 520 · 📋 1.7K - 12% open · ⏱️ 11.12.2021): ``` git clone https://github.com/facebookresearch/faiss ``` -- [PyPi](https://pypi.org/project/pymilvus) (📥 22K / month): +- [PyPi](https://pypi.org/project/pymilvus): ``` pip install pymilvus ``` -- [Conda](https://anaconda.org/conda-forge/faiss) (📥 190K · ⏱️ 19.04.2021): +- [Conda](https://anaconda.org/conda-forge/faiss) (📥 230K · ⏱️ 20.11.2021): ``` conda install -c conda-forge faiss ```
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Milvus (🥈27 · ⭐ 8.3K · 📈) - 一个开源的embedding嵌入向量相似度搜索引擎。Apache-2 +
NMSLIB (🥇26 · ⭐ 2.7K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 -- [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 170 · 🔀 1.1K · 📥 1.7K · 📋 3.6K - 6% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/nmslib/nmslib) (👨‍💻 45 · 🔀 370 · 📦 520 · 📋 380 - 14% open · ⏱️ 19.09.2021): ``` - git clone https://github.com/milvus-io/milvus + git clone https://github.com/nmslib/nmslib ``` -- [PyPi](https://pypi.org/project/pymilvus) (📥 22K / month): +- [PyPi](https://pypi.org/project/nmslib): ``` - pip install pymilvus + pip install nmslib ``` -- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (📥 520K · ⭐ 14 · ⏱️ 11.10.2021): +- [Conda](https://anaconda.org/conda-forge/nmslib) (📥 46K · ⏱️ 22.11.2021): ``` - docker pull milvusdb/milvus + conda install -c conda-forge nmslib ```
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PyNNDescent (🥈26 · ⭐ 490) - 适用于近似最近邻查找的Python库。BSD-2 +
PyNNDescent (🥈25 · ⭐ 530) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 -- [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 16 · 🔀 63 · 📦 820 · 📋 80 - 43% open · ⏱️ 27.09.2021): +- [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 18 · 🔀 68 · 📦 1K · 📋 88 - 44% open · ⏱️ 08.12.2021): ``` git clone https://github.com/lmcinnes/pynndescent ``` -- [PyPi](https://pypi.org/project/pynndescent) (📥 1.3M / month): +- [PyPi](https://pypi.org/project/pynndescent): ``` pip install pynndescent ``` -- [Conda](https://anaconda.org/conda-forge/pynndescent) (📥 300K · ⏱️ 06.07.2021): +- [Conda](https://anaconda.org/conda-forge/pynndescent) (📥 420K · ⏱️ 15.10.2021): ``` conda install -c conda-forge pynndescent ```
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hnswlib (🥉22 · ⭐ 1.7K) - 仅标头的C++/python库，用于快速近似最近邻查找。Apache-2 +
Annoy (🥈24 · ⭐ 9.3K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 + +- [GitHub](https://github.com/spotify/annoy) (👨‍💻 75 · 🔀 950 · 📦 1.9K · 📋 340 - 11% open · ⏱️ 18.10.2021): + + ``` + git clone https://github.com/spotify/annoy + ``` +- [PyPi](https://pypi.org/project/annoy): + ``` + pip install annoy + ``` +
+
hnswlib (🥉22 · ⭐ 1.8K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 -- [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 46 · 🔀 320 · 📦 150 · 📋 220 - 45% open · ⏱️ 30.06.2021): +- [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 52 · 🔀 340 · 📦 180 · 📋 220 - 46% open · ⏱️ 09.12.2021): ``` git clone https://github.com/nmslib/hnswlib @@ -9231,57 +9243,57 @@ _用于近似最近邻居搜索和向量索引/相似性搜索的库。_ pip install hnswlib ```
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Magnitude (🥉22 · ⭐ 1.5K · 💀) - 快速，高效的通用向量嵌入实用程序包。MIT +
Magnitude (🥉19 · ⭐ 1.5K · 💀) - A fast, efficient universal vector embedding utility package. MIT -- [GitHub](https://github.com/plasticityai/magnitude) (👨‍💻 4 · 🔀 100 · 📦 200 · 📋 80 - 36% open · ⏱️ 17.07.2020): +- [GitHub](https://github.com/plasticityai/magnitude) (👨‍💻 4 · 🔀 100 · 📦 210 · 📋 80 - 36% open · ⏱️ 17.07.2020): ``` git clone https://github.com/plasticityai/magnitude ``` -- [PyPi](https://pypi.org/project/pymagnitude) (📥 4.8K / month): +- [PyPi](https://pypi.org/project/pymagnitude): ``` pip install pymagnitude ```
-
NearPy (🥉20 · ⭐ 690 · 💀) - 用于快速（近似）最近邻搜索的Python框架。MIT +
NearPy (🥉16 · ⭐ 690 · 💀) - Python framework for fast (approximated) nearest neighbour search in.. MIT -- [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 56 · 📋 62 - 38% open · ⏱️ 21.10.2018): +- [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 63 · 📋 62 - 38% open · ⏱️ 21.10.2018): ``` git clone https://github.com/pixelogik/NearPy ``` -- [PyPi](https://pypi.org/project/NearPy) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/NearPy): ``` pip install NearPy ```
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N2 (🥉18 · ⭐ 490) - TOROS N2-快速运行的轻量级近似最近邻库。Apache-2 +
N2 (🥉16 · ⭐ 500 · 💤) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 -- [GitHub](https://github.com/kakao/n2) (👨‍💻 18 · 🔀 54 · 📦 19 · 📋 31 - 29% open · ⏱️ 20.05.2021): +- [GitHub](https://github.com/kakao/n2) (👨‍💻 18 · 🔀 61 · 📦 22 · 📋 30 - 33% open · ⏱️ 20.05.2021): ``` git clone https://github.com/kakao/n2 ``` -- [PyPi](https://pypi.org/project/n2) (📥 960 / month): +- [PyPi](https://pypi.org/project/n2): ``` pip install n2 ```
-
NGT (🥉17 · ⭐ 800) - 最近邻搜索算法实现包。Apache-2 +
NGT (🥉14 · ⭐ 830) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 -- [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 12 · 🔀 81 · 📋 81 - 8% open · ⏱️ 15.07.2021): +- [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 12 · 🔀 82 · 📋 83 - 9% open · ⏱️ 25.10.2021): ``` git clone https://github.com/yahoojapan/NGT ``` -- [PyPi](https://pypi.org/project/ngt) (📥 15K / month): +- [PyPi](https://pypi.org/project/ngt): ``` pip install ngt ```
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PySparNN (🥉11 · ⭐ 880 · 💀) - 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 · ⭐ 890 · 💀) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3 -- [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 140 · 📋 29 - 51% open · ⏱️ 31.01.2018): +- [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 150 · 📋 29 - 51% open · ⏱️ 31.01.2018): ``` git clone https://github.com/facebookresearch/pysparnn @@ -9289,284 +9301,284 @@ _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._ -
Pyro (🥇29 · ⭐ 7.1K) - 使用Python和PyTorch进行深度通用概率编程。Apache-2 +
hmmlearn (🥇29 · ⭐ 2.4K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 -- [GitHub](https://github.com/pyro-ppl/pyro) (👨‍💻 120 · 🔀 850 · 📦 550 · 📋 880 - 17% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 38 · 🔀 650 · 📦 1.1K · 📋 360 - 14% open · ⏱️ 12.12.2021): ``` - git clone https://github.com/pyro-ppl/pyro + git clone https://github.com/hmmlearn/hmmlearn ``` -- [PyPi](https://pypi.org/project/pyro-ppl) (📥 74K / month): +- [PyPi](https://pypi.org/project/hmmlearn) (📥 550K / month): ``` - pip install pyro-ppl + pip install hmmlearn + ``` +- [Conda](https://anaconda.org/conda-forge/hmmlearn) (📥 110K · ⏱️ 13.11.2021): + ``` + conda install -c conda-forge hmmlearn ```
-
GPyTorch (🥇29 · ⭐ 2.5K) - 高斯过程的高效和模块化实现。MIT +
filterpy (🥇28 · ⭐ 2K · 💤) - Python Kalman filtering and optimal estimation library. Implements.. MIT -- [GitHub](https://github.com/cornellius-gp/gpytorch) (👨‍💻 87 · 🔀 360 · 📦 390 · 📋 980 - 22% open · ⏱️ 01.10.2021): +- [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 36 · 🔀 470 · 📦 1.1K · 📋 190 - 20% open · ⏱️ 04.05.2021): ``` - git clone https://github.com/cornellius-gp/gpytorch + git clone https://github.com/rlabbe/filterpy ``` -- [PyPi](https://pypi.org/project/gpytorch) (📥 140K / month): +- [PyPi](https://pypi.org/project/filterpy) (📥 650K / month): ``` - pip install gpytorch + pip install filterpy + ``` +- [Conda](https://anaconda.org/conda-forge/filterpy) (📥 70K · ⏱️ 05.05.2020): + ``` + conda install -c conda-forge filterpy ```
-
hmmlearn (🥇28 · ⭐ 2.4K) - Python中的隐马尔可夫模型，具有类似于scikit-learn的API。BSD-3 +
GPflow (🥇26 · ⭐ 1.5K) - Gaussian processes in TensorFlow. Apache-2 -- [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 34 · 🔀 640 · 📦 1.1K · 📋 360 - 15% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 72 · 🔀 400 · 📦 310 · 📋 720 - 13% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/hmmlearn/hmmlearn + git clone https://github.com/GPflow/GPflow ``` -- [PyPi](https://pypi.org/project/hmmlearn) (📥 96K / month): +- [PyPi](https://pypi.org/project/gpflow): ``` - pip install hmmlearn + pip install gpflow ``` -- [Conda](https://anaconda.org/conda-forge/hmmlearn) (📥 100K · ⏱️ 31.08.2021): +- [Conda](https://anaconda.org/conda-forge/gpflow) (📥 9.8K · ⏱️ 06.11.2018): ``` - conda install -c conda-forge hmmlearn + conda install -c conda-forge gpflow ```
-
filterpy (🥇28 · ⭐ 2K) - Python卡尔曼过滤和最佳估计库。MIT +
pomegranate (🥈25 · ⭐ 2.8K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT -- [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 36 · 🔀 450 · 📦 1.1K · 📋 190 - 19% open · ⏱️ 04.05.2021): +- [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 65 · 🔀 510 · 📦 590 · 📋 640 - 5% open · ⏱️ 20.11.2021): ``` - git clone https://github.com/rlabbe/filterpy + git clone https://github.com/jmschrei/pomegranate ``` -- [PyPi](https://pypi.org/project/filterpy) (📥 1M / month): +- [PyPi](https://pypi.org/project/pomegranate): ``` - pip install filterpy + pip install pomegranate ``` -- [Conda](https://anaconda.org/conda-forge/filterpy) (📥 68K · ⏱️ 05.05.2020): +- [Conda](https://anaconda.org/conda-forge/pomegranate) (📥 77K · ⏱️ 16.11.2021): ``` - conda install -c conda-forge filterpy + conda install -c conda-forge pomegranate ```
-
patsy (🥇28 · ⭐ 800) - 使用符号公式描述Python中的统计模型。❗Unlicensed +
patsy (🥈25 · ⭐ 810) - Describing statistical models in Python using symbolic formulas. ❗Unlicensed -- [GitHub](https://github.com/pydata/patsy) (👨‍💻 16 · 🔀 84 · 📦 42K · 📋 130 - 46% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/pydata/patsy) (👨‍💻 16 · 🔀 85 · 📦 45K · 📋 130 - 46% open · ⏱️ 26.09.2021): ``` git clone https://github.com/pydata/patsy ``` -- [PyPi](https://pypi.org/project/patsy) (📥 4.1M / month): +- [PyPi](https://pypi.org/project/patsy): ``` pip install patsy ``` -- [Conda](https://anaconda.org/conda-forge/patsy) (📥 3.6M · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/patsy) (📥 4M · ⏱️ 26.09.2021): ``` conda install -c conda-forge patsy ```
-
PyMC3 (🥈26 · ⭐ 6.1K) - Python中的概率编程。❗Unlicensed +
Pyro (🥈24 · ⭐ 7.2K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 -- [GitHub](https://github.com/pymc-devs/pymc) (👨‍💻 330 · 🔀 1.4K · 📥 420 · 📦 550 · 📋 2.4K - 8% open · ⏱️ 12.10.2021): +- [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) - 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): ``` git clone https://github.com/pymc-devs/pymc3 ``` -- [PyPi](https://pypi.org/project/pymc3) (📥 270K / month): +- [PyPi](https://pypi.org/project/pymc3): ``` pip install pymc3 ``` -- [Conda](https://anaconda.org/conda-forge/pymc3) (📥 320K · ⏱️ 12.10.2021): +- [Conda](https://anaconda.org/conda-forge/pymc3) (📥 360K · ⏱️ 12.10.2021): ``` conda install -c conda-forge pymc3 ```
-
pomegranate (🥈26 · ⭐ 2.7K) - 在Python中快速，灵活且易于使用的概率建模。MIT +
tensorflow-probability (🥈24 · ⭐ 3.6K) - Probabilistic reasoning and statistical analysis in.. Apache-2 -- [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 63 · 🔀 490 · 📦 540 · 📋 630 - 8% open · ⏱️ 26.07.2021): +- [GitHub](https://github.com/tensorflow/probability) (👨‍💻 430 · 🔀 910 · 📋 1.1K - 42% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/jmschrei/pomegranate + git clone https://github.com/tensorflow/probability ``` -- [PyPi](https://pypi.org/project/pomegranate) (📥 48K / month): +- [PyPi](https://pypi.org/project/tensorflow-probability) (📥 1.5M / month): ``` - pip install pomegranate + pip install tensorflow-probability ``` -- [Conda](https://anaconda.org/conda-forge/pomegranate) (📥 73K · ⏱️ 28.08.2021): +- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (📥 48K · ⏱️ 22.10.2021): ``` - conda install -c conda-forge pomegranate + conda install -c conda-forge tensorflow-probability ```
-
GPflow (🥈26 · ⭐ 1.5K) - TensorFlow中的高斯过程。Apache-2 +
GPyTorch (🥈24 · ⭐ 2.6K) - A highly efficient and modular implementation of Gaussian Processes.. MIT -- [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 71 · 🔀 400 · 📦 300 · 📋 710 - 13% open · ⏱️ 21.09.2021): +- [GitHub](https://github.com/cornellius-gp/gpytorch) (👨‍💻 89 · 🔀 370 · 📦 450 · 📋 1K - 22% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/GPflow/GPflow - ``` -- [PyPi](https://pypi.org/project/gpflow) (📥 5.3K / month): - ``` - pip install gpflow + git clone https://github.com/cornellius-gp/gpytorch ``` -- [Conda](https://anaconda.org/conda-forge/gpflow) (📥 9.6K · ⏱️ 06.11.2018): +- [PyPi](https://pypi.org/project/gpytorch): ``` - conda install -c conda-forge gpflow + pip install gpytorch ```
-
pingouin (🥈26 · ⭐ 800) - 基于Pandas的Python统计软件包。❗️GPL-3.0 +
pingouin (🥈24 · ⭐ 870) - Statistical package in Python based on Pandas. ❗️GPL-3.0 -- [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 22 · 🔀 70 · 📦 340 · 📋 160 - 15% open · ⏱️ 02.09.2021): +- [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 23 · 🔀 76 · 📦 410 · 📋 180 - 13% open · ⏱️ 08.12.2021): ``` git clone https://github.com/raphaelvallat/pingouin ``` -- [PyPi](https://pypi.org/project/pingouin) (📥 190K / month): +- [PyPi](https://pypi.org/project/pingouin): ``` pip install pingouin ``` -- [Conda](https://anaconda.org/conda-forge/pingouin) (📥 46K · ⏱️ 17.08.2021): +- [Conda](https://anaconda.org/conda-forge/pingouin) (📥 49K · ⏱️ 29.10.2021): ``` conda install -c conda-forge pingouin ```
-
pgmpy (🥉25 · ⭐ 1.9K) - 用于学习（结构和参数）和推理的Python库。MIT +
pgmpy (🥉21 · ⭐ 1.9K) - Python Library for learning (Structure and Parameter) and inference.. MIT -- [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 98 · 🔀 590 · 📥 110 · 📦 270 · 📋 720 - 24% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 100 · 🔀 610 · 📥 120 · 📦 300 · 📋 730 - 25% open · ⏱️ 04.12.2021): ``` git clone https://github.com/pgmpy/pgmpy ``` -- [PyPi](https://pypi.org/project/pgmpy) (📥 60K / month): +- [PyPi](https://pypi.org/project/pgmpy): ``` pip install pgmpy ```
-
tensorflow-probability (🥉24 · ⭐ 3.5K) - 概率推理与统计分析。Apache-2 +
SALib (🥉21 · ⭐ 550) - Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,.. MIT -- [GitHub](https://github.com/tensorflow/probability) (👨‍💻 430 · 🔀 890 · 📋 1.1K - 42% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/SALib/SALib) (👨‍💻 34 · 🔀 160 · 📋 260 - 15% open · ⏱️ 25.11.2021): ``` - git clone https://github.com/tensorflow/probability + git clone https://github.com/SALib/SALib ``` -- [PyPi](https://pypi.org/project/tensorflow-probability) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/salib): ``` - pip install tensorflow-probability + pip install salib ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (📥 44K · ⏱️ 01.10.2021): +- [Conda](https://anaconda.org/conda-forge/salib) (📥 74K · ⏱️ 04.09.2021): ``` - conda install -c conda-forge tensorflow-probability + conda install -c conda-forge salib ```
-
Edward (🥉23 · ⭐ 4.7K · 💀) - TensorFlow中的一种概率编程语言。❗Unlicensed +
Edward (🥉20 · ⭐ 4.7K · 💀) - A probabilistic programming language in TensorFlow. Deep.. ❗Unlicensed -- [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 760 · 📥 14 · 📦 240 · 📋 510 - 36% open · ⏱️ 25.07.2018): +- [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 750 · 📥 15 · 📦 250 · 📋 510 - 36% open · ⏱️ 25.07.2018): ``` git clone https://github.com/blei-lab/edward ``` -- [PyPi](https://pypi.org/project/edward) (📥 3.5K / month): +- [PyPi](https://pypi.org/project/edward): ``` pip install edward ```
-
SALib (🥉23 · ⭐ 530) - Python（Numpy）中的灵敏度分析库。MIT +
scikit-posthocs (🥉19 · ⭐ 220) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT -- [GitHub](https://github.com/SALib/SALib) (👨‍💻 34 · 🔀 160 · 📋 250 - 15% open · ⏱️ 25.09.2021): +- [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 8 · 🔀 23 · 📥 23 · 📋 43 - 9% open · ⏱️ 26.11.2021): ``` - git clone https://github.com/SALib/SALib - ``` -- [PyPi](https://pypi.org/project/salib) (📥 100K / month): - ``` - pip install salib + git clone https://github.com/maximtrp/scikit-posthocs ``` -- [Conda](https://anaconda.org/conda-forge/salib) (📥 70K · ⏱️ 04.09.2021): +- [PyPi](https://pypi.org/project/scikit-posthocs) (📥 38K / month): ``` - conda install -c conda-forge salib + pip install scikit-posthocs ```
-
Orbit (🥉19 · ⭐ 690) - 用于贝叶斯预测的Python软件包，具有面向对象的设计。❗Unlicensed +
Orbit (🥉18 · ⭐ 840) - A Python package for Bayesian forecasting with object-oriented.. ❗Unlicensed -- [GitHub](https://github.com/uber/orbit) (👨‍💻 14 · 🔀 53 · 📦 4 · 📋 270 - 12% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/uber/orbit) (👨‍💻 14 · 🔀 61 · 📦 5 · 📋 300 - 12% open · ⏱️ 15.12.2021): ``` git clone https://github.com/uber/orbit ``` -- [PyPi](https://pypi.org/project/orbit-ml) (📥 13K / month): +- [PyPi](https://pypi.org/project/orbit-ml) (📥 3.1K / month): ``` pip install orbit-ml ```
-
bambi (🥉19 · ⭐ 680) - Python中的贝叶斯模型构建接口（Bambi）。MIT +
Baal (🥉18 · ⭐ 490) - Using approximate bayesian posteriors in deep nets for active learning. Apache-2 -- [GitHub](https://github.com/bambinos/bambi) (👨‍💻 21 · 🔀 62 · 📦 14 · 📋 200 - 14% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/ElementAI/baal) (👨‍💻 11 · 🔀 48 · 📋 62 - 29% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/bambinos/bambi + git clone https://github.com/ElementAI/baal ``` -- [PyPi](https://pypi.org/project/bambi) (📥 840 / month): +- [PyPi](https://pypi.org/project/baal) (📥 530 / month): ``` - pip install bambi + pip install baal ```
-
scikit-posthocs (🥉19 · ⭐ 220) - Python中的多个成对比较（Post Hoc）测试。MIT +
bambi (🥉17 · ⭐ 700) - BAyesian Model-Building Interface (Bambi) in Python. MIT -- [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 8 · 🔀 22 · 📥 23 · 📋 42 - 9% open · ⏱️ 11.09.2021): +- [GitHub](https://github.com/bambinos/bambi) (👨‍💻 21 · 🔀 67 · 📦 18 · 📋 210 - 14% open · ⏱️ 01.12.2021): ``` - git clone https://github.com/maximtrp/scikit-posthocs + git clone https://github.com/bambinos/bambi ``` -- [PyPi](https://pypi.org/project/scikit-posthocs) (📥 25K / month): +- [PyPi](https://pypi.org/project/bambi): ``` - pip install scikit-posthocs + pip install bambi ```
-
Funsor (🥉19 · ⭐ 180) - 用于概率编程的函数张量。Apache-2 +
Funsor (🥉17 · ⭐ 180) - Functional tensors for probabilistic programming. Apache-2 -- [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 9 · 🔀 15 · 📦 16 · 📋 140 - 47% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 9 · 🔀 14 · 📦 20 · 📋 140 - 47% open · ⏱️ 13.12.2021): ``` git clone https://github.com/pyro-ppl/funsor ``` -- [PyPi](https://pypi.org/project/funsor) (📥 830 / month): +- [PyPi](https://pypi.org/project/funsor): ``` pip install funsor ```
-
pyhsmm (🥉18 · ⭐ 500 · 💀) - HSMM和HMM中的贝叶斯推断。MIT +
pyhsmm (🥉16 · ⭐ 500 · 💀) - Bayesian inference in HSMMs and HMMs. MIT -- [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 21 · 📋 94 - 36% open · ⏱️ 24.08.2020): +- [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 23 · 📋 95 - 36% open · ⏱️ 24.08.2020): ``` git clone https://github.com/mattjj/pyhsmm ``` -- [PyPi](https://pypi.org/project/pyhsmm) (📥 190 / month): +- [PyPi](https://pypi.org/project/pyhsmm): ``` pip install pyhsmm ```
-
Baal (🥉17 · ⭐ 440) - 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/ElementAI/baal) (👨‍💻 11 · 🔀 43 · 📋 54 - 22% open · ⏱️ 12.10.2021): - - ``` - git clone https://github.com/ElementAI/baal - ``` -- [PyPi](https://pypi.org/project/baal) (📥 410 / month): - ``` - pip install baal - ``` -
-
PyStan (🥉17 · ⭐ 120) - PyStan是Stan的Python接口。ISC +
PyStan (🥉15 · ⭐ 140) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC -- [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 9 · 🔀 28 · 📋 160 - 4% open · ⏱️ 06.10.2021): +- [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 10 · 🔀 34 · 📋 160 - 3% open · ⏱️ 21.10.2021): ``` git clone https://github.com/stan-dev/pystan ``` -- [PyPi](https://pypi.org/project/pystan) (📥 1.5M / month): +- [PyPi](https://pypi.org/project/pystan): ``` pip install pystan ``` @@ -9575,7 +9587,7 @@ _提供概率编程/推理，贝叶斯推理，高斯过程或统计信息的功 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 +
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): @@ -9585,947 +9597,923 @@ _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 (🥇28 · ⭐ 5.3K) - 一个用于构造攻击的对抗性示例库。MIT +
CleverHans (🥇25 · ⭐ 5.4K) - An adversarial example library for constructing attacks,.. MIT -- [GitHub](https://github.com/cleverhans-lab/cleverhans) (👨‍💻 130 · 🔀 1.3K · 📦 260 · 📋 440 - 3% open · ⏱️ 23.09.2021): +- [GitHub](https://github.com/cleverhans-lab/cleverhans) (👨‍💻 130 · 🔀 1.3K · 📦 280 · 📋 440 - 4% open · ⏱️ 23.09.2021): ``` git clone https://github.com/cleverhans-lab/cleverhans ``` -- [PyPi](https://pypi.org/project/cleverhans) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/cleverhans): ``` pip install cleverhans ```
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Foolbox (🥈26 · ⭐ 2K) - 一个Python工具箱，用于创建欺骗神经网络的对抗示例。MIT +
Foolbox (🥈23 · ⭐ 2.1K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT -- [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 360 · 📦 240 · 📋 330 - 17% open · ⏱️ 05.06.2021): +- [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 360 · 📦 260 · 📋 330 - 18% open · ⏱️ 05.06.2021): ``` git clone https://github.com/bethgelab/foolbox ``` -- [PyPi](https://pypi.org/project/foolbox) (📥 2.1K / month): +- [PyPi](https://pypi.org/project/foolbox): ``` pip install foolbox ```
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TextAttack (🥈26 · ⭐ 1.7K) - TextAttack是用于对抗攻击，数据的Python框架。MIT +
TextAttack (🥈23 · ⭐ 1.8K) - TextAttack is a Python framework for adversarial attacks, data.. MIT -- [GitHub](https://github.com/QData/TextAttack) (👨‍💻 43 · 🔀 200 · 📦 32 · 📋 150 - 23% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/QData/TextAttack) (👨‍💻 46 · 🔀 210 · 📦 48 · 📋 170 - 13% open · ⏱️ 16.12.2021): ``` git clone https://github.com/QData/TextAttack ``` -- [PyPi](https://pypi.org/project/textattack) (📥 43K / month): +- [PyPi](https://pypi.org/project/textattack): ``` pip install textattack ```
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ART (🥉23 · ⭐ 2.5K) - 对抗性鲁棒性工具箱（ART）- 用于机器学习的Python库。MIT +
ART (🥉20 · ⭐ 2.6K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT -- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (👨‍💻 87 · 🔀 690 · 📦 160 · 📋 590 - 9% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (👨‍💻 87 · 🔀 730 · 📦 170 · 📋 610 - 11% open · ⏱️ 13.12.2021): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` -- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (📥 4.4K / month): +- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox): ``` pip install adversarial-robustness-toolbox ```
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advertorch (🥉18 · ⭐ 930) - 对抗性鲁棒性研究的工具箱。❗️GPL-3.0 +
robustness (🥉18 · ⭐ 640) - A library for experimenting with, training and evaluating neural.. MIT -- [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 18 · 🔀 150 · 📦 50 · 📋 47 - 29% open · ⏱️ 30.07.2021): +- [GitHub](https://github.com/MadryLab/robustness) (👨‍💻 13 · 🔀 120 · 📦 67 · 📋 67 - 19% open · ⏱️ 30.11.2021): ``` - git clone https://github.com/BorealisAI/advertorch + git clone https://github.com/MadryLab/robustness ``` -- [PyPi](https://pypi.org/project/advertorch) (📥 550 / month): +- [PyPi](https://pypi.org/project/robustness) (📥 880 / month): ``` - pip install advertorch + pip install robustness ```
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robustness (🥉18 · ⭐ 600 · 💤) - 一个用于实验，训练和评估神经网络的库。MIT +
advertorch (🥉16 · ⭐ 980) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 -- [GitHub](https://github.com/MadryLab/robustness) (👨‍💻 12 · 🔀 110 · 📦 62 · 📋 64 - 17% open · ⏱️ 04.03.2021): +- [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 18 · 🔀 160 · 📦 57 · 📋 48 - 31% open · ⏱️ 30.07.2021): ``` - git clone https://github.com/MadryLab/robustness + git clone https://github.com/BorealisAI/advertorch ``` -- [PyPi](https://pypi.org/project/robustness) (📥 2.7K / month): +- [PyPi](https://pypi.org/project/advertorch): ``` - pip install robustness + pip install advertorch ```
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AdvBox (🥉16 · ⭐ 1.2K) - Advbox是一个工具箱，用于生成对抗示例。Apache-2 +
AdvBox (🥉14 · ⭐ 1.2K · 💤) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 -- [GitHub](https://github.com/advboxes/AdvBox) (👨‍💻 19 · 🔀 240 · 📋 33 - 12% open · ⏱️ 03.05.2021): +- [GitHub](https://github.com/advboxes/AdvBox) (👨‍💻 19 · 🔀 240 · 📋 35 - 17% open · ⏱️ 03.05.2021): ``` git clone https://github.com/advboxes/AdvBox ``` -- [PyPi](https://pypi.org/project/advbox) (📥 46 / month): +- [PyPi](https://pypi.org/project/advbox): ``` 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 (🥇31 · ⭐ 5.4K) - CUDA加速了与NumPy兼容的数组库。MIT +
CuPy (🥇32 · ⭐ 5.6K) - A NumPy-compatible array library accelerated by CUDA. MIT -- [GitHub](https://github.com/cupy/cupy) (👨‍💻 270 · 🔀 480 · 📥 22K · 📦 840 · 📋 1.5K - 21% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/cupy/cupy) (👨‍💻 290 · 🔀 510 · 📥 23K · 📦 890 · 📋 1.6K - 19% open · ⏱️ 16.12.2021): ``` git clone https://github.com/cupy/cupy ``` -- [PyPi](https://pypi.org/project/cupy) (📥 100K / month): +- [PyPi](https://pypi.org/project/cupy) (📥 110K / month): ``` pip install cupy ``` -- [Conda](https://anaconda.org/conda-forge/cupy) (📥 950K · ⏱️ 02.10.2021): +- [Conda](https://anaconda.org/conda-forge/cupy) (📥 1.1M · ⏱️ 15.12.2021): ``` conda install -c conda-forge cupy ``` -- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (📥 53K · ⭐ 7 · ⏱️ 30.09.2021): +- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (📥 53K · ⭐ 7 · ⏱️ 09.12.2021): ``` docker pull cupy/cupy ```
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gpustat (🥇27 · ⭐ 2.6K) - 一个简单的命令行实用程序，用于查询和监控GPU状态。MIT +
gpustat (🥇27 · ⭐ 2.7K) - A simple command-line utility for querying and monitoring GPU status. MIT -- [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 12 · 🔀 200 · 📦 1.3K · 📋 71 - 23% open · ⏱️ 05.08.2021): +- [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 12 · 🔀 210 · 📦 1.5K · 📋 75 - 25% open · ⏱️ 13.08.2021): ``` git clone https://github.com/wookayin/gpustat ``` -- [PyPi](https://pypi.org/project/gpustat) (📥 300K / month): +- [PyPi](https://pypi.org/project/gpustat) (📥 400K / month): ``` pip install gpustat ``` -- [Conda](https://anaconda.org/conda-forge/gpustat) (📥 75K · ⏱️ 24.11.2020): +- [Conda](https://anaconda.org/conda-forge/gpustat) (📥 100K · ⏱️ 24.11.2020): ``` conda install -c conda-forge gpustat ```
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Apex (🥈23 · ⭐ 5.8K) - PyTorch扩展：易于实现混合精度和分布式的工具。BSD-3 +
Apex (🥈23 · ⭐ 6K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 -- [GitHub](https://github.com/NVIDIA/apex) (👨‍💻 86 · 🔀 800 · 📦 740 · 📋 880 - 55% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/NVIDIA/apex) (👨‍💻 88 · 🔀 850 · 📦 830 · 📋 900 - 56% open · ⏱️ 16.12.2021): ``` git clone https://github.com/NVIDIA/apex ``` -- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (📥 64K · ⏱️ 22.04.2021): +- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (📥 71K · ⏱️ 22.04.2021): ``` conda install -c conda-forge nvidia-apex ```
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GPUtil (🥈23 · ⭐ 770 · 💀) - 一个Python模块，用于从NVIDA GPU获取GPU状态。MIT +
GPUtil (🥈23 · ⭐ 800 · 💀) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT -- [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 86 · 📦 1.5K · 📋 25 - 44% open · ⏱️ 16.08.2019): +- [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 85 · 📦 1.6K · 📋 25 - 44% open · ⏱️ 16.08.2019): ``` git clone https://github.com/anderskm/gputil ``` -- [PyPi](https://pypi.org/project/gputil) (📥 340K / month): +- [PyPi](https://pypi.org/project/gputil) (📥 430K / month): ``` pip install gputil ```
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py3nvml (🥈23 · ⭐ 190) - NVML库的Python3接口。在内部获取NVIDIA GPU状态。BSD-3 +
py3nvml (🥈20 · ⭐ 200) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 -- [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 8 · 🔀 25 · 📦 320 · 📋 12 - 16% open · ⏱️ 06.09.2021): +- [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 8 · 🔀 28 · 📦 360 · 📋 12 - 16% open · ⏱️ 06.09.2021): ``` git clone https://github.com/fbcotter/py3nvml ``` -- [PyPi](https://pypi.org/project/py3nvml) (📥 120K / month): +- [PyPi](https://pypi.org/project/py3nvml): ``` pip install py3nvml ``` -- [Conda](https://anaconda.org/conda-forge/py3nvml) (📥 22K · ⏱️ 10.10.2020): +- [Conda](https://anaconda.org/conda-forge/py3nvml) (📥 24K · ⏱️ 19.11.2021): ``` conda install -c conda-forge py3nvml ```
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PyCUDA (🥈21 · ⭐ 1.2K) - 适用于Python的CUDA集成，有着出色的功能。❗Unlicensed +
cuDF (🥈19 · ⭐ 4.4K) - cuDF - GPU DataFrame Library. Apache-2 -- [GitHub](https://github.com/inducer/pycuda) (👨‍💻 74 · 🔀 240 · 📦 1K · 📋 200 - 27% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 230 · 🔀 570 · 📋 4.2K - 14% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/inducer/pycuda + git clone https://github.com/rapidsai/cudf ``` -- [PyPi](https://pypi.org/project/pycuda) (📥 30K / month): +- [PyPi](https://pypi.org/project/cudf) (📥 1.1K / month): ``` - pip install pycuda + pip install cudf ```
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cuDF (🥈19 · ⭐ 4.2K) - cuDF-GPU DataFrame库。Apache-2 +
ArrayFire (🥈19 · ⭐ 3.7K) - ArrayFire: a general purpose GPU library. ❗Unlicensed -- [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 220 · 🔀 550 · 📋 4K - 14% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 81 · 🔀 480 · 📥 1.7K · 📋 1.5K - 15% open · ⏱️ 15.10.2021): ``` - git clone https://github.com/rapidsai/cudf + git clone https://github.com/arrayfire/arrayfire ``` -- [PyPi](https://pypi.org/project/cudf) (📥 1K / month): +- [PyPi](https://pypi.org/project/arrayfire) (📥 520 / month): ``` - pip install cudf + pip install arrayfire ```
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ArrayFire (🥈19 · ⭐ 3.6K) - ArrayFire：通用GPU库。❗Unlicensed +
cuML (🥉18 · ⭐ 2.5K) - cuML - RAPIDS Machine Learning Library. Apache-2 -- [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 82 · 🔀 480 · 📥 1.6K · 📋 1.5K - 15% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 140 · 🔀 370 · 📋 1.9K - 32% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/arrayfire/arrayfire + git clone https://github.com/rapidsai/cuml ``` -- [PyPi](https://pypi.org/project/arrayfire) (📥 540 / month): +- [PyPi](https://pypi.org/project/cuml) (📥 750 / month): ``` - pip install arrayfire + pip install cuml ```
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scikit-cuda (🥈19 · ⭐ 860) - GPU工具库的python接口。❗Unlicensed +
DALI (🥉17 · ⭐ 3.6K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 -- [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 45 · 🔀 160 · 📦 140 · 📋 220 - 22% open · ⏱️ 13.07.2021): +- [GitHub](https://github.com/NVIDIA/DALI) (👨‍💻 67 · 🔀 450 · 📋 1.1K - 13% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/lebedov/scikit-cuda - ``` -- [PyPi](https://pypi.org/project/scikit-cuda) (📥 730 / month): - ``` - pip install scikit-cuda + git clone https://github.com/NVIDIA/DALI ```
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cuML (🥉18 · ⭐ 2.4K) - cuML-RAPIDS机器学习库。Apache-2 +
BlazingSQL (🥉17 · ⭐ 1.6K) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 -- [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 140 · 🔀 360 · 📋 1.8K - 32% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/BlazingDB/blazingsql) (👨‍💻 47 · 🔀 160 · 📋 710 - 17% open · ⏱️ 30.09.2021): ``` - git clone https://github.com/rapidsai/cuml + git clone https://github.com/BlazingDB/blazingsql ``` -- [PyPi](https://pypi.org/project/cuml) (📥 560 / month): +- [Conda](https://anaconda.org/blazingsql/blazingsql-protocol) (📥 940 · ⏱️ 11.11.2019): ``` - pip install cuml + conda install -c blazingsql blazingsql-protocol ```
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Vulkan Kompute (🥉18 · ⭐ 580) - 适用于跨供应商的通用GPU计算框架。Apache-2 +
PyCUDA (🥉17 · ⭐ 1.2K) - CUDA integration for Python, plus shiny features. ❗Unlicensed -- [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 15 · 🔀 46 · 📥 90 · 📦 2 · 📋 160 - 32% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/inducer/pycuda) (👨‍💻 74 · 🔀 240 · 📦 1.1K · 📋 210 - 26% open · ⏱️ 07.12.2021): ``` - git clone https://github.com/EthicalML/vulkan-kompute + git clone https://github.com/inducer/pycuda ``` -- [PyPi](https://pypi.org/project/kp) (📥 150 / month): +- [PyPi](https://pypi.org/project/pycuda): ``` - pip install kp + pip install pycuda ```
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DALI (🥉17 · ⭐ 3.5K) - GPU加速的库，其中包含高度优化的构建块。Apache-2 +
cuGraph (🥉17 · ⭐ 870) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 -- [GitHub](https://github.com/NVIDIA/DALI) (👨‍💻 63 · 🔀 430 · 📋 1K - 12% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 70 · 🔀 170 · 📋 730 - 8% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/NVIDIA/DALI + git clone https://github.com/rapidsai/cugraph + ``` +- [PyPi](https://pypi.org/project/cugraph) (📥 200 / month): + ``` + pip install cugraph ```
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BlazingSQL (🥉17 · ⭐ 1.6K) - BlazingSQL是一种用于GPU的轻量级，GPU加速的引擎。Apache-2 +
scikit-cuda (🥉17 · ⭐ 870) - Python interface to GPU-powered libraries. ❗Unlicensed -- [GitHub](https://github.com/BlazingDB/blazingsql) (👨‍💻 47 · 🔀 150 · 📋 700 - 16% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 45 · 🔀 170 · 📦 150 · 📋 220 - 23% open · ⏱️ 13.07.2021): ``` - git clone https://github.com/BlazingDB/blazingsql + git clone https://github.com/lebedov/scikit-cuda ``` -- [Conda](https://anaconda.org/blazingsql/blazingsql-protocol) (📥 940 · ⏱️ 11.11.2019): +- [PyPi](https://pypi.org/project/scikit-cuda): ``` - conda install -c blazingsql blazingsql-protocol + pip install scikit-cuda ```
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nvidia-ml-py3 (🥉17 · ⭐ 69 · 💀) - NVIDIA Management Library的Python3接口。❗Unlicensed +
Vulkan Kompute (🥉17 · ⭐ 620) - General purpose GPU compute framework for cross vendor.. Apache-2 -- [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 15 · 📦 4.2K · ⏱️ 06.03.2019): +- [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 16 · 🔀 49 · 📥 100 · 📦 2 · 📋 160 - 32% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/nicolargo/nvidia-ml-py3 + git clone https://github.com/EthicalML/vulkan-kompute ``` -- [PyPi](https://pypi.org/project/nvidia-ml-py3) (📥 530K / month): +- [PyPi](https://pypi.org/project/kp) (📥 96 / month): ``` - pip install nvidia-ml-py3 + pip install kp ```
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cuGraph (🥉16 · ⭐ 820) - cuGraph-RAPIDS图形分析库。Apache-2 +
cuSignal (🥉14 · ⭐ 550) - GPU accelerated signal processing. Apache-2 -- [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 68 · 🔀 160 · 📋 700 - 8% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 36 · 🔀 80 · 📋 120 - 9% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/rapidsai/cugraph - ``` -- [PyPi](https://pypi.org/project/cugraph) (📥 140 / month): - ``` - pip install cugraph + git clone https://github.com/rapidsai/cusignal ```
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SpeedTorch (🥉14 · ⭐ 630 · 💀) - 用于更快的Pytorch中CPU-GPU传输的工具库。MIT +
SpeedTorch (🥉13 · ⭐ 640 · 💀) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT -- [GitHub](https://github.com/Santosh-Gupta/SpeedTorch) (👨‍💻 3 · 🔀 38 · 📦 3 · 📋 5 - 60% open · ⏱️ 21.02.2020): +- [GitHub](https://github.com/Santosh-Gupta/SpeedTorch) (👨‍💻 3 · 🔀 39 · 📦 3 · 📋 6 - 66% open · ⏱️ 21.02.2020): ``` git clone https://github.com/Santosh-Gupta/SpeedTorch ``` -- [PyPi](https://pypi.org/project/SpeedTorch) (📥 81 / month): +- [PyPi](https://pypi.org/project/SpeedTorch): ``` pip install SpeedTorch ```
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cuSignal (🥉14 · ⭐ 530) - GPU加速信号处理。Apache-2 +
nvidia-ml-py3 (🥉11 · ⭐ 71 · 💀) - Python 3 Bindings for the NVIDIA Management Library. ❗Unlicensed -- [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 35 · 🔀 76 · 📋 120 - 8% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 15 · 📦 4.6K · ⏱️ 06.03.2019): ``` - git clone https://github.com/rapidsai/cusignal + git clone https://github.com/nicolargo/nvidia-ml-py3 + ``` +- [PyPi](https://pypi.org/project/nvidia-ml-py3): + ``` + pip install nvidia-ml-py3 ```
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ipyexperiments (🥉12 · ⭐ 140) - jupyter/ipython实验容器。❗Unlicensed +
ipyexperiments (🥉10 · ⭐ 140) - jupyter/ipython experiment containers for GPU and.. ❗Unlicensed -- [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 10 · 📦 5 · ⏱️ 16.09.2021): +- [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 10 · 📦 5 · ⏱️ 07.12.2021): ``` git clone https://github.com/stas00/ipyexperiments ``` -- [PyPi](https://pypi.org/project/ipyexperiments) (📥 160 / month): +- [PyPi](https://pypi.org/project/ipyexperiments): ``` 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._ -
TF Addons (🥇34 · ⭐ 1.4K) - 由TensorFlow 2.x维护的有用额外功能。Apache-2 +
tensorflow-hub (🥇28 · ⭐ 3K) - A library for transfer learning by reusing parts of.. Apache-2 -- [GitHub](https://github.com/tensorflow/addons) (👨‍💻 180 · 🔀 470 · 📦 4.3K · 📋 850 - 19% open · ⏱️ 09.10.2021): +- [GitHub](https://github.com/tensorflow/hub) (👨‍💻 83 · 🔀 1.6K · 📦 9.5K · 📋 630 - 2% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/tensorflow/addons + git clone https://github.com/tensorflow/hub ``` -- [PyPi](https://pypi.org/project/tensorflow-addons) (📥 12M / month): +- [PyPi](https://pypi.org/project/tensorflow-hub): ``` - pip install tensorflow-addons + pip install tensorflow-hub + ``` +- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (📥 59K · ⏱️ 18.04.2021): + ``` + conda install -c conda-forge tensorflow-hub ```
-
tensor2tensor (🥇32 · ⭐ 12K) - 设计深度学习模型和数据集的库。Apache-2 +
tensor2tensor (🥇27 · ⭐ 12K) - Library of deep learning models and datasets designed to.. Apache-2 -- [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 2.9K · 📦 1K · 📋 1.2K - 45% open · ⏱️ 17.09.2021): +- [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 2.9K · 📦 1.1K · 📋 1.2K - 45% open · ⏱️ 02.12.2021): ``` git clone https://github.com/tensorflow/tensor2tensor ``` -- [PyPi](https://pypi.org/project/tensor2tensor) (📥 390K / month): +- [PyPi](https://pypi.org/project/tensor2tensor): ``` pip install tensor2tensor ```
-
tensorflow-hub (🥈31 · ⭐ 3K) - 通过重用部分库来进行迁移学习的库。Apache-2 +
TF Addons (🥇27 · ⭐ 1.4K · 📉) - Useful extra functionality for TensorFlow 2.x maintained.. Apache-2 -- [GitHub](https://github.com/tensorflow/hub) (👨‍💻 77 · 🔀 1.6K · 📦 8.6K · 📋 610 - 1% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/tensorflow/addons) (👨‍💻 180 · 🔀 480 · 📦 4.9K · 📋 860 - 19% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/tensorflow/hub - ``` -- [PyPi](https://pypi.org/project/tensorflow-hub) (📥 3.1M / month): - ``` - pip install tensorflow-hub + git clone https://github.com/tensorflow/addons ``` -- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (📥 58K · ⏱️ 18.04.2021): +- [PyPi](https://pypi.org/project/tensorflow-addons): ``` - conda install -c conda-forge tensorflow-hub + pip install tensorflow-addons ```
-
TF Model Optimization (🥈29 · ⭐ 1.1K) - 用于优化ML模型以进行部署的工具包。Apache-2 +
TF Model Optimization (🥈24 · ⭐ 1.2K) - A toolkit to optimize ML models for deployment for.. Apache-2 -- [GitHub](https://github.com/tensorflow/model-optimization) (👨‍💻 62 · 🔀 240 · 📦 1.2K · 📋 250 - 45% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/tensorflow/model-optimization) (👨‍💻 64 · 🔀 250 · 📦 1.4K · 📋 260 - 45% open · ⏱️ 16.12.2021): ``` git clone https://github.com/tensorflow/model-optimization ``` -- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (📥 180K / month): +- [PyPi](https://pypi.org/project/tensorflow-model-optimization): ``` pip install tensorflow-model-optimization ```
-
TensorFlow Transform (🥈29 · ⭐ 880) - 输入管道框架。Apache-2 +
efficientnet (🥈22 · ⭐ 1.9K) - Implementation of EfficientNet model. Keras and.. Apache-2 -- [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 170 · 📦 560 · 📋 160 - 11% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 430 · 📥 200K · 📦 830 · 📋 110 - 48% open · ⏱️ 16.07.2021): ``` - git clone https://github.com/tensorflow/transform + git clone https://github.com/qubvel/efficientnet ``` -- [PyPi](https://pypi.org/project/tensorflow-transform) (📥 13M / month): +- [PyPi](https://pypi.org/project/efficientnet): ``` - pip install tensorflow-transform + pip install efficientnet ```
-
TensorFlow Cloud (🥉26 · ⭐ 310) - TensorFlow Cloud存储库提供的API。Apache-2 +
TensorFlow Transform (🥈22 · ⭐ 900 · 📉) - Input pipeline framework. Apache-2 -- [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 25 · 🔀 58 · 📦 98 · 📋 76 - 65% open · ⏱️ 07.09.2021): +- [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 180 · 📦 640 · 📋 170 - 11% open · ⏱️ 16.12.2021): ``` - git clone https://github.com/tensorflow/cloud + git clone https://github.com/tensorflow/transform ``` -- [PyPi](https://pypi.org/project/tensorflow-cloud) (📥 710K / month): +- [PyPi](https://pypi.org/project/tensorflow-transform): ``` - pip install tensorflow-cloud + pip install tensorflow-transform ```
-
efficientnet (🥉25 · ⭐ 1.9K) - EfficientNet模型的实现。Apache-2 +
Neural Structured Learning (🥉20 · ⭐ 890) - Training neural models with structured signals. Apache-2 -- [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 420 · 📥 190K · 📦 760 · 📋 110 - 47% open · ⏱️ 16.07.2021): +- [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 30 · 🔀 160 · 📦 150 · 📋 59 - 3% open · ⏱️ 06.12.2021): ``` - git clone https://github.com/qubvel/efficientnet + git clone https://github.com/tensorflow/neural-structured-learning ``` -- [PyPi](https://pypi.org/project/efficientnet) (📥 94K / month): +- [PyPi](https://pypi.org/project/neural-structured-learning): ``` - pip install efficientnet + pip install neural-structured-learning ```
-
Neural Structured Learning (🥉24 · ⭐ 870) - 用结构化信号训练神经模型。Apache-2 +
TensorFlow I/O (🥉19 · ⭐ 520) - Dataset, streaming, and file system extensions.. Apache-2 -- [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 30 · 🔀 160 · 📦 110 · 📋 59 - 3% open · ⏱️ 28.09.2021): +- [GitHub](https://github.com/tensorflow/io) (👨‍💻 83 · 🔀 200 · 📋 480 - 31% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/tensorflow/neural-structured-learning + git clone https://github.com/tensorflow/io ``` -- [PyPi](https://pypi.org/project/neural-structured-learning) (📥 11K / month): +- [PyPi](https://pypi.org/project/tensorflow-io): ``` - pip install neural-structured-learning + pip install tensorflow-io ```
-
TensorFlow I/O (🥉24 · ⭐ 500) - Dataset, streaming, and file system extensions.. Apache-2 +
TensorFlow Cloud (🥉19 · ⭐ 320) - The TensorFlow Cloud repository provides APIs that.. Apache-2 -- [GitHub](https://github.com/tensorflow/io) (👨‍💻 78 · 🔀 180 · 📋 460 - 32% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 25 · 🔀 64 · 📦 120 · 📋 80 - 67% open · ⏱️ 07.09.2021): ``` - git clone https://github.com/tensorflow/io + git clone https://github.com/tensorflow/cloud ``` -- [PyPi](https://pypi.org/project/tensorflow-io) (📥 140K / month): +- [PyPi](https://pypi.org/project/tensorflow-cloud): ``` - pip install tensorflow-io + pip install tensorflow-cloud ```
-
TensorNets (🥉18 · ⭐ 990 · 💤) - 具有预先训练的权重的高级网络定义。MIT +
TensorNets (🥉17 · ⭐ 1K · 💤) - High level network definitions with pre-trained weights in.. MIT -- [GitHub](https://github.com/taehoonlee/tensornets) (👨‍💻 6 · 🔀 180 · 📦 41 · 📋 58 - 27% open · ⏱️ 02.01.2021): +- [GitHub](https://github.com/taehoonlee/tensornets) (👨‍💻 6 · 🔀 190 · 📦 42 · 📋 58 - 27% open · ⏱️ 02.01.2021): ``` git clone https://github.com/taehoonlee/tensornets ``` -- [PyPi](https://pypi.org/project/tensornets) (📥 140 / month): +- [PyPi](https://pypi.org/project/tensornets): ``` pip install tensornets ```
-
TF Compression (🥉18 · ⭐ 530) - TensorFlow中的数据压缩。Apache-2 +
TF Compression (🥉15 · ⭐ 550) - Data compression in TensorFlow. Apache-2 -- [GitHub](https://github.com/tensorflow/compression) (👨‍💻 10 · 🔀 190 · 📋 74 - 4% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/tensorflow/compression) (👨‍💻 10 · 🔀 200 · 📋 76 - 3% open · ⏱️ 26.10.2021): ``` git clone https://github.com/tensorflow/compression ``` -- [PyPi](https://pypi.org/project/tensorflow-compression) (📥 710 / month): +- [PyPi](https://pypi.org/project/tensorflow-compression): ``` pip install tensorflow-compression ```
-
tffm (🥉17 · ⭐ 770 · 💀) - 任意阶乘分解机的TensorFlow实现。MIT +
tffm (🥉14 · ⭐ 770 · 💀) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT - [GitHub](https://github.com/geffy/tffm) (👨‍💻 10 · 🔀 180 · 📦 11 · 📋 39 - 43% open · ⏱️ 22.05.2020): ``` git clone https://github.com/geffy/tffm ``` -- [PyPi](https://pypi.org/project/tffm) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/tffm): ``` pip install tffm ```
-
Saliency (🥉16 · ⭐ 720) - 与框架无关的实现，可实现最新的显着性。Apache-2 +
Saliency (🥉14 · ⭐ 750) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 -- [GitHub](https://github.com/PAIR-code/saliency) (👨‍💻 14 · 🔀 150 · 📦 18 · ⏱️ 28.07.2021): +- [GitHub](https://github.com/PAIR-code/saliency) (👨‍💻 14 · 🔀 160 · 📦 19 · ⏱️ 28.07.2021): ``` git clone https://github.com/PAIR-code/saliency ``` -- [PyPi](https://pypi.org/project/saliency) (📥 550 / month): +- [PyPi](https://pypi.org/project/saliency): ``` pip install saliency ```

-## 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 · ⭐ 5.5K) - 一个解决不平衡类别数据建模的Python程序包。MIT +
imbalanced-learn (🥇31 · ⭐ 5.6K) - A Python Package to Tackle the Curse of Imbalanced.. MIT -- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (👨‍💻 58 · 🔀 1.1K · 📦 7.5K · 📋 480 - 8% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (👨‍💻 61 · 🔀 1.1K · 📦 8.4K · 📋 480 - 8% open · ⏱️ 07.12.2021): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` -- [PyPi](https://pypi.org/project/imbalanced-learn) (📥 2.2M / month): +- [PyPi](https://pypi.org/project/imbalanced-learn) (📥 2.8M / month): ``` pip install imbalanced-learn ``` -- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (📥 160K · ⏱️ 29.09.2021): +- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (📥 170K · ⏱️ 29.09.2021): ``` conda install -c conda-forge imbalanced-learn ```
-
MLxtend (🥇30 · ⭐ 3.7K) - 用于Python数据的扩展和帮助程序模块库。❗Unlicensed +
category_encoders (🥇30 · ⭐ 1.8K · 📈) - A library of sklearn compatible categorical variable.. BSD-3 -- [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 85 · 🔀 720 · 📦 4.3K · 📋 380 - 22% open · ⏱️ 02.09.2021): +- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (👨‍💻 48 · 🔀 330 · 📦 2.8K · 📋 220 - 28% open · ⏱️ 16.11.2021): + + ``` + git clone https://github.com/scikit-learn-contrib/category_encoders + ``` +- [PyPi](https://pypi.org/project/category_encoders) (📥 980K / month): + ``` + pip install category_encoders + ``` +- [Conda](https://anaconda.org/conda-forge/category_encoders) (📥 130K · ⏱️ 13.10.2021): + ``` + conda install -c conda-forge category_encoders + ``` +
+
MLxtend (🥈27 · ⭐ 3.7K) - A library of extension and helper modules for Python's data.. ❗Unlicensed + +- [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 85 · 🔀 720 · 📦 4.8K · 📋 390 - 23% open · ⏱️ 29.11.2021): ``` git clone https://github.com/rasbt/mlxtend ``` -- [PyPi](https://pypi.org/project/mlxtend) (📥 1.4M / month): +- [PyPi](https://pypi.org/project/mlxtend): ``` pip install mlxtend ``` -- [Conda](https://anaconda.org/conda-forge/mlxtend) (📥 180K · ⏱️ 03.09.2021): +- [Conda](https://anaconda.org/conda-forge/mlxtend) (📥 190K · ⏱️ 03.09.2021): ``` conda install -c conda-forge mlxtend ```
-
category_encoders (🥈25 · ⭐ 1.8K) - A library of sklearn compatible categorical variable.. BSD-3 +
sklearn-contrib-lightning (🥈21 · ⭐ 1.5K) - Large-scale linear classification, regression and.. ❗Unlicensed -- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (👨‍💻 43 · 🔀 320 · 📋 220 - 34% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 170 · 📥 100 · 📦 96 · 📋 85 - 52% open · ⏱️ 15.06.2021): ``` - git clone https://github.com/scikit-learn-contrib/category_encoders + git clone https://github.com/scikit-learn-contrib/lightning ``` -- [PyPi](https://pypi.org/project/category_encoders) (📥 710K / month): +- [PyPi](https://pypi.org/project/sklearn-contrib-lightning): ``` - pip install category_encoders + pip install sklearn-contrib-lightning ``` -- [Conda](https://anaconda.org/conda-forge/category_encoders) (📥 120K · ⏱️ 29.04.2020): +- [Conda](https://anaconda.org/conda-forge/sklearn-contrib-lightning) (📥 160K · ⏱️ 13.11.2021): ``` - conda install -c conda-forge category_encoders + conda install -c conda-forge sklearn-contrib-lightning ```
-
fancyimpute (🥈24 · ⭐ 1K) - 多元插补和矩阵补全算法。Apache-2 +
fancyimpute (🥈21 · ⭐ 1K) - Multivariate imputation and matrix completion algorithms.. Apache-2 -- [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 11 · 🔀 150 · 📦 1.1K · 📋 110 - 3% open · ⏱️ 26.08.2021): +- [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 12 · 🔀 160 · 📦 1.1K · 📋 110 - 0% open · ⏱️ 21.10.2021): ``` git clone https://github.com/iskandr/fancyimpute ``` -- [PyPi](https://pypi.org/project/fancyimpute) (📥 7.4K / month): +- [PyPi](https://pypi.org/project/fancyimpute): ``` pip install fancyimpute ```
-
scikit-opt (🥈23 · ⭐ 2.6K) - 遗传算法，粒子群优化等实现。MIT +
scikit-opt (🥈20 · ⭐ 2.8K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT -- [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 13 · 🔀 610 · 📦 48 · 📋 120 - 20% open · ⏱️ 26.09.2021): +- [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 13 · 🔀 660 · 📦 55 · 📋 130 - 22% open · ⏱️ 04.12.2021): ``` git clone https://github.com/guofei9987/scikit-opt ``` -- [PyPi](https://pypi.org/project/scikit-opt) (📥 1K / month): +- [PyPi](https://pypi.org/project/scikit-opt): ``` pip install scikit-opt ```
-
scikit-multilearn (🥈23 · ⭐ 690 · 💀) - 基于scikit-learn的多标签等模块。BSD-2 - -- [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 15 · 🔀 130 · 📦 550 · 📋 160 - 42% open · ⏱️ 21.05.2019): - - ``` - git clone https://github.com/scikit-multilearn/scikit-multilearn - ``` -- [PyPi](https://pypi.org/project/scikit-multilearn) (📥 84K / month): - ``` - pip install scikit-multilearn - ``` -
-
sklearn-contrib-lightning (🥈21 · ⭐ 1.5K) - 大规模线性分类，回归分析等。❗Unlicensed +
scikit-lego (🥈19 · ⭐ 670) - Extra blocks for scikit-learn pipelines. MIT -- [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 170 · 📥 71 · 📦 87 · 📋 84 - 52% open · ⏱️ 15.06.2021): +- [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 48 · 🔀 75 · 📦 39 · 📋 230 - 13% open · ⏱️ 09.12.2021): ``` - git clone https://github.com/scikit-learn-contrib/lightning + git clone https://github.com/koaning/scikit-lego ``` -- [PyPi](https://pypi.org/project/sklearn-contrib-lightning) (📥 2.8K / month): +- [PyPi](https://pypi.org/project/scikit-lego): ``` - pip install sklearn-contrib-lightning + pip install scikit-lego ``` -- [Conda](https://anaconda.org/conda-forge/sklearn-contrib-lightning) (📥 160K · ⏱️ 20.12.2020): +- [Conda](https://anaconda.org/conda-forge/scikit-lego) (📥 16K · ⏱️ 09.12.2021): ``` - conda install -c conda-forge sklearn-contrib-lightning + conda install -c conda-forge scikit-lego ```
-
scikit-lego (🥈21 · ⭐ 620) - scikit学习管道的额外块。MIT +
scikit-multilearn (🥉18 · ⭐ 710 · 💀) - A scikit-learn based module for multi-label et. al... BSD-2 -- [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 47 · 🔀 75 · 📦 33 · 📋 230 - 13% open · ⏱️ 30.09.2021): +- [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 15 · 🔀 130 · 📦 610 · 📋 170 - 43% open · ⏱️ 21.05.2019): ``` - git clone https://github.com/koaning/scikit-lego - ``` -- [PyPi](https://pypi.org/project/scikit-lego) (📥 25K / month): - ``` - pip install scikit-lego + git clone https://github.com/scikit-multilearn/scikit-multilearn ``` -- [Conda](https://anaconda.org/conda-forge/scikit-lego) (📥 15K · ⏱️ 03.07.2021): +- [PyPi](https://pypi.org/project/scikit-multilearn): ``` - conda install -c conda-forge scikit-lego + pip install scikit-multilearn ```
-
iterative-stratification (🥈21 · ⭐ 600) - scikit-learn交叉验证器。BSD-3 +
iterative-stratification (🥉18 · ⭐ 610) - scikit-learn cross validators for iterative.. BSD-3 -- [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 5 · 🔀 56 · 📦 170 · 📋 17 - 17% open · ⏱️ 03.10.2021): +- [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 6 · 🔀 56 · 📦 180 · 📋 19 - 21% open · ⏱️ 11.11.2021): ``` git clone https://github.com/trent-b/iterative-stratification ``` -- [PyPi](https://pypi.org/project/iterative-stratification) (📥 5.8K / month): +- [PyPi](https://pypi.org/project/iterative-stratification): ``` pip install iterative-stratification ```
-
combo (🥈21 · ⭐ 540) - （AAAI'20）用于机器学习模型的Python工具箱。BSD-2 xgboost +
combo (🥉17 · ⭐ 560) - (AAAI' 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost -- [GitHub](https://github.com/yzhao062/combo) (🔀 91 · 📦 400 · 📋 12 - 75% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/yzhao062/combo) (🔀 93 · 📦 440 · 📋 12 - 75% open · ⏱️ 02.10.2021): ``` git clone https://github.com/yzhao062/combo ``` -- [PyPi](https://pypi.org/project/combo) (📥 47K / month): +- [PyPi](https://pypi.org/project/combo): ``` pip install combo ```
-
sklearn-crfsuite (🥉20 · ⭐ 380 · 💀) - 用于CRFsuite的scikit-learn启发式API。❗Unlicensed +
sklearn-crfsuite (🥉16 · ⭐ 380 · 💀) - scikit-learn inspired API for CRFsuite. ❗Unlicensed -- [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 160 · 📦 3.1K · 📋 52 - 55% open · ⏱️ 05.12.2019): +- [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 180 · 📦 3.3K · 📋 53 - 56% open · ⏱️ 05.12.2019): ``` git clone https://github.com/TeamHG-Memex/sklearn-crfsuite ``` -- [PyPi](https://pypi.org/project/sklearn-crfsuite) (📥 120K / month): +- [PyPi](https://pypi.org/project/sklearn-crfsuite): ``` pip install sklearn-crfsuite ```
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skope-rules (🥉19 · ⭐ 420 · 💤) - 使用Python中的逻辑规则进行机器学习。❗Unlicensed +
skggm (🥉16 · ⭐ 190 · 💤) - Scikit-learn compatible estimation of general graphical models. MIT -- [GitHub](https://github.com/scikit-learn-contrib/skope-rules) (👨‍💻 18 · 🔀 68 · 📦 48 · 📋 27 - 81% open · ⏱️ 23.10.2020): +- [GitHub](https://github.com/skggm/skggm) (👨‍💻 5 · 🔀 34 · 📦 8 · 📋 75 - 37% open · ⏱️ 24.12.2020): ``` - git clone https://github.com/scikit-learn-contrib/skope-rules + git clone https://github.com/skggm/skggm ``` -- [PyPi](https://pypi.org/project/skope-rules) (📥 73K / month): +- [PyPi](https://pypi.org/project/skggm): ``` - pip install skope-rules + pip install skggm ```
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DESlib (🥉18 · ⭐ 350) - 一个用于动态分类器和集成选择的Python库。BSD-3 +
DESlib (🥉15 · ⭐ 370) - A Python library for dynamic classifier and ensemble selection. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (👨‍💻 13 · 🔀 54 · 📦 22 · 📋 140 - 7% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (👨‍💻 13 · 🔀 56 · 📦 22 · 📋 140 - 8% open · ⏱️ 10.10.2021): ``` git clone https://github.com/scikit-learn-contrib/DESlib ``` -- [PyPi](https://pypi.org/project/deslib) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/deslib): ``` pip install deslib ```
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scikit-tda (🥉18 · ⭐ 310) - Python的拓扑数据分析。❗Unlicensed +
scikit-tda (🥉15 · ⭐ 320) - Topological Data Analysis for Python. ❗Unlicensed -- [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 3 · 🔀 37 · 📦 21 · 📋 16 - 75% open · ⏱️ 03.08.2021): +- [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 3 · 🔀 38 · 📦 24 · 📋 16 - 75% open · ⏱️ 03.08.2021): ``` git clone https://github.com/scikit-tda/scikit-tda ``` -- [PyPi](https://pypi.org/project/scikit-tda) (📥 4.1K / month): +- [PyPi](https://pypi.org/project/scikit-tda): ``` pip install scikit-tda ```
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skggm (🥉17 · ⭐ 190 · 💤) - 通用图形模型的Scikit学习兼容估计。MIT +
skope-rules (🥉14 · ⭐ 420 · 💀) - machine learning with logical rules in Python. ❗Unlicensed -- [GitHub](https://github.com/skggm/skggm) (👨‍💻 5 · 🔀 34 · 📦 8 · 📋 75 - 37% open · ⏱️ 24.12.2020): +- [GitHub](https://github.com/scikit-learn-contrib/skope-rules) (👨‍💻 18 · 🔀 69 · 📦 58 · 📋 27 - 81% open · ⏱️ 23.10.2020): ``` - git clone https://github.com/skggm/skggm + git clone https://github.com/scikit-learn-contrib/skope-rules ``` -- [PyPi](https://pypi.org/project/skggm) (📥 110 / month): +- [PyPi](https://pypi.org/project/skope-rules): ``` - pip install skggm + pip install skope-rules ```
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celer (🥉15 · ⭐ 120) - L1型问题的快速求解器：Lasso，稀疏Logisitic回归等BSD-3 +
celer (🥉14 · ⭐ 130) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 -- [GitHub](https://github.com/mathurinm/celer) (👨‍💻 9 · 🔀 22 · 📦 8 · 📋 68 - 20% open · ⏱️ 05.10.2021): +- [GitHub](https://github.com/mathurinm/celer) (👨‍💻 9 · 🔀 23 · 📦 10 · 📋 69 - 20% open · ⏱️ 10.12.2021): ``` git clone https://github.com/mathurinm/celer ``` -- [PyPi](https://pypi.org/project/celer) (📥 220 / month): +- [PyPi](https://pypi.org/project/celer): ``` pip install celer ```
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dabl (🥉12 · ⭐ 110) - 数据分析基准库。BSD-3 +
dabl (🥉12 · ⭐ 110) - Data Analysis Baseline Library. BSD-3 - [GitHub](https://github.com/amueller/dabl) (👨‍💻 21 · 🔀 9 · ⏱️ 09.07.2021): ``` git clone https://github.com/amueller/dabl ``` -- [PyPi](https://pypi.org/project/dabl) (📥 1.7K / month): +- [PyPi](https://pypi.org/project/dabl) (📥 2.1K / month): ``` pip install dabl ```

-## 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._ -
pytorch-optimizer (🥇27 · ⭐ 2.1K) - torch-optimizer - pytorch的优化器集合。Apache-2 +
PML (🥇27 · ⭐ 3.9K) - The easiest way to use deep metric learning in your application. Modular,.. MIT -- [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 24 · 🔀 200 · 📦 330 · 📋 39 - 30% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 21 · 🔀 480 · 📦 180 · 📋 310 - 12% open · ⏱️ 08.12.2021): ``` - git clone https://github.com/jettify/pytorch-optimizer + git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` -- [PyPi](https://pypi.org/project/torch_optimizer) (📥 70K / month): +- [PyPi](https://pypi.org/project/pytorch-metric-learning) (📥 150K / month): ``` - pip install torch_optimizer + pip install pytorch-metric-learning + ``` +- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (📥 5.1K · ⏱️ 28.11.2021): + ``` + conda install -c metric-learning pytorch-metric-learning ```
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pretrainedmodels (🥇26 · ⭐ 8.2K · 💀) - pytorch预训练的ConvNets：NASNet，ResNeXt等BSD-3 +
pytorch-summary (🥇24 · ⭐ 3.3K · 💤) - Model summary in PyTorch similar to `model.summary()`.. MIT -- [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.7K · 📦 1.2K · 📋 170 - 47% open · ⏱️ 16.04.2020): +- [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 370 · 📦 3.9K · 📋 130 - 70% 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) (📥 46K / month): +- [PyPi](https://pypi.org/project/torchsummary) (📥 84K / month): ``` - pip install pretrainedmodels + pip install torchsummary ```
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PML (🥇25 · ⭐ 3.7K) - 在应用程序中使用深度度量学习的最简单方法。MIT +
pytorch-optimizer (🥇23 · ⭐ 2.2K) - torch-optimizer -- collection of optimizers for.. Apache-2 -- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 19 · 🔀 460 · 📦 140 · 📋 290 - 17% open · ⏱️ 03.08.2021): +- [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 25 · 🔀 210 · 📦 410 · 📋 43 - 34% open · ⏱️ 11.11.2021): ``` - git clone https://github.com/KevinMusgrave/pytorch-metric-learning - ``` -- [PyPi](https://pypi.org/project/pytorch-metric-learning) (📥 9.7K / month): - ``` - pip install pytorch-metric-learning + git clone https://github.com/jettify/pytorch-optimizer ``` -- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (📥 4.3K · ⏱️ 10.05.2021): +- [PyPi](https://pypi.org/project/torch_optimizer): ``` - conda install -c metric-learning pytorch-metric-learning + pip install torch_optimizer ```
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pytorch-summary (🥈23 · ⭐ 3.3K) - PyTorch中的模型摘要类似于`model.summary（）`。MIT +
pretrainedmodels (🥈22 · ⭐ 8.3K · 💀) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 -- [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 370 · 📦 3.4K · 📋 130 - 70% open · ⏱️ 10.05.2021): +- [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.7K · 📦 1.3K · 📋 170 - 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) (📥 110K / month): +- [PyPi](https://pypi.org/project/pretrainedmodels): ``` - pip install torchsummary + pip install pretrainedmodels ```
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SRU (🥈23 · ⭐ 2K) - 与CNN一样快地训练RNN（https://arxiv.org/abs/1709.02755）。MIT +
EfficientNet-PyTorch (🥈22 · ⭐ 6.7K · 💤) - A PyTorch implementation of EfficientNet and.. Apache-2 -- [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 290 · 📦 16 · 📋 120 - 43% open · ⏱️ 19.05.2021): +- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.3K · 📥 1M · 📋 260 - 49% open · ⏱️ 15.04.2021): ``` - git clone https://github.com/asappresearch/sru + git clone https://github.com/lukemelas/EfficientNet-PyTorch ``` -- [PyPi](https://pypi.org/project/sru) (📥 3.1K / month): +- [PyPi](https://pypi.org/project/efficientnet-pytorch) (📥 240K / month): ``` - pip install sru + pip install efficientnet-pytorch ```
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EfficientNet-PyTorch (🥈22 · ⭐ 6.5K) - EfficientNet等模型的PyTorch实现Apache-2 +
SRU (🥈22 · ⭐ 2K · 💤) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT -- [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.3K · 📥 860K · 📋 260 - 47% open · ⏱️ 15.04.2021): +- [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 290 · 📦 17 · 📋 120 - 44% open · ⏱️ 19.05.2021): ``` - git clone https://github.com/lukemelas/EfficientNet-PyTorch + git clone https://github.com/asappresearch/sru ``` -- [PyPi](https://pypi.org/project/efficientnet-pytorch) (📥 590K / month): +- [PyPi](https://pypi.org/project/sru) (📥 3K / month): ``` - pip install efficientnet-pytorch + pip install sru ```
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torchdiffeq (🥈22 · ⭐ 3.7K) - 具有完整GPU支持的可微分ODE求解器。MIT +
reformer-pytorch (🥈22 · ⭐ 1.6K) - Reformer, the efficient Transformer, in Pytorch. MIT -- [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 21 · 🔀 630 · 📦 150 · 📋 150 - 15% open · ⏱️ 22.09.2021): +- [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 10 · 🔀 220 · 📋 120 - 10% open · ⏱️ 06.11.2021): ``` - git clone https://github.com/rtqichen/torchdiffeq + git clone https://github.com/lucidrains/reformer-pytorch ``` -- [PyPi](https://pypi.org/project/torchdiffeq) (📥 5.8K / month): +- [PyPi](https://pypi.org/project/reformer-pytorch) (📥 16K / month): ``` - pip install torchdiffeq + pip install reformer-pytorch ```
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reformer-pytorch (🥈22 · ⭐ 1.6K) - Reformer，Pytorch中高效的transformer实现。MIT +
torchdiffeq (🥈21 · ⭐ 3.8K) - Differentiable ODE solvers with full GPU support and.. MIT -- [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 10 · 🔀 210 · 📋 120 - 10% open · ⏱️ 25.08.2021): +- [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 20 · 🔀 660 · 📦 180 · 📋 160 - 17% open · ⏱️ 22.09.2021): ``` - git clone https://github.com/lucidrains/reformer-pytorch + git clone https://github.com/rtqichen/torchdiffeq ``` -- [PyPi](https://pypi.org/project/reformer-pytorch) (📥 17K / month): +- [PyPi](https://pypi.org/project/torchdiffeq) (📥 8.2K / month): ``` - pip install reformer-pytorch + pip install torchdiffeq ```
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Torchmeta (🥈22 · ⭐ 1.5K) - 少量学习的扩展程序和数据加载器的集合。MIT +
Torchmeta (🥈21 · ⭐ 1.5K) - A collection of extensions and data-loaders for few-shot learning.. MIT -- [GitHub](https://github.com/tristandeleu/pytorch-meta) (👨‍💻 12 · 🔀 170 · 📦 62 · 📋 120 - 24% open · ⏱️ 20.09.2021): +- [GitHub](https://github.com/tristandeleu/pytorch-meta) (👨‍💻 12 · 🔀 180 · 📦 78 · 📋 120 - 26% open · ⏱️ 20.09.2021): ``` git clone https://github.com/tristandeleu/pytorch-meta ``` -- [PyPi](https://pypi.org/project/torchmeta) (📥 50K / month): +- [PyPi](https://pypi.org/project/torchmeta) (📥 1.4K / month): ``` pip install torchmeta ```
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TabNet (🥈21 · ⭐ 1.3K) - Efficient Neural Architecture Search的Pytorch实现。MIT +
TabNet (🥈21 · ⭐ 1.5K) - PyTorch implementation of TabNet paper :.. MIT -- [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 18 · 🔀 260 · 📋 160 - 12% open · ⏱️ 27.05.2021): +- [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 18 · 🔀 290 · 📋 180 - 8% open · ⏱️ 12.11.2021): ``` git clone https://github.com/dreamquark-ai/tabnet ``` -- [PyPi](https://pypi.org/project/pytorch-tabnet) (📥 17K / month): +- [PyPi](https://pypi.org/project/pytorch-tabnet) (📥 33K / month): ``` pip install pytorch-tabnet ```
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Pytorch Toolbelt (🥈21 · ⭐ 1.1K) - PyTorch扩展用于快速研发原型和Kaggle实验。MIT +
Pytorch Toolbelt (🥈21 · ⭐ 1.2K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT -- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 6 · 🔀 80 · 📋 21 - 14% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 6 · 🔀 85 · 📋 22 - 18% open · ⏱️ 06.12.2021): ``` git clone https://github.com/BloodAxe/pytorch-toolbelt ``` -- [PyPi](https://pypi.org/project/pytorch_toolbelt) (📥 9.7K / month): +- [PyPi](https://pypi.org/project/pytorch_toolbelt) (📥 14K / month): ``` pip install pytorch_toolbelt ```
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torch-scatter (🥉20 · ⭐ 780) - 优化图聚类的PyTorch扩展库MIT +
torch-scatter (🥉20 · ⭐ 840) - PyTorch Extension Library of Optimized Scatter Operations. MIT -- [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 17 · 🔀 86 · 📋 210 - 10% open · ⏱️ 16.09.2021): +- [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 18 · 🔀 86 · 📋 230 - 8% open · ⏱️ 13.11.2021): ``` git clone https://github.com/rusty1s/pytorch_scatter ``` -- [PyPi](https://pypi.org/project/torch-scatter) (📥 27K / month): +- [PyPi](https://pypi.org/project/torch-scatter) (📥 32K / month): ``` pip install torch-scatter ```
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Tensor Sensor (🥉20 · ⭐ 600 · 📈) - 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) (👨‍💻 3 · 🔀 30 · 📦 5 · 📋 23 - 39% open · ⏱️ 07.10.2021): - - ``` - git clone https://github.com/parrt/tensor-sensor - ``` -- [PyPi](https://pypi.org/project/tensor-sensor) (📥 5.6K / month): - ``` - pip install tensor-sensor - ``` -
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PyTorch Sparse (🥉20 · ⭐ 500) - 优化图聚类的PyTorch扩展库MIT +
PyTorch Sparse (🥉20 · ⭐ 540) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT -- [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 17 · 🔀 62 · 📋 140 - 15% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 17 · 🔀 68 · 📋 150 - 16% open · ⏱️ 13.11.2021): ``` git clone https://github.com/rusty1s/pytorch_sparse ``` -- [PyPi](https://pypi.org/project/torch-sparse) (📥 21K / month): +- [PyPi](https://pypi.org/project/torch-sparse) (📥 20K / month): ``` pip install torch-sparse ```
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Poutyne (🥉20 · ⭐ 500) - PyTorch的简化框架和实用程序。❗️LGPL-3.0 +
Poutyne (🥉20 · ⭐ 510) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 -- [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 16 · 🔀 51 · 📦 69 · 📋 44 - 13% open · ⏱️ 12.09.2021): +- [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 16 · 🔀 56 · 📦 73 · 📋 44 - 13% open · ⏱️ 09.11.2021): ``` git clone https://github.com/GRAAL-Research/poutyne ``` -- [PyPi](https://pypi.org/project/poutyne) (📥 5.5K / month): +- [PyPi](https://pypi.org/project/poutyne) (📥 5.8K / month): ``` pip install poutyne ```
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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 · 📦 120 · 📋 23 - 69% open · ⏱️ 06.03.2019): - - ``` - git clone https://github.com/Luolc/AdaBound - ``` -- [PyPi](https://pypi.org/project/adabound) (📥 1.1K / month): - ``` - pip install adabound - ``` -
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Antialiased CNNs (🥉19 · ⭐ 1.4K) - pip安装antialiased-cnns以提高稳定性等。❗️CC BY-NC-SA 4.0 +
Antialiased CNNs (🥉19 · ⭐ 1.5K) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 -- [GitHub](https://github.com/adobe/antialiased-cnns) (👨‍💻 6 · 🔀 180 · 📦 7 · 📋 40 - 22% open · ⏱️ 29.09.2021): +- [GitHub](https://github.com/adobe/antialiased-cnns) (👨‍💻 6 · 🔀 180 · 📦 12 · 📋 41 - 24% open · ⏱️ 29.09.2021): ``` git clone https://github.com/adobe/antialiased-cnns ``` -- [PyPi](https://pypi.org/project/antialiased-cnns) (📥 1.6K / month): +- [PyPi](https://pypi.org/project/antialiased-cnns) (📥 1.1K / month): ``` pip install antialiased-cnns ```
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EfficientNets (🥉19 · ⭐ 1.4K) - 预训练的EfficientNet，EfficientNet-Lite，MixNet等Apache-2 +
EfficientNets (🥉19 · ⭐ 1.4K) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 -- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 180 · 📦 77 · ⏱️ 08.07.2021): +- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 190 · 📦 87 · 📋 51 - 3% open · ⏱️ 08.07.2021): ``` git clone https://github.com/rwightman/gen-efficientnet-pytorch @@ -10535,142 +10523,166 @@ _Pytorch的拓展工具库。_ pip install geffnet ```
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Higher (🥉19 · ⭐ 1.2K) - 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 +
Higher (🥉19 · ⭐ 1.3K) - higher is a pytorch library allowing users to obtain higher.. Apache-2 -- [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 87 · 📦 78 · 📋 88 - 43% open · ⏱️ 21.06.2021): +- [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 95 · 📦 100 · 📋 95 - 47% open · ⏱️ 26.10.2021): ``` git clone https://github.com/facebookresearch/higher ``` -- [PyPi](https://pypi.org/project/higher) (📥 58K / month): +- [PyPi](https://pypi.org/project/higher) (📥 33K / month): ``` pip install higher ```
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Performer Pytorch (🥉18 · ⭐ 710) - Performer的实现。MIT +
Performer Pytorch (🥉19 · ⭐ 760) - An implementation of Performer, a linear attention-.. MIT -- [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 4 · 🔀 95 · 📦 30 · 📋 66 - 40% open · ⏱️ 21.08.2021): +- [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 6 · 🔀 99 · 📦 34 · 📋 68 - 39% open · ⏱️ 07.11.2021): ``` git clone https://github.com/lucidrains/performer-pytorch ``` -- [PyPi](https://pypi.org/project/performer-pytorch) (📥 1.1K / month): +- [PyPi](https://pypi.org/project/performer-pytorch) (📥 1.4K / month): ``` pip install performer-pytorch ```
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Tez (🥉18 · ⭐ 700 · 📈) - Tez是用于PyTorch的超级简单且轻巧的Trainer。Apache-2 +
Tez (🥉18 · ⭐ 730) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 -- [GitHub](https://github.com/abhishekkrthakur/tez) (🔀 100 · 📦 11 · 📋 23 - 60% open · ⏱️ 27.09.2021): +- [GitHub](https://github.com/abhishekkrthakur/tez) (🔀 110 · 📦 17 · 📋 26 - 61% open · ⏱️ 27.09.2021): ``` git clone https://github.com/abhishekkrthakur/tez ``` -- [PyPi](https://pypi.org/project/tez) (📥 1.2K / month): +- [PyPi](https://pypi.org/project/tez) (📥 1.5K / month): ``` pip install tez ```
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tinygrad (🥉16 · ⭐ 5K) - You like pytorch? You like micrograd? You love tinygrad!. MIT +
Pywick (🥉18 · ⭐ 360) - High-level batteries-included neural network training library.. ❗Unlicensed + +- [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 38 · 📦 5 · 📋 13 - 7% open · ⏱️ 22.10.2021): + + ``` + git clone https://github.com/achaiah/pywick + ``` +- [PyPi](https://pypi.org/project/pywick) (📥 5.1K / month): + ``` + pip install pywick + ``` +
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tinygrad (🥉16 · ⭐ 5.1K) - You like pytorch? You like micrograd? You love tinygrad!. MIT -- [GitHub](https://github.com/geohot/tinygrad) (👨‍💻 50 · 🔀 550 · 📦 1 · 📋 80 - 20% open · ⏱️ 06.08.2021): +- [GitHub](https://github.com/geohot/tinygrad) (👨‍💻 52 · 🔀 570 · 📦 1 · 📋 86 - 3% open · ⏱️ 12.12.2021): ``` git clone https://github.com/geohot/tinygrad ```
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Lambda Networks (🥉16 · ⭐ 1.5K · 💤) - LambdaNetworks的实现。MIT +
AdaBound (🥉16 · ⭐ 2.9K · 💀) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 + +- [GitHub](https://github.com/Luolc/AdaBound) (👨‍💻 2 · 🔀 320 · 📦 120 · 📋 24 - 70% open · ⏱️ 06.03.2019): + + ``` + git clone https://github.com/Luolc/AdaBound + ``` +- [PyPi](https://pypi.org/project/adabound): + ``` + pip install adabound + ``` +
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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): ``` git clone https://github.com/lucidrains/lambda-networks ``` -- [PyPi](https://pypi.org/project/lambda-networks) (📥 130 / month): +- [PyPi](https://pypi.org/project/lambda-networks) (📥 85 / month): ``` pip install lambda-networks ```
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torchsde (🥉15 · ⭐ 850) - 具有GPU支持且高效的可微分SDE求解器。Apache-2 +
Tensor Sensor (🥉16 · ⭐ 620) - The goal of this library is to generate more helpful.. MIT -- [GitHub](https://github.com/google-research/torchsde) (👨‍💻 5 · 🔀 90 · 📦 8 · 📋 41 - 17% open · ⏱️ 26.07.2021): +- [GitHub](https://github.com/parrt/tensor-sensor) (👨‍💻 3 · 🔀 31 · 📦 7 · 📋 23 - 34% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/google-research/torchsde + git clone https://github.com/parrt/tensor-sensor + ``` +- [PyPi](https://pypi.org/project/tensor-sensor): + ``` + pip install tensor-sensor ```
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Pywick (🥉15 · ⭐ 330) - 更高层次的pytorch神经网络训练库。❗Unlicensed +
torchsde (🥉15 · ⭐ 880) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 -- [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 37 · 📦 5 · 📋 13 - 23% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/google-research/torchsde) (👨‍💻 5 · 🔀 96 · 📦 9 · 📋 41 - 17% open · ⏱️ 26.07.2021): ``` - git clone https://github.com/achaiah/pywick - ``` -- [PyPi](https://pypi.org/project/pywick) (📥 77 / month): - ``` - pip install pywick + git clone https://github.com/google-research/torchsde ```
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Torch-Struct (🥉14 · ⭐ 980) - 快速，通用和经过测试的微分结构化预测。MIT +
Torch-Struct (🥉14 · ⭐ 1K) - Fast, general, and tested differentiable structured prediction.. MIT -- [GitHub](https://github.com/harvardnlp/pytorch-struct) (👨‍💻 13 · 🔀 75 · 📋 47 - 44% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/harvardnlp/pytorch-struct) (👨‍💻 13 · 🔀 76 · 📋 49 - 42% open · ⏱️ 04.11.2021): ``` git clone https://github.com/harvardnlp/pytorch-struct ```
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micrograd (🥉13 · ⭐ 1.8K · 💀) - 一个微型的标量值autograd引擎和一个神经网络库。MIT +
micrograd (🥉12 · ⭐ 1.8K · 💀) - A tiny scalar-valued autograd engine and a neural net library.. MIT - [GitHub](https://github.com/karpathy/micrograd) (👨‍💻 2 · 🔀 140 · 📦 4 · 📋 5 - 40% open · ⏱️ 18.04.2020): ``` git clone https://github.com/karpathy/micrograd ``` -- [PyPi](https://pypi.org/project/micrograd) (📥 32 / month): +- [PyPi](https://pypi.org/project/micrograd): ``` pip install micrograd ```

-## 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 ( ⭐ 1 · 🐣) - Collection of database clients for python. +🔗 Python DB Clients ( ⭐ 2) - Collection of database clients for python.
-## 中文自然语言处理 +## Chinese NLP -Back to top +Back to top -
jieba (🥇31 · ⭐ 27K · 💀) - Chinese Words Segementation Utilities. MIT +
jieba (🥇31 · ⭐ 28K · 💀) - Chinese Words Segementation Utilities. MIT -- [GitHub](https://github.com/fxsjy/jieba) (👨‍💻 48 · 🔀 6.1K · 📦 11K · 📋 780 - 73% open · ⏱️ 15.02.2020): +- [GitHub](https://github.com/fxsjy/jieba) (👨‍💻 48 · 🔀 6.2K · 📦 12K · 📋 790 - 73% open · ⏱️ 15.02.2020): ``` git clone https://github.com/fxsjy/jieba ``` -- [PyPi](https://pypi.org/project/jieba) (📥 460K / month): +- [PyPi](https://pypi.org/project/jieba) (📥 450K / month): ``` pip install jieba ``` -- [Conda](https://anaconda.org/conda-forge/jieba) (📥 94K · ⏱️ 30.05.2021): +- [Conda](https://anaconda.org/conda-forge/jieba) (📥 100K · ⏱️ 30.05.2021): ``` conda install -c conda-forge jieba ```
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snownlp (🥉21 · ⭐ 5.6K · 💀) - Python library for processing Chinese text. MIT +
snownlp (🥉22 · ⭐ 5.6K · 💀) - Python library for processing Chinese text. MIT -- [GitHub](https://github.com/isnowfy/snownlp) (👨‍💻 8 · 🔀 1.3K · 📦 710 · 📋 100 - 36% open · ⏱️ 19.01.2020): +- [GitHub](https://github.com/isnowfy/snownlp) (👨‍💻 8 · 🔀 1.3K · 📦 750 · 📋 100 - 37% open · ⏱️ 19.01.2020): ``` git clone https://github.com/isnowfy/snownlp ``` -- [PyPi](https://pypi.org/project/snownlp) (📥 4.8K / month): +- [PyPi](https://pypi.org/project/snownlp) (📥 8.8K / month): ``` pip install snownlp ``` @@ -10679,203 +10691,159 @@ _用于连接，操作和查询数据库的库。_ ## Others -Back to top +Back to top -
scipy (🥇42 · ⭐ 8.7K) - 用于数学，科学和工程的开源软件生态系统。BSD-3 +
scipy (🥇39 · ⭐ 8.9K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 -- [GitHub](https://github.com/scipy/scipy) (👨‍💻 1.2K · 🔀 3.8K · 📥 330K · 📦 410K · 📋 7.6K - 19% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/scipy/scipy) (👨‍💻 1.2K · 🔀 3.9K · 📥 330K · 📦 440K · 📋 7.8K - 18% open · ⏱️ 16.12.2021): ``` git clone https://github.com/scipy/scipy ``` -- [PyPi](https://pypi.org/project/scipy) (📥 30M / month): +- [PyPi](https://pypi.org/project/scipy): ``` pip install scipy ``` -- [Conda](https://anaconda.org/conda-forge/scipy) (📥 18M · ⏱️ 10.10.2021): +- [Conda](https://anaconda.org/conda-forge/scipy) (📥 20M · ⏱️ 25.11.2021): ``` conda install -c conda-forge scipy ```
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SymPy (🥇35 · ⭐ 8.5K) - 用纯Python编写的计算机代数系统。❗Unlicensed +
SymPy (🥇33 · ⭐ 8.7K) - A computer algebra system written in pure Python. ❗Unlicensed -- [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.1K · 🔀 3.4K · 📥 430K · 📦 36K · 📋 11K - 32% open · ⏱️ 10.10.2021): +- [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.1K · 🔀 3.5K · 📥 440K · 📦 38K · 📋 11K - 32% open · ⏱️ 15.12.2021): ``` git clone https://github.com/sympy/sympy ``` -- [PyPi](https://pypi.org/project/sympy) (📥 1.7M / month): +- [PyPi](https://pypi.org/project/sympy): ``` pip install sympy ``` -- [Conda](https://anaconda.org/conda-forge/sympy) (📥 1.7M · ⏱️ 09.10.2021): +- [Conda](https://anaconda.org/conda-forge/sympy) (📥 1.8M · ⏱️ 06.11.2021): ``` conda install -c conda-forge sympy ```
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PyOD (🥇30 · ⭐ 4.9K) - （JMLR'19）用于可扩展离群值检测的Python工具箱。BSD-2 +
PyOD (🥇31 · ⭐ 5.1K) - (JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 -- [GitHub](https://github.com/yzhao062/pyod) (👨‍💻 28 · 🔀 960 · 📦 880 · 📋 210 - 51% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/yzhao062/pyod) (👨‍💻 31 · 🔀 990 · 📦 1K · 📋 220 - 48% open · ⏱️ 01.11.2021): ``` git clone https://github.com/yzhao062/pyod ``` -- [PyPi](https://pypi.org/project/pyod) (📥 320K / month): +- [PyPi](https://pypi.org/project/pyod) (📥 540K / month): ``` pip install pyod ```
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Datasette (🥇29 · ⭐ 5.5K) - 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) (👨‍💻 57 · 🔀 340 · 📥 32 · 📦 520 · 📋 1.1K - 25% open · ⏱️ 10.10.2021): - - ``` - git clone https://github.com/simonw/datasette - ``` -- [PyPi](https://pypi.org/project/datasette) (📥 120K / month): - ``` - pip install datasette - ``` -
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Streamlit (🥈28 · ⭐ 16K) - Streamlit用Python构建数据应用程序的最快方法。Apache-2 - -- [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 120 · 🔀 1.4K · 📦 140 · 📋 2K - 27% open · ⏱️ 12.10.2021): - - ``` - git clone https://github.com/streamlit/streamlit - ``` -- [PyPi](https://pypi.org/project/streamlit) (📥 630K / month): - ``` - pip install streamlit - ``` -
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Autograd (🥈28 · ⭐ 5.5K · 💤) - 高效地计算导数的numpy代码。MIT +
DeepChem (🥇27 · ⭐ 3.3K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT -- [GitHub](https://github.com/HIPS/autograd) (👨‍💻 51 · 🔀 760 · 📦 2.5K · 📋 360 - 39% open · ⏱️ 03.03.2021): +- [GitHub](https://github.com/deepchem/deepchem) (👨‍💻 180 · 🔀 1.2K · 📦 65 · 📋 1.4K - 27% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/HIPS/autograd - ``` -- [PyPi](https://pypi.org/project/autograd) (📥 1.3M / month): - ``` - pip install autograd + git clone https://github.com/deepchem/deepchem ``` -- [Conda](https://anaconda.org/conda-forge/autograd) (📥 190K · ⏱️ 25.07.2019): +- [PyPi](https://pypi.org/project/deepchem) (📥 4K / month): ``` - conda install -c conda-forge autograd + pip install deepchem ```
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hdbscan (🥈28 · ⭐ 2K) - HDBSCAN群集的高性能实现。BSD-3 +
hdbscan (🥇27 · ⭐ 2K) - A high performance implementation of HDBSCAN clustering. BSD-3 -- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 72 · 🔀 340 · 📦 1K · 📋 390 - 62% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 74 · 🔀 360 · 📦 1.1K · 📋 400 - 62% open · ⏱️ 24.11.2021): ``` git clone https://github.com/scikit-learn-contrib/hdbscan ``` -- [PyPi](https://pypi.org/project/hdbscan) (📥 360K / month): +- [PyPi](https://pypi.org/project/hdbscan): ``` pip install hdbscan ``` -- [Conda](https://anaconda.org/conda-forge/hdbscan) (📥 880K · ⏱️ 14.02.2021): +- [Conda](https://anaconda.org/conda-forge/hdbscan) (📥 990K · ⏱️ 14.02.2021): ``` conda install -c conda-forge hdbscan ```
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carla (🥈27 · ⭐ 6.6K) - 用于自动驾驶研究的开源模拟器。MIT +
Cython BLIS (🥇27 · ⭐ 180) - Fast matrix-multiplication as a self-contained Python.. ❗Unlicensed -- [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 130 · 🔀 1.9K · 📦 91 · 📋 3.4K - 12% open · ⏱️ 04.10.2021): +- [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 10 · 🔀 29 · 📦 15K · 📋 27 - 18% open · ⏱️ 17.11.2021): ``` - git clone https://github.com/carla-simulator/carla - ``` -- [PyPi](https://pypi.org/project/carla) (📥 1.9K / month): - ``` - pip install carla + git clone https://github.com/explosion/cython-blis ``` -
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DeepChem (🥈26 · ⭐ 3.2K) - 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) (👨‍💻 170 · 🔀 1K · 📦 57 · 📋 1.3K - 29% open · ⏱️ 07.10.2021): - +- [PyPi](https://pypi.org/project/blis) (📥 5.5M / month): ``` - git clone https://github.com/deepchem/deepchem + pip install blis ``` -- [PyPi](https://pypi.org/project/deepchem) (📥 4.5K / month): +- [Conda](https://anaconda.org/conda-forge/cython-blis) (📥 1.2M · ⏱️ 04.11.2021): ``` - pip install deepchem + conda install -c conda-forge cython-blis ```
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TabPy (🥈26 · ⭐ 1.1K) - 快速执行Python代码，并在Tableau可视化文件中显示结果。MIT +
Pythran (🥈26 · ⭐ 1.7K) - Ahead of Time compiler for numeric kernels. BSD-3 -- [GitHub](https://github.com/tableau/TabPy) (👨‍💻 43 · 🔀 420 · 📦 76 · 📋 280 - 5% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 64 · 🔀 160 · 📦 89 · 📋 730 - 13% open · ⏱️ 14.12.2021): ``` - git clone https://github.com/tableau/TabPy + git clone https://github.com/serge-sans-paille/pythran ``` -- [PyPi](https://pypi.org/project/tabpy) (📥 14K / month): +- [PyPi](https://pypi.org/project/pythran) (📥 320K / month): ``` - pip install tabpy + pip install pythran + ``` +- [Conda](https://anaconda.org/conda-forge/pythran) (📥 210K · ⏱️ 14.12.2021): + ``` + conda install -c conda-forge pythran ```
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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 +
agate (🥈26 · ⭐ 1.1K) - A Python data analysis library that is optimized for humans instead of.. MIT -- [GitHub](https://github.com/wireservice/agate) (👨‍💻 49 · 🔀 130 · 📦 640 · 📋 640 - 0% open · ⏱️ 15.07.2021): +- [GitHub](https://github.com/wireservice/agate) (👨‍💻 49 · 🔀 130 · 📦 690 · 📋 640 - 0% open · ⏱️ 15.07.2021): ``` git clone https://github.com/wireservice/agate ``` -- [PyPi](https://pypi.org/project/agate) (📥 710K / month): +- [PyPi](https://pypi.org/project/agate) (📥 930K / month): ``` pip install agate ``` -- [Conda](https://anaconda.org/conda-forge/agate) (📥 71K · ⏱️ 16.07.2021): +- [Conda](https://anaconda.org/conda-forge/agate) (📥 74K · ⏱️ 16.07.2021): ``` conda install -c conda-forge agate ```
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PaddleHub (🥈25 · ⭐ 7K) - 基于PaddlePaddle的出色的预训练模型工具包。Apache-2 +
PaddleHub (🥈25 · ⭐ 7.3K) - Awesome pre-trained models toolkit based on.. Apache-2 -- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 46 · 🔀 1.4K · 📥 560 · 📦 480 · 📋 930 - 34% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 48 · 🔀 1.4K · 📥 560 · 📦 600 · 📋 970 - 36% open · ⏱️ 16.12.2021): ``` git clone https://github.com/PaddlePaddle/PaddleHub ``` -- [PyPi](https://pypi.org/project/paddlehub) (📥 8.8K / month): +- [PyPi](https://pypi.org/project/paddlehub) (📥 9.5K / month): ``` pip install paddlehub ```
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Trax (🥈25 · ⭐ 6.5K) - 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) (👨‍💻 71 · 🔀 640 · 📦 38 · 📋 200 - 39% open · ⏱️ 01.10.2021): - - ``` - git clone https://github.com/google/trax - ``` -- [PyPi](https://pypi.org/project/trax) (📥 3.1K / month): - ``` - pip install trax - ``` -
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Pythran (🥈25 · ⭐ 1.6K) - 用于数字内核的时间编译器。BSD-3 +
Autograd (🥈25 · ⭐ 5.6K · 💤) - Efficiently computes derivatives of numpy code. MIT -- [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 63 · 🔀 160 · 📦 70 · 📋 700 - 13% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/HIPS/autograd) (👨‍💻 51 · 🔀 770 · 📦 2.8K · 📋 360 - 39% open · ⏱️ 03.03.2021): ``` - git clone https://github.com/serge-sans-paille/pythran + git clone https://github.com/HIPS/autograd ``` -- [PyPi](https://pypi.org/project/pythran) (📥 49K / month): +- [PyPi](https://pypi.org/project/autograd): ``` - pip install pythran + pip install autograd ``` -- [Conda](https://anaconda.org/conda-forge/pythran) (📥 200K · ⏱️ 26.09.2021): +- [Conda](https://anaconda.org/conda-forge/autograd) (📥 200K · ⏱️ 25.07.2019): ``` - conda install -c conda-forge pythran + conda install -c conda-forge autograd ```
-
pyclustering (🥈25 · ⭐ 880 · 💤) - pyclustring是Python，C++数据挖掘库。BSD-3 +
pyclustering (🥈25 · ⭐ 900 · 💤) - pyclustring is a Python, C++ data mining library. BSD-3 -- [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 200 · 📥 370 · 📦 230 · 📋 640 - 8% open · ⏱️ 12.02.2021): +- [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 210 · 📥 380 · 📦 260 · 📋 640 - 8% open · ⏱️ 12.02.2021): ``` git clone https://github.com/annoviko/pyclustering @@ -10884,58 +10852,54 @@ _用于连接，操作和查询数据库的库。_ ``` pip install pyclustering ``` -- [Conda](https://anaconda.org/conda-forge/pyclustering) (📥 30K · ⏱️ 13.09.2021): +- [Conda](https://anaconda.org/conda-forge/pyclustering) (📥 32K · ⏱️ 13.09.2021): ``` conda install -c conda-forge pyclustering ```
-
pyjanitor (🥈25 · ⭐ 760) - 用于数据清理的API。MIT +
pyjanitor (🥈25 · ⭐ 780) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT -- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 94 · 🔀 130 · 📦 120 · 📋 420 - 23% open · ⏱️ 11.10.2021): +- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 95 · 🔀 130 · 📦 130 · 📋 420 - 20% open · ⏱️ 22.11.2021): ``` git clone https://github.com/ericmjl/pyjanitor ``` -- [PyPi](https://pypi.org/project/pyjanitor) (📥 11K / month): +- [PyPi](https://pypi.org/project/pyjanitor) (📥 13K / month): ``` pip install pyjanitor ``` -- [Conda](https://anaconda.org/conda-forge/pyjanitor) (📥 100K · ⏱️ 01.09.2021): +- [Conda](https://anaconda.org/conda-forge/pyjanitor) (📥 110K · ⏱️ 22.11.2021): ``` conda install -c conda-forge pyjanitor ```
-
Cython BLIS (🥈25 · ⭐ 180) - 快速矩阵乘法库。❗Unlicensed +
carla (🥈24 · ⭐ 7K) - Open-source simulator for autonomous driving research. MIT -- [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 10 · 🔀 28 · 📦 13K · 📋 22 - 22% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 140 · 🔀 2K · 📦 110 · 📋 3.6K - 12% open · ⏱️ 19.11.2021): ``` - git clone https://github.com/explosion/cython-blis - ``` -- [PyPi](https://pypi.org/project/blis) (📥 2.5M / month): - ``` - pip install blis + git clone https://github.com/carla-simulator/carla ``` -- [Conda](https://anaconda.org/conda-forge/cython-blis) (📥 1M · ⏱️ 31.01.2021): +- [PyPi](https://pypi.org/project/carla): ``` - conda install -c conda-forge cython-blis + pip install carla ```
-
metric-learn (🥉24 · ⭐ 1.2K) - Python中的度量学习算法。MIT +
Datasette (🥈24 · ⭐ 5.6K) - An open source multi-tool for exploring and publishing data. Apache-2 -- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 21 · 🔀 210 · 📦 170 · 📋 160 - 29% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/simonw/datasette) (👨‍💻 60 · 🔀 360 · 📥 34 · 📦 560 · 📋 1.2K - 26% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/scikit-learn-contrib/metric-learn + git clone https://github.com/simonw/datasette ``` -- [PyPi](https://pypi.org/project/metric-learn) (📥 8K / month): +- [PyPi](https://pypi.org/project/datasette): ``` - pip install metric-learn + pip install datasette ```
-
Gradio (🥉23 · ⭐ 3.7K) - 对任何模型做UI封装并与他人共享。Apache-2 +
Gradio (🥈24 · ⭐ 4.3K) - Wrap UIs around any model, share with anyone. Apache-2 -- [GitHub](https://github.com/gradio-app/gradio) (👨‍💻 28 · 🔀 230 · 📦 340 · 📋 180 - 9% open · ⏱️ 13.10.2021): +- [GitHub](https://github.com/gradio-app/gradio) (👨‍💻 36 · 🔀 260 · 📦 450 · 📋 230 - 14% open · ⏱️ 15.12.2021): ``` git clone https://github.com/gradio-app/gradio @@ -10945,182 +10909,230 @@ _用于连接，操作和查询数据库的库。_ pip install gradio ```
-
causalml (🥉23 · ⭐ 2.3K) - 利用机器学习提升建模和因果推理。❗Unlicensed +
causalml (🥉23 · ⭐ 2.5K) - Uplift modeling and causal inference with machine learning.. ❗Unlicensed -- [GitHub](https://github.com/uber/causalml) (👨‍💻 30 · 🔀 340 · 📦 31 · 📋 210 - 23% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/uber/causalml) (👨‍💻 31 · 🔀 380 · 📦 33 · 📋 230 - 16% open · ⏱️ 14.12.2021): ``` git clone https://github.com/uber/causalml ``` -- [PyPi](https://pypi.org/project/causalml) (📥 40K / month): +- [PyPi](https://pypi.org/project/causalml) (📥 41K / month): ``` pip install causalml ```
-
PySwarms (🥉22 · ⭐ 840) - 用于Python中粒子群优化的研究工具包。MIT +
PySwarms (🥉23 · ⭐ 870) - A research toolkit for particle swarm optimization in Python. MIT -- [GitHub](https://github.com/ljvmiranda921/pyswarms) (👨‍💻 43 · 🔀 270 · 📦 140 · 📋 190 - 6% open · ⏱️ 23.06.2021): +- [GitHub](https://github.com/ljvmiranda921/pyswarms) (👨‍💻 43 · 🔀 280 · 📦 150 · 📋 200 - 8% open · ⏱️ 23.06.2021): ``` git clone https://github.com/ljvmiranda921/pyswarms ``` -- [PyPi](https://pypi.org/project/pyswarms) (📥 32K / month): +- [PyPi](https://pypi.org/project/pyswarms) (📥 39K / month): ``` pip install pyswarms ```
-
findspark (🥉22 · ⭐ 420) - 查找pyspark并导入的工具库。BSD-3 +
Streamlit (🥉22 · ⭐ 17K) - Streamlit The fastest way to build data apps in Python. Apache-2 -- [GitHub](https://github.com/minrk/findspark) (👨‍💻 14 · 🔀 66 · 📦 2K · 📋 20 - 50% open · ⏱️ 14.06.2021): +- [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 130 · 🔀 1.5K · 📦 190 · 📋 2.1K - 23% open · ⏱️ 15.12.2021): ``` - git clone https://github.com/minrk/findspark + git clone https://github.com/streamlit/streamlit ``` -- [PyPi](https://pypi.org/project/findspark) (📥 1.7M / month): +- [PyPi](https://pypi.org/project/streamlit): ``` - pip install findspark + pip install streamlit ``` -- [Conda](https://anaconda.org/conda-forge/findspark) (📥 580K · ⏱️ 06.07.2018): +
+
Trax (🥉22 · ⭐ 6.7K) - 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): + ``` - conda install -c conda-forge findspark + git clone https://github.com/google/trax + ``` +- [PyPi](https://pypi.org/project/trax): + ``` + pip install trax ```
-
River (🥉20 · ⭐ 2.6K) - Python中的在线机器学习。BSD-3 +
TabPy (🥉22 · ⭐ 1.2K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT -- [GitHub](https://github.com/online-ml/river) (👨‍💻 67 · 🔀 280 · 📦 44 · 📋 320 - 0% open · ⏱️ 12.10.2021): +- [GitHub](https://github.com/tableau/TabPy) (👨‍💻 43 · 🔀 440 · 📦 79 · 📋 280 - 5% open · ⏱️ 11.10.2021): ``` - git clone https://github.com/online-ml/river + git clone https://github.com/tableau/TabPy + ``` +- [PyPi](https://pypi.org/project/tabpy): + ``` + pip install tabpy ```
-
pyopencl (🥉20 · ⭐ 850) - 适用于Python的OpenCL集成。❗Unlicensed +
metric-learn (🥉21 · ⭐ 1.2K) - Metric learning algorithms in Python. MIT -- [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 88 · 🔀 210 · 📦 560 · 📋 290 - 20% open · ⏱️ 07.10.2021): +- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 21 · 🔀 210 · 📦 180 · 📋 160 - 27% open · ⏱️ 17.11.2021): ``` - git clone https://github.com/inducer/pyopencl + git clone https://github.com/scikit-learn-contrib/metric-learn ``` -- [PyPi](https://pypi.org/project/pyopencl) (📥 11K / month): +- [PyPi](https://pypi.org/project/metric-learn): ``` - pip install pyopencl + pip install metric-learn ``` -- [Conda](https://anaconda.org/conda-forge/pyopencl) (📥 510K · ⏱️ 07.10.2021): +
+
StreamAlert (🥉20 · ⭐ 2.6K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 + +- [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 33 · 🔀 310 · 📋 340 - 24% open · ⏱️ 04.11.2021): + ``` - conda install -c conda-forge pyopencl + git clone https://github.com/airbnb/streamalert ```
-
Prince (🥉20 · ⭐ 700) - Python因子分析库（PCA，CA，MCA，MFA，FAMD）。MIT +
cleanlab (🥉20 · ⭐ 2.5K) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 -- [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 9 · 🔀 120 · 📦 150 · 📋 100 - 34% open · ⏱️ 08.10.2021): +- [GitHub](https://github.com/cleanlab/cleanlab) (👨‍💻 6 · 🔀 240 · 📦 24 · 📋 81 - 41% open · ⏱️ 08.11.2021): ``` - git clone https://github.com/MaxHalford/prince + git clone https://github.com/cgnorthcutt/cleanlab ``` -- [PyPi](https://pypi.org/project/prince) (📥 26K / month): +- [PyPi](https://pypi.org/project/cleanlab) (📥 5.7K / month): ``` - pip install prince + pip install cleanlab ```
-
SUOD (🥉20 · ⭐ 290) - （MLSys' 21）大型无人驾驶加速系统。BSD-2 +
gplearn (🥉20 · ⭐ 1K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 -- [GitHub](https://github.com/yzhao062/SUOD) (🔀 34 · 📦 370 · 📋 6 - 66% open · ⏱️ 02.10.2021): +- [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 10 · 🔀 180 · 📦 210 · 📋 170 - 26% open · ⏱️ 18.10.2021): ``` - git clone https://github.com/yzhao062/SUOD + git clone https://github.com/trevorstephens/gplearn ``` -- [PyPi](https://pypi.org/project/suod) (📥 35K / month): +- [PyPi](https://pypi.org/project/gplearn) (📥 2.6K / month): ``` - pip install suod + pip install gplearn ```
-
StreamAlert (🥉19 · ⭐ 2.6K · 💤) - StreamAlert是无服务器的实时数据分析框架。Apache-2 +
pyopencl (🥉20 · ⭐ 860) - OpenCL integration for Python, plus shiny features. ❗Unlicensed -- [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 31 · 🔀 310 · 📋 340 - 24% open · ⏱️ 10.02.2021): +- [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 90 · 🔀 210 · 📦 590 · 📋 290 - 20% open · ⏱️ 13.12.2021): ``` - git clone https://github.com/airbnb/streamalert + git clone https://github.com/inducer/pyopencl + ``` +- [PyPi](https://pypi.org/project/pyopencl) (📥 16K / month): + ``` + pip install pyopencl + ``` +- [Conda](https://anaconda.org/conda-forge/pyopencl) (📥 540K · ⏱️ 06.12.2021): + ``` + conda install -c conda-forge pyopencl ```
-
cleanlab (🥉19 · ⭐ 2.3K) - 机器学习的标准软件包。❗️AGPL-3.0 +
Prince (🥉20 · ⭐ 740) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT -- [GitHub](https://github.com/cleanlab/cleanlab) (👨‍💻 6 · 🔀 220 · 📦 19 · 📋 72 - 37% open · ⏱️ 06.06.2021): +- [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 10 · 🔀 130 · 📦 170 · 📋 100 - 33% open · ⏱️ 11.12.2021): ``` - git clone https://github.com/cgnorthcutt/cleanlab + git clone https://github.com/MaxHalford/prince ``` -- [PyPi](https://pypi.org/project/cleanlab) (📥 4.3K / month): +- [PyPi](https://pypi.org/project/prince) (📥 18K / month): ``` - pip install cleanlab + pip install prince ```
-
gplearn (🥉19 · ⭐ 1K) - 使用scikit-learn启发式API进行Python遗传编程。BSD-3 +
findspark (🥉20 · ⭐ 420) - Find pyspark to make it importable. BSD-3 -- [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 9 · 🔀 170 · 📦 190 · 📋 170 - 25% open · ⏱️ 01.07.2021): +- [GitHub](https://github.com/minrk/findspark) (👨‍💻 14 · 🔀 66 · 📦 2.1K · 📋 21 - 52% open · ⏱️ 14.06.2021): ``` - git clone https://github.com/trevorstephens/gplearn + git clone https://github.com/minrk/findspark ``` -- [PyPi](https://pypi.org/project/gplearn) (📥 5.3K / month): +- [PyPi](https://pypi.org/project/findspark): ``` - pip install gplearn + pip install findspark + ``` +- [Conda](https://anaconda.org/conda-forge/findspark) (📥 600K · ⏱️ 06.07.2018): + ``` + conda install -c conda-forge findspark + ``` +
+
River (🥉19 · ⭐ 3K) - Online machine learning in Python. BSD-3 + +- [GitHub](https://github.com/online-ml/river) (👨‍💻 70 · 🔀 320 · 📦 56 · 📋 330 - 1% open · ⏱️ 16.12.2021): + + ``` + git clone https://github.com/online-ml/river ```
-
impyute (🥉18 · ⭐ 290 · 💀) - 数据插补库可对缺少数据的数据集进行预处理。MIT +
impyute (🥉19 · ⭐ 300) - Data imputations library to preprocess datasets with missing data. MIT -- [GitHub](https://github.com/eltonlaw/impyute) (👨‍💻 10 · 🔀 42 · 📦 120 · 📋 63 - 42% open · ⏱️ 05.10.2019): +- [GitHub](https://github.com/eltonlaw/impyute) (👨‍💻 11 · 🔀 43 · 📦 120 · 📋 64 - 42% open · ⏱️ 06.11.2021): ``` git clone https://github.com/eltonlaw/impyute ``` -- [PyPi](https://pypi.org/project/impyute) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/impyute) (📥 2.5K / month): ``` pip install impyute ```
-
AstroML (🥉17 · ⭐ 780) - 天文学和天体物理学的机器学习，统计和数据挖掘.BSD-2 +
AstroML (🥉16 · ⭐ 790 · 💤) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 -- [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 260 · 📋 140 - 38% open · ⏱️ 07.04.2021): +- [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 260 · 📋 140 - 37% open · ⏱️ 07.04.2021): ``` git clone https://github.com/astroML/astroML ``` -- [PyPi](https://pypi.org/project/astroML) (📥 1K / month): +- [PyPi](https://pypi.org/project/astroML) (📥 1.1K / month): ``` pip install astroML ``` -- [Conda](https://anaconda.org/conda-forge/astroml) (📥 26K · ⏱️ 16.02.2020): +- [Conda](https://anaconda.org/conda-forge/astroml) (📥 27K · ⏱️ 16.02.2020): ``` conda install -c conda-forge astroml ```
-
BioPandas (🥉17 · ⭐ 380) - 在pandas DataFrames中处理分子结构。BSD-3 +
BioPandas (🥉16 · ⭐ 400) - Working with molecular structures in pandas DataFrames. BSD-3 -- [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 8 · 🔀 86 · 📋 39 - 38% open · ⏱️ 24.09.2021): +- [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 8 · 🔀 89 · 📋 39 - 38% open · ⏱️ 24.09.2021): ``` git clone https://github.com/rasbt/biopandas ``` -- [PyPi](https://pypi.org/project/biopandas) (📥 1.9K / month): +- [PyPi](https://pypi.org/project/biopandas) (📥 2.5K / month): ``` pip install biopandas ``` -- [Conda](https://anaconda.org/conda-forge/biopandas) (📥 88K · ⏱️ 31.08.2021): +- [Conda](https://anaconda.org/conda-forge/biopandas) (📥 93K · ⏱️ 31.08.2021): ``` conda install -c conda-forge biopandas ```
-
Feature Engine (🥉14 · ⭐ 3) - 具有sklearn类功能的功能工程包。BSD-3 +
SUOD (🥉16 · ⭐ 300) - (MLSys' 21) An Acceleration System for Large-scare Unsupervised.. BSD-2 + +- [GitHub](https://github.com/yzhao062/SUOD) (🔀 36 · 📦 400 · 📋 6 - 66% open · ⏱️ 02.10.2021): + + ``` + git clone https://github.com/yzhao062/SUOD + ``` +- [PyPi](https://pypi.org/project/suod): + ``` + pip install suod + ``` +
+
Feature Engine (🥉12 · ⭐ 9) - Feature engineering package with sklearn like functionality. BSD-3 -- [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 24 · 🔀 3 · ⏱️ 06.08.2021): +- [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 24 · 🔀 6 · ⏱️ 06.08.2021): ``` git clone https://github.com/solegalli/feature_engine ``` -- [PyPi](https://pypi.org/project/feature_engine) (📥 41K / month): +- [PyPi](https://pypi.org/project/feature_engine): ``` pip install feature_engine ``` -- [Conda](https://anaconda.org/conda-forge/feature_engine) (📥 5.6K · ⏱️ 01.09.2021): +- [Conda](https://anaconda.org/conda-forge/feature_engine) (📥 6.7K · ⏱️ 01.09.2021): ``` conda install -c conda-forge feature_engine ``` diff --git a/history/2021-12-16_changes.md b/history/2021-12-16_changes.md new file mode 100644 index 0000000..e1ea810 --- /dev/null +++ b/history/2021-12-16_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._ + +- 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 + +## 📉 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 + diff --git a/history/2021-12-16_projects.csv b/history/2021-12-16_projects.csv new file mode 100644 index 0000000..e8f71d3 --- /dev/null +++ b/history/2021-12-16_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,npm_id,npm_url,npm_monthly_downloads,trending,helm_id,snap_id,brew_id,maven_id,maven_url,dnf_id,yay_id,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 13:21:43.000000,2021-12-05 13:14:34.000000,2021-12-05 13:14:34.000000,407.0,37.0,74.0,2658,1257.0,Benchmarks of approximate nearest neighbor libraries in Python.,65.0,0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +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 13:09:27.000000,2021-12-09 17:23:26.000000,2021-12-09 17:23:25.000000,92.0,,2.0,1383,,Collection of web-scraping and crawling libraries.,7.0,0,2021-12-09 17:23:42.000000,2021.12.09,25.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +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 13:42:10.000000,2021-12-16 14:14:05.000000,2021-10-13 07:25:17.000000,,,,2,40.0,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 01:19:20.000000,2021-12-16 13:47:27.343423,2021-12-16 12:30:20.000000,69281.0,2582.0,31016.0,163234,122798.0,An Open Source Machine Learning Framework for Everyone.,3877.0,44,2021-11-04 21:39:30.000000,2.7.0,100.0,,tensorflow,conda-forge/tensorflow,tensorflow/tensorflow,https://www.tensorflow.org/overview,['tensorflow'],172239.0,172239.0,https://pypi.org/project/tensorflow,15088986.0,15990818.0,https://anaconda.org/conda-forge/tensorflow,2021-12-08 18:39:34.795000,2946036.0,https://hub.docker.com/r/tensorflow/tensorflow,2021-12-16 13:47:27.343423,1974.0,62716982.0,1.0,,,,,,,,,,,,,,,, +4,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 01:37:33.000000,2021-12-16 13:27:57.000000,2021-12-16 05:01:50.000000,13278.0,3379.0,18320.0,32004,28447.0,Flexible and powerful data analysis / manipulation library for..,2870.0,43,2021-12-12 14:25:33.000000,1.3.5,81.0,,pandas,conda-forge/pandas,,,['pandas'],595633.0,595633.0,https://pypi.org/project/pandas,70830591.0,71157140.0,https://anaconda.org/conda-forge/pandas,2021-12-13 14:57:19.916000,21787601.0,,,,,1.0,129295.0,,,,,,,,,,,,,,, +5,scipy,True,scipy/scipy,,others,https://github.com/scipy/scipy,https://github.com/scipy/scipy,BSD-3-Clause,2011-03-09 18:52:03.000000,2021-12-16 08:29:28.000000,2021-12-16 02:57:36.000000,3884.0,1461.0,6297.0,8937,26879.0,"Ecosystem of open-source software for mathematics, science, and engineering.",1208.0,39,2021-11-24 18:44:51.000000,1.7.3,60.0,,scipy,conda-forge/scipy,,,,435827.0,435827.0,https://pypi.org/project/scipy,,300980.0,https://anaconda.org/conda-forge/scipy,2021-11-25 04:00:02.224000,19875198.0,,,,,1.0,333882.0,,,,,,,,,,,,,,, +6,transformers,True,huggingface/transformers,,nlp,https://github.com/huggingface/transformers,https://github.com/huggingface/transformers,Apache-2.0,2018-10-29 13:56:00.000000,2021-12-16 13:48:49.000000,2021-12-16 09:42:02.000000,12594.0,327.0,7982.0,55666,8499.0,Transformers: State-of-the-art Natural Language..,1096.0,38,2021-12-15 19:02:04.000000,4.14.1,82.0,,transformers,conda-forge/transformers,,,"['pytorch', 'tensorflow']",19891.0,19891.0,https://pypi.org/project/transformers,3161673.0,3165063.0,https://anaconda.org/conda-forge/transformers,2021-12-16 07:26:40.527000,87167.0,,,,,1.0,1417.0,,,,,,,,,,,,,,, +7,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 09:43:38.000000,2021-12-16 12:49:50.000000,2021-12-15 16:09:07.000000,21647.0,1706.0,7327.0,48306,,scikit-learn: machine learning in Python.,2428.0,38,2021-10-25 10:58:33.000000,1.0.1,30.0,,scikit-learn,conda-forge/scikit-learn,,,['sklearn'],294280.0,294280.0,https://pypi.org/project/scikit-learn,24772784.0,24932945.0,https://anaconda.org/conda-forge/scikit-learn,2021-12-14 20:35:02.518000,10730089.0,,,,,1.0,758.0,,,,,,,,,,,,,,, +8,spaCy,True,explosion/spaCy,,nlp,https://github.com/explosion/spaCy,https://github.com/explosion/spaCy,MIT,2014-07-03 15:15:40.000000,2021-12-16 13:36:19.000000,2021-12-16 09:28:31.000000,3573.0,89.0,4864.0,21972,15208.0,Industrial-strength Natural Language Processing (NLP) in Python.,643.0,38,2021-12-07 16:30:56.000000,3.2.1,90.0,,spacy,conda-forge/spacy,,,,32809.0,32809.0,https://pypi.org/project/spacy,5901948.0,5945237.0,https://anaconda.org/conda-forge/spacy,2021-12-14 12:41:39.668000,2507875.0,,,,,1.0,3103.0,,,,,,,,,,,,,,, +9,numpy,True,numpy/numpy,,data-containers,https://github.com/numpy/numpy,https://github.com/numpy/numpy,BSD-3-Clause,2010-09-13 23:02:39.000000,2021-12-16 07:56:09.000000,2021-12-16 07:56:08.000000,6131.0,2053.0,8092.0,19075,,The fundamental package for scientific computing with Python.,1375.0,38,2021-11-05 01:42:23.000000,1.21.4,75.0,,numpy,conda-forge/numpy,,,,913632.0,913632.0,https://pypi.org/project/numpy,89789134.0,90200125.0,https://anaconda.org/conda-forge/numpy,2021-11-05 22:05:37.357000,27061478.0,,,,,1.0,432480.0,,,,,,,,,,,,,,, +10,XGBoost,True,dmlc/xgboost,,ml-frameworks,https://github.com/dmlc/xgboost,https://github.com/dmlc/xgboost,Apache-2.0,2014-02-06 17:28:03.000000,2021-12-16 12:37:29.000000,2021-12-16 12:37:29.000000,7735.0,259.0,3973.0,22003,5582.0,"Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or..",541.0,37,2021-11-23 09:49:14.000000,1.5.1,38.0,,xgboost,conda-forge/xgboost,,https://xgboost.readthedocs.io/en/latest/,,24873.0,24873.0,https://pypi.org/project/xgboost,8811576.0,8849382.0,https://anaconda.org/conda-forge/xgboost,2021-11-20 17:37:18.728000,2152861.0,,,,,1.0,3500.0,,,,,,,,,,,,,,, +11,Celery,True,celery/celery,,data-pipelines,https://github.com/celery/celery,https://github.com/celery/celery,,2009-04-24 11:31:24.000000,2021-12-16 09:01:37.000000,2021-12-16 09:01:37.000000,4009.0,445.0,4151.0,18373,11801.0,Asynchronous task queue/job queue based on distributed message passing.,1167.0,37,2021-11-16 14:56:22.000000,5.2.1,29.0,,celery,conda-forge/celery,,,,62046.0,62046.0,https://pypi.org/project/celery,4942446.0,4953520.0,https://anaconda.org/conda-forge/celery,2021-06-29 08:06:51.307000,764164.0,,,,,1.0,,,,,,,,,,,,,,,, +12,Faker,True,joke2k/faker,,data-loading,https://github.com/joke2k/faker,https://github.com/joke2k/faker,MIT,2012-11-12 23:00:09.000000,2021-12-13 19:58:58.000000,2021-12-07 15:58:43.000000,1496.0,128.0,402.0,13390,2821.0,Faker is a Python package that generates fake data for you.,432.0,37,2021-12-07 15:59:18.000000,10.0.0,130.0,,Faker,conda-forge/faker,,,,44706.0,44706.0,https://pypi.org/project/Faker,5274484.0,5283709.0,https://anaconda.org/conda-forge/faker,2021-12-07 17:49:18.201000,525851.0,,,,,1.0,,,,,,,,,,,,,,,, +13,Tensorboard,True,tensorflow/tensorboard,,ml-experiments,https://github.com/tensorflow/tensorboard,https://github.com/tensorflow/tensorboard,Apache-2.0,2017-05-15 20:08:07.000000,2021-12-16 13:56:12.000000,2021-12-16 04:03:42.000000,1408.0,512.0,1056.0,5718,4890.0,TensorFlow's Visualization Toolkit.,274.0,37,2021-10-13 16:15:14.000000,2.7.0,39.0,,tensorboard,conda-forge/tensorboard,,,['tensorflow'],88312.0,88312.0,https://pypi.org/project/tensorboard,12571478.0,12626488.0,https://anaconda.org/conda-forge/tensorboard,2021-11-10 21:16:52.072000,2695512.0,,,,,1.0,,,,,,,,,,,,,,,, +14,OpenAI Gym,True,openai/gym,,reinforcement-learning,https://github.com/openai/gym,https://github.com/openai/gym,MIT,2016-04-27 14:59:16.000000,2021-12-16 05:45:37.000000,2021-12-16 05:45:37.000000,6980.0,99.0,1344.0,25968,1445.0,A toolkit for developing and comparing reinforcement learning..,329.0,36,2021-10-02 00:37:17.000000,0.21.0,8.0,,gym,,,,,25133.0,25133.0,https://pypi.org/project/gym,931156.0,931156.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +15,shap,True,slundberg/shap,,interpretability,https://github.com/slundberg/shap,https://github.com/slundberg/shap,MIT,2016-11-22 19:17:08.000000,2021-12-14 08:13:11.000000,2021-12-04 17:24:08.000000,2193.0,1217.0,564.0,14897,2011.0,A game theoretic approach to explain the output of any machine learning model.,162.0,36,2021-10-20 18:36:57.000000,0.40.0,46.0,,shap,conda-forge/shap,,,,4027.0,4027.0,https://pypi.org/project/shap,4314059.0,4332114.0,https://anaconda.org/conda-forge/shap,2021-10-24 14:05:16.285000,722231.0,,,,,1.0,,,,,,,,,,,,,,,, +16,LightGBM,True,microsoft/LightGBM,,ml-frameworks,https://github.com/microsoft/LightGBM,https://github.com/microsoft/LightGBM,MIT,2016-08-05 05:45:50.000000,2021-12-16 00:41:30.000000,2021-12-15 21:28:26.000000,3351.0,138.0,2350.0,13279,2822.0,"A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,..",246.0,36,2021-10-27 22:59:08.000000,3.3.1,23.0,,lightgbm,conda-forge/lightgbm,,,,10310.0,10310.0,https://pypi.org/project/lightgbm,10921555.0,10939626.0,https://anaconda.org/conda-forge/lightgbm,2021-11-20 15:50:31.621000,834041.0,,,,,1.0,130769.0,,,,,,,,,,,,,,, +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 07:43:04.000000,2021-12-13 14:39:39.000000,2021-12-13 14:39:39.000000,3912.0,344.0,1360.0,12756,4263.0,Topic Modelling for Humans.,417.0,36,2021-09-18 14:21:47.000000,4.1.2,40.0,,gensim,conda-forge/gensim,,,,29082.0,29082.0,https://pypi.org/project/gensim,10195223.0,10210121.0,https://anaconda.org/conda-forge/gensim,2021-11-09 13:39:50.380000,757451.0,,,,,1.0,3501.0,,,,,,,,,,,,,,, +18,pytorch-lightning,True,PyTorchLightning/pytorch-lightning,,ml-frameworks,https://github.com/PyTorchLightning/pytorch-lightning,https://github.com/PyTorchLightning/pytorch-lightning,Apache-2.0,2019-03-31 00:45:57.000000,2021-12-16 13:48:24.000000,2021-12-16 12:57:03.000000,1999.0,371.0,3935.0,16620,6234.0,The lightweight PyTorch wrapper for high-performance..,588.0,35,2021-12-15 23:06:40.000000,1.5.6,82.0,,pytorch-lightning,conda-forge/pytorch-lightning,,,['pytorch'],6006.0,6006.0,https://pypi.org/project/pytorch-lightning,867115.0,888622.0,https://anaconda.org/conda-forge/pytorch-lightning,2021-12-16 09:11:14.920000,384090.0,,,,,1.0,4905.0,,,,,,,,,,,,,,, +19,onnx,True,onnx/onnx,,model-serialisation,https://github.com/onnx/onnx,https://github.com/onnx/onnx,Apache-2.0,2017-09-07 04:53:45.000000,2021-12-16 12:33:51.000000,2021-12-15 23:46:57.000000,2224.0,412.0,1312.0,11818,1862.0,Open standard for machine learning interoperability.,217.0,35,2021-10-26 17:29:47.000000,1.10.2,20.0,,onnx,conda-forge/onnx,,,,4967.0,4967.0,https://pypi.org/project/onnx,1236415.0,1243452.0,https://anaconda.org/conda-forge/onnx,2021-12-14 07:56:56.053000,327931.0,,,,,1.0,17283.0,,,,,,,,,,,,,,, +20,Seaborn,True,mwaskom/seaborn,,data-viz,https://github.com/mwaskom/seaborn,https://github.com/mwaskom/seaborn,BSD-3-Clause,2012-06-18 18:41:19.000000,2021-12-13 03:46:11.000000,2021-11-27 18:58:32.000000,1468.0,96.0,1845.0,9000,2812.0,Statistical data visualization using matplotlib.,161.0,35,2021-08-16 00:39:03.000000,0.11.2,24.0,,seaborn,conda-forge/seaborn,,,,129922.0,129922.0,https://pypi.org/project/seaborn,,49546.0,https://anaconda.org/conda-forge/seaborn,2021-08-16 06:42:17.619000,3170836.0,,,,,1.0,209.0,,,,,,,,,,,,,,, +21,Datasets,True,huggingface/datasets,,data-loading,https://github.com/huggingface/datasets,https://github.com/huggingface/datasets,Apache-2.0,2020-03-26 09:23:22.000000,2021-12-16 10:59:14.000000,2021-12-14 17:53:02.000000,1338.0,402.0,762.0,11596,2270.0,The largest hub of ready-to-use NLP datasets for ML models with..,355.0,34,2021-11-26 16:58:29.000000,1.16.1,38.0,,datasets,,,,,2429.0,2429.0,https://pypi.org/project/datasets,540554.0,540554.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +22,pydeck,True,visgl/deck.gl,,geospatial-data,https://github.com/visgl/deck.gl,https://github.com/visgl/deck.gl,MIT,2015-12-15 08:38:29.000000,2021-12-15 18:41:13.000000,2021-12-13 15:48:38.000000,1621.0,110.0,2196.0,9300,3888.0,WebGL2 powered geospatial visualization layers.,185.0,34,2021-12-09 17:45:11.000000,8.6.5,74.0,,pydeck,conda-forge/pydeck,,,['jupyter'],2063.0,2063.0,https://pypi.org/project/pydeck,657580.0,901112.0,https://anaconda.org/conda-forge/pydeck,2021-10-26 00:42:05.329000,63043.0,,,,,1.0,,deck.gl,https://www.npmjs.com/package/deck.gl,240667.0,,,,,,,,,,,, +23,joblib,True,joblib/joblib,,data-pipelines,https://github.com/joblib/joblib,https://github.com/joblib/joblib,BSD-3-Clause,2010-05-07 06:48:26.000000,2021-12-10 08:11:05.000000,2021-11-08 20:50:44.000000,302.0,287.0,376.0,2620,1385.0,Computing with Python functions.,106.0,34,,,23.0,,joblib,conda-forge/joblib,,,,148784.0,148784.0,https://pypi.org/project/joblib,26761374.0,26861509.0,https://anaconda.org/conda-forge/joblib,2021-10-07 20:15:36.705000,6508828.0,,,,,1.0,,,,,,,,,,,,,,,, +24,Thinc,True,explosion/thinc,,ml-frameworks,https://github.com/explosion/thinc,https://github.com/explosion/thinc,MIT,2014-10-16 16:34:59.000000,2021-12-16 12:02:54.000000,2021-12-16 12:02:53.000000,215.0,15.0,97.0,2421,5008.0,"A refreshing functional take on deep learning, compatible with your favorite..",42.0,34,2021-10-28 09:23:53.000000,8.0.12,55.0,,thinc,conda-forge/thinc,,,,17742.0,17742.0,https://pypi.org/project/thinc,5661331.0,5691891.0,https://anaconda.org/conda-forge/thinc,2021-12-08 16:36:35.030000,1772499.0,,,,,1.0,,,,,,,,,,,,,,,, +25,h5py,True,h5py/h5py,,data-containers,https://github.com/h5py/h5py,https://github.com/h5py/h5py,BSD-3-Clause,2012-09-21 00:40:02.000000,2021-12-11 15:44:28.000000,2021-12-11 15:44:27.000000,416.0,205.0,1055.0,1642,3849.0,HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5..,172.0,34,2021-11-16 09:55:10.000000,3.6.0,31.0,,h5py,conda-forge/h5py,,,,142713.0,142713.0,https://pypi.org/project/h5py,,98264.0,https://anaconda.org/conda-forge/h5py,2021-11-26 22:25:41.747000,6778342.0,,,,,1.0,1620.0,,,,,,,,,,,,,,, +26,PyTorch,True,pytorch/pytorch,,ml-frameworks,https://github.com/pytorch/pytorch,https://github.com/pytorch/pytorch,BSD-3-Clause,2016-08-13 05:26:41.000000,2021-12-16 14:02:24.000000,2021-12-16 13:44:40.000000,14007.0,7362.0,16296.0,52773,42445.0,Tensors and Dynamic neural networks in Python with strong GPU..,3007.0,33,2021-12-15 22:27:43.000000,1.10.1,37.0,,torch,pytorch/pytorch,,https://pytorch.org/docs/stable/index.html,['pytorch'],,,https://pypi.org/project/torch,6272196.0,6565011.0,https://anaconda.org/pytorch/pytorch,2021-12-15 21:52:11.758000,14347535.0,,,,,2.0,601.0,,,,,,,,,,,,,,, +27,Matplotlib,True,matplotlib/matplotlib,,data-viz,https://github.com/matplotlib/matplotlib,https://github.com/matplotlib/matplotlib,,2011-02-19 03:17:12.000000,2021-12-16 13:31:39.000000,2021-12-16 08:52:09.000000,6013.0,1426.0,6738.0,14724,,matplotlib: plotting with Python.,1316.0,33,2021-12-11 05:51:23.000000,3.5.1,62.0,,matplotlib,conda-forge/matplotlib,,,,473449.0,473449.0,https://pypi.org/project/matplotlib,,140965.0,https://anaconda.org/conda-forge/matplotlib,2021-12-13 20:23:04.086000,10572385.0,,,,,1.0,,,,,-7.0,,,,,,,,,,, +28,nltk,True,nltk/nltk,,nlp,https://github.com/nltk/nltk,https://github.com/nltk/nltk,Apache-2.0,2009-09-07 10:53:58.000000,2021-12-16 13:55:18.000000,2021-12-16 13:55:18.000000,2401.0,198.0,1362.0,10305,,Suite of libraries and programs for symbolic and statistical natural language processing for English.,412.0,33,,,12.0,,nltk,conda-forge/nltk,,,,123874.0,123874.0,https://pypi.org/project/nltk,9541646.0,9558517.0,https://anaconda.org/conda-forge/nltk,2021-10-11 12:28:19.966000,1079777.0,,,,,1.0,,,,,,,,,,,,,,,, +29,Arrow,True,apache/arrow,,data-containers,https://github.com/apache/arrow,https://github.com/apache/arrow,Apache-2.0,2016-02-17 08:00:23.000000,2021-12-16 13:43:47.000000,2021-12-15 15:48:31.000000,2030.0,12.0,683.0,8819,10577.0,Apache Arrow is a cross-language development platform for in-..,780.0,33,,,33.0,,pyarrow,conda-forge/arrow,,,,57.0,57.0,https://pypi.org/project/pyarrow,32386599.0,32399152.0,https://anaconda.org/conda-forge/arrow,2021-10-26 15:18:02.635000,841074.0,,,,,2.0,,,,,,,,,,,,,,,, +30,SymPy,True,sympy/sympy,,others,https://github.com/sympy/sympy,https://github.com/sympy/sympy,,2010-04-30 20:37:14.000000,2021-12-16 13:45:57.000000,2021-12-15 17:41:19.000000,3453.0,3748.0,7703.0,8683,49531.0,A computer algebra system written in pure Python.,1125.0,33,2021-10-08 23:27:06.000000,sympy-1.9,35.0,,sympy,conda-forge/sympy,,,,37822.0,37822.0,https://pypi.org/project/sympy,,31450.0,https://anaconda.org/conda-forge/sympy,2021-11-06 22:30:34.086000,1815334.0,,,,,1.0,439991.0,,,,,,,,,,,,,,, +31,pandas-profiling,True,pandas-profiling/pandas-profiling,,data-viz,https://github.com/pandas-profiling/pandas-profiling,https://github.com/pandas-profiling/pandas-profiling,MIT,2016-01-09 23:47:55.000000,2021-12-14 09:26:04.000000,2021-12-06 17:52:39.000000,1187.0,95.0,433.0,8322,922.0,Create HTML profiling reports from pandas DataFrame..,83.0,33,2021-09-27 23:08:38.000000,3.1.0,31.0,,pandas-profiling,conda-forge/pandas-profiling,,,"['jupyter', 'pandas']",6109.0,6109.0,https://pypi.org/project/pandas-profiling,2349086.0,2351910.0,https://anaconda.org/conda-forge/pandas-profiling,2021-09-28 13:50:05.966000,180768.0,,,,,1.0,,,,,,,,,,,,,,,, +32,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 03:14:04.000000,2021-12-13 16:53:48.000000,2021-12-13 16:17:47.000000,600.0,219.0,1344.0,7122,3102.0,Declarative statistical visualization library for Python.,133.0,33,2020-04-01 13:29:16.000000,4.1.0,19.0,,altair,conda-forge/altair,,,,19587.0,19587.0,https://pypi.org/project/altair,3966590.0,3982607.0,https://anaconda.org/conda-forge/altair,2020-04-01 16:49:36.519000,1041118.0,,,,,1.0,,,,,,,,,,,,,,,, +33,StatsModels,True,statsmodels/statsmodels,,ml-frameworks,https://github.com/statsmodels/statsmodels,https://github.com/statsmodels/statsmodels,BSD-3-Clause,2011-06-12 17:04:50.000000,2021-12-15 17:33:21.000000,2021-12-15 15:44:10.000000,2211.0,2097.0,2451.0,6929,,Statsmodels: statistical modeling and econometrics in Python.,348.0,33,2021-11-12 23:21:25.000000,0.13.1,19.0,,statsmodels,conda-forge/statsmodels,,,,54664.0,54664.0,https://pypi.org/project/statsmodels,7517406.0,7599148.0,https://anaconda.org/conda-forge/statsmodels,2021-11-13 01:23:06.115000,5395008.0,,,,,2.0,26.0,,,,,,,,,,,,,,, +34,Optuna,True,optuna/optuna,,hyperopt,https://github.com/optuna/optuna,https://github.com/optuna/optuna,MIT,2018-02-21 06:12:56.000000,2021-12-16 13:42:19.000000,2021-12-16 00:50:54.000000,619.0,120.0,885.0,5670,11085.0,A hyperparameter optimization framework.,167.0,33,2021-10-04 06:36:18.000000,2.10.0,42.0,,optuna,conda-forge/optuna,,,,2349.0,2349.0,https://pypi.org/project/optuna,815800.0,817735.0,https://anaconda.org/conda-forge/optuna,2021-10-04 08:58:48.864000,48385.0,,,,,1.0,,,,,,,,,,,,,,,, +35,geopy,True,geopy/geopy,,geospatial-data,https://github.com/geopy/geopy,https://github.com/geopy/geopy,MIT,2010-03-04 22:05:28.000000,2021-12-15 15:51:51.000000,2021-09-26 10:28:21.000000,541.0,23.0,227.0,3509,1072.0,Geocoding library for Python.,123.0,33,2021-07-11 12:18:10.000000,2.2.0,34.0,,geopy,conda-forge/geopy,,,,30489.0,30489.0,https://pypi.org/project/geopy,3824051.0,3833199.0,https://anaconda.org/conda-forge/geopy,2021-07-12 18:34:05.605000,631279.0,,,,,1.0,,,,,,,,,,,,,,,, +36,GeoPandas,True,geopandas/geopandas,,geospatial-data,https://github.com/geopandas/geopandas,https://github.com/geopandas/geopandas,BSD-3-Clause,2013-06-27 17:03:47.000000,2021-12-16 12:07:42.000000,2021-12-11 15:43:18.000000,623.0,333.0,835.0,2917,1505.0,Python tools for geographic data.,156.0,33,2021-10-16 06:59:55.000000,0.10.2,23.0,,geopandas,conda-forge/geopandas,,,['pandas'],11304.0,11304.0,https://pypi.org/project/geopandas,1988672.0,2006821.0,https://anaconda.org/conda-forge/geopandas,2021-12-01 18:19:27.710000,1250913.0,,,,,1.0,1301.0,,,,,,,,,,,,,,, +37,PaddlePaddle,True,PaddlePaddle/Paddle,,ml-frameworks,https://github.com/PaddlePaddle/Paddle,https://github.com/PaddlePaddle/Paddle,Apache-2.0,2016-08-15 06:59:08.000000,2021-12-16 13:38:51.000000,2021-12-16 13:02:56.000000,4048.0,2011.0,11886.0,17226,15069.0,PArallel Distributed Deep LEarning: Machine Learning..,672.0,32,2021-12-08 05:04:30.000000,2.2.1,51.0,,paddlepaddle,,,,['paddle'],83.0,83.0,https://pypi.org/project/paddlepaddle,109593.0,109832.0,,,,,,,,2.0,15306.0,,,,,,,,,,,,,,, +38,imgaug,True,aleju/imgaug,,image,https://github.com/aleju/imgaug,https://github.com/aleju/imgaug,MIT,2015-07-10 20:31:33.000000,2021-10-27 15:54:07.000000,2020-06-01 14:58:26.000000,2151.0,256.0,219.0,12102,2913.0,Image augmentation for machine learning experiments.,36.0,32,2020-02-06 06:18:40.000000,0.4.0,3.0,,imgaug,conda-forge/imgaug,,,,8431.0,8431.0,https://pypi.org/project/imgaug,260234.0,262195.0,https://anaconda.org/conda-forge/imgaug,2020-02-14 16:06:53.525000,58830.0,,,,,1.0,,,,,,,,,,,,,,,, +39,AllenNLP,True,allenai/allennlp,,nlp,https://github.com/allenai/allennlp,https://github.com/allenai/allennlp,Apache-2.0,2017-05-15 15:52:41.000000,2021-12-16 13:03:47.000000,2021-12-14 21:24:57.000000,2079.0,93.0,2373.0,10694,2357.0,"An open-source NLP research library, built on PyTorch.",254.0,32,2021-11-01 21:11:27.000000,2.8.0,53.0,,allennlp,,,,['pytorch'],2135.0,2135.0,https://pypi.org/project/allennlp,36836.0,36836.0,,,,,,,,1.0,43.0,,,,,,,,,,,,,,, +40,networkx,True,networkx/networkx,,graph,https://github.com/networkx/networkx,https://github.com/networkx/networkx,,2010-09-06 00:53:44.000000,2021-12-13 20:50:25.000000,2021-12-13 05:58:42.000000,2365.0,176.0,2452.0,10048,,Network Analysis in Python.,559.0,32,2021-09-09 22:07:01.000000,networkx-2.6.3,33.0,,networkx,conda-forge/networkx,,,,93090.0,93090.0,https://pypi.org/project/networkx,17098411.0,17181820.0,https://anaconda.org/conda-forge/networkx,2021-10-26 12:59:30.009000,5171377.0,,,,,1.0,57.0,,,,,,,,,,,,,,, +41,Albumentations,True,albumentations-team/albumentations,,image,https://github.com/albumentations-team/albumentations,https://github.com/albumentations-team/albumentations,MIT,2018-06-06 03:10:50.000000,2021-12-16 11:04:27.000000,2021-12-14 14:18:02.000000,1179.0,216.0,328.0,9335,693.0,Fast image augmentation library and an easy-to-use wrapper..,98.0,32,2021-10-04 09:30:05.000000,1.1.0,14.0,,albumentations,conda-forge/albumentations,,,['pytorch'],6014.0,6014.0,https://pypi.org/project/albumentations,206724.0,207687.0,https://anaconda.org/conda-forge/albumentations,2021-07-15 13:53:18.638000,28902.0,,,,,1.0,,,,,,,,,,,,,,,, +42,dask,True,dask/dask,,distributed-ml,https://github.com/dask/dask,https://github.com/dask/dask,BSD-3-Clause,2015-01-04 18:50:00.000000,2021-12-16 13:37:24.000000,2021-12-15 19:13:18.000000,1374.0,648.0,3370.0,9300,,Parallel computing with task scheduling.,490.0,32,,,109.0,,dask,conda-forge/dask,,,,32343.0,32343.0,https://pypi.org/project/dask,5740490.0,5811026.0,https://anaconda.org/conda-forge/dask,2021-12-11 02:29:38.463000,4725922.0,,,,,1.0,,,,,,stable/dask,,,,,,,,,, +43,MoviePy,True,Zulko/moviepy,,image,https://github.com/Zulko/moviepy,https://github.com/Zulko/moviepy,MIT,2013-08-12 09:39:28.000000,2021-11-14 16:13:10.000000,2021-11-12 17:14:13.000000,1141.0,327.0,764.0,8791,1072.0,Video editing with Python.,145.0,32,2020-05-07 16:29:35.000000,1.0.3,14.0,,moviepy,conda-forge/moviepy,,,,12257.0,12257.0,https://pypi.org/project/moviepy,1422123.0,1423987.0,https://anaconda.org/conda-forge/moviepy,2020-02-23 19:57:49.975000,98831.0,,,,,1.0,,,,,,,,,,,,,,,, +44,CuPy,True,cupy/cupy,,gpu-utilities,https://github.com/cupy/cupy,https://github.com/cupy/cupy,MIT,2016-11-01 09:54:45.000000,2021-12-16 11:40:38.000000,2021-12-16 06:45:14.000000,510.0,312.0,1264.0,5624,24079.0,A NumPy-compatible array library accelerated by CUDA.,287.0,32,2021-12-09 06:46:26.000000,10.0.0,100.0,,cupy,conda-forge/cupy,cupy/cupy,,,892.0,892.0,https://pypi.org/project/cupy,109628.0,152568.0,https://anaconda.org/conda-forge/cupy,2021-12-15 13:17:01.892000,1082265.0,https://hub.docker.com/r/cupy/cupy,2021-12-09 06:50:02.321705,7.0,53485.0,1.0,23304.0,,,,,,,,,,,,,,, +45,UMAP,True,lmcinnes/umap,,data-viz,https://github.com/lmcinnes/umap,https://github.com/lmcinnes/umap,BSD-3-Clause,2017-07-02 01:11:17.000000,2021-12-03 13:30:07.000000,2021-12-03 13:30:07.000000,565.0,291.0,285.0,5265,1506.0,Uniform Manifold Approximation and Projection.,94.0,32,2021-10-29 16:28:45.000000,0.5.2,25.0,,umap-learn,,,,,4211.0,4211.0,https://pypi.org/project/umap-learn,1636762.0,1636762.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +46,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 01:03:33.000000,2021-12-16 14:06:40.000000,2021-12-15 18:45:02.000000,704.0,294.0,637.0,1529,2293.0,A library for training and deploying machine learning..,237.0,32,2021-12-13 20:51:14.000000,2.72.0,100.0,,sagemaker,,,,"['mxnet', 'tensorflow']",980.0,980.0,https://pypi.org/project/sagemaker,2283526.0,2283526.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +47,PySpark,True,apache/spark,,ml-frameworks,https://github.com/apache/spark,https://github.com/apache/spark,Apache-2.0,2014-02-25 08:00:08.000000,2021-12-16 12:08:23.000000,2021-12-16 06:22:51.000000,23831.0,,,31597,31915.0,Apache Spark Python API.,2585.0,31,,,20.0,,pyspark,conda-forge/pyspark,,,['spark'],,,https://pypi.org/project/pyspark,15382068.0,15406432.0,https://anaconda.org/conda-forge/pyspark,2021-10-18 11:47:59.356000,1388789.0,,,,,2.0,,,,,,stable/spark,,,,,,,,,, +48,jieba,True,fxsjy/jieba,,chinese-nlp,https://github.com/fxsjy/jieba,https://github.com/fxsjy/jieba,MIT,2012-09-29 07:52:01.000000,2021-07-25 14:17:48.000000,2020-02-15 08:33:35.000000,6208.0,578.0,208.0,27550,523.0,Chinese Words Segementation Utilities.,48.0,31,2020-01-20 14:23:50.000000,0.42.1,9.0,,jieba,conda-forge/jieba,,,,11942.0,11942.0,https://pypi.org/project/jieba,451184.0,452960.0,https://anaconda.org/conda-forge/jieba,2021-05-30 19:33:02.597000,99509.0,,,,,1.0,,,,,,,,,,,,,,,, +49,fastText,True,facebookresearch/fastText,,nlp,https://github.com/facebookresearch/fastText,https://github.com/facebookresearch/fastText,MIT,2016-07-16 13:38:42.000000,2021-12-09 15:16:36.000000,2020-07-18 00:20:40.000000,4259.0,402.0,596.0,23200,379.0,Library for fast text representation and classification.,58.0,31,2020-04-28 09:51:33.000000,0.9.2,4.0,,fasttext,conda-forge/fasttext,,,,2406.0,2406.0,https://pypi.org/project/fasttext,472522.0,473030.0,https://anaconda.org/conda-forge/fasttext,2021-11-08 12:46:40.327000,25448.0,,,,,1.0,,,,,,,,,,,,,,,, +50,Bokeh,True,bokeh/bokeh,,data-viz,https://github.com/bokeh/bokeh,https://github.com/bokeh/bokeh,BSD-3-Clause,2012-03-26 15:40:01.000000,2021-12-16 13:16:34.000000,2021-12-16 13:16:34.000000,3772.0,685.0,6101.0,15819,,"Interactive Data Visualization in the browser, from Python.",587.0,31,,,44.0,,bokeh,conda-forge/bokeh,,,,42095.0,42095.0,https://pypi.org/project/bokeh,2092661.0,2203729.0,https://anaconda.org/conda-forge/bokeh,2021-11-22 21:24:20.205000,6219829.0,,,,,2.0,,,,,,,,,,,,,,,, +51,dash,True,plotly/dash,,data-viz,https://github.com/plotly/dash,https://github.com/plotly/dash,MIT,2015-04-10 01:53:08.000000,2021-12-16 09:50:07.000000,2021-12-15 16:03:15.000000,1551.0,528.0,616.0,15585,5518.0,"Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript..",102.0,31,2021-09-04 01:00:46.000000,2.0.0,76.0,,dash,conda-forge/dash,,,,162.0,162.0,https://pypi.org/project/dash,840989.0,848772.0,https://anaconda.org/conda-forge/dash,2021-09-21 14:47:05.413000,334671.0,,,,,2.0,,,,,,,,,,,,,,,, +52,ChatterBot,True,gunthercox/ChatterBot,,nlp,https://github.com/gunthercox/ChatterBot,https://github.com/gunthercox/ChatterBot,BSD-3-Clause,2014-09-28 14:49:00.000000,2021-11-24 23:13:22.000000,2021-06-01 10:43:00.000000,3844.0,278.0,1247.0,11806,1848.0,"ChatterBot is a machine learning, conversational dialog engine..",103.0,31,2020-08-22 18:42:43.000000,1.0.8,86.0,,chatterbot,,,,,4042.0,4042.0,https://pypi.org/project/chatterbot,33110.0,33110.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +53,dlib,True,davisking/dlib,,ml-frameworks,https://github.com/davisking/dlib,https://github.com/davisking/dlib,BSL-1.0,2014-01-29 00:45:33.000000,2021-12-16 13:17:08.000000,2021-12-16 13:16:59.000000,2554.0,32.0,1936.0,10779,7995.0,A toolkit for making real world machine learning and data analysis..,171.0,31,2021-03-28 13:36:18.000000,19.22,23.0,,dlib,conda-forge/dlib,,,,12432.0,12432.0,https://pypi.org/project/dlib,125816.0,132123.0,https://anaconda.org/conda-forge/dlib,2021-04-03 09:47:47.788000,377340.0,,,,,2.0,24815.0,,,,,,,,,,,,,,, +54,Theano,True,Theano/Theano,,ml-frameworks,https://github.com/Theano/Theano,https://github.com/Theano/Theano,,2011-08-10 03:48:06.000000,2021-12-01 00:24:43.000000,2021-11-23 08:52:10.000000,2405.0,578.0,2086.0,9499,28127.0,"Theano is a Python library that allows you to define, optimize, and..",384.0,31,,,8.0,,theano,conda-forge/theano,,,,11890.0,11890.0,https://pypi.org/project/theano,228410.0,255985.0,https://anaconda.org/conda-forge/theano,2021-11-10 16:59:17.809000,1792427.0,,,,,2.0,,,,,,,,,,,,,,,, +55,fuzzywuzzy,True,seatgeek/fuzzywuzzy,,nlp,https://github.com/seatgeek/fuzzywuzzy,https://github.com/seatgeek/fuzzywuzzy,GPL-2.0,2011-07-08 19:32:34.000000,2021-11-02 23:56:01.000000,2021-09-09 20:54:41.000000,859.0,80.0,102.0,8579,384.0,Fuzzy String Matching in Python.,70.0,31,2020-02-13 22:14:12.000000,0.18.0,23.0,,fuzzywuzzy,conda-forge/fuzzywuzzy,,,,10615.0,10615.0,https://pypi.org/project/fuzzywuzzy,5285562.0,5290805.0,https://anaconda.org/conda-forge/fuzzywuzzy,2020-11-18 12:59:01.409000,340810.0,,,,,1.0,,,,,,,,,,,,,,,, +56,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 10:53:51.000000,2021-12-15 18:18:30.000000,2021-12-15 14:26:59.000000,1259.0,596.0,608.0,6675,1020.0,Sentence Embeddings with BERT & XLNet.,67.0,31,2021-10-01 09:10:30.000000,2.1.0,29.0,,sentence-transformers,,,,['pytorch'],2065.0,2065.0,https://pypi.org/project/sentence-transformers,562595.0,562595.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +57,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 05:08:26.000000,2021-12-08 12:43:13.000000,2021-12-07 14:20:09.000000,1087.0,41.0,439.0,5614,757.0,A Python Package to Tackle the Curse of Imbalanced..,61.0,31,2021-09-29 13:11:34.000000,0.8.1,28.0,,imbalanced-learn,conda-forge/imbalanced-learn,,,['sklearn'],8420.0,8420.0,https://pypi.org/project/imbalanced-learn,2800403.0,2803895.0,https://anaconda.org/conda-forge/imbalanced-learn,2021-09-29 14:10:14.261000,174645.0,,,,,1.0,,,,,,,,,,,,,,,, +58,sentencepiece,True,google/sentencepiece,,nlp,https://github.com/google/sentencepiece,https://github.com/google/sentencepiece,Apache-2.0,2017-03-07 10:03:48.000000,2021-12-06 11:05:06.000000,2021-07-02 15:44:09.000000,731.0,46.0,443.0,5537,697.0,Unsupervised text tokenizer for Neural Network-based text..,57.0,31,2021-06-17 16:55:39.000000,0.1.96,21.0,,sentencepiece,conda-forge/sentencepiece,,,,11562.0,11562.0,https://pypi.org/project/sentencepiece,3285748.0,3293856.0,https://anaconda.org/conda-forge/sentencepiece,2021-11-05 06:32:08.219000,129972.0,,,,,1.0,18543.0,,,,,,,,,,,,,,, +59,PyOD,True,yzhao062/pyod,,others,https://github.com/yzhao062/pyod,https://github.com/yzhao062/pyod,BSD-2-Clause,2017-10-03 20:29:04.000000,2021-12-12 14:28:00.000000,2021-11-01 13:46:08.000000,988.0,107.0,113.0,5077,1398.0,(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly..,31.0,31,2021-10-27 18:18:19.000000,0.9.5,22.0,,pyod,,,,,1013.0,1013.0,https://pypi.org/project/pyod,537149.0,537149.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +60,xmltodict,True,martinblech/xmltodict,,data-loading,https://github.com/martinblech/xmltodict,https://github.com/martinblech/xmltodict,MIT,2012-04-17 14:38:21.000000,2021-12-15 19:37:06.000000,2020-04-26 05:15:03.000000,424.0,64.0,136.0,4630,205.0,Python module that makes working with XML feel like you are..,41.0,31,,,3.0,,xmltodict,conda-forge/xmltodict,,,,33782.0,33782.0,https://pypi.org/project/xmltodict,14805384.0,14825724.0,https://anaconda.org/conda-forge/xmltodict,2019-02-11 11:53:14.803000,1301806.0,,,,,1.0,,,,,,,,,,,,,,,, +61,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 16:30:04.000000,2021-12-16 06:02:32.000000,2021-12-16 05:56:43.000000,482.0,785.0,2683.0,4092,9267.0,"A data orchestrator for machine learning, analytics, and ETL.",176.0,31,2021-12-10 16:06:54.000000,0.13.11,100.0,,dagster,conda-forge/dagster,,,,271.0,271.0,https://pypi.org/project/dagster,191092.0,207955.0,https://anaconda.org/conda-forge/dagster,2021-12-10 15:43:44.978000,421595.0,,,,,1.0,,,,,,,,,,,,,,,, +62,Shapely,True,Toblerity/Shapely,,geospatial-data,https://github.com/shapely/shapely,https://github.com/shapely/shapely,BSD-3-Clause,2011-12-31 19:43:11.000000,2021-12-13 08:41:35.000000,2021-12-13 08:41:35.000000,435.0,144.0,657.0,2552,,Manipulation and analysis of geometric objects.,131.0,31,2021-10-25 16:52:16.000000,1.8.0,14.0,shapely/shapely,shapely,conda-forge/shapely,,,,24619.0,24619.0,https://pypi.org/project/shapely,6058974.0,6100197.0,https://anaconda.org/conda-forge/shapely,2021-11-20 09:37:12.537000,3050512.0,,,,,2.0,,,,,,,,,,,,,,,, +63,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 21:10:54.000000,2021-12-15 05:01:56.230000,2021-10-12 13:32:38.000000,406.0,199.0,385.0,2253,1570.0,Sequential model-based optimization with a `scipy.optimize`..,75.0,31,2021-10-12 15:33:19.000000,0.9.0,23.0,,scikit-optimize,conda-forge/scikit-optimize,,,,2219.0,2219.0,https://pypi.org/project/scikit-optimize,498870.0,508657.0,https://anaconda.org/conda-forge/scikit-optimize,2021-12-15 05:01:56.230000,518719.0,,,,,1.0,,,,,,,,,,,,,,,, +64,DeepSpeech,True,mozilla/DeepSpeech,,audio,https://github.com/mozilla/DeepSpeech,https://github.com/mozilla/DeepSpeech,MPL-2.0,2016-06-02 15:04:53.000000,2021-12-03 15:25:49.000000,2021-11-17 17:52:52.000000,3238.0,113.0,1929.0,18670,3466.0,"DeepSpeech is an open source embedded (offline, on-..",162.0,30,2020-12-10 15:58:47.000000,0.9.3,100.0,,deepspeech,,,,['tensorflow'],643.0,643.0,https://pypi.org/project/deepspeech,,19626.0,,,,,,,,1.0,765422.0,,,,26.0,,,,,,,,,,, +65,jax,True,google/jax,,ml-frameworks,https://github.com/google/jax,https://github.com/google/jax,Apache-2.0,2018-10-25 21:25:02.000000,2021-12-16 14:02:30.000000,2021-12-16 13:44:16.000000,1386.0,777.0,1988.0,15537,,"Composable transformations of Python+NumPy programs: differentiate,..",343.0,30,2021-12-08 19:20:03.000000,jax-v0.2.26,40.0,,jax,conda-forge/jaxlib,,,,3065.0,3065.0,https://pypi.org/project/jax,1440732.0,1449236.0,https://anaconda.org/conda-forge/jaxlib,2021-12-10 12:52:23.006000,246626.0,,,,,2.0,,,,,,,,,,,,,,,, +66,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 05:51:12.000000,2021-12-14 22:32:49.000000,2021-12-14 22:12:47.000000,2387.0,46.0,376.0,15200,1217.0,"PyTorch image models, scripts, pretrained weights --..",62.0,30,2021-10-04 00:02:48.000000,0.1-rsb-weights,27.0,,,,,,['pytorch'],1594.0,1594.0,,,25161.0,,,,,,,,1.0,779991.0,,,,,,,,,,,,,,, +67,EasyOCR,True,JaidedAI/EasyOCR,,ocr,https://github.com/JaidedAI/EasyOCR,https://github.com/JaidedAI/EasyOCR,Apache-2.0,2020-03-14 11:46:39.000000,2021-12-13 07:13:56.000000,2021-10-15 02:56:26.000000,1711.0,138.0,329.0,13363,474.0,Ready-to-use OCR with 80+ supported languages and all popular writing..,90.0,30,2021-09-11 09:36:28.000000,1.4.1,15.0,,easyocr,,,,,754.0,754.0,https://pypi.org/project/easyocr,118037.0,166406.0,,,,,,,,1.0,870646.0,,,,,,,,,,,,,,, +68,flair,True,flairNLP/flair,,nlp,https://github.com/flairNLP/flair,https://github.com/flairNLP/flair,,2018-06-11 11:04:18.000000,2021-12-16 13:18:45.000000,2021-12-16 13:16:48.000000,1477.0,84.0,1621.0,11057,4093.0,A very simple framework for state-of-the-art Natural Language Processing..,214.0,30,2021-11-18 08:33:59.000000,0.10,19.0,,flair,,,,['pytorch'],1079.0,1079.0,https://pypi.org/project/flair,66697.0,66697.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +69,Lime,True,marcotcr/lime,,interpretability,https://github.com/marcotcr/lime,https://github.com/marcotcr/lime,BSD-2-Clause,2016-03-15 22:18:10.000000,2021-10-19 11:55:10.000000,2021-07-29 23:17:25.000000,1487.0,21.0,525.0,9389,531.0,Lime: Explaining the predictions of any machine learning classifier.,61.0,30,2020-04-03 22:05:03.000000,0.2.0.0,18.0,,lime,conda-forge/lime,,,,1795.0,1795.0,https://pypi.org/project/lime,1333338.0,1334814.0,https://anaconda.org/conda-forge/lime,2020-06-28 01:02:41.538000,88575.0,,,,,1.0,,,,,,,,,,,,,,,, +70,TextBlob,True,sloria/TextBlob,,nlp,https://github.com/sloria/TextBlob,https://github.com/sloria/TextBlob,MIT,2013-06-30 18:29:18.000000,2021-12-09 03:19:59.000000,2021-10-22 03:17:05.000000,1013.0,87.0,154.0,7988,535.0,"Simple, Pythonic, text processing--Sentiment analysis, part-of-speech..",35.0,30,2013-09-26 02:29:01.000000,0.7.0,7.0,,textblob,conda-forge/textblob,,,,16169.0,16169.0,https://pypi.org/project/textblob,821479.0,823757.0,https://anaconda.org/conda-forge/textblob,2019-02-24 23:32:55.233000,145852.0,,,,,2.0,97.0,,,,,,,,,,,,,,, +71,tensorboardX,True,lanpa/tensorboardX,,ml-experiments,https://github.com/lanpa/tensorboardX,https://github.com/lanpa/tensorboardX,MIT,2017-06-13 13:54:19.000000,2021-11-21 09:07:50.000000,2021-09-12 12:57:41.000000,832.0,62.0,361.0,7183,474.0,"tensorboard for pytorch (and chainer, mxnet, numpy, ...).",67.0,30,2021-07-09 12:36:58.000000,2.4,14.0,,tensorboardX,conda-forge/tensorboardx,,,,16037.0,16037.0,https://pypi.org/project/tensorboardX,684478.0,697816.0,https://anaconda.org/conda-forge/tensorboardx,2021-08-10 02:00:22.589000,626628.0,,,,,1.0,341.0,,,,,,,,,,,,,,, +72,Pydub,True,jiaaro/pydub,,audio,https://github.com/jiaaro/pydub,https://github.com/jiaaro/pydub,MIT,2011-05-02 18:42:38.000000,2021-11-08 23:25:49.000000,2021-06-08 14:06:40.000000,767.0,197.0,253.0,5771,742.0,Manipulate audio with a simple and easy high level interface.,90.0,30,2021-03-10 02:10:41.000000,0.25.1,31.0,,pydub,conda-forge/pydub,,,,9877.0,9877.0,https://pypi.org/project/pydub,916369.0,916920.0,https://anaconda.org/conda-forge/pydub,2021-03-13 05:16:50.142000,19853.0,,,,,1.0,,,,,,,,,,,,,,,, +73,Chainer,True,chainer/chainer,,ml-frameworks,https://github.com/chainer/chainer,https://github.com/chainer/chainer,MIT,2015-06-05 05:50:37.000000,2021-06-10 09:05:27.000000,2021-06-10 08:30:31.000000,1315.0,11.0,2026.0,5652,30595.0,A flexible framework of neural networks for deep learning.,320.0,30,2021-06-10 09:05:28.000000,7.8.0,100.0,,chainer,,,,,2447.0,2447.0,https://pypi.org/project/chainer,23450.0,23450.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +74,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 22:38:21.000000,2021-12-10 03:14:33.000000,2021-12-10 03:14:33.000000,309.0,162.0,197.0,2437,862.0,Hyperparameter tuning for humans.,41.0,30,2021-11-05 17:13:27.000000,1.1.0,8.0,,keras-tuner,,,,['tensorflow'],1012.0,1012.0,https://pypi.org/project/keras-tuner,974288.0,974288.0,,,,,,,,1.0,,,,,6.0,,,,,,,,,,, +75,xarray,True,pydata/xarray,,data-containers,https://github.com/pydata/xarray,https://github.com/pydata/xarray,Apache-2.0,2013-09-30 17:21:10.000000,2021-12-15 22:06:56.000000,2021-12-13 09:47:02.000000,740.0,816.0,2189.0,2350,,N-D labeled arrays and datasets in Python.,347.0,30,2021-12-10 02:07:25.000000,0.20.2,63.0,,xarray,conda-forge/xarray,,,,8498.0,8498.0,https://pypi.org/project/xarray,1205424.0,1268668.0,https://anaconda.org/conda-forge/xarray,2021-12-10 08:48:43.752000,4363849.0,,,,,2.0,,,,,,,,,,,,,,,, +76,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 19:32:37.000000,2021-11-28 14:52:41.000000,2021-11-16 22:47:58.000000,331.0,64.0,161.0,1796,740.0,A library of sklearn compatible categorical variable encoders.,48.0,30,2021-10-13 15:40:27.000000,2.3.0-rerelease,12.0,,category_encoders,conda-forge/category_encoders,,,['sklearn'],2782.0,2782.0,https://pypi.org/project/category_encoders,984229.0,986302.0,https://anaconda.org/conda-forge/category_encoders,2021-10-13 18:33:34.503000,134772.0,,,,,1.0,,,,,5.0,,,,,,,,,,, +77,Geocoder,True,DenisCarriere/geocoder,,geospatial-data,https://github.com/DenisCarriere/geocoder,https://github.com/DenisCarriere/geocoder,MIT,2014-01-13 04:19:21.000000,2021-08-26 23:24:43.000000,2018-10-12 15:53:05.000000,260.0,72.0,217.0,1403,1251.0,Python Geocoder.,74.0,30,2016-09-05 17:57:51.000000,1.17.3,18.0,,geocoder,conda-forge/geocoder,,,,4216.0,4216.0,https://pypi.org/project/geocoder,2141030.0,2142664.0,https://anaconda.org/conda-forge/geocoder,2019-06-27 16:40:50.469000,94815.0,,,,,2.0,,,,,,,geocoder,,,,,,,,, +78,imageio,True,imageio/imageio,,image,https://github.com/imageio/imageio,https://github.com/imageio/imageio,BSD-2-Clause,2013-05-04 22:56:45.000000,2021-12-09 10:32:02.335000,2021-12-08 19:10:14.000000,190.0,69.0,332.0,960,1308.0,Python library for reading and writing image data.,83.0,30,2021-12-08 19:10:28.000000,2.13.3,18.0,,imageio,conda-forge/imageio,,,,52841.0,52841.0,https://pypi.org/project/imageio,,40971.0,https://anaconda.org/conda-forge/imageio,2021-12-09 10:32:02.335000,2417263.0,,,,,1.0,45.0,,,,,,,,,,,,,,, +79,Keras,True,keras-team/keras,,ml-frameworks,https://github.com/keras-team/keras,https://github.com/keras-team/keras,,2015-03-28 00:35:42.000000,2021-12-16 03:21:15.000000,2021-12-16 02:21:46.000000,18089.0,195.0,10776.0,53452,6283.0,Deep Learning for humans.,1008.0,29,2021-11-03 16:24:54.000000,2.7.0,32.0,,keras,conda-forge/keras,,https://keras.io,['tensorflow'],,,https://pypi.org/project/keras,7565794.0,7596585.0,https://anaconda.org/conda-forge/keras,2021-11-25 20:30:37.739000,1970658.0,,,,,2.0,,,,,,,,,,,,,,,, +80,Airflow,True,apache/airflow,,data-pipelines,https://github.com/apache/airflow,https://github.com/apache/airflow,Apache-2.0,2015-04-13 18:04:58.000000,2021-12-16 13:54:43.000000,2021-12-16 13:36:53.000000,9405.0,817.0,3801.0,24388,,"Platform to programmatically author, schedule, and monitor workflows.",2186.0,29,2021-11-15 18:37:15.000000,2.2.2,41.0,,apache-airflow,conda-forge/airflow,apache/airflow,,,,,https://pypi.org/project/apache-airflow,4310156.0,5009795.0,https://anaconda.org/conda-forge/airflow,2021-11-15 23:14:59.448000,506064.0,https://hub.docker.com/r/apache/airflow,2021-12-15 08:53:33.893106,307.0,55003637.0,1.0,219896.0,,,,,stable/airflow,,,,,,,,,, +81,zipline,True,quantopian/zipline,,financial-data,https://github.com/quantopian/zipline,https://github.com/quantopian/zipline,Apache-2.0,2012-10-19 15:50:29.000000,2021-11-01 20:36:25.000000,2020-10-14 16:36:49.000000,3881.0,313.0,651.0,14706,6226.0,"Zipline, a Pythonic Algorithmic Trading Library.",153.0,29,2020-10-05 15:43:07.000000,1.4.1,13.0,,zipline,,,,,798.0,798.0,https://pypi.org/project/zipline,4263.0,4263.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +82,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 17:04:44.000000,2021-12-16 13:54:32.000000,2021-12-16 11:22:13.000000,1674.0,65.0,1156.0,12594,6858.0,An easier way to build neural search on the cloud.,134.0,29,2021-12-12 10:10:42.000000,2.6.2,100.0,,jina,,jinaai/jina,,,188.0,188.0,https://pypi.org/project/jina,12776.0,57936.0,,,,https://hub.docker.com/r/jinaai/jina,2021-12-16 11:51:40.764849,6.0,993541.0,2.0,,,,,,,,,,,,,,,, +83,pyecharts,True,pyecharts/pyecharts,,data-viz,https://github.com/pyecharts/pyecharts,https://github.com/pyecharts/pyecharts,MIT,2017-06-22 02:50:25.000000,2021-12-13 09:21:35.000000,2021-11-16 06:25:52.000000,2550.0,26.0,1497.0,11793,1522.0,Python Echarts Plotting Library.,30.0,29,,,,,pyecharts,,,https://github.com/pyecharts/pyecharts/blob/master/README.en.md,['jupyter'],1947.0,1947.0,https://pypi.org/project/pyecharts,86917.0,86917.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +84,Plotly,True,plotly/plotly.py,,data-viz,https://github.com/plotly/plotly.py,https://github.com/plotly/plotly.py,MIT,2013-11-21 05:53:08.000000,2021-12-16 02:57:21.000000,2021-12-16 02:57:21.000000,2032.0,986.0,1152.0,10694,5323.0,The interactive graphing library for Python (includes Plotly Express).,189.0,29,2021-11-15 14:40:20.000000,5.4.0,78.0,,plotly,conda-forge/plotly,,,,9.0,9.0,https://pypi.org/project/plotly,,91727.0,https://anaconda.org/conda-forge/plotly,2021-11-15 16:33:27.242000,2124327.0,,,,,2.0,,plotlywidget,https://www.npmjs.com/package/plotlywidget,58535.0,,,,,,,,,,,, +85,ParlAI,True,facebookresearch/ParlAI,,nlp,https://github.com/facebookresearch/ParlAI,https://github.com/facebookresearch/ParlAI,MIT,2017-04-24 17:10:44.000000,2021-12-15 21:44:38.000000,2021-12-15 21:44:37.000000,1666.0,88.0,1111.0,8506,3892.0,A framework for training and evaluating AI models on a variety of..,168.0,29,2021-10-12 19:29:24.000000,1.5.1,19.0,,parlai,,,,['pytorch'],54.0,54.0,https://pypi.org/project/parlai,2292.0,2292.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +86,Prefect,True,PrefectHQ/prefect,,data-pipelines,https://github.com/PrefectHQ/prefect,https://github.com/PrefectHQ/prefect,Apache-2.0,2018-06-29 21:59:26.000000,2021-12-16 04:37:15.000000,2021-12-15 17:01:53.000000,732.0,372.0,1599.0,7933,14232.0,The easiest way to automate your data.,278.0,29,2021-12-01 00:23:48.000000,0.15.10,100.0,,prefect,conda-forge/prefect,,,,526.0,526.0,https://pypi.org/project/prefect,,6942.0,https://anaconda.org/conda-forge/prefect,2021-12-01 07:32:48.953000,229089.0,,,,,1.0,,,,,,,,,,,,,,,, +87,Catboost,True,catboost/catboost,,ml-frameworks,https://github.com/catboost/catboost,https://github.com/catboost/catboost,Apache-2.0,2017-07-18 05:29:04.000000,2021-12-16 13:59:39.000000,2021-12-16 13:59:37.000000,908.0,320.0,1357.0,6264,19943.0,"A fast, scalable, high performance Gradient Boosting on Decision..",930.0,29,2021-11-04 04:25:01.000000,1.0.3,76.0,,catboost,conda-forge/catboost,,,,,,https://pypi.org/project/catboost,3316191.0,3338070.0,https://anaconda.org/conda-forge/catboost,2021-11-09 18:53:14.338000,881835.0,,,,,2.0,69981.0,,,,,,,,,,,,,,, +88,yfinance,True,ranaroussi/yfinance,,financial-data,https://github.com/ranaroussi/yfinance,https://github.com/ranaroussi/yfinance,Apache-2.0,2017-05-21 10:16:15.000000,2021-12-15 03:43:38.000000,2021-11-21 10:41:35.000000,1390.0,380.0,322.0,6144,,Yahoo! Finance market data downloader (+faster Pandas Datareader).,49.0,29,2021-11-20 20:46:57.000000,0.1.67,4.0,,yfinance,ranaroussi/yfinance,,,,8392.0,8392.0,https://pypi.org/project/yfinance,318996.0,323044.0,https://anaconda.org/ranaroussi/yfinance,2021-07-10 20:29:09.532000,20241.0,,,,,1.0,,,,,,,,,,,,,,,, +89,Bayesian Optimization,True,fmfn/BayesianOptimization,,hyperopt,https://github.com/fmfn/BayesianOptimization,https://github.com/fmfn/BayesianOptimization,MIT,2014-06-06 08:18:56.000000,2021-11-25 04:39:23.000000,2020-12-19 01:11:23.000000,1190.0,45.0,172.0,5609,199.0,A Python implementation of global optimization with..,27.0,29,2020-05-16 16:03:51.000000,1.2.0,7.0,,bayesian-optimization,,,,,993.0,993.0,https://pypi.org/project/bayesian-optimization,190000.0,190001.0,,,,,,,,1.0,70.0,,,,,,,,,,,,,,, +90,folium,True,python-visualization/folium,,geospatial-data,https://github.com/python-visualization/folium,https://github.com/python-visualization/folium,MIT,2013-05-09 04:21:35.000000,2021-12-07 19:23:42.000000,2021-11-30 20:51:51.000000,2005.0,176.0,712.0,5544,,Python Data. Leaflet.js Maps.,124.0,29,2021-11-19 21:01:43.000000,0.12.1.post1,22.0,,folium,conda-forge/folium,,,,13313.0,13313.0,https://pypi.org/project/folium,706635.0,713601.0,https://anaconda.org/conda-forge/folium,2021-12-03 19:47:05.533000,480672.0,,,,,2.0,,,,,,,,,,,,,,,, +91,Beam,True,apache/beam,,data-pipelines,https://github.com/apache/beam,https://github.com/apache/beam,,2016-02-02 08:00:06.000000,2021-12-16 09:28:07.000000,2021-12-16 04:57:25.000000,3178.0,,,5149,33916.0,"Unified programming model to define and execute data processing pipelines, including ETL, batch and stream processing.",1185.0,29,2021-11-11 20:03:02.000000,2.34.0,16.0,,apache-beam,,,,,,,https://pypi.org/project/apache-beam,3812107.0,3812107.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +92,GluonCV,True,dmlc/gluon-cv,,image,https://github.com/dmlc/gluon-cv,https://github.com/dmlc/gluon-cv,Apache-2.0,2018-02-26 01:33:21.000000,2021-11-14 01:12:13.000000,2021-11-14 01:12:13.000000,1106.0,48.0,741.0,4999,886.0,Gluon CV Toolkit.,114.0,29,2021-03-09 00:20:06.000000,0.10.0,10.0,,gluoncv,,,,['mxnet'],636.0,636.0,https://pypi.org/project/gluoncv,542554.0,542554.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +93,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 22:07:20.000000,2021-12-16 09:58:21.000000,2021-12-15 23:56:09.000000,1849.0,135.0,2021.0,4686,,Image processing in Python.,537.0,29,2021-12-15 17:06:01.000000,0.19.1,17.0,,scikit-image,conda-forge/scikit-image,,,,88350.0,88350.0,https://pypi.org/project/scikit-image,,45738.0,https://anaconda.org/conda-forge/scikit-image,2021-12-10 00:06:53.398000,3064501.0,,,,,2.0,,,,,,,,,,,,,,,, +94,Tablib,True,jazzband/tablib,,data-loading,https://github.com/jazzband/tablib,https://github.com/jazzband/tablib,MIT,2011-03-28 02:36:50.000000,2021-11-04 13:12:37.000000,2021-11-04 13:12:37.000000,548.0,28.0,207.0,4053,1135.0,"Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c.",115.0,29,2021-10-26 12:41:48.000000,3.1.0,11.0,,tablib,conda-forge/tablib,,,,12524.0,12524.0,https://pypi.org/project/tablib,,1124.0,https://anaconda.org/conda-forge/tablib,2021-10-26 16:07:13.884000,68612.0,,,,,2.0,,,,,,,,,,,,,,,, +95,einops,True,arogozhnikov/einops,,ml-frameworks,https://github.com/arogozhnikov/einops,https://github.com/arogozhnikov/einops,MIT,2018-09-22 00:45:08.000000,2021-12-16 06:56:05.000000,2021-12-14 06:14:18.000000,156.0,29.0,58.0,4017,382.0,"Deep learning operations reinvented (for pytorch, tensorflow, jax and..",13.0,29,2021-08-31 22:49:08.000000,0.3.2,4.0,,einops,conda-forge/einops,,,,1621.0,1621.0,https://pypi.org/project/einops,1291461.0,1291803.0,https://anaconda.org/conda-forge/einops,2021-08-31 23:13:47.214000,9255.0,,,,,2.0,,,,,,,,,,,,,,,, +96,Koalas,True,databricks/koalas,,data-containers,https://github.com/databricks/koalas,https://github.com/databricks/koalas,Apache-2.0,2019-01-03 21:46:54.000000,2021-10-26 06:53:37.000000,2021-10-21 22:12:35.000000,322.0,87.0,483.0,3044,1547.0,Koalas: pandas API on Apache Spark.,51.0,29,2021-10-19 22:26:46.000000,1.8.2,47.0,,koalas,conda-forge/koalas,,,"['spark', 'pandas']",162.0,162.0,https://pypi.org/project/koalas,2327492.0,2331042.0,https://anaconda.org/conda-forge/koalas,2021-10-20 00:43:43.868000,109145.0,,,,,2.0,998.0,,,,,,,,,,,,,,, +97,missingno,True,ResidentMario/missingno,,data-viz,https://github.com/ResidentMario/missingno,https://github.com/ResidentMario/missingno,MIT,2016-03-27 15:18:50.000000,2021-07-04 16:10:24.000000,2021-07-04 16:09:34.000000,381.0,11.0,102.0,3016,180.0,Missing data visualization module for Python.,17.0,29,2021-07-04 16:11:08.000000,0.5.0,4.0,,missingno,conda-forge/missingno,,,,5715.0,5715.0,https://pypi.org/project/missingno,719551.0,722161.0,https://anaconda.org/conda-forge/missingno,2020-02-15 10:07:41.253000,138350.0,,,,,2.0,,,,,,,,,,,,,,,, +98,hmmlearn,True,hmmlearn/hmmlearn,,probabilistics,https://github.com/hmmlearn/hmmlearn,https://github.com/hmmlearn/hmmlearn,BSD-3-Clause,2014-03-23 10:33:09.000000,2021-12-12 12:47:48.000000,2021-12-12 12:47:36.000000,652.0,51.0,313.0,2388,389.0,"Hidden Markov Models in Python, with scikit-learn like API.",38.0,29,2021-02-03 14:33:20.000000,0.2.5,7.0,,hmmlearn,conda-forge/hmmlearn,,,['sklearn'],1147.0,1147.0,https://pypi.org/project/hmmlearn,546800.0,549672.0,https://anaconda.org/conda-forge/hmmlearn,2021-11-13 15:23:53.699000,106299.0,,,,,1.0,,,,,,,,,,,,,,,, +99,ImageHash,True,JohannesBuchner/imagehash,,image,https://github.com/JohannesBuchner/imagehash,https://github.com/JohannesBuchner/imagehash,BSD-2-Clause,2013-03-02 23:32:48.000000,2021-11-28 20:34:50.000000,2021-09-07 19:15:32.000000,281.0,11.0,92.0,2208,209.0,A Python Perceptual Image Hashing Module.,20.0,29,2021-03-25 13:49:48.000000,4.1.0,6.0,,ImageHash,conda-forge/imagehash,,,,3920.0,3920.0,https://pypi.org/project/ImageHash,1161766.0,1164434.0,https://anaconda.org/conda-forge/imagehash,2021-07-15 15:00:27.543000,162759.0,,,,,2.0,,,,,,,,,,,,,,,, +100,xlrd,True,python-excel/xlrd,,data-loading,https://github.com/python-excel/xlrd,https://github.com/python-excel/xlrd,,2012-03-07 04:50:48.000000,2021-08-21 19:45:33.000000,2021-08-21 19:45:33.000000,408.0,,,1953,503.0,Please use openpyxl where you can...,51.0,29,,,4.0,,xlrd,conda-forge/xlrd,,,,86460.0,86460.0,https://pypi.org/project/xlrd,12181252.0,12215498.0,https://anaconda.org/conda-forge/xlrd,2021-01-09 20:35:27.639000,1952060.0,,,,,2.0,,,,,,,,,,,,,,,, +101,Lifelines,True,CamDavidsonPilon/lifelines,,medical-data,https://github.com/CamDavidsonPilon/lifelines,https://github.com/CamDavidsonPilon/lifelines,MIT,2013-08-28 00:16:42.000000,2021-12-01 02:47:32.482000,2021-11-30 19:30:36.000000,439.0,215.0,619.0,1762,2154.0,Survival analysis in Python.,98.0,29,2021-11-30 20:20:04.000000,0.26.4,100.0,,lifelines,conda-forge/lifelines,,,,730.0,730.0,https://pypi.org/project/lifelines,315808.0,318485.0,https://anaconda.org/conda-forge/lifelines,2021-12-01 02:47:32.482000,176712.0,,,,,1.0,,,,,,,,,,,,,,,, +102,Rasterio,True,mapbox/rasterio,,geospatial-data,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,,2013-11-04 16:36:27.000000,2021-12-15 23:03:16.000000,2021-12-15 23:03:16.000000,439.0,138.0,1349.0,1640,3464.0,Rasterio reads and writes geospatial raster datasets.,118.0,29,2021-10-21 15:00:11.000000,1.3a2,72.0,rasterio/rasterio,rasterio,conda-forge/rasterio,,,,4105.0,4105.0,https://pypi.org/project/rasterio,724384.0,743963.0,https://anaconda.org/conda-forge/rasterio,2021-12-03 17:40:11.927000,1350356.0,,,,,2.0,742.0,,,,,,,,,,,,,,, +103,pyLDAvis,True,bmabey/pyLDAvis,,interpretability,https://github.com/bmabey/pyLDAvis,https://github.com/bmabey/pyLDAvis,BSD-3-Clause,2015-04-09 22:48:03.000000,2021-11-22 20:42:31.000000,2021-03-24 13:03:31.000000,316.0,83.0,77.0,1550,240.0,Python library for interactive topic model visualization. Port of..,32.0,29,2021-03-24 13:05:21.000000,3.3.1,5.0,,pyldavis,conda-forge/pyldavis,,,['jupyter'],2894.0,2894.0,https://pypi.org/project/pyldavis,589187.0,589946.0,https://anaconda.org/conda-forge/pyldavis,2021-03-24 15:17:07.309000,31900.0,,,,,1.0,,,,,,,,,,,,,,,, +104,ipyleaflet,True,jupyter-widgets/ipyleaflet,,geospatial-data,https://github.com/jupyter-widgets/ipyleaflet,https://github.com/jupyter-widgets/ipyleaflet,MIT,2014-05-07 16:32:10.000000,2021-12-13 09:58:05.000000,2021-12-13 09:58:05.000000,297.0,174.0,281.0,1199,978.0,A Jupyter - Leaflet.js bridge.,72.0,29,2021-12-06 12:32:04.000000,0.15.0,61.0,,ipyleaflet,conda-forge/ipyleaflet,,,['jupyter'],1323.0,1323.0,https://pypi.org/project/ipyleaflet,58931.0,117386.0,https://anaconda.org/conda-forge/ipyleaflet,2021-12-09 18:45:12.043000,780730.0,,,,,2.0,,jupyter-leaflet,https://www.npmjs.com/package/jupyter-leaflet,46803.0,,,,,,,,,,,, +105,pyproj,True,pyproj4/pyproj,,geospatial-data,https://github.com/pyproj4/pyproj,https://github.com/pyproj4/pyproj,MIT,2014-12-29 21:38:25.000000,2021-12-06 16:22:25.000000,2021-12-06 16:20:24.000000,166.0,6.0,449.0,688,,Python interface to PROJ (cartographic projections and coordinate..,44.0,29,2021-11-18 01:48:03.000000,3.3.0,39.0,,pyproj,conda-forge/pyproj,,,,12252.0,12252.0,https://pypi.org/project/pyproj,3907277.0,3945558.0,https://anaconda.org/conda-forge/pyproj,2021-11-18 03:35:21.354000,2756292.0,,,,,2.0,,,,,,,,,,,,,,,, +106,NIPYPE,True,nipy/nipype,,medical-data,https://github.com/nipy/nipype,https://github.com/nipy/nipype,Apache-2.0,2010-07-22 17:06:49.000000,2021-12-15 21:43:27.000000,2021-12-15 21:43:27.000000,440.0,342.0,896.0,604,14314.0,Workflows and interfaces for neuroimaging packages.,227.0,29,2021-10-20 17:40:54.000000,1.7.0,38.0,,nipype,conda-forge/nipype,,,,808.0,808.0,https://pypi.org/project/nipype,31736.0,38738.0,https://anaconda.org/conda-forge/nipype,2021-10-20 17:02:23.801000,455134.0,,,,,1.0,,,,,,,,,,,,,,,, +107,Fastai,True,fastai/fastai,,ml-frameworks,https://github.com/fastai/fastai,https://github.com/fastai/fastai,Apache-2.0,2017-09-09 17:43:36.000000,2021-12-07 14:34:43.000000,2021-11-29 01:25:55.000000,6987.0,82.0,1445.0,21711,1851.0,The fastai deep learning library.,178.0,28,2021-10-23 07:15:54.000000,2.5.3,32.0,,fastai,,,,['pytorch'],,,https://pypi.org/project/fastai,239558.0,239558.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +108,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 16:21:15.000000,2021-12-16 08:30:14.000000,2021-12-16 01:25:44.000000,6526.0,1736.0,7693.0,19797,11753.0,"Lightweight, Portable, Flexible Distributed/Mobile Deep Learning..",971.0,28,2021-03-03 01:00:20.000000,1.8.0,29.0,,mxnet,mxnet,,,['mxnet'],,,https://pypi.org/project/mxnet,335778.0,336283.0,https://anaconda.org/anaconda/mxnet,2020-02-29 00:58:31.007000,6842.0,,,,,2.0,24322.0,,,,,,,,,,,,,,, +109,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 19:38:30.000000,2021-12-16 13:48:53.000000,2021-12-16 09:20:54.000000,3044.0,1820.0,6820.0,18527,10731.0,"An open source framework that provides a simple, universal API for..",604.0,28,2021-12-03 19:08:29.000000,ray-1.9.0,50.0,,ray,,,,,3542.0,3542.0,https://pypi.org/project/ray,,,,,,,,,,1.0,,,,,,,,,,,,,,,, +110,luigi,True,spotify/luigi,,data-pipelines,https://github.com/spotify/luigi,https://github.com/spotify/luigi,Apache-2.0,2012-09-20 15:06:38.000000,2021-12-09 17:36:00.000000,2021-11-27 16:59:30.000000,2226.0,70.0,850.0,15223,4011.0,Luigi is a Python module that helps you build complex pipelines of batch..,568.0,28,2021-04-15 11:39:33.000000,3.0.3,51.0,,luigi,luigi,,,,1608.0,1608.0,https://pypi.org/project/luigi,,121.0,https://anaconda.org/anaconda/luigi,2021-04-17 18:49:18.708000,8524.0,,,,,2.0,,,,,,stable/luigi,,,,,,,,,, +111,dgl,True,dmlc/dgl,,graph,https://github.com/dmlc/dgl,https://github.com/dmlc/dgl,Apache-2.0,2018-04-20 14:49:09.000000,2021-12-16 06:14:11.000000,2021-12-15 05:42:26.000000,1878.0,275.0,999.0,8636,2039.0,"Python package built to ease deep learning on graph, on top of existing..",178.0,28,2021-11-08 04:09:08.000000,0.7.2,20.0,,dgl,,,,,,,https://pypi.org/project/dgl,67952.0,67952.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +112,rq,True,rq/rq,,data-pipelines,https://github.com/rq/rq,https://github.com/rq/rq,,2011-11-14 10:53:48.000000,2021-12-14 14:40:21.000000,2021-12-11 11:36:16.000000,1243.0,157.0,769.0,8057,1618.0,Simple job queues for Python.,249.0,28,2021-12-07 12:48:17.000000,1.10.1,19.0,,rq,conda-forge/rq,,,,9246.0,9246.0,https://pypi.org/project/rq,,1012.0,https://anaconda.org/conda-forge/rq,2021-06-30 09:49:43.099000,65793.0,,,,,2.0,,,,,,,,,,,,,,,, +113,tensorpack,True,tensorpack/tensorpack,,ml-frameworks,https://github.com/tensorpack/tensorpack,https://github.com/tensorpack/tensorpack,Apache-2.0,2015-12-25 23:08:44.000000,2021-11-27 04:08:51.000000,2021-11-27 04:08:51.000000,1786.0,12.0,1330.0,6134,2937.0,"A Neural Net Training Interface on TensorFlow, with focus on..",58.0,28,2019-01-18 19:18:13.000000,doc-v0.9.0.1,3.0,,tensorpack,,,,['tensorflow'],916.0,916.0,https://pypi.org/project/tensorpack,27287.0,27289.0,,,,,,,,2.0,128.0,,,,,,,,,,,,,,, +114,Hyperopt,True,hyperopt/hyperopt,,hyperopt,https://github.com/hyperopt/hyperopt,https://github.com/hyperopt/hyperopt,,2011-09-06 22:24:59.000000,2021-11-30 14:23:20.000000,2021-11-29 10:21:36.000000,808.0,356.0,231.0,5993,1194.0,Distributed Asynchronous Hyperparameter Optimization in Python.,93.0,28,,,6.0,,hyperopt,conda-forge/hyperopt,,,,5402.0,5402.0,https://pypi.org/project/hyperopt,1906683.0,1914534.0,https://anaconda.org/conda-forge/hyperopt,2020-10-14 07:57:14.292000,306206.0,,,,,1.0,,,,,,,,,,,,,,,, +115,featuretools,True,alteryx/featuretools,,hyperopt,https://github.com/alteryx/featuretools,https://github.com/alteryx/featuretools,BSD-3-Clause,2017-09-08 22:15:17.000000,2021-12-15 22:35:48.000000,2021-12-12 16:35:25.000000,747.0,148.0,554.0,5891,,An open source python library for automated feature engineering.,57.0,28,2021-12-02 23:03:19.000000,1.3.0,96.0,,featuretools,conda-forge/featuretools,,,,893.0,893.0,https://pypi.org/project/featuretools,1142504.0,1144560.0,https://anaconda.org/conda-forge/featuretools,2021-12-03 15:45:58.881000,74017.0,,,,,1.0,,,,,,,,,,,,,,,, +116,DeepPavlov,True,deepmipt/DeepPavlov,,nlp,https://github.com/deepmipt/DeepPavlov,https://github.com/deepmipt/DeepPavlov,Apache-2.0,2017-11-17 14:35:29.000000,2021-12-16 13:20:05.000000,2021-09-28 17:29:02.000000,974.0,98.0,498.0,5519,2607.0,An open source library for deep learning end-to-end dialog..,67.0,28,2021-09-28 17:33:03.000000,0.17.1,46.0,,deeppavlov,,,,['tensorflow'],237.0,237.0,https://pypi.org/project/deeppavlov,10736.0,10736.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +117,Tokenizers,True,huggingface/tokenizers,,nlp,https://github.com/huggingface/tokenizers,https://github.com/huggingface/tokenizers,Apache-2.0,2019-11-01 17:52:20.000000,2021-12-15 18:43:39.000000,2021-12-15 14:55:48.000000,407.0,148.0,385.0,5074,1494.0,Fast State-of-the-Art Tokenizers optimized for Research and..,46.0,28,2021-09-08 07:18:04.000000,python-v0.11.0,43.0,,tokenizers,conda-forge/tokenizers,,,,38.0,38.0,https://pypi.org/project/tokenizers,3795178.0,3801376.0,https://anaconda.org/conda-forge/tokenizers,2021-09-22 14:56:29.695000,105372.0,,,,,2.0,,,,,,,,,,,,,,,, +118,imutils,True,jrosebr1/imutils,,image,https://github.com/PyImageSearch/imutils,https://github.com/PyImageSearch/imutils,MIT,2015-01-11 20:05:39.000000,2021-12-09 01:25:49.387000,2021-01-15 10:46:45.000000,934.0,83.0,76.0,3917,138.0,A series of convenience functions to make basic image processing..,20.0,28,,,3.0,PyImageSearch/imutils,imutils,conda-forge/imutils,,,,21470.0,21470.0,https://pypi.org/project/imutils,471980.0,474443.0,https://anaconda.org/conda-forge/imutils,2021-12-09 01:25:49.387000,73891.0,,,,,2.0,,,,,,,,,,,,,,,, +119,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 02:38:00.000000,2021-12-16 14:13:52.000000,2021-12-14 21:28:40.000000,701.0,280.0,2119.0,3909,2481.0,dbt (data build tool) enables data analysts and engineers to transform..,189.0,28,2021-12-03 18:50:15.000000,1.0.0,96.0,dbt-labs/dbt-core,dbt,conda-forge/dbt,,,,226.0,226.0,https://pypi.org/project/dbt,,3090.0,https://anaconda.org/conda-forge/dbt,2021-12-09 22:07:39.668000,188501.0,,,,,2.0,21.0,,,,,,,dbt,,,,,,,, +120,ftfy,True,LuminosoInsight/python-ftfy,,nlp,https://github.com/rspeer/python-ftfy,https://github.com/rspeer/python-ftfy,MIT,2012-08-24 16:14:59.000000,2021-05-25 06:35:21.702000,2021-05-17 19:04:10.000000,101.0,11.0,111.0,3116,590.0,"Fixes mojibake and other glitches in Unicode text, after the fact.",18.0,28,2021-08-23 21:02:05.000000,6.0.3,10.0,rspeer/python-ftfy,ftfy,conda-forge/ftfy,,,,4459.0,4459.0,https://pypi.org/project/ftfy,965660.0,968055.0,https://anaconda.org/conda-forge/ftfy,2021-05-25 06:35:21.702000,134135.0,,,,,2.0,,,,,,,,,,,,,,,, +121,TensorFlow Datasets,True,tensorflow/datasets,,data-loading,https://github.com/tensorflow/datasets,https://github.com/tensorflow/datasets,Apache-2.0,2018-09-10 21:27:22.000000,2021-12-16 13:46:12.000000,2021-12-16 13:12:24.000000,1135.0,308.0,602.0,3094,4462.0,TFDS is a collection of datasets ready to use with..,238.0,28,2021-07-28 12:29:08.000000,4.4.0,18.0,,tensorflow-datasets,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-datasets,1929359.0,1929359.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +122,tensorflow-hub,True,tensorflow/hub,,tensorflow-utils,https://github.com/tensorflow/hub,https://github.com/tensorflow/hub,Apache-2.0,2018-03-12 07:55:42.000000,2021-12-13 10:38:32.000000,2021-12-13 10:38:29.000000,1578.0,13.0,614.0,3007,1017.0,A library for transfer learning by reusing parts of..,83.0,28,2021-04-14 13:17:26.000000,0.12.0,15.0,,tensorflow-hub,conda-forge/tensorflow-hub,,,['tensorflow'],9537.0,9537.0,https://pypi.org/project/tensorflow-hub,,1412.0,https://anaconda.org/conda-forge/tensorflow-hub,2021-04-18 18:01:14.779000,59328.0,,,,,1.0,,,,,,,,,,,,,,,, +123,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 22:55:20.000000,2021-10-17 18:07:36.000000,2021-05-08 08:05:59.000000,374.0,20.0,127.0,2524,287.0,Pandas integration with sklearn.,37.0,28,2021-05-08 08:32:08.000000,2.1.0,3.0,,sklearn-pandas,,,,"['sklearn', 'pandas']",3212.0,3212.0,https://pypi.org/project/sklearn-pandas,490284.0,490284.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +124,filterpy,True,rlabbe/filterpy,,probabilistics,https://github.com/rlabbe/filterpy,https://github.com/rlabbe/filterpy,MIT,2014-07-15 02:15:19.000000,2021-12-16 11:37:45.000000,2021-05-04 18:33:52.000000,468.0,40.0,154.0,2040,542.0,Python Kalman filtering and optimal estimation library. Implements..,36.0,28,,,5.0,,filterpy,conda-forge/filterpy,,,,1143.0,1143.0,https://pypi.org/project/filterpy,649303.0,650602.0,https://anaconda.org/conda-forge/filterpy,2020-05-05 21:13:59.073000,70155.0,,,,,1.0,,,,,,,,,,,,,,,, +125,Cartopy,True,mapbox/rasterio,,geospatial-data,https://github.com/rasterio/rasterio,https://github.com/rasterio/rasterio,,2013-11-04 16:36:27.000000,2021-12-15 23:03:16.000000,2021-12-15 23:03:16.000000,439.0,138.0,1349.0,1640,3464.0,Rasterio reads and writes geospatial raster datasets.,118.0,28,2021-10-21 15:00:11.000000,1.3a2,19.0,rasterio/rasterio,Cartopy,conda-forge/cartopy,,,,4105.0,4105.0,https://pypi.org/project/Cartopy,128488.0,155718.0,https://anaconda.org/conda-forge/cartopy,2021-11-20 12:45:41.185000,1878264.0,,,,,3.0,742.0,,,,,,,,,,,,,,, +126,dask.distributed,True,dask/distributed,,distributed-ml,https://github.com/dask/distributed,https://github.com/dask/distributed,,2015-09-13 18:42:29.000000,2021-12-16 12:09:27.000000,2021-12-14 17:08:32.000000,564.0,700.0,1652.0,1281,,A distributed task scheduler for Dask.,256.0,28,,,129.0,,distributed,conda-forge/distributed,,,,21336.0,21336.0,https://pypi.org/project/distributed,6980171.0,7068915.0,https://anaconda.org/conda-forge/distributed,2021-12-11 01:03:02.700000,5945879.0,,,,,1.0,,,,,,,,,,,,,,,, +127,PyFlink,True,apache/flink,,ml-frameworks,https://github.com/apache/flink,https://github.com/apache/flink,Apache-2.0,2014-06-07 07:00:10.000000,2021-12-16 14:03:17.000000,2021-12-16 14:01:03.000000,9778.0,,,17767,29182.0,Apache Flink Python API.,1423.0,27,,,,,apache-flink,,,,,,,https://pypi.org/project/apache-flink,8167.0,8167.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +128,MMDetection,True,open-mmlab/mmdetection,,image,https://github.com/open-mmlab/mmdetection,https://github.com/open-mmlab/mmdetection,Apache-2.0,2018-08-22 07:06:06.000000,2021-12-16 13:29:28.000000,2021-12-16 07:47:28.000000,5751.0,352.0,4527.0,17616,1860.0,OpenMMLab Detection Toolbox and Benchmark.,286.0,27,2021-12-15 08:28:12.000000,2.0.0,27.0,,,,,,['pytorch'],204.0,204.0,,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +129,tensor2tensor,True,tensorflow/tensor2tensor,,tensorflow-utils,https://github.com/tensorflow/tensor2tensor,https://github.com/tensorflow/tensor2tensor,Apache-2.0,2017-06-15 16:57:39.000000,2021-12-02 18:50:34.000000,2021-12-02 18:50:33.000000,2917.0,561.0,669.0,11859,4361.0,Library of deep learning models and datasets designed to..,235.0,27,2020-06-17 16:10:01.000000,1.15.7,75.0,,tensor2tensor,,,,['tensorflow'],1093.0,1093.0,https://pypi.org/project/tensor2tensor,,,,,,,,,,1.0,,,,,,,,,,,,,,,, +130,mlflow,True,mlflow/mlflow,,ml-experiments,https://github.com/mlflow/mlflow,https://github.com/mlflow/mlflow,Apache-2.0,2018-06-05 16:05:58.000000,2021-12-16 12:30:14.000000,2021-12-16 09:32:05.000000,2340.0,797.0,1175.0,10891,2405.0,Open source platform for the machine learning lifecycle.,345.0,27,2021-11-30 01:37:44.000000,1.22.0,47.0,,mlflow,conda-forge/mlflow,,,,,,https://pypi.org/project/mlflow,,14252.0,https://anaconda.org/conda-forge/mlflow,2021-12-08 06:29:58.220000,456078.0,,,,,1.0,,,,,,,,,,,,,,,, +131,Sonnet,True,deepmind/sonnet,,ml-frameworks,https://github.com/deepmind/sonnet,https://github.com/deepmind/sonnet,Apache-2.0,2017-04-03 11:34:35.000000,2021-12-15 15:36:35.000000,2021-12-15 15:36:30.000000,1218.0,19.0,147.0,9123,,TensorFlow-based neural network library.,53.0,27,2020-03-27 10:36:19.000000,2.0.0,13.0,,dm-sonnet,conda-forge/sonnet,,,['tensorflow'],727.0,727.0,https://pypi.org/project/dm-sonnet,379647.0,380153.0,https://anaconda.org/conda-forge/sonnet,2020-11-14 18:13:23.843000,12672.0,,,,,2.0,,,,,,,,,,,,,,,, +132,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 06:43:43.000000,2021-12-16 14:18:06.000000,2021-12-16 14:18:06.000000,1340.0,203.0,3937.0,9012,12634.0,An open source embedding vector similarity search engine powered by..,177.0,27,2021-06-16 06:50:46.000000,1.1.1,100.0,,pymilvus,,milvusdb/milvus,,,,,https://pypi.org/project/pymilvus,,25202.0,,,,https://hub.docker.com/r/milvusdb/milvus,2021-11-26 07:36:40.300171,16.0,662172.0,1.0,6102.0,,,,,,,,,,,,,,, +133,glfw,True,glfw/glfw,,image,https://github.com/glfw/glfw,https://github.com/glfw/glfw,Zlib,2013-04-18 15:24:53.000000,2021-12-14 17:40:16.000000,2021-12-14 17:35:30.000000,2971.0,410.0,1065.0,8406,4368.0,"A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input.",177.0,27,2021-12-09 22:27:23.000000,3.3.6,17.0,,glfw,conda-forge/glfw,,,,1.0,1.0,https://pypi.org/project/glfw,80160.0,112943.0,https://anaconda.org/conda-forge/glfw,2021-12-10 00:25:15.337000,41963.0,,,,,2.0,2555490.0,,,,,,,,,,,,,,, +134,TPOT,True,EpistasisLab/tpot,,hyperopt,https://github.com/EpistasisLab/tpot,https://github.com/EpistasisLab/tpot,LGPL-3.0,2015-11-03 21:08:40.000000,2021-07-01 15:13:10.000000,2021-01-06 15:17:46.000000,1415.0,231.0,602.0,8376,2368.0,A Python Automated Machine Learning tool that optimizes machine..,108.0,27,2021-01-06 15:19:33.000000,0.11.7,27.0,,tpot,conda-forge/tpot,,,['sklearn'],1229.0,1229.0,https://pypi.org/project/tpot,,2196.0,https://anaconda.org/conda-forge/tpot,2021-03-05 04:04:38.005000,138361.0,,,,,2.0,,,,,,,,,,,,,,,, +135,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 19:36:58.000000,2021-12-15 23:15:29.000000,2021-12-15 17:08:43.000000,1675.0,143.0,973.0,7814,9543.0,Vowpal Wabbit is a machine learning system which pushes the..,310.0,27,2021-07-14 17:10:52.000000,8.11.0,18.0,,vowpalwabbit,,,,,,,https://pypi.org/project/vowpalwabbit,54025.0,54025.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +136,Kornia,True,kornia/kornia,,image,https://github.com/kornia/kornia,https://github.com/kornia/kornia,,2018-08-22 10:31:37.000000,2021-12-16 14:04:55.000000,2021-12-12 10:05:13.000000,539.0,109.0,384.0,5597,1926.0,Open Source Differentiable Computer Vision Library for PyTorch.,144.0,27,2021-12-03 21:27:30.000000,0.6.2,25.0,,kornia,,,,['pytorch'],834.0,834.0,https://pypi.org/project/kornia,180360.0,180364.0,,,,,,,,2.0,165.0,,,,,,,,,,,,,,, +137,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 05:52:45.000000,2021-12-06 16:48:47.000000,2021-12-04 04:01:32.000000,782.0,19.0,942.0,4951,2669.0,A system for quickly generating training data with weak supervision.,74.0,27,2021-11-19 18:13:31.000000,0.9.8,14.0,,snorkel,conda-forge/snorkel,,,,135.0,135.0,https://pypi.org/project/snorkel,58051.0,58884.0,https://anaconda.org/conda-forge/snorkel,2021-11-23 19:36:48.917000,23726.0,,,,,2.0,901.0,,,,,,,,,,,,,,, +138,csvkit,True,wireservice/csvkit,,data-loading,https://github.com/wireservice/csvkit,https://github.com/wireservice/csvkit,MIT,2011-04-01 03:00:30.000000,2021-10-08 18:06:14.000000,2021-10-08 18:06:12.000000,541.0,63.0,771.0,4805,1767.0,"A suite of utilities for converting to and working with CSV, the king of..",100.0,27,,,6.0,,csvkit,conda-forge/csvkit,,,,966.0,966.0,https://pypi.org/project/csvkit,53774.0,54785.0,https://anaconda.org/conda-forge/csvkit,2021-07-13 23:18:29.990000,57627.0,,,,,2.0,,,,,,,,,,,,,,,, +139,DEAP,True,deap/deap,,distributed-ml,https://github.com/DEAP/deap,https://github.com/DEAP/deap,LGPL-3.0,2014-05-21 20:07:39.000000,2021-11-21 13:38:50.000000,2021-11-21 13:38:49.000000,923.0,182.0,245.0,4519,2179.0,Distributed Evolutionary Algorithms in Python.,76.0,27,,,4.0,,deap,conda-forge/deap,,,,2291.0,2291.0,https://pypi.org/project/deap,193036.0,195414.0,https://anaconda.org/conda-forge/deap,2021-11-07 17:27:38.136000,156977.0,,,,,2.0,,,,,,,,,,,,,,,, +140,InterpretML,True,interpretml/interpret,,interpretability,https://github.com/interpretml/interpret,https://github.com/interpretml/interpret,MIT,2019-05-03 05:47:52.000000,2021-12-11 02:48:25.000000,2021-12-11 02:47:34.000000,536.0,84.0,179.0,4350,1791.0,Fit interpretable models. Explain blackbox machine learning.,28.0,27,2021-09-23 20:41:03.000000,0.2.7,31.0,,interpret,,,,['jupyter'],138.0,138.0,https://pypi.org/project/interpret,53858.0,53858.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +141,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 00:13:54.000000,2021-11-30 10:48:50.965000,2021-11-28 00:07:58.000000,290.0,47.0,368.0,4241,973.0,A scikit-learn compatible neural network library that wraps..,47.0,27,2021-10-31 15:54:20.000000,0.11.0,10.0,,skorch,conda-forge/skorch,,,"['pytorch', 'sklearn']",418.0,418.0,https://pypi.org/project/skorch,18756.0,31426.0,https://anaconda.org/conda-forge/skorch,2021-11-30 10:48:50.965000,494147.0,,,,,2.0,,,,,,,,,,,,,,,, +142,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 17:20:35.000000,2021-12-15 23:47:36.000000,2021-12-08 02:55:41.000000,482.0,40.0,270.0,3924,803.0,"The easiest way to use deep metric learning in your application. Modular,..",21.0,27,2021-11-28 20:20:55.000000,1.0.0,38.0,,pytorch-metric-learning,metric-learning/pytorch-metric-learning,,,['pytorch'],175.0,175.0,https://pypi.org/project/pytorch-metric-learning,151188.0,151410.0,https://anaconda.org/metric-learning/pytorch-metric-learning,2021-11-28 19:31:02.821000,5122.0,,,,,1.0,,,,,,,,,,,,,,,, +143,MLxtend,True,rasbt/mlxtend,,sklearn-utils,https://github.com/rasbt/mlxtend,https://github.com/rasbt/mlxtend,,2014-08-14 01:56:16.000000,2021-11-29 20:19:30.000000,2021-11-29 20:19:30.000000,720.0,90.0,297.0,3729,1249.0,A library of extension and helper modules for Python's data..,85.0,27,2021-09-02 23:54:04.000000,0.19.0,24.0,,mlxtend,conda-forge/mlxtend,,,['sklearn'],4778.0,4778.0,https://pypi.org/project/mlxtend,,3598.0,https://anaconda.org/conda-forge/mlxtend,2021-09-03 13:27:33.719000,190708.0,,,,,2.0,,,,,,,,,,,,,,,, +144,DeepChem,True,deepchem/deepchem,,others,https://github.com/deepchem/deepchem,https://github.com/deepchem/deepchem,MIT,2015-09-24 23:20:28.000000,2021-12-15 16:49:58.000000,2021-12-15 16:36:07.000000,1171.0,371.0,984.0,3319,7340.0,"Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,..",175.0,27,2021-03-18 03:08:50.000000,2.5.0,14.0,,deepchem,,,,['tensorflow'],65.0,65.0,https://pypi.org/project/deepchem,4045.0,4045.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +145,dyNET,True,clab/dynet,,ml-frameworks,https://github.com/clab/dynet,https://github.com/clab/dynet,Apache-2.0,2015-02-08 23:09:21.000000,2021-09-07 23:47:31.000000,2021-01-27 15:43:03.000000,669.0,256.0,659.0,3267,3267.0,DyNet: The Dynamic Neural Network Toolkit.,156.0,27,2020-10-21 13:39:07.000000,2.1.2,9.0,,dyNET,,,,,199.0,199.0,https://pypi.org/project/dyNET,20324.0,20393.0,,,,,,,,2.0,4282.0,,,,,,,,,,,,,,, +146,plotnine,True,has2k1/plotnine,,data-viz,https://github.com/has2k1/plotnine,https://github.com/has2k1/plotnine,GPL-2.0,2017-04-24 19:00:44.000000,2021-12-14 20:38:27.000000,2021-12-14 20:02:29.000000,147.0,76.0,379.0,2875,1711.0,A grammar of graphics for Python.,89.0,27,2021-03-25 12:57:10.000000,0.8.0,10.0,,plotnine,conda-forge/plotnine,,,,2751.0,2751.0,https://pypi.org/project/plotnine,186321.0,188900.0,https://anaconda.org/conda-forge/plotnine,2021-03-25 12:31:04.423000,141856.0,,,,,2.0,,,,,,,,,,,,,,,, +147,Captum,True,pytorch/captum,,interpretability,https://github.com/pytorch/captum,https://github.com/pytorch/captum,BSD-3-Clause,2019-08-27 15:34:41.000000,2021-12-16 00:18:48.000000,2021-12-14 23:33:54.000000,290.0,65.0,236.0,2825,883.0,Model interpretability and understanding for PyTorch.,77.0,27,2021-11-02 21:47:58.000000,0.4.1,6.0,,captum,,,,['pytorch'],343.0,343.0,https://pypi.org/project/captum,36615.0,36615.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +148,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 07:56:13.000000,2021-12-16 13:26:40.000000,2021-12-16 06:39:27.000000,346.0,6.0,319.0,2802,1668.0,Accelerated deep learning R&D.,101.0,27,2021-11-30 07:36:48.000000,21.11,36.0,,catalyst,,,,['pytorch'],447.0,447.0,https://pypi.org/project/catalyst,10946.0,10946.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +149,datashader,True,holoviz/datashader,,data-viz,https://github.com/holoviz/datashader,https://github.com/holoviz/datashader,,2015-12-23 18:02:20.000000,2021-12-15 14:06:25.000000,2021-11-29 09:59:14.000000,328.0,127.0,353.0,2667,1298.0,Quickly and accurately render even the largest data.,45.0,27,2021-06-09 23:30:20.000000,0.13.0,24.0,,datashader,conda-forge/datashader,,,,905.0,905.0,https://pypi.org/project/datashader,62560.0,67644.0,https://anaconda.org/conda-forge/datashader,2021-06-10 09:04:19.929000,249151.0,,,,,2.0,,,,,,,,,,,,,,,, +150,gpustat,True,wookayin/gpustat,,gpu-utilities,https://github.com/wookayin/gpustat,https://github.com/wookayin/gpustat,MIT,2016-04-24 10:46:43.000000,2021-11-07 22:16:42.000000,2021-08-13 10:24:05.000000,207.0,19.0,56.0,2659,170.0,A simple command-line utility for querying and monitoring GPU status.,12.0,27,2019-07-22 06:37:00.000000,0.6.0,7.0,,gpustat,conda-forge/gpustat,,,,1478.0,1478.0,https://pypi.org/project/gpustat,404123.0,407284.0,https://anaconda.org/conda-forge/gpustat,2020-11-24 19:59:04.772000,104338.0,,,,,1.0,,,,,,,,,,,,,,,, +151,mrjob,True,Yelp/mrjob,,data-pipelines,https://github.com/Yelp/mrjob,https://github.com/Yelp/mrjob,Apache-2.0,2010-10-13 18:35:21.000000,2021-11-08 11:23:32.000000,2020-11-16 22:20:52.000000,571.0,202.0,1093.0,2574,8622.0,Run MapReduce jobs on Hadoop or Amazon Web Services.,142.0,27,,,13.0,,mrjob,conda-forge/mrjob,,,,896.0,896.0,https://pypi.org/project/mrjob,,6662.0,https://anaconda.org/conda-forge/mrjob,2020-12-24 22:44:29.424000,419725.0,,,,,2.0,,,,,,,,,,,,,,,, +152,Flax,True,google/flax,,ml-frameworks,https://github.com/google/flax,https://github.com/google/flax,Apache-2.0,2020-01-10 09:48:37.000000,2021-12-16 13:41:34.000000,2021-12-13 15:36:15.000000,269.0,133.0,275.0,2439,,Flax is a neural network library for JAX that is designed for..,123.0,27,2021-10-27 21:00:28.000000,0.3.6,10.0,,flax,,,,['jax'],561.0,561.0,https://pypi.org/project/flax,1255346.0,1255347.0,,,,,,,,2.0,31.0,,,,7.0,,,,,,,,,,, +153,Cufflinks,True,santosjorge/cufflinks,,data-viz,https://github.com/santosjorge/cufflinks,https://github.com/santosjorge/cufflinks,MIT,2014-11-19 20:59:33.000000,2021-11-25 17:30:29.000000,2021-02-25 05:05:09.000000,558.0,81.0,123.0,2413,452.0,Productivity Tools for Plotly + Pandas.,38.0,27,,,,,cufflinks,,,,['pandas'],4845.0,4845.0,https://pypi.org/project/cufflinks,277898.0,277898.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +154,GluonNLP,True,dmlc/gluon-nlp,,nlp,https://github.com/dmlc/gluon-nlp,https://github.com/dmlc/gluon-nlp,Apache-2.0,2018-04-04 20:57:13.000000,2021-12-02 15:56:37.000000,2021-08-24 19:11:38.000000,487.0,232.0,295.0,2346,840.0,"Toolkit that enables easy text preprocessing, datasets loading and neural models building to help you speed up your..",82.0,27,2020-08-13 19:16:27.000000,0.10.0,15.0,,gluonnlp,,,,['mxnet'],677.0,677.0,https://pypi.org/project/gluonnlp,156871.0,156871.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +155,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 13:32:37.000000,2021-11-26 23:18:05.000000,2021-11-24 18:26:20.000000,358.0,250.0,151.0,2031,923.0,A high performance implementation of HDBSCAN clustering.,74.0,27,2020-03-19 19:12:55.000000,0.8.26,37.0,,hdbscan,conda-forge/hdbscan,,,['sklearn'],1119.0,1119.0,https://pypi.org/project/hdbscan,,15196.0,https://anaconda.org/conda-forge/hdbscan,2021-02-14 03:07:15.749000,987770.0,,,,,1.0,,,,,,,,,,,,,,,, +156,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 03:31:13.000000,2021-12-16 14:08:47.000000,2021-12-16 14:01:00.000000,937.0,325.0,3535.0,1763,,MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python.,277.0,27,2021-12-01 22:25:51.000000,0.24.1,36.0,,mne,conda-forge/mne,,,,1298.0,1298.0,https://pypi.org/project/mne,36842.0,39914.0,https://anaconda.org/conda-forge/mne,2021-12-02 00:46:15.614000,178229.0,,,,,2.0,,,,,,,,,,,,,,,, +157,TF Addons,True,tensorflow/addons,,tensorflow-utils,https://github.com/tensorflow/addons,https://github.com/tensorflow/addons,Apache-2.0,2018-11-26 23:57:17.000000,2021-12-15 06:31:51.000000,2021-12-15 06:31:51.000000,482.0,170.0,691.0,1422,1423.0,Useful extra functionality for TensorFlow 2.x maintained by..,182.0,27,2021-11-10 21:09:55.000000,0.15.0,28.0,,tensorflow-addons,,,,['tensorflow'],4895.0,4895.0,https://pypi.org/project/tensorflow-addons,,,,,,,,,,1.0,,,,,-7.0,,,,,,,,,,, +158,Mesh,True,tensorflow/mesh,,distributed-ml,https://github.com/tensorflow/mesh,https://github.com/tensorflow/mesh,Apache-2.0,2018-09-20 20:23:34.000000,2021-11-09 23:55:29.000000,2021-10-18 19:57:56.000000,195.0,61.0,14.0,1166,643.0,Mesh TensorFlow: Model Parallelism Made Easier.,44.0,27,2018-12-11 00:09:43.000000,0.0.5,4.0,,mesh-tensorflow,,,,['tensorflow'],613.0,613.0,https://pypi.org/project/mesh-tensorflow,401326.0,401326.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +159,Wand,True,emcconville/wand,,image,https://github.com/emcconville/wand,https://github.com/emcconville/wand,MIT,2011-09-30 21:36:38.000000,2021-11-20 16:28:51.000000,2021-11-20 16:28:47.000000,189.0,13.0,347.0,1132,1741.0,The ctypes-based simple ImageMagick binding for Python.,97.0,27,2021-08-17 02:43:04.000000,0.6.7,19.0,,wand,,,,,7882.0,7882.0,https://pypi.org/project/wand,,142.0,,,,,,,,2.0,5271.0,,,,,,,,,,,,,,, +160,PyVista,True,pyvista/pyvista,,data-viz,https://github.com/pyvista/pyvista,https://github.com/pyvista/pyvista,MIT,2017-05-31 18:01:42.000000,2021-12-15 04:04:34.000000,2021-12-15 04:04:34.000000,198.0,175.0,468.0,1049,2250.0,3D plotting and mesh analysis through a streamlined interface for the..,64.0,27,2021-09-10 03:06:55.000000,0.32.0,37.0,,pyvista,conda-forge/pyvista,,,['jupyter'],542.0,542.0,https://pypi.org/project/pyvista,36159.0,40489.0,https://anaconda.org/conda-forge/pyvista,2021-09-12 01:56:26.368000,134024.0,,,,,2.0,383.0,,,,,,,,,,,,,,, +161,petl,True,petl-developers/petl,,data-pipelines,https://github.com/petl-developers/petl,https://github.com/petl-developers/petl,MIT,2011-08-19 09:51:03.000000,2021-12-16 03:45:53.000000,2021-12-16 03:45:43.000000,165.0,73.0,351.0,952,1155.0,Python Extract Transform and Load Tables of Data.,51.0,27,2021-10-15 03:48:10.000000,1.7.5,37.0,,petl,conda-forge/petl,,http://petl.readthedocs.org,,581.0,581.0,https://pypi.org/project/petl,46463.0,47314.0,https://anaconda.org/conda-forge/petl,2021-04-05 21:49:41.242000,53667.0,,,,,2.0,,,,,,,,,,,,,,,, +162,igraph,True,igraph/python-igraph,,graph,https://github.com/igraph/python-igraph,https://github.com/igraph/python-igraph,GPL-2.0,2015-01-08 23:55:16.000000,2021-12-16 07:45:08.000000,2021-12-13 12:11:37.000000,206.0,32.0,324.0,902,1839.0,Python interface for igraph.,56.0,27,2021-10-29 01:08:18.000000,0.9.8,13.0,,python-igraph,conda-forge/igraph,,,,385.0,385.0,https://pypi.org/project/python-igraph,217954.0,227345.0,https://anaconda.org/conda-forge/igraph,2021-11-12 06:30:55.873000,263080.0,,,,,1.0,295995.0,,,,,,,,,,,,,,, +163,Fiona,True,Toblerity/Fiona,,geospatial-data,https://github.com/Toblerity/Fiona,https://github.com/Toblerity/Fiona,,2011-12-31 19:47:00.000000,2021-12-09 00:51:57.000000,2021-12-09 00:51:57.000000,169.0,72.0,572.0,871,1273.0,Fiona reads and writes geographic data files.,65.0,27,2020-02-22 01:07:12.000000,1.8.13.post1,39.0,,fiona,conda-forge/fiona,,,,7336.0,7336.0,https://pypi.org/project/fiona,2309966.0,2344975.0,https://anaconda.org/conda-forge/fiona,2021-12-01 17:00:06.524000,2415658.0,,,,,3.0,,,,,,,,,,,,,,,, +164,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 14:49:40.000000,2021-12-16 01:37:55.000000,2021-12-14 10:48:48.000000,130.0,166.0,275.0,825,1517.0,"An implementation of chunked, compressed, N-dimensional arrays for Python.",52.0,27,2021-11-19 08:11:03.000000,2.10.3,36.0,,zarr,conda-forge/zarr,,,,968.0,968.0,https://pypi.org/project/zarr,,17513.0,https://anaconda.org/conda-forge/zarr,2021-11-19 10:43:50.744000,1173427.0,,,,,2.0,,,,,,,,,,,,,,,, +165,Bottleneck,True,pydata/bottleneck,,data-containers,https://github.com/pydata/bottleneck,https://github.com/pydata/bottleneck,BSD-2-Clause,2010-11-27 23:21:22.000000,2021-11-04 11:55:30.352000,2021-01-24 18:39:03.000000,74.0,37.0,179.0,680,1241.0,Fast NumPy array functions written in C.,21.0,27,,,8.0,,Bottleneck,conda-forge/bottleneck,,,,28879.0,28879.0,https://pypi.org/project/Bottleneck,,26810.0,https://anaconda.org/conda-forge/bottleneck,2021-11-04 11:55:30.352000,1796315.0,,,,,2.0,,,,,,,,,,,,,,,, +166,geojson,True,jazzband/geojson,,geospatial-data,https://github.com/jazzband/geojson,https://github.com/jazzband/geojson,BSD-3-Clause,2011-07-01 20:39:48.000000,2021-11-11 11:08:46.000000,2021-11-11 10:02:01.000000,85.0,19.0,58.0,675,455.0,Python bindings and utilities for GeoJSON.,45.0,27,,,9.0,,geojson,conda-forge/geojson,,,,8199.0,8199.0,https://pypi.org/project/geojson,685713.0,692439.0,https://anaconda.org/conda-forge/geojson,2019-08-11 12:10:34.426000,464150.0,,,,,3.0,,,,,,,,,,,,,,,, +167,hvPlot,True,holoviz/hvplot,,data-viz,https://github.com/holoviz/hvplot,https://github.com/holoviz/hvplot,BSD-3-Clause,2018-03-19 14:22:41.000000,2021-12-16 12:19:48.000000,2021-12-16 11:17:47.000000,62.0,139.0,262.0,489,430.0,"A high-level plotting API for pandas, dask, xarray, and networkx built on..",33.0,27,2021-07-26 16:25:50.000000,0.7.3,11.0,,hvplot,conda-forge/hvplot,,,,943.0,943.0,https://pypi.org/project/hvplot,79747.0,83223.0,https://anaconda.org/conda-forge/hvplot,2021-07-23 14:04:28.244000,139041.0,,,,,2.0,,,,,,,,,,,,,,,, +168,NiBabel,True,nipy/nibabel,,medical-data,https://github.com/nipy/nibabel,https://github.com/nipy/nibabel,,2010-07-22 16:28:30.000000,2021-11-19 13:45:46.000000,2021-09-30 22:21:56.000000,218.0,105.0,309.0,454,5065.0,Python package to access a cacophony of neuro-imaging file formats.,93.0,27,2020-11-28 22:19:50.000000,3.2.1,32.0,,nibabel,conda-forge/nibabel,,,,5915.0,5915.0,https://pypi.org/project/nibabel,154574.0,160574.0,https://anaconda.org/conda-forge/nibabel,2020-11-29 03:40:05.178000,402049.0,,,,,2.0,,,,,,,,,,,,,,,, +169,audioread,True,beetbox/audioread,,audio,https://github.com/beetbox/audioread,https://github.com/beetbox/audioread,MIT,2011-11-08 19:53:18.000000,2021-12-03 18:19:53.000000,2021-12-03 18:19:53.000000,89.0,29.0,46.0,381,251.0,cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding..,21.0,27,,,5.0,,audioread,conda-forge/audioread,,,,6871.0,6871.0,https://pypi.org/project/audioread,538386.0,544058.0,https://anaconda.org/conda-forge/audioread,2021-11-07 14:43:40.465000,368729.0,,,,,1.0,,,,,,,,,,,,,,,, +170,Cython BLIS,True,explosion/cython-blis,,others,https://github.com/explosion/cython-blis,https://github.com/explosion/cython-blis,,2017-10-15 09:56:16.000000,2021-12-13 14:15:12.000000,2021-11-17 12:08:58.000000,29.0,5.0,22.0,182,532.0,Fast matrix-multiplication as a self-contained Python library no..,10.0,27,2021-10-27 09:16:31.000000,0.7.5,8.0,,blis,conda-forge/cython-blis,,,,14659.0,14659.0,https://pypi.org/project/blis,5488438.0,5523640.0,https://anaconda.org/conda-forge/cython-blis,2021-11-04 20:09:22.632000,1161672.0,,,,,1.0,,,,,,,,,,,,,,,, +171,detectron2,True,facebookresearch/detectron2,,image,https://github.com/facebookresearch/detectron2,https://github.com/facebookresearch/detectron2,Apache-2.0,2019-09-05 21:30:20.000000,2021-12-14 19:09:47.000000,2021-12-08 22:08:51.000000,4907.0,122.0,2647.0,19222,,Detectron2 is FAIR's next-generation platform for object..,195.0,26,2021-11-15 22:08:26.000000,0.6,10.0,,,conda-forge/detectron2,,,['pytorch'],439.0,439.0,,,1883.0,https://anaconda.org/conda-forge/detectron2,2021-07-30 18:54:13.472000,35786.0,,,,,2.0,,,,,,,,,,,,,,,, +172,PaddleOCR,True,PaddlePaddle/PaddleOCR,,ocr,https://github.com/PaddlePaddle/PaddleOCR,https://github.com/PaddlePaddle/PaddleOCR,Apache-2.0,2020-05-08 10:38:16.000000,2021-12-16 13:04:52.000000,2021-12-10 11:08:18.000000,3616.0,910.0,2619.0,18043,,Awesome multilingual OCR toolkits based on PaddlePaddle..,58.0,26,2021-05-26 11:43:06.000000,2.1.1,4.0,,paddleocr,,,,['paddle'],450.0,450.0,https://pypi.org/project/paddleocr,37971.0,37971.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +173,Magenta,True,magenta/magenta,,audio,https://github.com/magenta/magenta,https://github.com/magenta/magenta,Apache-2.0,2016-05-05 20:10:40.000000,2021-10-18 02:01:53.000000,2021-06-30 21:44:13.000000,3462.0,292.0,569.0,17261,,Magenta: Music and Art Generation with Machine Intelligence.,149.0,26,2020-09-08 13:05:49.000000,2.1.2,47.0,,magenta,,,,['tensorflow'],328.0,328.0,https://pypi.org/project/magenta,7511.0,7511.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +174,Faiss,True,facebookresearch/faiss,,nn-search,https://github.com/facebookresearch/faiss,https://github.com/facebookresearch/faiss,MIT,2017-02-07 16:07:05.000000,2021-12-15 18:46:25.000000,2021-12-11 11:28:29.000000,2378.0,215.0,1447.0,15623,,A library for efficient similarity search and clustering of dense vectors.,90.0,26,2021-05-28 09:08:34.000000,1.7.1,12.0,,pymilvus,conda-forge/faiss,,,,523.0,523.0,https://pypi.org/project/pymilvus,,11882.0,https://anaconda.org/conda-forge/faiss,2021-11-20 08:01:48.432000,225764.0,,,,,1.0,,,,,,,,,,,,,,,, +175,InsightFace,True,deepinsight/insightface,,image,https://github.com/deepinsight/insightface,https://github.com/deepinsight/insightface,MIT,2017-09-01 00:36:51.000000,2021-12-03 17:00:53.000000,2021-12-03 17:00:53.000000,3502.0,950.0,812.0,10876,1912.0,Face Analysis Project on MXNet and PyTorch.,31.0,26,,,,,insightface,,,,['mxnet'],120.0,120.0,https://pypi.org/project/insightface,22554.0,22554.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +176,TFlearn,True,tflearn/tflearn,,ml-frameworks,https://github.com/tflearn/tflearn,https://github.com/tflearn/tflearn,,2016-03-31 12:05:53.000000,2021-01-25 09:41:59.000000,2020-11-30 04:34:51.000000,2334.0,547.0,362.0,9571,613.0,Deep learning library featuring a higher-level API for TensorFlow.,128.0,26,2020-11-11 19:26:11.000000,0.5.0,8.0,,tflearn,,,,['tensorflow'],3657.0,3657.0,https://pypi.org/project/tflearn,13338.0,13338.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +177,wordcloud,True,amueller/word_cloud,,data-viz,https://github.com/amueller/word_cloud,https://github.com/amueller/word_cloud,MIT,2012-11-04 22:57:59.000000,2021-11-19 09:10:54.000000,2021-11-13 00:48:18.000000,2112.0,93.0,360.0,8491,549.0,A little word cloud generator in Python.,64.0,26,2018-07-26 17:23:44.000000,1.5.0,9.0,,wordcloud,conda-forge/wordcloud,,,,,,https://pypi.org/project/wordcloud,675470.0,679390.0,https://anaconda.org/conda-forge/wordcloud,2021-11-15 20:34:05.364000,250937.0,,,,,2.0,,,,,,,,,,,,,,,, +178,AutoKeras,True,keras-team/autokeras,,hyperopt,https://github.com/keras-team/autokeras,https://github.com/keras-team/autokeras,Apache-2.0,2017-11-19 23:18:20.000000,2021-12-04 04:40:36.000000,2021-12-04 04:40:18.000000,1304.0,61.0,727.0,8265,1274.0,AutoML library for deep learning.,130.0,26,2021-11-02 00:16:03.000000,1.0.16.post1,53.0,,autokeras,,,,['tensorflow'],259.0,259.0,https://pypi.org/project/autokeras,,34.0,,,,,,,,2.0,1708.0,,,,,,,,,,,,,,, +179,PySyft,True,OpenMined/PySyft,,privacy-ml,https://github.com/OpenMined/PySyft,https://github.com/OpenMined/PySyft,Apache-2.0,2017-07-18 20:41:16.000000,2021-12-10 05:00:26.000000,2021-12-10 05:00:25.000000,1719.0,287.0,2754.0,7805,9339.0,A library for answering questions using data you cannot see.,426.0,26,2021-12-01 19:45:11.000000,0.6.0,22.0,,syft,,,,['pytorch'],,,https://pypi.org/project/syft,4747.0,4747.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +180,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 14:03:03.000000,2021-11-29 10:48:23.000000,2021-05-06 12:01:05.000000,820.0,76.0,76.0,6744,264.0,Visualizations for machine learning datasets.,28.0,26,2019-07-01 16:35:20.000000,1.0.0,4.0,,facets-overview,,,,['jupyter'],92.0,92.0,https://pypi.org/project/facets-overview,153277.0,153277.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +181,imageai,True,OlafenwaMoses/ImageAI,,image,https://github.com/OlafenwaMoses/ImageAI,https://github.com/OlafenwaMoses/ImageAI,MIT,2018-03-19 23:12:33.000000,2021-12-04 10:57:04.000000,2021-05-08 20:05:36.000000,1841.0,233.0,424.0,6728,292.0,A python library built to empower developers to build applications and..,15.0,26,2021-01-04 19:24:41.000000,essentials-v5,10.0,,imageai,,,,,1004.0,1004.0,https://pypi.org/project/imageai,,15469.0,,,,,,,,2.0,680676.0,,,,,,,,,,,,,,, +182,faust,True,robinhood/faust,,data-pipelines,https://github.com/robinhood/faust,https://github.com/robinhood/faust,,2017-03-08 18:36:11.000000,2021-10-26 06:31:36.000000,2020-10-09 12:59:42.000000,491.0,219.0,236.0,5897,4137.0,Python Stream Processing.,93.0,26,2018-05-24 05:44:13.000000,1.0.10d3,3.0,,faust,,,,,895.0,895.0,https://pypi.org/project/faust,423234.0,423234.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +183,Metaflow,True,Netflix/metaflow,,ml-experiments,https://github.com/Netflix/metaflow,https://github.com/Netflix/metaflow,Apache-2.0,2019-09-17 17:48:25.000000,2021-12-16 09:49:13.000000,2021-12-16 06:20:31.000000,425.0,159.0,189.0,5105,397.0,Build and manage real-life data science projects with ease.,42.0,26,2021-12-09 06:46:37.000000,2.4.5,35.0,,metaflow,conda-forge/metaflow,,,,232.0,232.0,https://pypi.org/project/metaflow,,1218.0,https://anaconda.org/conda-forge/metaflow,2021-12-09 09:01:48.220000,29252.0,,,,,2.0,,,,,,,,,,,,,,,, +184,Kedro,True,quantumblacklabs/kedro,,data-pipelines,https://github.com/quantumblacklabs/kedro,https://github.com/quantumblacklabs/kedro,Apache-2.0,2019-04-18 10:29:56.000000,2021-12-16 13:04:52.000000,2021-12-16 09:55:02.000000,532.0,47.0,542.0,4760,,"A Python framework for creating reproducible, maintainable and modular..",134.0,26,2021-12-09 15:59:58.000000,0.17.6,28.0,,kedro,,,,,637.0,637.0,https://pypi.org/project/kedro,231567.0,231567.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +185,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 15:08:24.000000,2021-12-16 14:17:18.000000,2021-12-13 16:32:32.000000,700.0,246.0,535.0,4732,,A unified framework for machine learning with time series.,132.0,26,2021-12-08 17:37:25.000000,0.9.0,17.0,,sktime,,,,['sklearn'],312.0,312.0,https://pypi.org/project/sktime,143741.0,143743.0,,,,,,,,1.0,64.0,,,,,,,,,,,,,,, +186,PDFMiner,True,euske/pdfminer,,data-loading,https://github.com/euske/pdfminer,https://github.com/euske/pdfminer,MIT,2010-12-12 12:50:22.000000,2021-02-16 14:43:27.000000,2020-01-18 07:00:32.000000,962.0,190.0,40.0,4706,540.0,Python PDF Parser (Not actively maintained). Check out pdfminer.six.,28.0,26,,,2.0,,pdfminer,conda-forge/pdfminer,,,,2668.0,2668.0,https://pypi.org/project/pdfminer,149146.0,149460.0,https://anaconda.org/conda-forge/pdfminer,2021-02-15 15:07:18.804000,20159.0,,,,,2.0,,,,,,,,,,,,,,,, +187,PyCaret,True,pycaret/pycaret,,ml-experiments,https://github.com/pycaret/pycaret,https://github.com/pycaret/pycaret,MIT,2019-11-23 18:40:48.000000,2021-12-15 23:32:25.000000,2021-12-15 10:09:20.000000,1049.0,195.0,1028.0,4575,2025.0,"An open-source, low-code machine learning library in Python.",68.0,26,2021-11-19 19:06:42.000000,2.3.5,14.0,,pycaret,,,,,1587.0,1587.0,https://pypi.org/project/pycaret,,29.0,,,,,,,,2.0,498.0,,,,,,,,,,,,,,, +188,pyfolio,True,quantopian/pyfolio,,financial-data,https://github.com/quantopian/pyfolio,https://github.com/quantopian/pyfolio,Apache-2.0,2015-06-01 15:31:39.000000,2021-09-29 21:14:06.000000,2020-07-15 13:46:58.000000,1268.0,132.0,265.0,4164,1184.0,Portfolio and risk analytics in Python.,55.0,26,2019-04-15 11:38:22.000000,0.9.2,8.0,,pyfolio,conda-forge/pyfolio,,,,341.0,341.0,https://pypi.org/project/pyfolio,5618.0,5786.0,https://anaconda.org/conda-forge/pyfolio,2020-05-16 14:11:57.267000,7751.0,,,,,1.0,,,,,,,,,,,,,,,, +189,Hub,True,activeloopai/Hub,,data-pipelines,https://github.com/activeloopai/Hub,https://github.com/activeloopai/Hub,MPL-2.0,2019-08-09 06:17:59.000000,2021-12-16 14:13:56.000000,2021-12-16 11:23:43.000000,321.0,45.0,262.0,3988,2201.0,Fastest unstructured dataset management for TensorFlow/PyTorch...,88.0,26,2021-11-29 01:57:28.000000,2.1.1,29.0,,hub,,,,"['tensorflow', 'pytorch']",136.0,136.0,https://pypi.org/project/hub,2190.0,2190.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +190,AutoGluon,True,awslabs/autogluon,,hyperopt,https://github.com/awslabs/autogluon,https://github.com/awslabs/autogluon,Apache-2.0,2019-07-29 18:51:24.000000,2021-12-16 02:47:45.000000,2021-12-16 00:37:37.000000,501.0,124.0,439.0,3913,722.0,"AutoGluon: AutoML for Text, Image, and Tabular Data.",62.0,26,2021-08-31 20:47:54.000000,0.3.1,14.0,,autogluon,,,,['mxnet'],86.0,86.0,https://pypi.org/project/autogluon,19242.0,19242.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +191,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 07:59:50.000000,2021-12-16 08:34:45.000000,2021-12-16 06:51:49.000000,893.0,268.0,778.0,3811,2680.0,BigDL: Distributed Deep Learning Framework for Apache Spark.,128.0,26,2021-07-09 12:20:26.000000,0.13.0,14.0,,bigdl,,,,,31.0,31.0,https://pypi.org/project/bigdl,16115.0,16115.0,,,,,,,,2.0,,,,,,,,,com.intel.analytics.bigdl:bigdl-SPARK_2.4,https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4,,,,,, +192,Ignite,True,pytorch/ignite,,ml-frameworks,https://github.com/pytorch/ignite,https://github.com/pytorch/ignite,BSD-3-Clause,2017-11-23 17:31:21.000000,2021-12-16 10:42:27.000000,2021-12-15 13:07:53.000000,496.0,113.0,835.0,3793,1290.0,High-level library to help with training and evaluating neural..,158.0,26,2021-10-13 09:09:00.000000,0.4.7,18.0,,pytorch-ignite,pytorch/ignite,,,['pytorch'],,,https://pypi.org/project/pytorch-ignite,76157.0,77948.0,https://anaconda.org/pytorch/ignite,2021-10-19 15:47:07.847000,75231.0,,,,,3.0,,,,,,,,,,,,,,,, +193,wandb client,True,wandb/client,,ml-experiments,https://github.com/wandb/client,https://github.com/wandb/client,MIT,2017-03-24 05:46:23.000000,2021-12-16 09:54:00.000000,2021-12-16 09:36:23.000000,280.0,259.0,1181.0,3566,4341.0,A tool for visualizing and tracking your machine learning..,97.0,26,2021-11-19 17:08:43.000000,0.12.7,78.0,,wandb,,,,,,,https://pypi.org/project/wandb,541506.0,541506.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +194,Dedupe,True,dedupeio/dedupe,,nlp,https://github.com/dedupeio/dedupe,https://github.com/dedupeio/dedupe,MIT,2012-04-20 14:57:36.000000,2021-10-14 13:15:50.000000,2021-10-14 13:15:50.000000,440.0,63.0,603.0,3241,2842.0,"A python library for accurate and scalable fuzzy matching, record..",61.0,26,,,,,dedupe,,,,,206.0,206.0,https://pypi.org/project/dedupe,245324.0,245324.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +195,bqplot,True,bqplot/bqplot,,data-viz,https://github.com/bqplot/bqplot,https://github.com/bqplot/bqplot,Apache-2.0,2015-09-26 04:02:18.000000,2021-12-10 10:01:28.000000,2021-12-10 09:31:11.000000,426.0,196.0,353.0,3196,3439.0,Plotting library for IPython/Jupyter notebooks.,55.0,26,2021-10-01 09:14:45.000000,0.12.31,54.0,,bqplot,conda-forge/bqplot,,,['jupyter'],28.0,28.0,https://pypi.org/project/bqplot,,39487.0,https://anaconda.org/conda-forge/bqplot,2021-10-01 09:49:41.042000,906099.0,,,,,2.0,,bqplot,https://www.npmjs.com/package/bqplot,25964.0,,,,,,,,,,,, +196,Blaze,True,blaze/blaze,,data-containers,https://github.com/blaze/blaze,https://github.com/blaze/blaze,,2012-10-26 14:25:22.000000,2020-02-01 19:33:09.000000,2019-08-15 21:14:59.000000,355.0,250.0,500.0,3011,7496.0,NumPy and Pandas interface to Big Data.,64.0,26,2016-07-19 20:40:03.000000,0.11.0,14.0,,blaze,conda-forge/blaze,,,,7974.0,7974.0,https://pypi.org/project/blaze,12943.0,16695.0,https://anaconda.org/conda-forge/blaze,2018-07-15 22:16:17.685000,195131.0,,,,,2.0,,,,,,,,,,,,,,,, +197,NMSLIB,True,nmslib/nmslib,,nn-search,https://github.com/nmslib/nmslib,https://github.com/nmslib/nmslib,Apache-2.0,2013-07-10 11:06:06.000000,2021-11-22 21:32:33.032000,2021-09-19 04:51:57.000000,368.0,54.0,331.0,2651,1511.0,Non-Metric Space Library (NMSLIB): An efficient similarity search..,45.0,26,2021-02-03 16:40:09.000000,2.1.1,19.0,,nmslib,conda-forge/nmslib,,,,518.0,518.0,https://pypi.org/project/nmslib,,2289.0,https://anaconda.org/conda-forge/nmslib,2021-11-22 21:32:33.032000,45794.0,,,,,1.0,,,,,,,,,,,,,,,, +198,aubio,True,aubio/aubio,,audio,https://github.com/aubio/aubio,https://github.com/aubio/aubio,GPL-3.0,2009-12-04 21:07:44.000000,2021-11-09 17:08:03.654000,2021-01-19 09:51:49.000000,327.0,120.0,175.0,2601,4111.0,a library for audio and music analysis.,24.0,26,2019-02-27 09:00:43.000000,0.4.9,8.0,,aubio,conda-forge/aubio,,,,275.0,275.0,https://pypi.org/project/aubio,,8374.0,https://anaconda.org/conda-forge/aubio,2021-11-09 17:08:03.654000,477354.0,,,,,2.0,,,,,,,,,,,,,,,, +199,TextDistance,True,life4/textdistance,,nlp,https://github.com/life4/textdistance,https://github.com/life4/textdistance,MIT,2017-05-05 08:46:10.000000,2021-12-03 13:09:42.000000,2021-11-29 10:29:02.000000,202.0,,,2570,321.0,"Compute distance between sequences. 30+ algorithms, pure python..",11.0,26,2021-01-29 09:04:46.000000,.4.2.1,8.0,,textdistance,conda-forge/textdistance,,,,1416.0,1416.0,https://pypi.org/project/textdistance,278464.0,280024.0,https://anaconda.org/conda-forge/textdistance,2021-10-27 17:04:18.548000,66717.0,,,,,2.0,414.0,,,,,,,,,,,,,,, +200,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 13:05:52.000000,2021-12-02 04:55:04.000000,2021-12-02 04:55:04.000000,294.0,61.0,270.0,2305,955.0,"Utils for streaming large files (S3, HDFS, gzip, bz2...).",89.0,26,2021-08-28 11:06:42.000000,5.2.1,41.0,,smart-open,,,,,,,https://pypi.org/project/smart-open,16408673.0,16408673.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +201,BoTorch,True,pytorch/botorch,,hyperopt,https://github.com/pytorch/botorch,https://github.com/pytorch/botorch,MIT,2018-07-30 23:59:57.000000,2021-12-15 23:32:46.000000,2021-12-14 22:28:19.000000,227.0,48.0,180.0,2141,,Bayesian optimization in PyTorch.,64.0,26,2021-12-09 00:16:14.000000,0.6.0,19.0,,botorch,,,,['pytorch'],191.0,191.0,https://pypi.org/project/botorch,130830.0,130830.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +202,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 13:08:13.000000,2021-12-06 15:56:44.000000,2021-12-06 15:56:44.000000,247.0,68.0,178.0,1908,,A machine learning toolkit dedicated to time-series data.,36.0,26,2021-08-16 07:09:52.000000,0.5.2,21.0,,tslearn,conda-forge/tslearn,,,['sklearn'],361.0,361.0,https://pypi.org/project/tslearn,120562.0,125989.0,https://anaconda.org/conda-forge/tslearn,2021-08-16 11:07:26.939000,244227.0,,,,,1.0,,,,,,,,,,,,,,,, +203,Ax,True,facebook/Ax,,hyperopt,https://github.com/facebook/Ax,https://github.com/facebook/Ax,MIT,2019-02-09 15:23:44.000000,2021-12-16 06:27:43.000000,2021-12-16 01:35:38.000000,174.0,21.0,297.0,1664,,Adaptive Experimentation Platform.,108.0,26,2021-09-15 01:33:56.000000,0.2.2,23.0,,ax-platform,,,,['pytorch'],225.0,225.0,https://pypi.org/project/ax-platform,104492.0,104492.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +204,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 08:02:14.000000,2021-12-14 10:56:04.258000,2021-12-14 08:14:27.000000,162.0,102.0,627.0,1663,3489.0,Ahead of Time compiler for numeric kernels.,64.0,26,,,24.0,,pythran,conda-forge/pythran,,,,89.0,89.0,https://pypi.org/project/pythran,322482.0,327397.0,https://anaconda.org/conda-forge/pythran,2021-12-14 10:56:04.258000,211384.0,,,,,2.0,,,,,,,,,,,pythran,python-pythran,,,, +205,GPflow,True,GPflow/GPflow,,probabilistics,https://github.com/GPflow/GPflow,https://github.com/GPflow/GPflow,Apache-2.0,2016-01-14 11:29:24.000000,2021-12-14 11:03:22.000000,2021-12-14 11:03:17.000000,396.0,96.0,622.0,1546,2248.0,Gaussian processes in TensorFlow.,72.0,26,2021-10-26 09:33:33.000000,2.3.0,32.0,,gpflow,conda-forge/gpflow,,,['tensorflow'],313.0,313.0,https://pypi.org/project/gpflow,,228.0,https://anaconda.org/conda-forge/gpflow,2018-11-06 08:51:39.744000,9808.0,,,,,1.0,,,,,,,,,,,,,,,, +206,snakemake,True,snakemake/snakemake,,ml-experiments,https://github.com/snakemake/snakemake,https://github.com/snakemake/snakemake,MIT,2015-10-17 15:43:54.867000,2021-12-15 21:25:21.000000,2021-12-09 09:36:54.000000,274.0,497.0,292.0,1191,,This is the development home of the workflow management system..,229.0,26,2021-12-09 09:37:52.000000,6.12.3,139.0,,snakemake,bioconda/snakemake,,,,989.0,989.0,https://pypi.org/project/snakemake,,4870.0,https://anaconda.org/bioconda/snakemake,2021-12-09 16:32:30.693000,360401.0,,,,,2.0,,,,,,,,,,,,,,,, +207,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 19:08:49.000000,2021-12-16 07:41:10.000000,2021-12-16 07:41:09.000000,224.0,14.0,47.0,1135,1079.0,Model analysis tools for TensorFlow.,36.0,26,2021-12-02 04:29:18.000000,0.36.0,46.0,,tensorflow-model-analysis,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/tensorflow-model-analysis,7025030.0,7025030.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +208,arviz,True,arviz-devs/arviz,,interpretability,https://github.com/arviz-devs/arviz,https://github.com/arviz-devs/arviz,Apache-2.0,2015-07-29 11:51:10.000000,2021-12-15 23:34:31.000000,2021-12-15 22:58:11.000000,254.0,135.0,554.0,1121,,Exploratory analysis of Bayesian models with Python.,106.0,26,2021-10-03 10:45:16.000000,0.11.4,24.0,,arviz,conda-forge/arviz,,,,1705.0,1705.0,https://pypi.org/project/arviz,,18715.0,https://anaconda.org/conda-forge/arviz,2021-10-03 15:30:41.137000,580116.0,,,,,2.0,111.0,,,,,,,,,,,,,,, +209,agate,True,wireservice/agate,,others,https://github.com/wireservice/agate,https://github.com/wireservice/agate,MIT,2014-04-25 13:59:09.000000,2021-10-06 19:36:50.000000,2021-07-15 17:22:49.000000,133.0,6.0,630.0,1072,1466.0,A Python data analysis library that is optimized for humans instead of machines.,49.0,26,,,5.0,,agate,conda-forge/agate,,,,690.0,690.0,https://pypi.org/project/agate,933259.0,934540.0,https://anaconda.org/conda-forge/agate,2021-07-16 07:46:42.405000,74299.0,,,,,2.0,,,,,,,,,,,,,,,, +210,spacy-transformers,True,explosion/spacy-transformers,,nlp,https://github.com/explosion/spacy-transformers,https://github.com/explosion/spacy-transformers,MIT,2019-07-26 19:12:34.000000,2021-12-16 08:05:17.000000,2021-12-16 08:05:17.000000,127.0,,,1059,1385.0,"Use pretrained transformers like BERT, XLNet and GPT-2..",18.0,26,2021-12-07 09:10:50.000000,1.1.3,26.0,,spacy-transformers,,,,['spacy'],338.0,338.0,https://pypi.org/project/spacy-transformers,85377.0,85377.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +211,ktrain,True,amaiya/ktrain,,ml-frameworks,https://github.com/amaiya/ktrain,https://github.com/amaiya/ktrain,Apache-2.0,2019-02-06 17:01:39.000000,2021-11-23 15:55:56.000000,2021-11-23 15:55:56.000000,217.0,4.0,373.0,928,2545.0,ktrain is a Python library that makes deep learning and AI more..,12.0,26,2021-11-05 20:42:40.000000,0.28.3,100.0,,ktrain,,,,['tensorflow'],245.0,245.0,https://pypi.org/project/ktrain,26181.0,26181.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +212,Hail,True,hail-is/hail,,medical-data,https://github.com/hail-is/hail,https://github.com/hail-is/hail,MIT,2015-10-27 20:55:42.000000,2021-12-16 02:35:21.000000,2021-12-16 02:35:21.000000,200.0,22.0,1967.0,766,7617.0,Scalable genomic data analysis.,76.0,26,2021-11-19 18:16:50.000000,0.2.79,67.0,,hail,,,,['spark'],45.0,45.0,https://pypi.org/project/hail,20101.0,20101.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +213,Face Recognition,True,ageitgey/face_recognition,,image,https://github.com/ageitgey/face_recognition,https://github.com/ageitgey/face_recognition,MIT,2017-03-03 21:52:39.000000,2021-12-04 17:06:24.000000,2021-06-14 10:10:40.000000,11592.0,636.0,552.0,42530,219.0,The world's simplest facial recognition api for..,47.0,25,2018-04-02 17:18:43.000000,1.2.2,2.0,,face_recognition,,,,['pytorch'],,,https://pypi.org/project/face_recognition,51580.0,51588.0,,,,,,,,2.0,451.0,,,,,,,,,,,,,,, +214,Rasa,True,RasaHQ/rasa,,nlp,https://github.com/RasaHQ/rasa,https://github.com/RasaHQ/rasa,Apache-2.0,2016-10-14 12:27:49.000000,2021-12-16 14:01:22.000000,2021-12-16 08:55:57.000000,3704.0,847.0,5473.0,13213,,Open source machine learning framework to automate text- and voice-..,518.0,25,2021-12-09 17:03:27.000000,2.8.16,100.0,,rasa,,,,['tensorflow'],,,https://pypi.org/project/rasa,234745.0,234745.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +215,NNI,True,microsoft/nni,,hyperopt,https://github.com/microsoft/nni,https://github.com/microsoft/nni,MIT,2018-06-01 05:51:44.000000,2021-12-15 08:38:51.000000,2021-12-15 04:54:30.000000,1461.0,225.0,1223.0,10690,2421.0,"An open source AutoML toolkit for automate machine learning lifecycle,..",153.0,25,2021-11-04 00:55:22.000000,2.5,32.0,,nni,,,,,160.0,160.0,https://pypi.org/project/nni,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +216,Turi Create,True,apple/turicreate,,ml-frameworks,https://github.com/apple/turicreate,https://github.com/apple/turicreate,BSD-3-Clause,2017-12-01 00:42:04.000000,2021-11-29 19:55:31.000000,2021-11-29 19:55:31.000000,1087.0,471.0,1281.0,10522,,Turi Create simplifies the development of custom machine learning..,82.0,25,2020-09-30 22:44:07.000000,6.4.1,30.0,,turicreate,,,,,280.0,280.0,https://pypi.org/project/turicreate,26141.0,26243.0,,,,,,,,3.0,4926.0,,,,,,,,,,,,,,, +217,backtrader,True,mementum/backtrader,,financial-data,https://github.com/mementum/backtrader,https://github.com/mementum/backtrader,GPL-3.0,2015-01-10 07:14:52.000000,2021-12-13 14:32:30.000000,2021-07-17 22:17:12.000000,2299.0,,,7830,2385.0,Python Backtesting library for trading strategies.,52.0,25,,,,,backtrader,,,,,840.0,840.0,https://pypi.org/project/backtrader,14842.0,14842.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +218,PaddleHub,True,PaddlePaddle/PaddleHub,,others,https://github.com/PaddlePaddle/PaddleHub,https://github.com/PaddlePaddle/PaddleHub,Apache-2.0,2018-12-21 06:00:48.000000,2021-12-16 08:35:44.000000,2021-12-16 03:29:03.000000,1446.0,350.0,620.0,7279,,Awesome pre-trained models toolkit based on PaddlePaddle.300+..,48.0,25,2021-04-16 08:20:11.000000,2.1.0,27.0,,paddlehub,,,,['paddle'],597.0,597.0,https://pypi.org/project/paddlehub,9540.0,9556.0,,,,,,,,2.0,560.0,,,,,,,,,,,,,,, +219,Modin,True,modin-project/modin,,data-containers,https://github.com/modin-project/modin,https://github.com/modin-project/modin,,2018-06-21 21:35:05.000000,2021-12-16 13:20:02.000000,2021-12-16 06:39:17.000000,461.0,631.0,1576.0,6633,1645.0,Modin: Speed up your Pandas workflows by changing a single line of..,85.0,25,2021-11-24 01:48:43.000000,0.12.0,43.0,,modin,,,,['pandas'],519.0,519.0,https://pypi.org/project/modin,,4775.0,,,,,,,,2.0,195797.0,,,,,,,,,,,,,,, +220,Autograd,True,HIPS/autograd,,others,https://github.com/HIPS/autograd,https://github.com/HIPS/autograd,MIT,2014-11-24 15:50:23.000000,2021-04-22 18:19:00.000000,2021-03-03 09:27:58.000000,767.0,142.0,219.0,5568,1376.0,Efficiently computes derivatives of numpy code.,51.0,25,2015-03-05 19:30:11.000000,1.0,4.0,,autograd,conda-forge/autograd,,,,2750.0,2750.0,https://pypi.org/project/autograd,,3054.0,https://anaconda.org/conda-forge/autograd,2019-07-25 18:29:55.493000,195472.0,,,,,2.0,,,,,,,,,,,,,,,, +221,OpenNMT,True,OpenNMT/OpenNMT-py,,nlp,https://github.com/OpenNMT/OpenNMT-py,https://github.com/OpenNMT/OpenNMT-py,MIT,2017-02-22 19:01:50.000000,2021-12-08 13:58:12.000000,2021-12-08 13:58:12.000000,1928.0,79.0,1202.0,5377,2586.0,Open Source Neural Machine Translation in PyTorch.,172.0,25,2021-09-14 08:48:31.000000,2.2.0,32.0,,OpenNMT-py,,,,['pytorch'],118.0,118.0,https://pypi.org/project/OpenNMT-py,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +222,CleverHans,True,cleverhans-lab/cleverhans,,adversarial,https://github.com/cleverhans-lab/cleverhans,https://github.com/cleverhans-lab/cleverhans,MIT,2016-09-15 00:28:04.000000,2021-11-28 16:27:56.000000,2021-09-23 22:14:27.000000,1292.0,19.0,422.0,5353,3201.0,"An adversarial example library for constructing attacks,..",128.0,25,2021-07-24 08:48:41.000000,4.0.0,8.0,,cleverhans,,,,['tensorflow'],282.0,282.0,https://pypi.org/project/cleverhans,,,,,,,,,,1.0,,,,,,,,,,,,,,,, +223,VisualDL,True,PaddlePaddle/VisualDL,,ml-experiments,https://github.com/PaddlePaddle/VisualDL,https://github.com/PaddlePaddle/VisualDL,Apache-2.0,2017-12-20 12:34:31.000000,2021-12-09 05:37:02.000000,2021-11-26 06:55:16.000000,569.0,57.0,332.0,4256,,Deep Learning Visualization Toolkit.,31.0,25,2021-09-06 08:03:22.000000,2.2.1,11.0,,visualdl,,,,['paddle'],840.0,840.0,https://pypi.org/project/visualdl,53053.0,53061.0,,,,,,,,2.0,156.0,,,,,,,,,,,,,,, +224,haystack,True,deepset-ai/haystack,,nlp,https://github.com/deepset-ai/haystack,https://github.com/deepset-ai/haystack,Apache-2.0,2019-11-14 09:05:28.000000,2021-12-16 13:02:05.000000,2021-12-16 13:02:04.000000,580.0,144.0,894.0,3362,963.0,End-to-end Python framework for building natural language search..,87.0,25,2021-12-08 08:05:22.000000,1.0.0,11.0,,haystack,,,,,94.0,94.0,https://pypi.org/project/haystack,1470.0,1470.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +225,ClearML,True,allegroai/clearml,,ml-experiments,https://github.com/allegroai/clearml,https://github.com/allegroai/clearml,Apache-2.0,2019-06-10 08:18:32.000000,2021-12-14 18:49:34.000000,2021-12-14 18:49:34.000000,384.0,138.0,284.0,2861,1452.0,ClearML - Auto-Magical Suite of tools to streamline your ML..,42.0,25,2021-11-08 09:06:16.000000,1.1.4,51.0,,clearml,,allegroai/trains,,,168.0,168.0,https://pypi.org/project/clearml,,1015.0,,,,https://hub.docker.com/r/allegroai/trains,2020-10-05 10:16:46.865671,,30095.0,2.0,377.0,,,,,,,,,,,,,,, +226,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 09:34:48.000000,2021-12-16 04:25:17.000000,2021-12-12 13:54:37.000000,219.0,38.0,399.0,2854,541.0,Visualizer for pandas data structures.,18.0,25,2021-11-16 03:33:21.000000,1.61.0,103.0,,dtale,conda-forge/dtale,,,"['pandas', 'jupyter']",274.0,274.0,https://pypi.org/project/dtale,47895.0,52433.0,https://anaconda.org/conda-forge/dtale,2021-11-18 04:41:08.411000,99852.0,,,,,2.0,,,,,,,,,,,,,,,, +227,pomegranate,True,jmschrei/pomegranate,,probabilistics,https://github.com/jmschrei/pomegranate,https://github.com/jmschrei/pomegranate,MIT,2014-11-24 18:36:58.000000,2021-12-01 22:51:35.000000,2021-11-20 02:50:26.000000,507.0,32.0,606.0,2787,930.0,"Fast, flexible and easy to use probabilistic modelling in Python.",65.0,25,2016-03-30 20:01:37.000000,0.4.0,7.0,,pomegranate,conda-forge/pomegranate,,,,591.0,591.0,https://pypi.org/project/pomegranate,,2662.0,https://anaconda.org/conda-forge/pomegranate,2021-11-16 01:22:35.020000,77224.0,,,,,2.0,,,,,,,,,,,,,,,, +228,AzureML SDK,True,Azure/MachineLearningNotebooks,,ml-experiments,https://github.com/Azure/MachineLearningNotebooks,https://github.com/Azure/MachineLearningNotebooks,MIT,2018-08-17 17:29:14.000000,2021-12-13 18:36:09.000000,2021-12-13 18:36:08.000000,1940.0,193.0,1013.0,2785,1164.0,Python notebooks with ML and deep learning examples with Azure..,57.0,25,2019-08-29 17:25:28.000000,80469,28.0,,azureml-sdk,,,,,,,https://pypi.org/project/azureml-sdk,1874529.0,1874540.0,,,,,,,,2.0,426.0,,,,,,,,,,,,,,, +229,Core ML Tools,True,apple/coremltools,,model-serialisation,https://github.com/apple/coremltools,https://github.com/apple/coremltools,BSD-3-Clause,2017-06-30 07:39:02.000000,2021-12-14 22:33:17.000000,2021-12-14 22:33:17.000000,369.0,317.0,516.0,2483,,Core ML tools contain supporting tools for Core ML model..,117.0,25,2021-11-09 18:31:11.000000,5.1,25.0,,coremltools,,,,,701.0,701.0,https://pypi.org/project/coremltools,76568.0,76643.0,,,,,,,,1.0,3840.0,,,,,,,,,,,,,,, +230,neuralcoref,True,huggingface/neuralcoref,,nlp,https://github.com/huggingface/neuralcoref,https://github.com/huggingface/neuralcoref,MIT,2017-07-03 13:04:16.000000,2021-10-10 04:28:21.000000,2021-06-22 10:51:48.000000,423.0,60.0,228.0,2451,116.0,Fast Coreference Resolution in spaCy with Neural Networks.,21.0,25,2019-04-08 11:28:27.000000,4.0.0,5.0,,neuralcoref,conda-forge/neuralcoref,,,,428.0,428.0,https://pypi.org/project/neuralcoref,53343.0,53818.0,https://anaconda.org/conda-forge/neuralcoref,2020-02-21 22:10:40.453000,10361.0,,,,,2.0,296.0,,,,,,,,,,,,,,, +231,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 02:27:30.000000,2021-12-15 08:43:37.000000,2021-12-15 07:27:18.000000,688.0,416.0,838.0,2447,3413.0,"Distributed Tensorflow, Keras and PyTorch on Apache..",105.0,25,2021-07-19 00:31:21.000000,0.11.0,13.0,,analytics-zoo,,,,['spark'],3.0,3.0,https://pypi.org/project/analytics-zoo,12878.0,12878.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +232,fastNLP,True,fastnlp/fastNLP,,nlp,https://github.com/fastnlp/fastNLP,https://github.com/fastnlp/fastNLP,Apache-2.0,2018-03-07 13:30:20.000000,2021-12-06 12:23:20.000000,2021-12-06 11:37:15.000000,399.0,34.0,143.0,2439,1769.0,fastNLP: A Modularized and Extensible NLP Framework. Currently still..,54.0,25,2020-11-06 15:31:29.000000,0.6.0,7.0,,fastnlp,,,,,52.0,52.0,https://pypi.org/project/fastnlp,1668.0,1669.0,,,,,,,,2.0,65.0,,,,,,,,,,,,,,, +233,scikit-plot,True,reiinakano/scikit-plot,,interpretability,https://github.com/reiinakano/scikit-plot,https://github.com/reiinakano/scikit-plot,MIT,2017-02-04 06:22:59.000000,2021-08-11 23:58:11.000000,2018-08-19 12:37:47.000000,256.0,19.0,39.0,2160,130.0,An intuitive library to add plotting functionality to..,13.0,25,2018-08-19 12:21:01.000000,0.3.7,17.0,,scikit-plot,conda-forge/scikit-plot,,,['sklearn'],1544.0,1544.0,https://pypi.org/project/scikit-plot,388253.0,390200.0,https://anaconda.org/conda-forge/scikit-plot,2019-06-05 14:23:59.043000,103210.0,,,,,2.0,,,,,,,,,,,,,,,, +234,Alphalens,True,quantopian/alphalens,,financial-data,https://github.com/quantopian/alphalens,https://github.com/quantopian/alphalens,Apache-2.0,2016-06-03 21:49:15.000000,2021-12-05 06:35:06.000000,2020-04-27 18:40:41.000000,793.0,38.0,145.0,2128,522.0,Performance analysis of predictive (alpha) stock factors.,25.0,25,2020-04-30 15:42:52.000000,0.4.0,10.0,,alphalens,conda-forge/alphalens,,,,468.0,468.0,https://pypi.org/project/alphalens,2327.0,2630.0,https://anaconda.org/conda-forge/alphalens,2020-05-16 13:52:44.922000,13946.0,,,,,2.0,,,,,,,,,,,,,,,, +235,HoloViews,True,holoviz/holoviews,,data-viz,https://github.com/holoviz/holoviews,https://github.com/holoviz/holoviews,BSD-3-Clause,2014-05-07 16:59:22.000000,2021-12-16 12:54:59.000000,2021-12-15 21:32:35.000000,330.0,788.0,1910.0,2060,10268.0,"With Holoviews, your data visualizes itself.",116.0,25,2021-09-30 16:18:23.000000,1.14.6,62.0,,holoviews,conda-forge/holoviews,,,['jupyter'],,,https://pypi.org/project/holoviews,,12368.0,https://anaconda.org/conda-forge/holoviews,2021-09-17 16:26:42.464000,617534.0,,,,,2.0,,@pyviz/jupyterlab_pyviz,https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz,3152.0,,,,,,,,,,,, +236,python-magic,True,ahupp/python-magic,,data-loading,https://github.com/ahupp/python-magic,https://github.com/ahupp/python-magic,,2010-03-31 22:40:33.000000,2021-11-05 19:10:38.471000,2021-10-23 17:27:22.000000,225.0,23.0,140.0,2005,298.0,A python wrapper for libmagic.,53.0,25,,,5.0,,python-magic,conda-forge/python-magic,,,,21262.0,21262.0,https://pypi.org/project/python-magic,,1991.0,https://anaconda.org/conda-forge/python-magic,2021-11-05 19:10:38.471000,111507.0,,,,,3.0,,,,,,,,,,,,,,,, +237,jellyfish,True,jamesturk/jellyfish,,nlp,https://github.com/jamesturk/jellyfish,https://github.com/jamesturk/jellyfish,BSD-2-Clause,2010-07-09 20:41:11.000000,2021-12-15 06:50:41.727000,2021-11-16 18:49:21.000000,142.0,9.0,98.0,1565,,a python library for doing approximate and phonetic matching of..,25.0,25,,,9.0,,jellyfish,conda-forge/jellyfish,,,,3033.0,3033.0,https://pypi.org/project/jellyfish,1664228.0,1666776.0,https://anaconda.org/conda-forge/jellyfish,2021-12-15 06:50:41.727000,160527.0,,,,,2.0,,,,,,,,,,,,,,,, +238,tesserocr,True,sirfz/tesserocr,,ocr,https://github.com/sirfz/tesserocr,https://github.com/sirfz/tesserocr,MIT,2015-12-17 23:29:36.000000,2021-11-09 18:12:48.000000,2021-11-09 18:12:47.000000,202.0,74.0,158.0,1562,178.0,A Python wrapper for the tesseract-ocr API.,26.0,25,2021-06-19 21:08:11.000000,2.5.2,13.0,,tesserocr,conda-forge/tesserocr,,,,579.0,579.0,https://pypi.org/project/tesserocr,,2393.0,https://anaconda.org/conda-forge/tesserocr,2021-01-13 16:38:14.456000,62234.0,,,,,2.0,,,,,,,,,,,,,,,, +239,torchaudio,True,pytorch/audio,,audio,https://github.com/pytorch/audio,https://github.com/pytorch/audio,BSD-2-Clause,2017-05-05 00:38:05.000000,2021-12-16 12:43:35.000000,2021-12-15 15:06:55.000000,355.0,112.0,441.0,1501,1168.0,Data manipulation and transformation for audio signal..,145.0,25,2021-10-21 15:55:34.000000,0.10.0,15.0,,torchaudio,,,,['pytorch'],,,https://pypi.org/project/torchaudio,382488.0,382488.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +240,Alibi,True,SeldonIO/alibi,,interpretability,https://github.com/SeldonIO/alibi,https://github.com/SeldonIO/alibi,Apache-2.0,2019-02-26 10:10:56.000000,2021-12-16 00:03:29.000000,2021-12-13 12:02:52.000000,159.0,97.0,146.0,1408,350.0,Algorithms for monitoring and explaining machine learning models.,18.0,25,2021-11-18 13:42:16.000000,0.6.2,21.0,,alibi,,,,,125.0,125.0,https://pypi.org/project/alibi,15311.0,15311.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +241,TF Recommenders,True,tensorflow/recommenders,,recommender-systems,https://github.com/tensorflow/recommenders,https://github.com/tensorflow/recommenders,Apache-2.0,2020-06-26 21:38:01.000000,2021-12-15 21:29:36.000000,2021-12-09 19:38:11.000000,151.0,109.0,95.0,1121,,TensorFlow Recommenders is a library for building..,29.0,25,2021-08-23 23:20:47.000000,0.6.0,12.0,,tensorflow-recommenders,,,,['tensorflow'],61.0,61.0,https://pypi.org/project/tensorflow-recommenders,248622.0,248622.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +242,pyclustering,True,annoviko/pyclustering,,others,https://github.com/annoviko/pyclustering,https://github.com/annoviko/pyclustering,BSD-3-Clause,2014-02-25 18:59:03.000000,2021-11-19 04:07:59.000000,2021-02-12 19:04:59.000000,209.0,55.0,589.0,902,2079.0,"pyclustring is a Python, C++ data mining library.",26.0,25,2020-11-25 22:33:07.000000,0.10.1.2,18.0,,pyclustering,conda-forge/pyclustering,,,,255.0,255.0,https://pypi.org/project/pyclustering,44514.0,45869.0,https://anaconda.org/conda-forge/pyclustering,2021-09-13 14:29:08.300000,32377.0,,,,,2.0,378.0,,,,,,,,,,,,,,, +243,patsy,True,pydata/patsy,,probabilistics,https://github.com/pydata/patsy,https://github.com/pydata/patsy,,2012-07-10 12:30:06.000000,2021-09-26 16:29:44.000000,2021-09-26 16:29:39.000000,85.0,60.0,68.0,806,539.0,Describing statistical models in Python using symbolic formulas.,16.0,25,2021-09-27 02:10:26.000000,0.5.2,9.0,,patsy,conda-forge/patsy,,,,44661.0,44661.0,https://pypi.org/project/patsy,,62492.0,https://anaconda.org/conda-forge/patsy,2021-09-26 14:43:31.594000,3999537.0,,,,,2.0,,,,,,,,,,,,,,,, +244,pyjanitor,True,ericmjl/pyjanitor,,others,https://github.com/pyjanitor-devs/pyjanitor,https://github.com/pyjanitor-devs/pyjanitor,MIT,2018-03-04 22:43:33.000000,2021-12-11 10:22:09.000000,2021-11-22 18:59:22.000000,131.0,86.0,334.0,780,1162.0,Clean APIs for data cleaning. Python implementation of R package Janitor.,95.0,25,2021-11-21 02:25:32.000000,0.22.0,50.0,pyjanitor-devs/pyjanitor,pyjanitor,conda-forge/pyjanitor,,,,130.0,130.0,https://pypi.org/project/pyjanitor,13224.0,15653.0,https://anaconda.org/conda-forge/pyjanitor,2021-11-22 17:28:45.154000,109344.0,,,,,2.0,,,,,,,,,,,,,,,, +245,PyNNDescent,True,lmcinnes/pynndescent,,nn-search,https://github.com/lmcinnes/pynndescent,https://github.com/lmcinnes/pynndescent,BSD-2-Clause,2018-02-07 23:23:54.000000,2021-12-08 17:38:15.000000,2021-12-08 17:38:15.000000,68.0,39.0,49.0,529,534.0,A Python nearest neighbor descent for approximate nearest neighbors.,18.0,25,2021-10-15 14:06:19.000000,0.5.5,17.0,,pynndescent,conda-forge/pynndescent,,,,1047.0,1047.0,https://pypi.org/project/pynndescent,,13921.0,https://anaconda.org/conda-forge/pynndescent,2021-10-15 15:32:23.572000,417651.0,,,,,2.0,,,,,,,,,,,,,,,, +246,spleeter,True,deezer/spleeter,,audio,https://github.com/deezer/spleeter,https://github.com/deezer/spleeter,MIT,2019-09-26 15:40:46.000000,2021-12-08 16:06:40.000000,2021-12-08 16:06:40.000000,1923.0,103.0,502.0,18114,474.0,Deezer source separation library including pretrained models.,18.0,24,2021-09-03 09:59:00.000000,2.3.0,10.0,,spleeter,conda-forge/spleeter,,,['tensorflow'],,,https://pypi.org/project/spleeter,,53977.0,https://anaconda.org/conda-forge/spleeter,2020-06-30 14:33:43.220000,61436.0,,,,,2.0,1339521.0,,,,,,,,,,,,,,, +247,horovod,True,horovod/horovod,,distributed-ml,https://github.com/horovod/horovod,https://github.com/horovod/horovod,,2017-08-09 19:39:59.000000,2021-12-16 11:11:53.000000,2021-12-16 07:31:48.000000,1926.0,254.0,1662.0,11937,1114.0,"Distributed training framework for TensorFlow, Keras, PyTorch, and..",140.0,24,2021-10-06 17:52:54.000000,0.23.0,14.0,,horovod,,,,,475.0,475.0,https://pypi.org/project/horovod,,,,,,,,,,2.0,,,,,,stable/horovod,,,,,,,,,, +248,Annoy,True,spotify/annoy,,nn-search,https://github.com/spotify/annoy,https://github.com/spotify/annoy,Apache-2.0,2013-04-01 20:29:40.000000,2021-10-18 14:07:24.000000,2021-10-18 14:07:24.000000,952.0,38.0,298.0,9255,832.0,Approximate Nearest Neighbors in C++/Python optimized for memory usage..,75.0,24,2020-09-18 16:07:34.000000,1.17.0,17.0,,annoy,,,,,1866.0,1866.0,https://pypi.org/project/annoy,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +249,Pillow,True,python-pillow/Pillow,,image,https://github.com/python-pillow/Pillow,https://github.com/python-pillow/Pillow,PIL,2012-07-24 21:38:39.000000,2021-12-15 20:39:46.000000,2021-12-15 09:14:04.000000,1632.0,137.0,2214.0,9236,,The friendly PIL fork (Python Imaging Library).,375.0,24,2021-10-15 08:16:09.000000,8.4.0,42.0,,Pillow,conda-forge/pillow,,,,,,https://pypi.org/project/Pillow,,175108.0,https://anaconda.org/conda-forge/pillow,2021-11-10 16:07:31.860000,11907351.0,,,,,2.0,,,,,-16.0,,,,,,,,,,, +250,Ciphey,True,Ciphey/Ciphey,,nlp,https://github.com/Ciphey/Ciphey,https://github.com/Ciphey/Ciphey,MIT,2019-07-16 20:20:39.000000,2021-12-06 03:13:19.000000,2021-11-03 02:20:58.000000,561.0,43.0,228.0,9115,1873.0,"Automatically decrypt encryptions without knowing the key or cipher,..",46.0,24,2021-06-06 17:14:16.000000,5.14.0,29.0,,ciphey,,remnux/ciphey,,,,,https://pypi.org/project/ciphey,14521.0,14994.0,,,,https://hub.docker.com/r/remnux/ciphey,2021-11-16 13:31:49.535232,5.0,13729.0,2.0,,,,,,,,,,,,,,,, +251,DVC,True,iterative/dvc,,ml-experiments,https://github.com/iterative/dvc,https://github.com/iterative/dvc,Apache-2.0,2017-03-04 08:16:33.000000,2021-12-16 13:15:46.000000,2021-12-16 07:04:47.000000,851.0,580.0,2849.0,8999,,Data Version Control | Git for Data & Models.,252.0,24,2021-12-11 03:50:49.000000,2.9.2,176.0,,dvc,conda-forge/dvc,,,,,,https://pypi.org/project/dvc,355550.0,391232.0,https://anaconda.org/conda-forge/dvc,2021-12-14 10:36:02.968000,952336.0,,,,,2.0,48333.0,,,,,,,dvc,,,,,dvc,dvc,, +252,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 23:58:12.000000,2021-12-16 10:35:58.000000,2021-12-16 03:49:48.000000,914.0,147.0,479.0,8016,2295.0,Ludwig is a toolbox that allows to train and evaluate deep..,108.0,24,2021-06-15 04:22:19.000000,0.4,11.0,,ludwig,,,,['tensorflow'],98.0,98.0,https://pypi.org/project/ludwig,3807.0,3807.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +253,Pyro,True,pyro-ppl/pyro,,probabilistics,https://github.com/pyro-ppl/pyro,https://github.com/pyro-ppl/pyro,Apache-2.0,2017-06-16 05:03:47.000000,2021-12-15 22:17:23.000000,2021-12-14 16:16:38.000000,851.0,160.0,738.0,7223,2298.0,Deep universal probabilistic programming with Python and PyTorch.,116.0,24,2021-12-14 16:17:56.000000,1.8.0,27.0,,pyro-ppl,,,,['pytorch'],592.0,592.0,https://pypi.org/project/pyro-ppl,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +254,carla,True,carla-simulator/carla,,others,https://github.com/carla-simulator/carla,https://github.com/carla-simulator/carla,MIT,2017-10-24 09:06:23.000000,2021-12-16 14:02:16.000000,2021-11-19 11:13:47.000000,2012.0,453.0,3137.0,7005,5439.0,Open-source simulator for autonomous driving research.,138.0,24,2021-11-16 19:51:12.000000,0.9.13,24.0,,carla,,,,,112.0,112.0,https://pypi.org/project/carla,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +255,NuPIC,True,numenta/nupic,,ml-frameworks,https://github.com/numenta/nupic,https://github.com/numenta/nupic,AGPL-3.0,2013-04-05 23:14:27.000000,2021-03-25 21:39:47.000000,2019-10-23 20:45:07.000000,1550.0,450.0,1337.0,6291,6625.0,Numenta Platform for Intelligent Computing is an implementation..,121.0,24,2018-06-01 15:12:12.000000,1.0.5,47.0,,nupic,,,,,107.0,107.0,https://pypi.org/project/nupic,3272.0,3272.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +256,PyMC3,True,pymc-devs/pymc3,,probabilistics,https://github.com/pymc-devs/pymc,https://github.com/pymc-devs/pymc,,2009-05-05 09:43:50.000000,2021-12-16 10:01:25.000000,2021-12-16 09:45:25.000000,1418.0,202.0,2261.0,6212,,Probabilistic Programming in Python: Bayesian Modeling and..,348.0,24,2021-08-24 01:16:57.000000,3.11.4,29.0,pymc-devs/pymc,pymc3,conda-forge/pymc3,,,,569.0,569.0,https://pypi.org/project/pymc3,,5830.0,https://anaconda.org/conda-forge/pymc3,2021-10-12 16:32:39.553000,360690.0,,,,,2.0,1194.0,,,,,,,,,,,,,,, +257,DeepSpeed,True,microsoft/DeepSpeed,,distributed-ml,https://github.com/microsoft/DeepSpeed,https://github.com/microsoft/DeepSpeed,MIT,2020-01-23 18:35:18.000000,2021-12-15 01:41:18.000000,2021-12-15 01:33:48.000000,642.0,339.0,380.0,6023,815.0,DeepSpeed is a deep learning optimization library that makes..,86.0,24,2021-12-01 01:16:49.000000,0.5.8,24.0,,deepspeed,,deepspeed/deepspeed,,['pytorch'],127.0,127.0,https://pypi.org/project/deepspeed,,532.0,,,,https://hub.docker.com/r/deepspeed/deepspeed,2021-05-05 21:39:11.981563,3.0,12239.0,2.0,,,,,,,,,,,,,,,, +258,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 15:38:10.000000,2021-12-16 14:12:43.000000,2021-11-09 19:34:35.000000,1074.0,94.0,717.0,5914,2582.0,Automated Machine Learning with scikit-learn.,77.0,24,2021-11-09 09:49:43.000000,0.14.1,29.0,,auto-sklearn,,,,['sklearn'],240.0,240.0,https://pypi.org/project/auto-sklearn,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +259,stanza,True,stanfordnlp/stanza,,nlp,https://github.com/stanfordnlp/stanza,https://github.com/stanfordnlp/stanza,,2017-09-26 08:00:56.000000,2021-12-15 23:14:04.000000,2021-11-18 23:03:56.000000,742.0,73.0,539.0,5886,,Official Stanford NLP Python Library for Many Human Languages.,41.0,24,2021-10-06 06:28:19.000000,1.3.0,12.0,,stanza,stanfordnlp/stanza,,,,784.0,784.0,https://pypi.org/project/stanza,245739.0,245953.0,https://anaconda.org/stanfordnlp/stanza,2021-10-05 07:17:34.873000,4501.0,,,,,2.0,,,,,,,,,,,,,,,, +260,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 00:18:46.000000,2021-12-16 14:18:34.000000,2021-12-16 02:35:51.000000,779.0,128.0,980.0,5800,,Always know what to expect from your data.,252.0,24,2021-12-09 22:20:11.000000,0.13.46,100.0,,great_expectations,,,,,,,https://pypi.org/project/great_expectations,2638395.0,2638395.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +261,Datasette,True,simonw/datasette,,others,https://github.com/simonw/datasette,https://github.com/simonw/datasette,Apache-2.0,2017-10-23 00:39:03.000000,2021-12-15 17:58:21.000000,2021-12-15 17:58:01.000000,357.0,309.0,878.0,5636,1830.0,An open source multi-tool for exploring and publishing data.,60.0,24,2021-11-30 06:50:48.000000,0.59.4,100.0,,datasette,,,,,564.0,564.0,https://pypi.org/project/datasette,,0.0,,,,,,,,2.0,34.0,,,,,,,datasette,,,,,,,, +262,Gradio,True,gradio-app/gradio,,others,https://github.com/gradio-app/gradio,https://github.com/gradio-app/gradio,Apache-2.0,2018-12-19 08:24:04.000000,2021-12-15 03:06:53.000000,2021-12-15 02:53:02.000000,264.0,34.0,200.0,4290,2713.0,"Wrap UIs around any model, share with anyone.",36.0,24,2021-10-19 21:31:06.000000,2.4.0,2.0,,gradio,,,,,450.0,450.0,https://pypi.org/project/gradio,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +263,Perspective,True,finos/perspective,,data-viz,https://github.com/finos/perspective,https://github.com/finos/perspective,Apache-2.0,2017-11-02 16:27:54.000000,2021-12-16 00:44:33.000000,2021-12-16 00:44:32.000000,409.0,61.0,413.0,3985,4956.0,Streaming pivot visualization via WebAssembly.,65.0,24,,,,,perspective-python,,,,['jupyter'],219.0,219.0,https://pypi.org/project/perspective-python,5547.0,7734.0,,,,,,,,3.0,,@finos/perspective-jupyterlab,https://www.npmjs.com/package/@finos/perspective-jupyterlab,2187.0,,,,,,,,,,,, +264,Tesseract,True,madmaze/pytesseract,,ocr,https://github.com/madmaze/pytesseract,https://github.com/madmaze/pytesseract,Apache-2.0,2010-10-27 23:02:49.000000,2021-12-08 07:47:43.000000,2021-12-08 07:47:40.000000,554.0,10.0,274.0,3929,436.0,Python-tesseract is an optical character recognition (OCR) tool for python.,38.0,24,2021-06-04 21:45:12.000000,0.3.8,21.0,,pytesseract,conda-forge/pytesseract,,,,,,https://pypi.org/project/pytesseract,853682.0,870185.0,https://anaconda.org/conda-forge/pytesseract,2021-06-05 17:42:22.118000,478609.0,,,,,2.0,,,,,,,,,,,,,,,, +265,lightfm,True,lyst/lightfm,,recommender-systems,https://github.com/lyst/lightfm,https://github.com/lyst/lightfm,Apache-2.0,2015-07-30 08:34:00.000000,2021-10-29 14:19:26.000000,2021-02-07 21:16:06.000000,611.0,89.0,344.0,3881,428.0,"A Python implementation of LightFM, a hybrid recommendation algorithm.",44.0,24,2020-11-27 19:48:30.000000,1.16,8.0,,lightfm,conda-forge/lightfm,,,,607.0,607.0,https://pypi.org/project/lightfm,,2368.0,https://anaconda.org/conda-forge/lightfm,2021-02-07 22:19:58.097000,111304.0,,,,,1.0,,,,,,,,,,,,,,,, +266,sacred,True,IDSIA/sacred,,ml-experiments,https://github.com/IDSIA/sacred,https://github.com/IDSIA/sacred,MIT,2014-03-31 18:05:29.000000,2021-12-01 20:34:46.000000,2021-11-05 12:51:21.000000,335.0,92.0,427.0,3676,1314.0,"Sacred is a tool to help you configure, organize, log and reproduce..",95.0,24,2020-11-26 21:37:36.000000,0.8.2,10.0,,sacred,,,,,1141.0,1141.0,https://pypi.org/project/sacred,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +267,tensorflow-probability,True,tensorflow/probability,,probabilistics,https://github.com/tensorflow/probability,https://github.com/tensorflow/probability,Apache-2.0,2017-10-23 23:50:54.000000,2021-12-14 22:49:54.000000,2021-12-14 22:49:53.000000,912.0,467.0,628.0,3551,,Probabilistic reasoning and statistical analysis in..,432.0,24,2021-11-18 15:49:59.000000,0.15.0,41.0,,tensorflow-probability,conda-forge/tensorflow-probability,,,['tensorflow'],,,https://pypi.org/project/tensorflow-probability,1492038.0,1493446.0,https://anaconda.org/conda-forge/tensorflow-probability,2021-10-22 19:50:42.522000,47889.0,,,,,2.0,,,,,,,,,,,,,,,, +268,pytorch-summary,True,sksq96/pytorch-summary,,pytorch-utils,https://github.com/sksq96/pytorch-summary,https://github.com/sksq96/pytorch-summary,MIT,2018-04-23 13:58:04.000000,2021-06-20 09:40:21.000000,2021-05-10 18:34:53.000000,374.0,91.0,39.0,3338,57.0,Model summary in PyTorch similar to `model.summary()`..,11.0,24,,,,,torchsummary,,,,['pytorch'],3894.0,3894.0,https://pypi.org/project/torchsummary,84163.0,84163.0,,,,,,,,1.0,,,,,,,,,,,,,,,, +269,Darts,True,unit8co/darts,,time-series-data,https://github.com/unit8co/darts,https://github.com/unit8co/darts,Apache-2.0,2018-09-13 15:17:28.000000,2021-12-16 12:35:10.000000,2021-12-14 10:53:17.000000,278.0,106.0,183.0,3222,664.0,A python library for easy manipulation and forecasting of time series.,41.0,24,2021-11-28 09:29:16.000000,0.14.0,22.0,,u8darts,,unit8/darts,,,22.0,22.0,https://pypi.org/project/u8darts,3687.0,3692.0,,,,https://hub.docker.com/r/unit8/darts,2021-11-28 09:42:06.260681,,227.0,2.0,,,,,,,,,,,,,,,, +270,textract,True,deanmalmgren/textract,,data-loading,https://github.com/deanmalmgren/textract,https://github.com/deanmalmgren/textract,MIT,2014-07-03 20:36:59.000000,2021-12-06 14:05:13.000000,2021-08-21 17:07:52.000000,439.0,76.0,126.0,3162,579.0,extract text from any document. no muss. no fuss.,39.0,24,2021-08-21 17:09:22.000000,1.6.4,16.0,,textract,conda-forge/textract,,,,,,https://pypi.org/project/textract,73924.0,74132.0,https://anaconda.org/conda-forge/textract,2021-08-22 03:37:29.204000,13143.0,,,,,3.0,,,,,,,,,,,,,,,, +271,xLearn,True,aksnzhy/xlearn,,ml-frameworks,https://github.com/aksnzhy/xlearn,https://github.com/aksnzhy/xlearn,Apache-2.0,2017-06-10 08:09:31.000000,2021-01-28 14:17:44.000000,2020-03-03 10:12:35.000000,511.0,185.0,110.0,2967,1340.0,"High performance, easy-to-use, and scalable machine learning (ML)..",30.0,24,2019-04-25 02:10:05.000000,0.4.4,15.0,,xlearn,,,,,72.0,72.0,https://pypi.org/project/xlearn,2886.0,2953.0,,,,,,,,3.0,3021.0,,,,,,,,,,,,,,, +272,torchtext,True,pytorch/text,,nlp,https://github.com/pytorch/text,https://github.com/pytorch/text,BSD-3-Clause,2016-12-12 00:56:03.000000,2021-12-16 12:34:23.000000,2021-12-13 15:40:17.000000,642.0,258.0,335.0,2911,847.0,Data loaders and abstractions for text and NLP.,118.0,24,2021-10-21 17:20:17.000000,0.11.0-rc3,16.0,,torchtext,,,,['pytorch'],,,https://pypi.org/project/torchtext,122332.0,122332.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +273,VisPy,True,vispy/vispy,,data-viz,https://github.com/vispy/vispy,https://github.com/vispy/vispy,,2013-03-21 18:43:22.000000,2021-12-10 15:34:00.000000,2021-12-10 15:33:59.000000,571.0,257.0,1013.0,2771,,High-performance interactive 2D/3D data visualization library.,166.0,24,2021-11-24 17:23:39.000000,0.9.4,25.0,,vispy,conda-forge/vispy,,,['jupyter'],648.0,648.0,https://pypi.org/project/vispy,45256.0,49203.0,https://anaconda.org/conda-forge/vispy,2021-11-24 21:55:08.590000,196833.0,,,,,3.0,,vispy,https://www.npmjs.com/package/vispy,11.0,,,,,,,,,,,, +274,GPyTorch,True,cornellius-gp/gpytorch,,probabilistics,https://github.com/cornellius-gp/gpytorch,https://github.com/cornellius-gp/gpytorch,MIT,2017-06-09 14:48:20.000000,2021-12-15 12:39:39.000000,2021-12-15 12:39:38.000000,373.0,233.0,783.0,2621,3536.0,A highly efficient and modular implementation of Gaussian Processes..,89.0,24,2021-12-04 15:47:50.000000,1.6.0,25.0,,gpytorch,,,,['pytorch'],449.0,449.0,https://pypi.org/project/gpytorch,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +275,implicit,True,benfred/implicit,,recommender-systems,https://github.com/benfred/implicit,https://github.com/benfred/implicit,MIT,2016-04-17 03:45:23.000000,2021-12-07 19:05:43.000000,2021-10-02 05:11:29.000000,505.0,84.0,283.0,2564,,Fast Python Collaborative Filtering for Implicit Feedback Datasets.,30.0,24,,,13.0,,implicit,conda-forge/implicit,,,,519.0,519.0,https://pypi.org/project/implicit,119258.0,126107.0,https://anaconda.org/conda-forge/implicit,2021-08-29 07:42:53.163000,321930.0,,,,,1.0,,,,,,,,,,,,,,,, +276,facenet-pytorch,True,timesler/facenet-pytorch,,image,https://github.com/timesler/facenet-pytorch,https://github.com/timesler/facenet-pytorch,MIT,2019-05-25 01:29:24.000000,2021-12-13 14:59:32.000000,2021-12-13 12:07:11.000000,547.0,52.0,89.0,2559,235.0,Pretrained Pytorch face detection (MTCNN) and recognition..,14.0,24,2020-09-07 23:53:20.000000,2.4.1,6.0,,facenet-pytorch,,,,['pytorch'],574.0,574.0,https://pypi.org/project/facenet-pytorch,,7011.0,,,,,,,,2.0,175287.0,,,,,,,,,,,,,,, +277,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 17:17:29.000000,2021-12-16 13:57:39.000000,2021-12-13 16:16:01.000000,480.0,216.0,419.0,2370,824.0,Probabilistic time series modeling in Python.,79.0,24,2021-08-12 10:04:36.000000,0.8.1,40.0,,gluonts,,,,['mxnet'],,,https://pypi.org/project/gluonts,76149.0,76149.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +278,TorchServe,True,pytorch/serve,,model-serialisation,https://github.com/pytorch/serve,https://github.com/pytorch/serve,Apache-2.0,2019-10-03 03:17:43.000000,2021-12-16 06:42:01.000000,2021-12-15 06:35:49.000000,419.0,108.0,635.0,2315,2451.0,Model Serving on PyTorch.,94.0,24,2021-11-18 19:18:43.000000,0.5.0,10.0,,torchserve,pytorch/torchserve,pytorch/torchserve,,['pytorch'],,,https://pypi.org/project/torchserve,,37481.0,https://anaconda.org/pytorch/torchserve,2021-11-19 20:52:30.682000,16819.0,https://hub.docker.com/r/pytorch/torchserve,2021-11-22 21:46:40.121540,9.0,951747.0,2.0,725.0,,,,,,,,,,,,,,, +279,Hyperas,True,maxpumperla/hyperas,,hyperopt,https://github.com/maxpumperla/hyperas,https://github.com/maxpumperla/hyperas,MIT,2016-02-19 14:45:10.000000,2021-11-19 13:23:59.000000,2021-11-19 13:23:56.000000,299.0,90.0,158.0,2109,211.0,Keras + Hyperopt: A very simple wrapper for convenient..,21.0,24,,,,,hyperas,,,,['tensorflow'],222.0,222.0,https://pypi.org/project/hyperas,11667.0,11667.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +280,Essentia,True,MTG/essentia,,audio,https://github.com/MTG/essentia,https://github.com/MTG/essentia,AGPL-3.0,2013-06-03 14:53:47.000000,2021-12-16 11:34:45.000000,2021-12-16 11:34:16.000000,425.0,320.0,596.0,1982,2946.0,"C++ library for audio and music analysis, description and..",73.0,24,2015-03-31 16:33:30.000000,2.0,6.0,,essentia,,,,,256.0,256.0,https://pypi.org/project/essentia,2266.0,2266.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +281,PyTextRank,True,DerwenAI/pytextrank,,nlp,https://github.com/DerwenAI/pytextrank,https://github.com/DerwenAI/pytextrank,MIT,2016-10-02 18:39:12.000000,2021-10-10 01:12:32.000000,2021-10-10 01:07:35.000000,292.0,22.0,57.0,1673,,Python implementation of TextRank for phrase extraction and..,17.0,24,2021-10-10 01:10:23.000000,3.2.2,18.0,,pytextrank,,,,,218.0,218.0,https://pypi.org/project/pytextrank,17529.0,17529.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +282,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 20:47:15.000000,2021-12-13 16:55:02.000000,2021-11-18 15:43:53.000000,497.0,54.0,59.0,1592,342.0,A comprehensive set of fairness metrics for datasets and..,46.0,24,2021-03-04 18:01:29.000000,0.4.0,9.0,,aif360,,,,,130.0,130.0,https://pypi.org/project/aif360,7259.0,7259.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +283,bt,True,pmorissette/bt,,financial-data,https://github.com/pmorissette/bt,https://github.com/pmorissette/bt,MIT,2014-06-19 16:06:28.000000,2021-05-15 18:58:08.000000,2021-05-15 18:58:08.000000,291.0,46.0,221.0,1243,438.0,bt - flexible backtesting for Python.,24.0,24,2021-04-21 02:49:56.000000,0.2.9,2.0,,bt,,,,,88.0,88.0,https://pypi.org/project/bt,10238.0,10238.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +284,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 01:09:14.000000,2021-12-16 10:11:53.000000,2021-12-09 07:41:07.000000,821.0,92.0,290.0,1186,3318.0,Documentation and samples for ArcGIS API for Python.,73.0,24,2021-10-04 20:36:31.000000,1.9.1,29.0,,arcgis,,esridocker/arcgis-api-python-notebook,,,,,https://pypi.org/project/arcgis,56676.0,56770.0,,,,https://hub.docker.com/r/esridocker/arcgis-api-python-notebook,2021-10-05 23:20:06.966942,33.0,5398.0,3.0,1050.0,,,,,,,,,,,,,,, +285,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 20:34:28.000000,2021-12-16 06:56:35.000000,2021-12-16 06:56:30.000000,251.0,119.0,145.0,1166,694.0,A toolkit to optimize ML models for deployment for..,64.0,24,2021-09-30 10:12:08.000000,0.7.0,15.0,,tensorflow-model-optimization,,,,['tensorflow'],1366.0,1366.0,https://pypi.org/project/tensorflow-model-optimization,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +286,empyrical,True,quantopian/empyrical,,financial-data,https://github.com/quantopian/empyrical,https://github.com/quantopian/empyrical,Apache-2.0,2016-03-18 10:22:52.000000,2020-10-14 13:28:13.625000,2020-10-14 13:22:39.000000,270.0,23.0,26.0,873,167.0,Common financial risk and performance metrics. Used by zipline and..,22.0,24,2020-10-13 21:28:25.000000,0.5.5,9.0,,empyrical,conda-forge/empyrical,,,,760.0,760.0,https://pypi.org/project/empyrical,32538.0,32849.0,https://anaconda.org/conda-forge/empyrical,2020-10-14 13:28:13.625000,14332.0,,,,,2.0,,,,,,,,,,,,,,,, +287,pingouin,True,raphaelvallat/pingouin,,probabilistics,https://github.com/raphaelvallat/pingouin,https://github.com/raphaelvallat/pingouin,GPL-3.0,2018-04-01 01:10:22.000000,2021-12-08 18:19:29.000000,2021-12-08 18:19:29.000000,76.0,24.0,154.0,868,1160.0,Statistical package in Python based on Pandas.,23.0,24,2021-10-28 22:09:53.000000,0.5.0,35.0,,pingouin,conda-forge/pingouin,,,,411.0,411.0,https://pypi.org/project/pingouin,,1359.0,https://anaconda.org/conda-forge/pingouin,2021-10-29 00:37:42.640000,48940.0,,,,,2.0,,,,,,,,,,,,,,,, +288,arch,True,bashtage/arch,,financial-data,https://github.com/bashtage/arch,https://github.com/bashtage/arch,NCSA,2014-08-29 15:41:28.000000,2021-11-19 16:04:07.000000,2021-11-19 15:39:38.000000,191.0,12.0,149.0,840,,ARCH models in Python.,30.0,24,2021-11-19 15:59:01.000000,5.1.0,35.0,,arch,,,,,423.0,423.0,https://pypi.org/project/arch,183249.0,183249.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +289,Nilearn,True,nilearn/nilearn,,medical-data,https://github.com/nilearn/nilearn,https://github.com/nilearn/nilearn,,2011-01-09 19:02:23.000000,2021-12-16 09:24:24.000000,2021-12-16 09:09:18.000000,421.0,228.0,1278.0,791,,Machine learning for NeuroImaging in Python.,177.0,24,2021-09-16 14:49:56.000000,0.8.1,16.0,,nilearn,conda-forge/nilearn,,,['sklearn'],1321.0,1321.0,https://pypi.org/project/nilearn,21352.0,23336.0,https://anaconda.org/conda-forge/nilearn,2021-09-16 18:04:31.312000,132821.0,,,,,2.0,14.0,,,,,,,,,,,,,,, +290,pyahocorasick,True,WojciechMula/pyahocorasick,,nlp,https://github.com/WojciechMula/pyahocorasick,https://github.com/WojciechMula/pyahocorasick,BSD-3-Clause,2013-05-30 19:55:46.000000,2021-11-22 22:26:54.000000,2021-11-22 22:26:54.000000,95.0,38.0,72.0,665,416.0,Python module (C extension and plain python) implementing Aho-..,23.0,24,,,4.0,,pyahocorasick,conda-forge/pyahocorasick,,,,835.0,835.0,https://pypi.org/project/pyahocorasick,320847.0,323690.0,https://anaconda.org/conda-forge/pyahocorasick,2020-10-13 12:20:05.350000,136492.0,,,,,2.0,,,,,,,,,,,,,,,, +291,Intake,True,intake/intake,,data-loading,https://github.com/intake/intake,https://github.com/intake/intake,BSD-2-Clause,2017-08-14 20:44:22.000000,2021-12-01 16:10:43.000000,2021-12-01 16:10:43.000000,110.0,72.0,210.0,665,1757.0,"Intake is a lightweight package for finding, investigating, loading and..",67.0,24,,,17.0,,intake,conda-forge/intake,,,,324.0,324.0,https://pypi.org/project/intake,11562.0,14860.0,https://anaconda.org/conda-forge/intake,2021-10-11 21:27:08.665000,122053.0,,,,,3.0,,,,,,,,,,,,,,,, +292,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 21:24:50.000000,2021-12-16 00:23:41.000000,2021-12-14 18:57:50.000000,66.0,47.0,262.0,575,79524.0,TensorFlow ROCm port.,3890.0,24,2019-10-11 17:16:09.000000,2.0.0-rocm,2.0,,tensorflow-rocm,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-rocm,1442.0,1442.0,,,,,,,,3.0,17.0,,,,,,,,,,,,,,, +293,Cornac,True,PreferredAI/cornac,,recommender-systems,https://github.com/PreferredAI/cornac,https://github.com/PreferredAI/cornac,Apache-2.0,2018-07-17 06:31:35.000000,2021-11-22 07:20:04.000000,2021-09-30 10:13:24.000000,81.0,1.0,73.0,486,1230.0,A Comparative Framework for Multimodal Recommender Systems.,13.0,24,2021-09-26 07:01:44.000000,1.14.1,40.0,,cornac,conda-forge/cornac,,,,68.0,68.0,https://pypi.org/project/cornac,7227.0,13437.0,https://anaconda.org/conda-forge/cornac,2021-11-15 19:24:15.089000,192533.0,,,,,1.0,,,,,,,,,,,,,,,, +294,DIPY,True,dipy/dipy,,medical-data,https://github.com/dipy/dipy,https://github.com/dipy/dipy,,2010-02-06 11:43:08.000000,2021-12-15 06:16:29.000000,2021-12-03 03:48:36.000000,318.0,99.0,636.0,482,11739.0,DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic..,127.0,24,,,12.0,,dipy,conda-forge/dipy,,,,475.0,475.0,https://pypi.org/project/dipy,8605.0,12695.0,https://anaconda.org/conda-forge/dipy,2021-05-06 13:36:55.402000,274065.0,,,,,2.0,,,,,,,,,,,,,,,, +295,fairseq,True,pytorch/fairseq,,nlp,https://github.com/pytorch/fairseq,https://github.com/pytorch/fairseq,MIT,2017-08-29 16:26:12.000000,2021-12-16 00:15:45.000000,2021-12-16 00:15:38.000000,3750.0,1077.0,2019.0,14840,,Facebook AI Research Sequence-to-Sequence Toolkit written in Python.,367.0,23,2021-01-05 20:26:03.000000,0.10.2,13.0,,fairseq,,,,['pytorch'],606.0,606.0,https://pypi.org/project/fairseq,,3.0,,,,,,,,2.0,157.0,,,,,,,,,,,,,,, +296,Prophet,True,facebook/prophet,,time-series-data,https://github.com/facebook/prophet,https://github.com/facebook/prophet,MIT,2016-11-16 01:50:08.000000,2021-11-09 17:34:47.000000,2021-10-03 23:20:15.000000,3902.0,162.0,1577.0,13826,,Tool for producing high quality forecasts for time series data that has..,137.0,23,2021-04-02 23:45:16.000000,1.0,10.0,,fbprophet,,,,,,,https://pypi.org/project/fbprophet,1172117.0,1172128.0,,,,,,,,2.0,639.0,,,,,,,,,,,,,,, +297,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 16:03:03.000000,2021-12-16 09:28:59.000000,2021-12-16 09:28:56.000000,2253.0,862.0,1459.0,13334,5220.0,Geometric Deep Learning Extension Library for PyTorch.,229.0,23,2021-10-26 12:41:58.000000,2.0.2,29.0,pyg-team/pytorch_geometric,torch-geometric,,,,['pytorch'],,,https://pypi.org/project/torch-geometric,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +298,torchvision,True,pytorch/vision,,image,https://github.com/pytorch/vision,https://github.com/pytorch/vision,BSD-3-Clause,2016-11-09 23:11:43.000000,2021-12-16 13:37:37.000000,2021-12-16 13:37:37.000000,5334.0,461.0,1543.0,10531,,"Datasets, Transforms and Models specific to Computer Vision.",444.0,23,2021-12-16 10:07:38.000000,0.11.2,26.0,,torchvision,conda-forge/torchvision,,,['pytorch'],,,https://pypi.org/project/torchvision,,3248.0,https://anaconda.org/conda-forge/torchvision,2021-09-27 23:35:13.750000,155921.0,,,,,2.0,,,,,,,,,,,,,,,, +299,cortex,True,cortexlabs/cortex,,model-serialisation,https://github.com/cortexlabs/cortex,https://github.com/cortexlabs/cortex,Apache-2.0,2019-01-24 04:43:14.000000,2021-12-16 03:42:42.000000,2021-12-14 22:43:29.000000,575.0,104.0,972.0,7622,2294.0,Cost-effective serverless computing at scale.,23.0,23,2021-12-08 02:15:29.000000,0.41.0,61.0,,cortex,,,,,,,https://pypi.org/project/cortex,1193.0,1193.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +300,tsfresh,True,blue-yonder/tsfresh,,time-series-data,https://github.com/blue-yonder/tsfresh,https://github.com/blue-yonder/tsfresh,MIT,2016-10-26 11:29:17.000000,2021-12-15 07:31:01.000000,2021-12-15 07:31:01.000000,929.0,38.0,433.0,6079,398.0,Automatic extraction of relevant features from time series:.,80.0,23,2021-03-06 08:49:53.000000,0.18.0,10.0,,tsfresh,conda-forge/tsfresh,,,['sklearn'],,,https://pypi.org/project/tsfresh,264668.0,266112.0,https://anaconda.org/conda-forge/tsfresh,2021-03-07 06:57:04.012000,70780.0,,,,,2.0,,,,,,,,,,,,,,,, +301,Apex,True,NVIDIA/apex,,gpu-utilities,https://github.com/NVIDIA/apex,https://github.com/NVIDIA/apex,BSD-3-Clause,2018-04-23 16:28:52.000000,2021-12-16 09:43:38.000000,2021-12-16 06:21:57.000000,850.0,510.0,392.0,5952,906.0,A PyTorch Extension: Tools for easy mixed precision and distributed..,88.0,23,,,1.0,,,conda-forge/nvidia-apex,,,['pytorch'],826.0,826.0,,,2724.0,https://anaconda.org/conda-forge/nvidia-apex,2021-04-22 16:13:47.237000,70840.0,,,,,2.0,,,,,,,,,,,,,,,, +302,mmdnn,True,Microsoft/MMdnn,,model-serialisation,https://github.com/microsoft/MMdnn,https://github.com/microsoft/MMdnn,MIT,2017-08-16 08:03:52.000000,2021-03-01 14:17:24.000000,2020-08-14 02:32:30.000000,948.0,318.0,288.0,5471,1083.0,MMdnn is a set of tools to help users inter-operate among different deep..,85.0,23,2020-07-24 06:14:52.000000,0.3.1,12.0,,mmdnn,,,,,66.0,66.0,https://pypi.org/project/mmdnn,1091.0,1161.0,,,,,,,,2.0,3474.0,,,,,,,,,,,,,,, +303,flashtext,True,vi3k6i5/flashtext,,nlp,https://github.com/vi3k6i5/flashtext,https://github.com/vi3k6i5/flashtext,MIT,2017-08-15 18:03:01.000000,2021-07-26 20:38:52.000000,2020-05-03 07:13:22.000000,551.0,45.0,51.0,5011,108.0,Extract Keywords from sentence or Replace keywords in sentences.,7.0,23,,,,,flashtext,,,,,646.0,646.0,https://pypi.org/project/flashtext,461955.0,461955.0,,,,,,,,2.0,,,,,6.0,,,,,,,,,,, +304,espnet,True,espnet/espnet,,audio,https://github.com/espnet/espnet,https://github.com/espnet/espnet,Apache-2.0,2017-12-13 00:45:11.000000,2021-12-16 10:49:26.000000,2021-12-16 09:36:27.000000,1349.0,230.0,1330.0,4528,13328.0,End-to-End Speech Processing Toolkit.,209.0,23,2021-11-10 08:24:03.000000,.0.10.4,40.0,,espnet,,,,,25.0,25.0,https://pypi.org/project/espnet,,1.0,,,,,,,,2.0,74.0,,,,,,,,,,,,,,, +305,Lucid,True,tensorflow/lucid,,interpretability,https://github.com/tensorflow/lucid,https://github.com/tensorflow/lucid,Apache-2.0,2018-01-25 17:41:44.000000,2021-07-02 01:49:08.000000,2021-03-19 15:48:33.000000,583.0,70.0,100.0,4343,667.0,A collection of infrastructure and tools for research in neural..,40.0,23,2021-03-19 15:59:35.000000,0.3.10,15.0,,lucid,,,,['tensorflow'],592.0,592.0,https://pypi.org/project/lucid,1043.0,1043.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +306,mlpack,True,mlpack/mlpack,,ml-frameworks,https://github.com/mlpack/mlpack,https://github.com/mlpack/mlpack,,2014-12-17 18:16:59.000000,2021-12-15 20:39:39.000000,2021-12-15 06:18:01.000000,1369.0,48.0,1335.0,3854,27254.0,mlpack: a scalable C++ machine learning library --.,281.0,23,2020-10-28 16:27:07.000000,3.4.2,40.0,,mlpack,conda-forge/mlpack,,,,,,https://pypi.org/project/mlpack,271.0,2616.0,https://anaconda.org/conda-forge/mlpack,2021-11-09 18:05:21.719000,96150.0,,,,,3.0,,,,,,,,,,,,,,,, +307,vaderSentiment,True,cjhutto/vaderSentiment,,nlp,https://github.com/cjhutto/vaderSentiment,https://github.com/cjhutto/vaderSentiment,MIT,2014-11-17 16:31:45.000000,2021-06-15 23:12:57.000000,2021-03-15 18:43:06.000000,819.0,30.0,74.0,3304,127.0,VADER Sentiment Analysis. VADER (Valence Aware Dictionary and..,10.0,23,2014-11-17 16:34:37.000000,0.5,1.0,,vadersentiment,,,,,3284.0,3284.0,https://pypi.org/project/vadersentiment,219492.0,219492.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +308,nevergrad,True,facebookresearch/nevergrad,,hyperopt,https://github.com/facebookresearch/nevergrad,https://github.com/facebookresearch/nevergrad,MIT,2018-11-21 00:33:17.000000,2021-12-15 18:14:42.000000,2021-12-15 18:12:10.000000,298.0,58.0,152.0,3184,,A Python toolbox for performing gradient-free optimization.,46.0,23,,,17.0,,nevergrad,conda-forge/nevergrad,,,,268.0,268.0,https://pypi.org/project/nevergrad,31737.0,32722.0,https://anaconda.org/conda-forge/nevergrad,2021-06-14 12:44:22.518000,19700.0,,,,,2.0,,,,,,,,,,,,,,,, +309,keras-vis,True,raghakot/keras-vis,,interpretability,https://github.com/raghakot/keras-vis,https://github.com/raghakot/keras-vis,MIT,2016-11-11 23:27:34.000000,2020-04-20 01:03:13.000000,2020-04-20 01:03:12.000000,614.0,114.0,99.0,2900,195.0,Neural network visualization toolkit for keras.,10.0,23,,,8.0,,keras-vis,,,,['tensorflow'],1502.0,1502.0,https://pypi.org/project/keras-vis,3623.0,3623.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +310,MMLSpark,True,Azure/mmlspark,,distributed-ml,https://github.com/microsoft/SynapseML,https://github.com/microsoft/SynapseML,MIT,2017-06-05 08:23:44.000000,2021-12-15 23:54:58.000000,2021-12-15 17:59:15.000000,586.0,194.0,281.0,2888,999.0,Microsoft Machine Learning for Apache Spark.,78.0,23,2021-11-16 05:19:37.000000,0.9.4,22.0,microsoft/SynapseML,mmlspark,,,,['spark'],,,https://pypi.org/project/mmlspark,53430.0,53430.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +311,Neural Network Libraries,True,sony/nnabla,,ml-frameworks,https://github.com/sony/nnabla,https://github.com/sony/nnabla,Apache-2.0,2017-06-26 01:07:10.000000,2021-12-16 12:02:14.000000,2021-12-16 12:02:10.000000,304.0,17.0,44.0,2512,2941.0,Neural Network Libraries.,63.0,23,2021-11-25 10:43:29.000000,1.23.0,55.0,,nnabla,,,,,,,https://pypi.org/project/nnabla,3511.0,3521.0,,,,,,,,3.0,533.0,,,,,,,,,,,,,,, +312,causalml,True,uber/causalml,,others,https://github.com/uber/causalml,https://github.com/uber/causalml,,2019-07-09 02:08:58.000000,2021-12-14 03:11:02.000000,2021-12-14 03:11:02.000000,377.0,39.0,195.0,2496,394.0,Uplift modeling and causal inference with machine learning..,31.0,23,2021-08-02 20:46:49.000000,0.11.1,5.0,,causalml,,,,,33.0,33.0,https://pypi.org/project/causalml,41290.0,41290.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +313,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 03:16:39.000000,2021-12-13 10:09:33.000000,2021-11-11 16:56:57.000000,208.0,15.0,28.0,2236,430.0,torch-optimizer -- collection of optimizers for..,25.0,23,2021-10-31 02:57:04.000000,0.3.0,20.0,,torch_optimizer,,,,['pytorch'],407.0,407.0,https://pypi.org/project/torch_optimizer,,,,,,,,,,1.0,,,,,,,,,,,,,,,, +314,Foolbox,True,bethgelab/foolbox,,adversarial,https://github.com/bethgelab/foolbox,https://github.com/bethgelab/foolbox,MIT,2017-06-14 13:05:48.000000,2021-11-10 19:47:32.000000,2021-06-05 09:38:18.000000,365.0,60.0,269.0,2105,1648.0,A Python toolbox to create adversarial examples that fool neural networks..,32.0,23,2021-02-23 07:09:34.000000,3.3.1,56.0,,foolbox,,,,,255.0,255.0,https://pypi.org/project/foolbox,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +315,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 05:00:36.000000,2021-08-22 16:33:38.000000,2021-07-10 15:56:42.000000,242.0,17.0,49.0,1997,447.0,Basic Utilities for PyTorch Natural Language Processing (NLP).,18.0,23,2019-11-04 05:16:00.000000,0.5.0,5.0,,pytorch-nlp,,,,['pytorch'],313.0,313.0,https://pypi.org/project/pytorch-nlp,7932.0,7932.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +316,polyglot,True,aboSamoor/polyglot,,nlp,https://github.com/aboSamoor/polyglot,https://github.com/aboSamoor/polyglot,GPL-3.0,2014-06-30 02:07:45.000000,2021-04-28 03:41:03.000000,2020-09-22 22:35:28.000000,304.0,136.0,64.0,1930,271.0,Multilingual text (NLP) processing toolkit.,26.0,23,,,,,polyglot,,,,,619.0,619.0,https://pypi.org/project/polyglot,85955.0,85955.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +317,TextAttack,True,QData/TextAttack,,adversarial,https://github.com/QData/TextAttack,https://github.com/QData/TextAttack,MIT,2019-10-15 00:51:44.000000,2021-12-16 02:24:09.000000,2021-12-16 02:24:09.000000,214.0,24.0,150.0,1771,2403.0,"TextAttack is a Python framework for adversarial attacks, data..",46.0,23,2021-11-10 01:24:27.000000,0.3.4,11.0,,textattack,,,,,48.0,48.0,https://pypi.org/project/textattack,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +318,scattertext,True,JasonKessler/scattertext,,nlp,https://github.com/JasonKessler/scattertext,https://github.com/JasonKessler/scattertext,Apache-2.0,2016-07-21 01:47:12.000000,2021-11-15 13:11:26.058000,2021-11-15 03:48:32.000000,231.0,17.0,65.0,1715,356.0,Beautiful visualizations of how language differs among document..,12.0,23,2017-03-13 05:31:21.000000,0.0.2.4.4,13.0,,scattertext,conda-forge/scattertext,,,,251.0,251.0,https://pypi.org/project/scattertext,3239.0,4375.0,https://anaconda.org/conda-forge/scattertext,2021-11-15 13:11:26.058000,59076.0,,,,,2.0,,,,,,,,,,,,,,,, +319,mtcnn,True,ipazc/mtcnn,,image,https://github.com/ipazc/mtcnn,https://github.com/ipazc/mtcnn,MIT,2018-01-05 04:08:32.000000,2021-11-22 17:31:06.000000,2021-07-09 11:06:18.000000,429.0,60.0,37.0,1688,56.0,"MTCNN face detection implementation for TensorFlow, as a PIP package.",15.0,23,,,,,mtcnn,,,,['tensorflow'],1744.0,1744.0,https://pypi.org/project/mtcnn,33141.0,33141.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +320,HyperTools,True,ContextLab/hypertools,,data-viz,https://github.com/ContextLab/hypertools,https://github.com/ContextLab/hypertools,MIT,2016-09-27 21:31:25.000000,2021-07-19 16:15:16.000000,2021-07-19 16:15:16.000000,155.0,67.0,122.0,1678,1599.0,A Python toolbox for gaining geometric insights into high-dimensional..,21.0,23,2021-06-15 19:22:07.000000,0.7.0,20.0,,hypertools,,,,,161.0,161.0,https://pypi.org/project/hypertools,991.0,991.0,,,,,,,,3.0,8.0,,,,,,,,,,,,,,, +321,TensorFlow Privacy,True,tensorflow/privacy,,privacy-ml,https://github.com/tensorflow/privacy,https://github.com/tensorflow/privacy,Apache-2.0,2018-12-21 18:46:46.000000,2021-12-14 21:14:59.000000,2021-12-14 18:33:04.000000,326.0,56.0,85.0,1526,557.0,Library for training machine learning models with..,43.0,23,2021-07-14 18:55:00.000000,0.6.2,9.0,,tensorflow-privacy,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-privacy,22707.0,22709.0,,,,,,,,2.0,59.0,,,,,,,,,,,,,,, +322,Karate Club,True,benedekrozemberczki/karateclub,,graph,https://github.com/benedekrozemberczki/karateclub,https://github.com/benedekrozemberczki/karateclub,GPL-3.0,2019-12-05 17:35:56.000000,2021-11-21 17:31:34.000000,2021-11-21 17:31:16.000000,172.0,1.0,64.0,1459,2202.0,Karate Club: An API Oriented Open-source Python Framework for..,13.0,23,2021-09-29 21:05:51.000000,_10202,97.0,,karateclub,,,,,65.0,65.0,https://pypi.org/project/karateclub,5154.0,5154.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +323,CausalNex,True,quantumblacklabs/causalnex,,interpretability,https://github.com/quantumblacklabs/causalnex,https://github.com/quantumblacklabs/causalnex,Apache-2.0,2019-12-12 15:26:09.000000,2021-11-11 15:15:24.000000,2021-11-11 15:06:17.000000,147.0,13.0,87.0,1389,155.0,A Python library that helps data scientists to infer..,22.0,23,2021-11-11 15:15:24.000000,0.11.0,15.0,,causalnex,,,,"['pytorch', 'sklearn']",33.0,33.0,https://pypi.org/project/causalnex,4352.0,4352.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +324,fklearn,True,nubank/fklearn,,ml-frameworks,https://github.com/nubank/fklearn,https://github.com/nubank/fklearn,Apache-2.0,2019-02-27 14:32:57.000000,2021-12-06 18:25:49.000000,2021-12-06 18:24:05.000000,151.0,19.0,21.0,1362,131.0,fklearn: Functional Machine Learning.,40.0,23,2021-12-06 18:25:50.000000,1.24.0,20.0,,fklearn,,,,,10.0,10.0,https://pypi.org/project/fklearn,3968.0,3968.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +325,ViZDoom,True,mwydmuch/ViZDoom,,reinforcement-learning,https://github.com/mwydmuch/ViZDoom,https://github.com/mwydmuch/ViZDoom,,2015-06-26 18:38:23.000000,2021-12-13 14:31:49.000000,2021-12-13 14:31:38.000000,302.0,82.0,343.0,1296,1522.0,Doom-based AI Research Platform for Reinforcement Learning from Raw..,45.0,23,2021-11-22 11:15:55.000000,1.1.11,22.0,,vizdoom,,,,,118.0,118.0,https://pypi.org/project/vizdoom,,165.0,,,,,,,,1.0,11409.0,,,,,,,,,,,,,,, +326,livelossplot,True,stared/livelossplot,,ml-experiments,https://github.com/stared/livelossplot,https://github.com/stared/livelossplot,MIT,2018-03-10 17:51:43.000000,2021-10-12 11:52:57.000000,2021-10-12 11:52:20.000000,138.0,3.0,70.0,1141,328.0,"Live training loss plot in Jupyter Notebook for Keras,..",17.0,23,,,,,livelossplot,,,,['jupyter'],693.0,693.0,https://pypi.org/project/livelossplot,78647.0,78647.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +327,Graphviz,True,xflr6/graphviz,,data-viz,https://github.com/xflr6/graphviz,https://github.com/xflr6/graphviz,MIT,2014-01-12 17:49:29.000000,2021-12-15 10:43:17.000000,2021-12-15 10:43:09.000000,162.0,4.0,118.0,1113,1128.0,Simple Python interface for Graphviz.,17.0,23,,,,,graphviz,,,,,26399.0,26399.0,https://pypi.org/project/graphviz,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +328,ffn,True,pmorissette/ffn,,financial-data,https://github.com/pmorissette/ffn,https://github.com/pmorissette/ffn,MIT,2014-06-19 15:54:09.000000,2021-05-15 18:59:42.000000,2021-04-24 00:58:10.000000,192.0,16.0,80.0,1018,351.0,ffn - a financial function library for Python.,26.0,23,2021-04-21 02:47:05.000000,0.3.6,3.0,,ffn,,,,,160.0,160.0,https://pypi.org/project/ffn,41707.0,41707.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +329,PySAL,True,pysal/pysal,,geospatial-data,https://github.com/pysal/pysal,https://github.com/pysal/pysal,BSD-3-Clause,2013-02-19 17:27:42.000000,2021-10-18 18:27:28.000000,2021-10-18 18:27:28.000000,254.0,10.0,591.0,949,4136.0,PySAL: Python Spatial Analysis Library Meta-Package.,73.0,23,2021-08-01 00:02:42.000000,2.5.0,20.0,,pysal,conda-forge/pysal,,,,,,https://pypi.org/project/pysal,21599.0,28223.0,https://anaconda.org/conda-forge/pysal,2021-08-02 16:50:41.186000,430566.0,,,,,3.0,,,,,,,,,,,,,,,, +330,bcolz,True,Blosc/bcolz,,data-containers,https://github.com/Blosc/bcolz,https://github.com/Blosc/bcolz,,2010-08-18 15:27:02.000000,2021-09-07 20:42:40.000000,2020-09-10 12:12:45.000000,124.0,122.0,122.0,935,1280.0,A columnar data container that can be compressed.,33.0,23,2018-04-13 07:34:26.000000,1.2.1,3.0,,bcolz,conda-forge/bcolz,,,,1683.0,1683.0,https://pypi.org/project/bcolz,13680.0,18492.0,https://anaconda.org/conda-forge/bcolz,2019-11-05 21:09:48.045000,279116.0,,,,,3.0,,,,,,,,,,,,,,,, +331,PySwarms,True,ljvmiranda921/pyswarms,,others,https://github.com/ljvmiranda921/pyswarms,https://github.com/ljvmiranda921/pyswarms,MIT,2017-07-12 12:04:45.000000,2021-12-03 19:52:38.000000,2021-06-23 11:19:05.000000,280.0,16.0,181.0,866,409.0,A research toolkit for particle swarm optimization in Python.,43.0,23,2020-11-14 05:18:38.000000,.1.2.0,15.0,,pyswarms,,,,,147.0,147.0,https://pypi.org/project/pyswarms,38587.0,38587.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +332,TensorFlow Text,True,tensorflow/text,,nlp,https://github.com/tensorflow/text,https://github.com/tensorflow/text,Apache-2.0,2019-05-29 22:10:03.000000,2021-12-16 07:19:51.000000,2021-12-08 17:16:06.000000,163.0,24.0,116.0,864,577.0,Making text a first-class citizen in TensorFlow.,66.0,23,2021-11-19 12:59:24.000000,2.7.3,33.0,,tensorflow-text,,,,['tensorflow'],1248.0,1248.0,https://pypi.org/project/tensorflow-text,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +333,GPUtil,True,anderskm/gputil,,gpu-utilities,https://github.com/anderskm/gputil,https://github.com/anderskm/gputil,MIT,2017-01-16 11:57:43.000000,2020-10-01 05:42:49.000000,2019-08-16 09:00:15.000000,85.0,11.0,14.0,802,140.0,A Python module for getting the GPU status from NVIDA GPUs using..,13.0,23,2018-12-18 08:58:49.000000,1.4.0,8.0,,gputil,,,,,1633.0,1633.0,https://pypi.org/project/gputil,433301.0,433301.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +334,kapre,True,keunwoochoi/kapre,,audio,https://github.com/keunwoochoi/kapre,https://github.com/keunwoochoi/kapre,MIT,2016-12-14 18:36:36.000000,2021-12-14 18:04:32.000000,2021-11-14 01:15:18.000000,137.0,11.0,82.0,794,193.0,kapre: Keras Audio Preprocessors.,13.0,23,2021-11-14 01:12:39.000000,Kapre-0.3.6,9.0,,kapre,,,,['tensorflow'],1246.0,1246.0,https://pypi.org/project/kapre,1796.0,1796.0,,,,,,,,2.0,19.0,,,,,,,,,,,,,,, +335,GPyOpt,True,SheffieldML/GPyOpt,,hyperopt,https://github.com/SheffieldML/GPyOpt,https://github.com/SheffieldML/GPyOpt,BSD-3-Clause,2014-08-13 09:58:25.000000,2020-11-17 10:32:02.000000,2020-11-05 15:16:04.000000,236.0,99.0,186.0,782,514.0,Gaussian Process Optimization using GPy.,49.0,23,2020-03-19 21:21:18.000000,1.2.6,1.0,,gpyopt,,,,,234.0,234.0,https://pypi.org/project/gpyopt,18098.0,18098.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +336,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 15:56:06.000000,2021-11-30 22:00:24.715000,2021-11-30 14:46:11.000000,210.0,186.0,234.0,770,,Scalable Machine Learning with Dask.,69.0,23,2021-11-30 15:20:30.000000,2021.11.30,25.0,,dask-ml,conda-forge/dask-ml,,,,527.0,527.0,https://pypi.org/project/dask-ml,,5116.0,https://anaconda.org/conda-forge/dask-ml,2021-11-30 22:00:24.715000,255843.0,,,,,2.0,,,,,,,,,,,,,,,, +337,Pandas-Bokeh,True,PatrikHlobil/Pandas-Bokeh,,data-viz,https://github.com/PatrikHlobil/Pandas-Bokeh,https://github.com/PatrikHlobil/Pandas-Bokeh,MIT,2018-11-23 20:49:14.000000,2021-11-01 09:41:26.000000,2021-05-10 08:14:09.000000,93.0,27.0,66.0,735,289.0,Bokeh Plotting Backend for Pandas and GeoPandas.,12.0,23,2021-04-11 17:42:31.000000,0.5.5,5.0,,pandas-bokeh,,,,['pandas'],256.0,256.0,https://pypi.org/project/pandas-bokeh,10826.0,10826.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +338,Sentinelsat,True,sentinelsat/sentinelsat,,geospatial-data,https://github.com/sentinelsat/sentinelsat,https://github.com/sentinelsat/sentinelsat,GPL-3.0,2015-05-22 20:32:26.000000,2021-12-02 13:46:18.000000,2021-12-02 13:46:18.000000,186.0,7.0,306.0,701,,Search and download Copernicus Sentinel satellite images.,42.0,23,2021-08-19 17:36:48.000000,1.1.0,11.0,,sentinelsat,,,,,256.0,256.0,https://pypi.org/project/sentinelsat,23218.0,23221.0,,,,,,,,3.0,226.0,,,,,,,,,,,,,,, +339,SDV,True,sdv-dev/SDV,,data-loading,https://github.com/sdv-dev/SDV,https://github.com/sdv-dev/SDV,MIT,2018-05-11 15:56:50.000000,2021-12-15 19:05:18.000000,2021-12-15 19:05:17.000000,105.0,137.0,277.0,597,946.0,"Synthetic Data Generation for tabular, relational and time series data.",39.0,23,2021-11-22 21:06:54.000000,0.13.0,32.0,,sdv,,,,,41.0,41.0,https://pypi.org/project/sdv,22571.0,22571.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +340,snowballstemmer,True,snowballstem/snowball,,nlp,https://github.com/snowballstem/snowball,https://github.com/snowballstem/snowball,BSD-3-Clause,2013-02-23 07:17:42.000000,2021-12-08 15:51:34.000000,2021-11-16 18:29:31.000000,144.0,13.0,44.0,534,918.0,Snowball compiler and stemming algorithms.,28.0,23,,,6.0,,snowballstemmer,conda-forge/snowballstemmer,,,,4.0,4.0,https://pypi.org/project/snowballstemmer,5730798.0,5786181.0,https://anaconda.org/conda-forge/snowballstemmer,2021-11-17 09:59:16.947000,3544512.0,,,,,2.0,,,,,,,,,,,,,,,, +341,python-ternary,True,marcharper/python-ternary,,data-viz,https://github.com/marcharper/python-ternary,https://github.com/marcharper/python-ternary,MIT,2012-08-07 23:48:55.000000,2021-10-21 03:04:53.000000,2021-10-21 03:04:53.000000,128.0,25.0,90.0,498,393.0,Ternary plotting library for python with matplotlib.,27.0,23,2021-02-17 18:23:31.000000,1.0.8,8.0,,python-ternary,conda-forge/python-ternary,,,,76.0,76.0,https://pypi.org/project/python-ternary,21060.0,21946.0,https://anaconda.org/conda-forge/python-ternary,2021-02-17 22:38:55.625000,60284.0,,,,,3.0,17.0,,,,,,,,,,,,,,, +342,CNTK,True,microsoft/CNTK,,ml-frameworks,https://github.com/microsoft/CNTK,https://github.com/microsoft/CNTK,,2015-11-26 09:52:06.000000,2021-08-27 04:46:43.000000,2020-03-31 15:55:14.000000,4270.0,753.0,2524.0,17116,16116.0,"Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.",271.0,22,2019-04-26 14:13:32.000000,2.7,32.0,,cntk,,,,,,,https://pypi.org/project/cntk,1528.0,1723.0,,,,,,,,3.0,13894.0,,,,,,,,,,,,,,, +343,Streamlit,True,streamlit/streamlit,,others,https://github.com/streamlit/streamlit,https://github.com/streamlit/streamlit,Apache-2.0,2019-08-24 00:14:52.000000,2021-12-16 06:34:37.000000,2021-12-15 21:32:11.000000,1499.0,499.0,1644.0,16884,,Streamlit The fastest way to build data apps in Python.,132.0,22,2021-11-11 19:39:24.000000,1.2.0,26.0,,streamlit,,,,,187.0,187.0,https://pypi.org/project/streamlit,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +344,baselines,True,openai/baselines,,reinforcement-learning,https://github.com/openai/baselines,https://github.com/openai/baselines,MIT,2017-05-24 01:58:13.000000,2021-12-03 07:10:56.000000,2020-01-31 13:06:18.000000,3312.0,391.0,430.0,12153,347.0,OpenAI Baselines: high-quality implementations of reinforcement..,114.0,22,,,,,baselines,,,,,358.0,358.0,https://pypi.org/project/baselines,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +345,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 15:54:23.000000,2021-07-29 10:41:37.000000,2020-04-16 08:02:22.000000,1715.0,80.0,91.0,8314,154.0,"Pretrained ConvNets for pytorch: NASNet, ResNeXt,..",22.0,22,,,,,pretrainedmodels,,,,['pytorch'],1331.0,1331.0,https://pypi.org/project/pretrainedmodels,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +346,Qlib,True,microsoft/qlib,,financial-data,https://github.com/microsoft/qlib,https://github.com/microsoft/qlib,MIT,2020-08-14 06:46:00.000000,2021-12-15 12:41:48.000000,2021-12-14 10:13:04.000000,1209.0,123.0,248.0,7564,,"Qlib is an AI-oriented quantitative investment platform, which aims to..",72.0,22,2021-12-07 23:35:35.000000,0.8.0,10.0,,pyqlib,,,,['pytorch'],8.0,8.0,https://pypi.org/project/pyqlib,3237.0,3254.0,,,,,,,,3.0,269.0,,,,,,,,,,,,,,, +347,Vaex,True,vaexio/vaex,,data-containers,https://github.com/vaexio/vaex,https://github.com/vaexio/vaex,MIT,2014-09-27 09:44:42.000000,2021-12-16 13:43:20.000000,2021-12-16 13:43:20.000000,520.0,284.0,608.0,6788,3341.0,"Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and..",62.0,22,2018-03-29 14:50:46.000000,aexpaper_1,22.0,,vaex,conda-forge/vaex,,,,,,https://pypi.org/project/vaex,22009.0,23948.0,https://anaconda.org/conda-forge/vaex,2021-11-30 10:56:24.298000,120117.0,,,,,3.0,220.0,,,,,,,,,,,,,,, +348,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 05:24:11.000000,2021-11-02 08:10:31.000000,2021-04-15 15:16:36.000000,1321.0,130.0,134.0,6681,162.0,A PyTorch implementation of EfficientNet and..,24.0,22,2020-03-01 03:29:43.000000,1.0,1.0,,efficientnet-pytorch,,,,['pytorch'],,,https://pypi.org/project/efficientnet-pytorch,241342.0,291100.0,,,,,,,,2.0,1044926.0,,,,,,,,,,,,,,, +349,Trax,True,google/trax,,others,https://github.com/google/trax,https://github.com/google/trax,Apache-2.0,2019-10-05 15:09:14.000000,2021-12-09 04:26:32.000000,2021-12-03 21:48:53.000000,665.0,84.0,119.0,6664,1590.0,Trax Deep Learning with Clear Code and Speed.,74.0,22,2021-10-26 20:29:38.000000,1.4.1,18.0,,trax,,,,,40.0,40.0,https://pypi.org/project/trax,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +350,SpeechRecognition,True,Uberi/speech_recognition,,audio,https://github.com/Uberi/speech_recognition,https://github.com/Uberi/speech_recognition,,2014-04-23 04:53:54.000000,2021-12-14 05:54:09.000000,2021-12-14 05:54:08.000000,1935.0,212.0,279.0,5993,361.0,"Speech recognition module for Python, supporting..",41.0,22,2017-12-05 14:05:14.000000,3.8.1,23.0,,SpeechRecognition,conda-forge/speechrecognition,,,,,,https://pypi.org/project/SpeechRecognition,241569.0,243622.0,https://anaconda.org/conda-forge/speechrecognition,2021-12-13 09:59:53.408000,131418.0,,,,,3.0,,,,,,,,,,,,,,,, +351,snownlp,True,isnowfy/snownlp,,chinese-nlp,https://github.com/isnowfy/snownlp,https://github.com/isnowfy/snownlp,MIT,2013-11-26 11:46:56.000000,2020-01-19 02:39:05.000000,2020-01-19 02:39:03.000000,1287.0,39.0,65.0,5644,57.0,Python library for processing Chinese text.,8.0,22,,,,,snownlp,,,,,754.0,754.0,https://pypi.org/project/snownlp,8773.0,8773.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +352,OCRmyPDF,True,jbarlow83/OCRmyPDF,,ocr,https://github.com/ocrmypdf/OCRmyPDF,https://github.com/ocrmypdf/OCRmyPDF,MPL-2.0,2013-12-20 08:26:28.000000,2021-12-11 07:21:29.000000,2021-12-11 05:49:04.000000,511.0,87.0,690.0,5534,3132.0,"OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them..",58.0,22,2016-02-17 09:22:48.000000,4.0,5.0,ocrmypdf/OCRmyPDF,ocrmypdf,,,,,,,https://pypi.org/project/ocrmypdf,21222.0,21222.0,,,,,,,,2.0,,,,,,,,ocrmypdf,,,,,ocrmypdf,,, +353,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 15:53:12.000000,2020-11-20 07:32:13.000000,2019-11-11 22:14:54.000000,1271.0,10.0,219.0,5165,308.0,Deep Reinforcement Learning for Keras.,40.0,22,2018-05-01 14:27:32.000000,0.4.2,8.0,,keras-rl,,,,['tensorflow'],540.0,540.0,https://pypi.org/project/keras-rl,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +354,scikit-surprise,True,NicolasHug/Surprise,,recommender-systems,https://github.com/NicolasHug/Surprise,https://github.com/NicolasHug/Surprise,BSD-3-Clause,2016-10-23 14:59:38.000000,2021-11-18 20:15:44.176000,2020-08-05 17:45:59.000000,888.0,42.0,292.0,5146,622.0,A Python scikit for building and analyzing recommender..,38.0,22,,,6.0,,scikit-surprise,conda-forge/scikit-surprise,,,,,,https://pypi.org/project/scikit-surprise,72420.0,76769.0,https://anaconda.org/conda-forge/scikit-surprise,2021-11-18 20:15:44.176000,204426.0,,,,,2.0,,,,,,,,,,,,,,,, +355,librosa,True,librosa/librosa,,audio,https://github.com/librosa/librosa,https://github.com/librosa/librosa,ISC,2012-10-20 14:21:01.000000,2021-12-14 15:13:16.000000,2021-12-13 17:46:07.000000,760.0,33.0,888.0,4895,,Python library for audio and music analysis.,92.0,22,2021-05-26 10:10:29.000000,0.8.1,31.0,,librosa,conda-forge/librosa,,,,,,https://pypi.org/project/librosa,560803.0,567242.0,https://anaconda.org/conda-forge/librosa,2021-05-26 10:44:27.607000,418543.0,,,,,3.0,,,,,,,,,,,,,,,, +356,TinyDB,True,msiemens/tinydb,,data-containers,https://github.com/msiemens/tinydb,https://github.com/msiemens/tinydb,MIT,2013-07-12 23:31:13.000000,2021-12-14 10:05:58.000000,2021-12-04 14:24:59.000000,408.0,6.0,265.0,4712,637.0,TinyDB is a lightweight document oriented database optimized for your..,70.0,22,2021-09-23 18:07:35.000000,4.5.2,56.0,,tinydb,conda-forge/tinydb,,,,,,https://pypi.org/project/tinydb,,2292.0,https://anaconda.org/conda-forge/tinydb,2021-09-23 23:38:10.536000,151335.0,,,,,3.0,,,,,,,,,,,,,,,, +357,Image Deduplicator,True,idealo/imagededup,,image,https://github.com/idealo/imagededup,https://github.com/idealo/imagededup,Apache-2.0,2019-04-05 12:10:54.000000,2021-12-11 13:35:48.000000,2020-11-23 17:40:40.000000,334.0,28.0,59.0,3904,460.0,Finding duplicate images made easy!.,10.0,22,2020-11-23 17:55:24.000000,0.2.4,5.0,,imagededup,,,,['tensorflow'],21.0,21.0,https://pypi.org/project/imagededup,2817.0,2817.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +358,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 21:45:14.000000,2021-12-15 21:04:45.000000,2021-12-13 19:09:48.000000,529.0,37.0,333.0,3849,,Code for the paper Exploring the Limits of Transfer Learning with a..,44.0,22,2020-04-03 19:06:25.000000,0.4.0,1.0,,t5,,,,['tensorflow'],72.0,72.0,https://pypi.org/project/t5,8141.0,8141.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +359,Lasagne,True,Lasagne/Lasagne,,ml-frameworks,https://github.com/Lasagne/Lasagne,https://github.com/Lasagne/Lasagne,,2014-09-11 15:31:41.000000,2019-11-20 20:28:31.000000,2019-11-20 20:28:30.000000,935.0,115.0,402.0,3799,1161.0,Lightweight library to build and train neural networks in Theano.,72.0,22,2015-08-13 21:00:09.000000,0.1,1.0,,lasagne,,,,,880.0,880.0,https://pypi.org/project/lasagne,3040.0,3040.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +360,FATE,True,FederatedAI/FATE,,privacy-ml,https://github.com/FederatedAI/FATE,https://github.com/FederatedAI/FATE,Apache-2.0,2019-01-24 10:32:43.000000,2021-12-16 10:02:18.000000,2021-12-14 04:10:57.000000,1104.0,341.0,676.0,3771,9678.0,An Industrial Grade Federated Learning Framework.,68.0,22,2021-11-24 09:37:50.000000,1.7.0,29.0,,,,,,,,,,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +361,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 21:28:32.000000,2021-12-07 23:06:23.000000,2021-12-07 23:03:39.000000,815.0,22.0,172.0,3641,941.0,"An open source reinforcement learning framework for training,..",57.0,22,2021-05-10 18:04:30.000000,1.0.3,6.0,,tensortrade,,,,,27.0,27.0,https://pypi.org/project/tensortrade,1019.0,1019.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +362,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 16:16:36.000000,2021-11-17 15:23:01.000000,2021-05-03 12:18:31.000000,479.0,55.0,196.0,3583,2154.0,Snips Python library to extract meaning from text.,22.0,22,2020-01-15 09:51:41.000000,0.20.2,58.0,,snips-nlu,,,,,,,https://pypi.org/project/snips-nlu,4497.0,4497.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +363,PyAlgoTrade,True,gbeced/pyalgotrade,,financial-data,https://github.com/gbeced/pyalgotrade,https://github.com/gbeced/pyalgotrade,Apache-2.0,2012-03-07 01:09:54.000000,2021-11-28 22:07:38.000000,2018-08-21 02:42:52.000000,1198.0,36.0,84.0,3562,1156.0,Python Algorithmic Trading Library.,11.0,22,,,,,pyalgotrade,,,,,98.0,98.0,https://pypi.org/project/pyalgotrade,980.0,980.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +364,Alpha Vantage,True,RomelTorres/alpha_vantage,,financial-data,https://github.com/RomelTorres/alpha_vantage,https://github.com/RomelTorres/alpha_vantage,MIT,2017-04-29 17:23:00.000000,2021-12-06 01:38:57.000000,2021-06-14 05:10:42.000000,626.0,4.0,248.0,3555,497.0,A python wrapper for Alpha Vantage API for financial data.,39.0,22,2020-12-21 02:37:29.000000,2.3.1,5.0,,alpha_vantage,,,,,,,https://pypi.org/project/alpha_vantage,23243.0,23243.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +365,DoWhy,True,Microsoft/dowhy,,interpretability,https://github.com/microsoft/dowhy,https://github.com/microsoft/dowhy,MIT,2018-05-31 13:07:04.000000,2021-12-05 16:33:38.000000,2021-12-05 16:33:33.000000,520.0,47.0,114.0,3474,471.0,DoWhy is a Python library for causal inference that supports explicit..,45.0,22,2021-03-03 03:44:46.000000,0.6,6.0,,dowhy,conda-forge/dowhy,,,,78.0,78.0,https://pypi.org/project/dowhy,,213.0,https://anaconda.org/conda-forge/dowhy,2021-04-28 19:20:04.698000,4062.0,,,,,2.0,24.0,,,,,,,,,,,,,,, +366,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 13:41:13.000000,2021-11-02 15:48:01.000000,2021-06-02 09:45:13.000000,571.0,80.0,108.0,3287,150.0,Super-scale your images and run experiments with..,10.0,22,2020-01-08 15:35:45.000000,2.2.0,1.0,,ISR,,idealo/image-super-resolution-gpu,,['tensorflow'],68.0,68.0,https://pypi.org/project/ISR,5781.0,5786.0,,,,https://hub.docker.com/r/idealo/image-super-resolution-gpu,2019-04-01 13:48:45.697251,,192.0,3.0,,,,,,,,,,,,,,,, +367,Chartify,True,spotify/chartify,,data-viz,https://github.com/spotify/chartify,https://github.com/spotify/chartify,Apache-2.0,2018-09-17 14:12:05.000000,2021-09-17 06:10:10.000000,2021-02-05 18:49:02.000000,271.0,40.0,31.0,3052,195.0,Python library that makes it easy for data scientists to create..,21.0,22,2020-11-02 22:13:24.000000,3.0.3,16.0,,chartify,conda-forge/chartify,,,,61.0,61.0,https://pypi.org/project/chartify,,466.0,https://anaconda.org/conda-forge/chartify,2020-11-07 19:52:50.628000,17251.0,,,,,3.0,,,,,,,,,,,,,,,, +368,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 10:44:32.000000,2021-07-19 16:40:30.000000,2020-12-08 16:56:38.000000,1020.0,415.0,1100.0,2860,16205.0,Unified and efficient Machine Learning.,248.0,22,2019-07-05 10:23:31.000000,shogun_6.1.4,10.0,,,conda-forge/shogun,shogun/shogun,,,,,,,2086.0,https://anaconda.org/conda-forge/shogun,2018-06-25 20:49:17.070000,109975.0,https://hub.docker.com/r/shogun/shogun,2019-01-31 13:45:10.435327,1.0,1472.0,3.0,,,,,,,,shogun,,,,,,,, +369,Hummingbird,True,microsoft/hummingbird,,model-serialisation,https://github.com/microsoft/hummingbird,https://github.com/microsoft/hummingbird,MIT,2020-03-12 20:27:03.000000,2021-12-16 02:06:44.000000,2021-12-16 00:55:51.000000,205.0,49.0,177.0,2704,,Hummingbird compiles trained ML models into tensor computation for..,27.0,22,2021-12-14 19:31:26.000000,0.4.2,15.0,,hummingbird-ml,,,,,20.0,20.0,https://pypi.org/project/hummingbird-ml,3102.0,3109.0,,,,,,,,3.0,147.0,,,,,,,,,,,,,,, +370,Sumy,True,miso-belica/sumy,,nlp,https://github.com/miso-belica/sumy,https://github.com/miso-belica/sumy,Apache-2.0,2013-02-20 12:56:48.000000,2021-11-23 21:07:29.000000,2021-11-23 21:07:29.000000,454.0,13.0,80.0,2701,,Module for automatic summarization of text documents and HTML pages.,21.0,22,2021-10-21 17:21:15.000000,0.9.0,13.0,,sumy,,,,,1035.0,1035.0,https://pypi.org/project/sumy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +371,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 13:37:30.000000,2021-12-09 18:45:30.000000,2021-12-09 18:45:24.000000,489.0,81.0,441.0,2520,1091.0,Arctic is a high performance datastore for numeric data.,72.0,22,2020-12-01 23:17:26.000000,1.79.4,5.0,,arctic,conda-forge/arctic,,,,143.0,143.0,https://pypi.org/project/arctic,,544.0,https://anaconda.org/conda-forge/arctic,2019-12-16 08:57:24.231000,16820.0,,,,,3.0,178.0,,,,,,,,,,,,,,, +372,PandasGUI,True,adamerose/pandasgui,,data-viz,https://github.com/adamerose/PandasGUI,https://github.com/adamerose/PandasGUI,MIT,2019-06-12 02:19:42.000000,2021-12-09 23:12:05.000000,2021-09-25 15:27:41.000000,154.0,32.0,109.0,2492,706.0,A GUI for Pandas DataFrames.,10.0,22,,,,,pandasgui,,,,['pandas'],118.0,118.0,https://pypi.org/project/pandasgui,9327.0,9327.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +373,eli5,True,TeamHG-Memex/eli5,,interpretability,https://github.com/TeamHG-Memex/eli5,https://github.com/TeamHG-Memex/eli5,MIT,2016-09-15 01:04:57.000000,2021-06-10 22:02:56.000000,2020-01-22 07:39:36.000000,306.0,137.0,111.0,2477,1198.0,A library for debugging/inspecting machine learning classifiers and..,14.0,22,,,10.0,,eli5,conda-forge/eli5,,,,,,https://pypi.org/project/eli5,1568402.0,1570335.0,https://anaconda.org/conda-forge/eli5,2021-01-25 08:24:59.385000,106356.0,,,,,2.0,,,,,,,,,,,,,,,, +374,Acme,True,deepmind/acme,,reinforcement-learning,https://github.com/deepmind/acme,https://github.com/deepmind/acme,Apache-2.0,2020-05-01 09:18:12.000000,2021-12-13 14:00:06.000000,2021-12-13 13:59:30.000000,286.0,40.0,104.0,2436,659.0,A library of reinforcement learning components and agents.,53.0,22,2021-12-09 12:30:43.000000,0.2.4,10.0,,dm-acme,,,,['tensorflow'],47.0,47.0,https://pypi.org/project/dm-acme,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +375,DeepVariant,True,google/deepvariant,,medical-data,https://github.com/google/deepvariant,https://github.com/google/deepvariant,BSD-3-Clause,2017-11-23 01:56:22.000000,2021-12-16 06:56:52.044000,2021-12-10 22:24:30.000000,575.0,4.0,446.0,2397,1838.0,DeepVariant is an analysis pipeline that uses a deep neural..,21.0,22,2021-12-10 07:12:31.000000,1.3.0,17.0,,,bioconda/deepvariant,,,['tensorflow'],,,,,840.0,https://anaconda.org/bioconda/deepvariant,2021-12-16 06:56:52.044000,35892.0,,,,,2.0,3743.0,,,,,,,,,,,,,,, +376,Texar,True,asyml/texar,,nlp,https://github.com/asyml/texar,https://github.com/asyml/texar,Apache-2.0,2017-07-22 19:02:05.000000,2021-08-26 09:49:50.000000,2020-07-29 00:38:30.000000,356.0,31.0,126.0,2236,1719.0,"Toolkit for Machine Learning, Natural Language Processing, and..",43.0,22,2019-11-19 03:54:40.000000,0.2.4,6.0,,texar,,,,['tensorflow'],17.0,17.0,https://pypi.org/project/texar,175.0,175.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +377,StellarGraph,True,stellargraph/stellargraph,,graph,https://github.com/stellargraph/stellargraph,https://github.com/stellargraph/stellargraph,Apache-2.0,2018-04-13 07:35:51.000000,2021-12-07 09:11:08.000000,2021-10-29 06:15:49.000000,325.0,248.0,729.0,2232,2515.0,StellarGraph - Machine Learning on Graphs.,36.0,22,2020-06-30 05:15:21.000000,1.2.1,25.0,,stellargraph,,,,['tensorflow'],100.0,100.0,https://pypi.org/project/stellargraph,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +378,STUMPY,True,TDAmeritrade/stumpy,,time-series-data,https://github.com/TDAmeritrade/stumpy,https://github.com/TDAmeritrade/stumpy,BSD-3-Clause,2019-05-03 19:23:44.000000,2021-12-15 14:27:05.960000,2021-12-15 14:09:52.000000,192.0,27.0,241.0,2018,,STUMPY is a powerful and scalable Python library for computing a Matrix..,26.0,22,2021-12-15 14:24:52.000000,1.10.1,22.0,,stumpy,conda-forge/stumpy,,,,,,https://pypi.org/project/stumpy,315054.0,316148.0,https://anaconda.org/conda-forge/stumpy,2021-12-15 14:27:05.960000,33941.0,,,,,2.0,,,,,,,,,,,,,,,, +379,SRU,True,asappresearch/sru,,pytorch-utils,https://github.com/asappresearch/sru,https://github.com/asappresearch/sru,MIT,2017-08-28 20:37:41.000000,2021-06-29 18:11:30.000000,2021-05-19 15:52:48.000000,294.0,54.0,67.0,2008,400.0,Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755).,21.0,22,2021-05-18 16:12:33.000000,2.6.0,29.0,,sru,,,,['pytorch'],17.0,17.0,https://pypi.org/project/sru,2990.0,2990.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +380,m2cgen,True,BayesWitnesses/m2cgen,,model-serialisation,https://github.com/BayesWitnesses/m2cgen,https://github.com/BayesWitnesses/m2cgen,MIT,2019-01-13 02:32:55.000000,2021-11-25 12:36:04.000000,2021-11-25 12:36:04.000000,161.0,34.0,48.0,1959,327.0,"Transform ML models into a native code (Java, C, Python, Go, JavaScript,..",12.0,22,2020-09-18 19:17:26.000000,0.9.0,12.0,,m2cgen,,,,,7.0,7.0,https://pypi.org/project/m2cgen,54193.0,54193.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +381,efficientnet,True,qubvel/efficientnet,,tensorflow-utils,https://github.com/qubvel/efficientnet,https://github.com/qubvel/efficientnet,Apache-2.0,2019-05-30 20:21:09.000000,2021-08-16 07:14:52.000000,2021-07-16 09:03:20.000000,433.0,52.0,56.0,1918,66.0,Implementation of EfficientNet model. Keras and..,10.0,22,2020-09-15 16:22:45.000000,1.1.1,8.0,,efficientnet,,,,['tensorflow'],833.0,833.0,https://pypi.org/project/efficientnet,,6373.0,,,,,,,,2.0,197574.0,,,,,,,,,,,,,,, +382,langid,True,saffsd/langid.py,,nlp,https://github.com/saffsd/langid.py,https://github.com/saffsd/langid.py,,2011-04-29 00:16:56.000000,2020-01-01 10:49:30.000000,2017-07-15 02:49:17.000000,276.0,26.0,45.0,1891,242.0,Stand-alone language identification system.,9.0,22,,,,,langid,,,,,868.0,868.0,https://pypi.org/project/langid,330437.0,330437.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +383,dtreeviz,True,parrt/dtreeviz,,interpretability,https://github.com/parrt/dtreeviz,https://github.com/parrt/dtreeviz,MIT,2018-08-13 21:45:15.000000,2021-12-03 00:18:48.000000,2021-12-03 00:18:48.000000,235.0,18.0,93.0,1852,373.0,A python library for decision tree visualization and model interpretation.,17.0,22,2021-11-10 22:55:11.000000,1.3.2,21.0,,dtreeviz,,,,,274.0,274.0,https://pypi.org/project/dtreeviz,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +384,swifter,True,jmcarpenter2/swifter,,data-containers,https://github.com/jmcarpenter2/swifter,https://github.com/jmcarpenter2/swifter,MIT,2018-04-07 21:37:19.000000,2021-10-27 19:07:25.000000,2021-06-25 21:30:09.000000,84.0,23.0,83.0,1840,427.0,A package which efficiently applies any function to a pandas..,14.0,22,,,19.0,,swifter,conda-forge/swifter,,,['pandas'],437.0,437.0,https://pypi.org/project/swifter,,3907.0,https://anaconda.org/conda-forge/swifter,2021-06-26 01:03:15.021000,125043.0,,,,,3.0,,,,,,,,,,,,,,,, +385,hnswlib,True,nmslib/hnswlib,,nn-search,https://github.com/nmslib/hnswlib,https://github.com/nmslib/hnswlib,Apache-2.0,2017-07-06 13:08:46.000000,2021-12-09 22:46:38.000000,2021-12-09 22:20:16.000000,336.0,103.0,118.0,1813,347.0,Header-only C++/python library for fast approximate nearest neighbors.,52.0,22,2021-12-09 22:30:29.000000,0.6.0,5.0,,hnswlib,,,,,177.0,177.0,https://pypi.org/project/hnswlib,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +386,numexpr,True,pydata/numexpr,,data-containers,https://github.com/pydata/numexpr,https://github.com/pydata/numexpr,MIT,2013-11-30 22:33:48.000000,2021-12-16 07:15:20.000000,2021-12-10 22:32:48.000000,164.0,56.0,258.0,1698,701.0,"Fast numerical array expression evaluator for Python, NumPy, PyTables,..",59.0,22,2020-12-29 18:58:07.000000,2.7.2,12.0,,numexpr,conda-forge/numexpr,,,,,,https://pypi.org/project/numexpr,,53045.0,https://anaconda.org/conda-forge/numexpr,2021-12-09 17:29:02.384000,3394915.0,,,,,3.0,,,,,,,,,,,,,,,, +387,reformer-pytorch,True,lucidrains/reformer-pytorch,,pytorch-utils,https://github.com/lucidrains/reformer-pytorch,https://github.com/lucidrains/reformer-pytorch,MIT,2020-01-09 20:42:37.000000,2021-11-06 23:08:35.000000,2021-11-06 23:08:22.000000,218.0,12.0,104.0,1643,245.0,"Reformer, the efficient Transformer, in Pytorch.",10.0,22,2021-11-06 23:08:36.000000,1.4.4,21.0,,reformer-pytorch,,,,['pytorch'],,,https://pypi.org/project/reformer-pytorch,16111.0,16111.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +388,datasketch,True,ekzhu/datasketch,,data-containers,https://github.com/ekzhu/datasketch,https://github.com/ekzhu/datasketch,MIT,2015-03-20 01:21:46.000000,2021-12-16 05:59:19.000000,2021-12-16 05:57:50.000000,229.0,27.0,96.0,1633,201.0,"MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,..",20.0,22,2021-12-16 05:59:19.000000,1.5.5,22.0,,datasketch,,,,,334.0,334.0,https://pypi.org/project/datasketch,,0.0,,,,,,,,3.0,18.0,,,,,,,,,,,,,,, +389,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,2019-12-06 11:33:34.000000,2021-12-10 20:17:18.000000,2021-12-10 20:17:18.000000,256.0,86.0,210.0,1626,1788.0,Pytorch framework for doing deep learning on point clouds.,29.0,22,2021-04-30 08:59:56.000000,1.3.0,11.0,,torch-points3d,,,,['pytorch'],4.0,4.0,https://pypi.org/project/torch-points3d,1004.0,1004.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +390,Elephas,True,maxpumperla/elephas,,distributed-ml,https://github.com/maxpumperla/elephas,https://github.com/maxpumperla/elephas,MIT,2015-08-13 12:09:19.000000,2021-11-18 11:51:00.000000,2021-08-17 01:01:38.000000,288.0,16.0,136.0,1521,501.0,Distributed Deep learning with Keras & Spark.,27.0,22,2021-08-17 01:14:44.000000,3.0.0,9.0,,elephas,,,,"['keras', 'spark']",51.0,51.0,https://pypi.org/project/elephas,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +391,chainercv,True,chainer/chainercv,,image,https://github.com/chainer/chainercv,https://github.com/chainer/chainercv,MIT,2017-02-13 04:15:10.000000,2021-07-01 16:54:50.000000,2020-01-07 11:48:31.000000,309.0,37.0,168.0,1462,4930.0,ChainerCV: a Library for Deep Learning in Computer Vision.,39.0,22,2019-06-12 11:55:02.000000,0.13.1,13.0,,chainercv,,,,,272.0,272.0,https://pypi.org/project/chainercv,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +392,FinTA,True,peerchemist/finta,,financial-data,https://github.com/peerchemist/finta,https://github.com/peerchemist/finta,LGPL-3.0,2016-09-01 21:02:46.000000,2021-10-19 18:06:53.000000,2021-10-19 18:06:53.000000,440.0,17.0,63.0,1381,392.0,Common financial technical indicators implemented in Pandas.,27.0,22,2021-04-03 08:51:49.000000,1.3,18.0,,finta,,,,,138.0,138.0,https://pypi.org/project/finta,7179.0,7179.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +393,sense2vec,True,explosion/sense2vec,,nlp,https://github.com/explosion/sense2vec,https://github.com/explosion/sense2vec,MIT,2016-01-23 22:15:49.000000,2021-08-16 11:44:51.000000,2021-08-16 11:44:51.000000,217.0,16.0,88.0,1322,454.0,Contextually-keyed word vectors.,17.0,22,2021-02-07 06:11:17.000000,2.0.0,16.0,,sense2vec,conda-forge/sense2vec,,,,103.0,103.0,https://pypi.org/project/sense2vec,,1412.0,https://anaconda.org/conda-forge/sense2vec,2021-07-14 13:20:19.752000,23898.0,,,,,3.0,23194.0,,,,,,,,,,,,,,, +394,petastorm,True,uber/petastorm,,distributed-ml,https://github.com/uber/petastorm,https://github.com/uber/petastorm,Apache-2.0,2018-06-15 23:15:29.000000,2021-10-27 18:10:41.000000,2021-10-27 18:10:41.000000,217.0,127.0,132.0,1312,664.0,Petastorm library enables single machine or distributed training..,43.0,22,2021-09-04 05:46:37.000000,0.11.3,36.0,,petastorm,,,,,53.0,53.0,https://pypi.org/project/petastorm,,7.0,,,,,,,,3.0,309.0,,,,,,,,,,,,,,, +395,NiftyNet,True,NifTK/NiftyNet,,medical-data,https://github.com/NifTK/NiftyNet,https://github.com/NifTK/NiftyNet,Apache-2.0,2017-08-30 07:55:43.000000,2020-04-21 19:54:52.000000,2020-04-21 19:54:51.000000,388.0,100.0,224.0,1290,2848.0,[unmaintained] An open-source convolutional neural..,58.0,22,2019-10-09 19:33:30.000000,0.6.0,8.0,,niftynet,,,,['tensorflow'],37.0,37.0,https://pypi.org/project/niftynet,378.0,378.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +396,ogb,True,snap-stanford/ogb,,graph,https://github.com/snap-stanford/ogb,https://github.com/snap-stanford/ogb,MIT,2019-11-22 22:13:57.000000,2021-12-06 08:19:01.000000,2021-12-06 08:19:01.000000,235.0,,178.0,1171,576.0,"Benchmark datasets, data loaders, and evaluators for graph machine learning.",18.0,22,2021-09-29 04:42:13.000000,1.3.2,13.0,,ogb,,,,,192.0,192.0,https://pypi.org/project/ogb,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +397,TabPy,True,tableau/TabPy,,others,https://github.com/tableau/TabPy,https://github.com/tableau/TabPy,MIT,2016-09-27 21:26:03.000000,2021-11-24 19:05:40.000000,2021-10-11 22:49:25.000000,435.0,16.0,267.0,1170,842.0,Execute Python code on the fly and display results in Tableau visualizations:.,43.0,22,2021-08-12 13:25:16.000000,2.4.0,17.0,,tabpy,,,,,79.0,79.0,https://pypi.org/project/tabpy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +398,TaskTiger,True,closeio/tasktiger,,data-pipelines,https://github.com/closeio/tasktiger,https://github.com/closeio/tasktiger,MIT,2015-05-14 00:26:32.000000,2021-12-02 17:42:12.000000,2021-12-02 17:40:09.000000,59.0,22.0,35.0,1103,273.0,Python task queue using Redis.,24.0,22,2021-12-02 17:42:13.000000,0.16,7.0,,tasktiger,,,,,21.0,21.0,https://pypi.org/project/tasktiger,2201.0,2201.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +399,PyTables,True,PyTables/PyTables,,data-containers,https://github.com/PyTables/PyTables,https://github.com/PyTables/PyTables,BSD-3-Clause,2011-06-03 19:44:46.000000,2021-12-15 18:04:57.000000,2021-12-15 18:04:56.000000,202.0,164.0,465.0,1088,3998.0,A Python package to manage extremely large amounts of data.,103.0,22,2019-10-28 19:25:55.000000,3.6.1,11.0,,tables,conda-forge/pytables,,,,,,https://pypi.org/project/tables,,56083.0,https://anaconda.org/conda-forge/pytables,2021-11-29 19:12:08.113000,3589242.0,,,,,3.0,163.0,,,,,,,,,,,,,,, +400,pmdarima,True,alkaline-ml/pmdarima,,time-series-data,https://github.com/alkaline-ml/pmdarima,https://github.com/alkaline-ml/pmdarima,MIT,2017-03-30 14:58:30.000000,2021-12-09 18:13:28.000000,2021-11-28 21:48:59.000000,187.0,19.0,241.0,1066,1043.0,A statistical library designed to fill the void in Python's time series..,19.0,22,2021-11-05 12:34:36.000000,1.8.4,36.0,,pmdarima,,,,,1582.0,1582.0,https://pypi.org/project/pmdarima,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +401,pandasql,True,yhat/pandasql,,data-containers,https://github.com/yhat/pandasql,https://github.com/yhat/pandasql,MIT,2013-02-18 01:53:56.000000,2020-08-14 13:00:13.000000,2017-02-01 15:40:30.000000,148.0,42.0,23.0,1060,127.0,sqldf for pandas.,15.0,22,,,,,pandasql,,,,['pandas'],1026.0,1026.0,https://pypi.org/project/pandasql,1111862.0,1111862.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +402,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 07:17:48.000000,2021-12-10 23:59:46.000000,2021-10-12 06:35:26.000000,207.0,31.0,25.0,1006,316.0,Interpretability and explainability of data and machine..,29.0,22,2020-10-28 09:32:21.000000,0.2.1,2.0,,aix360,,,,,36.0,36.0,https://pypi.org/project/aix360,1447.0,1447.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +403,Opacus,True,pytorch/opacus,,privacy-ml,https://github.com/pytorch/opacus,https://github.com/pytorch/opacus,Apache-2.0,2019-12-07 01:58:09.000000,2021-12-16 06:15:46.000000,2021-12-14 03:36:10.000000,159.0,17.0,92.0,997,,Training PyTorch models with differential privacy.,40.0,22,2021-12-01 08:54:00.000000,1.0.0,11.0,,opacus,,,,['pytorch'],69.0,69.0,https://pypi.org/project/opacus,4007.0,4009.0,,,,,,,,2.0,40.0,,,,,,,,,,,,,,, +404,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 18:42:09.000000,2021-11-13 15:59:24.399000,2021-10-25 08:00:42.000000,97.0,3.0,95.0,930,578.0,"Extensible, parallel implementations of t-SNE.",10.0,22,2021-04-25 19:32:11.000000,0.6.0,16.0,,opentsne,conda-forge/opentsne,,,,269.0,269.0,https://pypi.org/project/opentsne,,3528.0,https://anaconda.org/conda-forge/opentsne,2021-11-13 15:59:24.399000,127027.0,,,,,3.0,,,,,,,,,,,,,,,, +405,TensorFlow Transform,True,tensorflow/transform,,tensorflow-utils,https://github.com/tensorflow/transform,https://github.com/tensorflow/transform,Apache-2.0,2017-02-10 00:36:53.000000,2021-12-16 07:41:02.000000,2021-12-16 07:41:01.000000,178.0,20.0,151.0,898,730.0,Input pipeline framework.,27.0,22,2021-12-02 20:53:21.000000,1.5.0,33.0,,tensorflow-transform,,,,['tensorflow'],639.0,639.0,https://pypi.org/project/tensorflow-transform,,,,,,,,,,2.0,,,,,-7.0,,,,,,,,,,, +406,tf-explain,True,sicara/tf-explain,,interpretability,https://github.com/sicara/tf-explain,https://github.com/sicara/tf-explain,MIT,2019-07-15 08:26:24.000000,2021-11-30 09:54:42.000000,2021-11-30 09:54:40.000000,89.0,37.0,49.0,887,206.0,Interpretability Methods for tf.keras models with Tensorflow 2.x.,16.0,22,2021-11-18 20:27:53.000000,0.3.1,7.0,,tf-explain,,,,['tensorflow'],92.0,92.0,https://pypi.org/project/tf-explain,2268.0,2268.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +407,mahotas,True,luispedro/mahotas,,image,https://github.com/luispedro/mahotas,https://github.com/luispedro/mahotas,,2010-01-31 00:13:06.000000,2021-12-07 00:42:53.000000,2021-12-07 00:42:43.000000,138.0,15.0,61.0,723,1286.0,Computer Vision in Python.,32.0,22,2019-10-10 18:17:19.000000,1.4.8,9.0,,mahotas,conda-forge/mahotas,,,,721.0,721.0,https://pypi.org/project/mahotas,,4472.0,https://anaconda.org/conda-forge/mahotas,2021-11-17 20:03:30.117000,308622.0,,,,,3.0,,,,,,,,,,,,,,,, +408,pySBD,True,nipunsadvilkar/pySBD,,nlp,https://github.com/nipunsadvilkar/pySBD,https://github.com/nipunsadvilkar/pySBD,MIT,2017-06-11 06:15:20.000000,2021-04-25 08:42:15.000000,2021-02-11 16:40:18.000000,42.0,12.0,48.0,393,279.0,pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence..,6.0,22,2021-02-11 16:42:37.000000,0.3.4,15.0,,pysbd,,,,,253.0,253.0,https://pypi.org/project/pysbd,39246.0,39246.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +409,StaticFrame,True,InvestmentSystems/static-frame,,data-containers,https://github.com/InvestmentSystems/static-frame,https://github.com/InvestmentSystems/static-frame,MIT,2018-01-03 15:07:52.000000,2021-12-16 03:52:21.000000,2021-12-16 03:52:16.000000,23.0,37.0,321.0,256,3332.0,Immutable and grow-only Pandas-like DataFrames with a more explicit..,16.0,22,2021-12-01 17:49:53.000000,0.8.31,115.0,,static-frame,conda-forge/static-frame,,,,10.0,10.0,https://pypi.org/project/static-frame,,3819.0,https://anaconda.org/conda-forge/static-frame,2021-12-01 20:00:21.054000,129863.0,,,,,3.0,,,,,,,,,,,,,,,, +410,tabulator-py,True,frictionlessdata/tabulator-py,,data-loading,https://github.com/frictionlessdata/tabulator-py,https://github.com/frictionlessdata/tabulator-py,MIT,2015-08-24 05:34:38.000000,2021-06-01 12:40:01.000000,2021-03-22 13:33:48.000000,42.0,,178.0,216,,Python library for reading and writing tabular data via streams.,27.0,22,2021-03-21 07:42:12.000000,1.53.5,100.0,,tabulator,conda-forge/tabulator-py,,,,669.0,669.0,https://pypi.org/project/tabulator,371191.0,372037.0,https://anaconda.org/conda-forge/tabulator-py,2018-07-24 12:57:07.018000,45684.0,,,,,3.0,,,,,,,,,,,,,,,, +411,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 06:44:03.000000,2019-10-16 15:01:43.000000,2018-07-23 21:04:09.000000,24.0,3.0,9.0,134,90.0,Get list of common stop words in various languages in Python.,8.0,22,2018-07-23 20:58:34.000000,2018.7.23,7.0,,stop-words,,,,,1383.0,1383.0,https://pypi.org/project/stop-words,199632.0,199632.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +412,textgenrnn,True,minimaxir/textgenrnn,,nlp,https://github.com/minimaxir/textgenrnn,https://github.com/minimaxir/textgenrnn,,2017-08-07 02:13:37.000000,2021-06-18 06:05:47.000000,2020-07-14 02:41:10.000000,706.0,116.0,86.0,4583,174.0,Easily train your own text-generating neural network of any..,19.0,21,2020-02-03 01:07:00.000000,2.0.0,12.0,,textgenrnn,,,,['tensorflow'],948.0,948.0,https://pypi.org/project/textgenrnn,854.0,868.0,,,,,,,,3.0,622.0,,,,,,,,,,,,,,, +413,torchdiffeq,True,rtqichen/torchdiffeq,,pytorch-utils,https://github.com/rtqichen/torchdiffeq,https://github.com/rtqichen/torchdiffeq,MIT,2018-11-14 17:51:25.000000,2021-09-22 21:49:42.000000,2021-09-22 21:49:42.000000,662.0,28.0,129.0,3822,224.0,Differentiable ODE solvers with full GPU support and..,20.0,21,,,,,torchdiffeq,,,,['pytorch'],179.0,179.0,https://pypi.org/project/torchdiffeq,8169.0,8169.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +414,segmentation_models,True,qubvel/segmentation_models,,image,https://github.com/qubvel/segmentation_models,https://github.com/qubvel/segmentation_models,MIT,2018-06-05 13:27:56.000000,2021-12-06 07:58:05.000000,2020-04-17 09:51:20.000000,836.0,199.0,253.0,3572,204.0,Segmentation models with pretrained backbones. Keras and TensorFlow Keras.,14.0,21,2020-01-10 11:28:38.000000,1.0.1,4.0,,segmentation_models,,,,['tensorflow'],,,https://pypi.org/project/segmentation_models,56851.0,56851.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +415,MatchZoo,True,NTMC-Community/MatchZoo,,nlp,https://github.com/NTMC-Community/MatchZoo,https://github.com/NTMC-Community/MatchZoo,Apache-2.0,2017-06-08 08:55:22.000000,2021-06-03 02:58:49.000000,2021-06-02 17:38:16.000000,892.0,28.0,429.0,3567,1810.0,"Facilitating the design, comparison and sharing of deep..",36.0,21,2019-10-09 19:24:22.000000,2.2,2.0,,matchzoo,,,,['tensorflow'],10.0,10.0,https://pypi.org/project/matchzoo,196.0,196.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +416,phonenumbers,True,daviddrysdale/python-phonenumbers,,nlp,https://github.com/daviddrysdale/python-phonenumbers,https://github.com/daviddrysdale/python-phonenumbers,Apache-2.0,2011-04-21 03:06:38.000000,2021-12-14 07:47:12.000000,2021-12-14 07:47:10.000000,346.0,3.0,127.0,2898,,Python port of Google's libphonenumber.,25.0,21,,,49.0,,phonenumbers,conda-forge/phonenumbers,,,,,,https://pypi.org/project/phonenumbers,2669303.0,2676940.0,https://anaconda.org/conda-forge/phonenumbers,2021-12-07 17:32:59.008000,504054.0,,,,,3.0,,,,,,,,,,,,,,,, +417,PyQtGraph,True,pyqtgraph/pyqtgraph,,data-viz,https://github.com/pyqtgraph/pyqtgraph,https://github.com/pyqtgraph/pyqtgraph,,2013-09-12 07:18:21.000000,2021-12-15 18:20:57.000000,2021-12-15 18:20:57.000000,876.0,278.0,676.0,2657,3138.0,Fast data visualization and GUI tools for scientific / engineering..,214.0,21,2021-10-11 03:04:34.000000,pyqtgraph-0.12.3,8.0,,pyqtgraph,conda-forge/pyqtgraph,,,,,,https://pypi.org/project/pyqtgraph,,3571.0,https://anaconda.org/conda-forge/pyqtgraph,2021-10-11 16:15:08.513000,210729.0,,,,,3.0,,,,,,,,,,,,,,,, +418,ta,True,bukosabino/ta,,financial-data,https://github.com/bukosabino/ta,https://github.com/bukosabino/ta,MIT,2018-01-02 18:08:48.000000,2021-12-10 13:46:33.000000,2021-12-08 10:31:50.000000,631.0,96.0,89.0,2644,590.0,Technical Analysis Library using Pandas and Numpy.,24.0,21,,,,,ta,,,,,902.0,902.0,https://pypi.org/project/ta,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +419,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 19:36:44.000000,2021-12-16 14:06:14.000000,2021-12-16 13:18:16.000000,508.0,75.0,520.0,2516,13128.0,State of the Art Natural Language Processing.,104.0,21,2021-11-25 15:16:53.000000,3.3.4,94.0,,spark-nlp,,,,['spark'],,,https://pypi.org/project/spark-nlp,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +420,Texthero,True,jbesomi/texthero,,nlp,https://github.com/jbesomi/texthero,https://github.com/jbesomi/texthero,MIT,2020-04-06 15:16:05.000000,2021-07-19 13:56:08.000000,2021-07-19 13:56:08.000000,205.0,47.0,59.0,2403,269.0,"Text preprocessing, representation and visualization from zero to hero.",18.0,21,2021-07-01 16:53:52.000000,1.1.0,4.0,,texthero,,,,,,,https://pypi.org/project/texthero,17552.0,17556.0,,,,,,,,3.0,87.0,,,,,,,,,,,,,,, +421,TF-Agents,True,tensorflow/agents,,reinforcement-learning,https://github.com/tensorflow/agents,https://github.com/tensorflow/agents,Apache-2.0,2018-11-17 00:29:12.000000,2021-12-10 16:28:02.000000,2021-12-10 16:25:50.000000,562.0,99.0,414.0,2130,1986.0,"TF-Agents: A reliable, scalable and easy to use TensorFlow..",114.0,21,,,,,tf-agents,,,,['tensorflow'],649.0,649.0,https://pypi.org/project/tf-agents,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +422,ipyparallel,True,ipython/ipyparallel,,distributed-ml,https://github.com/ipython/ipyparallel,https://github.com/ipython/ipyparallel,,2015-04-09 07:43:55.000000,2021-12-13 20:00:05.000000,2021-12-08 07:51:51.000000,813.0,47.0,263.0,2123,,Interactive Parallel Computing in Python.,104.0,21,,,18.0,,ipyparallel,conda-forge/ipyparallel,,,['jupyter'],1764.0,1764.0,https://pypi.org/project/ipyparallel,,7965.0,https://anaconda.org/conda-forge/ipyparallel,2021-12-02 07:17:02.707000,541685.0,,,,,3.0,,,,,,,,,,,,,,,, +423,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 02:42:08.000000,2021-10-20 10:08:48.000000,2020-12-31 13:27:01.000000,572.0,19.0,51.0,2012,120.0,This library provides common speech features for ASR including MFCCs and filterbank energies.,19.0,21,2020-01-14 14:12:10.000000,0.6.1,3.0,,python_speech_features,,,,,,,https://pypi.org/project/python_speech_features,131121.0,131121.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +424,Spektral,True,danielegrattarola/spektral,,graph,https://github.com/danielegrattarola/spektral,https://github.com/danielegrattarola/spektral,MIT,2019-01-17 11:19:10.000000,2021-12-15 18:13:55.000000,2021-10-26 09:35:54.000000,258.0,37.0,159.0,1942,1033.0,Graph Neural Networks with Keras and Tensorflow 2.,19.0,21,2020-11-30 12:54:14.000000,1.0,1.0,,spektral,,,,"['tensorflow""']",87.0,87.0,https://pypi.org/project/spektral,4395.0,4395.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +425,PyFunctional,True,EntilZha/PyFunctional,,data-pipelines,https://github.com/EntilZha/PyFunctional,https://github.com/EntilZha/PyFunctional,MIT,2015-02-05 17:17:51.000000,2021-11-26 14:50:52.000000,2021-11-05 18:58:53.000000,104.0,5.0,119.0,1941,520.0,Python library for creating data pipelines with chain functional..,25.0,21,2021-01-12 19:21:07.000000,1.4.3,11.0,,pyfunctional,,,,,368.0,368.0,https://pypi.org/project/pyfunctional,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +426,pgmpy,True,pgmpy/pgmpy,,probabilistics,https://github.com/pgmpy/pgmpy,https://github.com/pgmpy/pgmpy,MIT,2013-09-20 08:18:58.000000,2021-12-04 18:46:10.000000,2021-12-04 18:46:09.000000,606.0,184.0,549.0,1940,6.0,Python Library for learning (Structure and Parameter) and inference..,101.0,21,2021-09-30 16:00:43.000000,0.1.16,6.0,,pgmpy,,,,,295.0,295.0,https://pypi.org/project/pgmpy,,6.0,,,,,,,,3.0,115.0,,,,,,,,,,,,,,, +427,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 12:09:24.000000,2021-11-29 01:17:29.243000,2021-11-28 19:31:51.000000,458.0,9.0,348.0,1646,616.0,Python sync/async framework for Interactive Brokers API.,29.0,21,,,15.0,,ib_insync,conda-forge/ib-insync,,,,,,https://pypi.org/project/ib_insync,8702.0,9176.0,https://anaconda.org/conda-forge/ib-insync,2021-11-29 01:17:29.243000,13764.0,,,,,3.0,,,,,,,,,,,,,,,, +428,checklist,True,marcotcr/checklist,,interpretability,https://github.com/marcotcr/checklist,https://github.com/marcotcr/checklist,MIT,2020-03-09 17:18:49.000000,2021-11-23 19:38:48.000000,2021-09-28 21:55:38.000000,146.0,1.0,79.0,1539,247.0,Beyond Accuracy: Behavioral Testing of NLP models with CheckList.,12.0,21,,,,,checklist,,,,['jupyter'],58.0,58.0,https://pypi.org/project/checklist,14329.0,14329.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +429,Torchmeta,True,tristandeleu/pytorch-meta,,pytorch-utils,https://github.com/tristandeleu/pytorch-meta,https://github.com/tristandeleu/pytorch-meta,MIT,2018-12-04 23:36:45.000000,2021-12-07 20:25:01.000000,2021-09-20 16:03:46.000000,184.0,32.0,88.0,1507,382.0,A collection of extensions and data-loaders for few-shot learning..,12.0,21,,,,,torchmeta,,,,['pytorch'],78.0,78.0,https://pypi.org/project/torchmeta,1424.0,1424.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +430,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 13:53:52.000000,2021-11-13 15:37:21.493000,2021-06-15 21:53:37.000000,173.0,45.0,40.0,1500,728.0,"Large-scale linear classification, regression and..",17.0,21,2021-06-16 21:04:08.000000,0.6.1,4.0,,sklearn-contrib-lightning,conda-forge/sklearn-contrib-lightning,,,['sklearn'],96.0,96.0,https://pypi.org/project/sklearn-contrib-lightning,,2477.0,https://anaconda.org/conda-forge/sklearn-contrib-lightning,2021-11-13 15:37:21.493000,159937.0,,,,,2.0,102.0,,,,,,,,,,,,,,, +431,RecBole,True,RUCAIBox/RecBole,,recommender-systems,https://github.com/RUCAIBox/RecBole,https://github.com/RUCAIBox/RecBole,MIT,2020-06-11 15:18:11.000000,2021-12-09 11:53:17.000000,2021-12-09 11:53:17.000000,249.0,43.0,216.0,1489,3378.0,"A unified, comprehensive and efficient recommendation library.",41.0,21,2021-09-16 10:28:53.000000,1.0.0,6.0,,recbole,aibox/recbole,,,['pytorch'],,,https://pypi.org/project/recbole,,69.0,https://anaconda.org/aibox/recbole,2021-09-16 16:45:01.892000,909.0,,,,,3.0,,,,,,,,,,,,,,,, +432,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 04:03:23.000000,2021-11-10 16:43:45.000000,2021-03-10 15:44:00.000000,122.0,69.0,108.0,1476,978.0,Extract Transform Load for Python 3.5+.,37.0,21,,,,,bonobo,,,http://docs.bonobo-project.org/en/master/,,127.0,127.0,https://pypi.org/project/bonobo,4317.0,4317.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +433,TabNet,True,dreamquark-ai/tabnet,,pytorch-utils,https://github.com/dreamquark-ai/tabnet,https://github.com/dreamquark-ai/tabnet,MIT,2019-10-17 11:17:32.000000,2021-11-12 19:33:57.000000,2021-11-12 19:32:28.000000,292.0,14.0,161.0,1462,168.0,PyTorch implementation of TabNet paper :..,18.0,21,2021-02-02 08:05:08.000000,3.1.1,15.0,,pytorch-tabnet,,,,['pytorch'],,,https://pypi.org/project/pytorch-tabnet,33303.0,33303.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +434,streamparse,True,Parsely/streamparse,,data-pipelines,https://github.com/Parsely/streamparse,https://github.com/Parsely/streamparse,,2014-05-02 20:33:50.000000,2021-06-21 22:49:33.000000,2020-12-18 18:43:59.000000,212.0,62.0,263.0,1445,1059.0,"Run Python in Apache Storm topologies. Pythonic API, CLI..",41.0,21,2020-10-07 19:53:15.000000,4.0.0,42.0,,streamparse,,,,,52.0,52.0,https://pypi.org/project/streamparse,5641.0,5641.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +435,FARM,True,deepset-ai/FARM,,nlp,https://github.com/deepset-ai/FARM,https://github.com/deepset-ai/FARM,Apache-2.0,2019-07-17 14:51:12.000000,2021-11-23 16:56:58.000000,2021-11-23 16:56:58.000000,208.0,15.0,381.0,1438,592.0,Fast & easy transfer learning for NLP. Harvesting language models..,36.0,21,2021-06-10 09:45:12.000000,0.8.0,22.0,,farm,,,,['pytorch'],,,https://pypi.org/project/farm,5662.0,5662.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +436,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 08:29:47.000000,2021-12-08 20:56:26.000000,2021-11-17 13:54:36.000000,214.0,44.0,117.0,1201,280.0,Metric learning algorithms in Python.,21.0,21,2020-07-02 12:55:51.000000,0.6.2,10.0,,metric-learn,,,,['sklearn'],181.0,181.0,https://pypi.org/project/metric-learn,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +437,Pytorch Toolbelt,True,BloodAxe/pytorch-toolbelt,,pytorch-utils,https://github.com/BloodAxe/pytorch-toolbelt,https://github.com/BloodAxe/pytorch-toolbelt,MIT,2019-03-15 16:02:49.000000,2021-12-12 12:08:15.000000,2021-12-06 21:24:44.000000,85.0,4.0,18.0,1160,744.0,PyTorch extensions for fast R&D prototyping and Kaggle..,6.0,21,2021-08-12 07:48:52.000000,0.4.4,21.0,,pytorch_toolbelt,,,,['pytorch'],,,https://pypi.org/project/pytorch_toolbelt,14218.0,14218.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +438,SciSpacy,True,allenai/scispacy,,nlp,https://github.com/allenai/scispacy,https://github.com/allenai/scispacy,Apache-2.0,2018-09-24 21:45:52.000000,2021-09-08 22:25:11.000000,2021-07-15 18:43:58.000000,143.0,35.0,194.0,1064,,A full spaCy pipeline and models for scientific/biomedical..,21.0,21,2021-02-12 22:55:45.000000,0.4.0,6.0,,scispacy,,,,,369.0,369.0,https://pypi.org/project/scispacy,28068.0,28068.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +439,fancyimpute,True,iskandr/fancyimpute,,sklearn-utils,https://github.com/iskandr/fancyimpute,https://github.com/iskandr/fancyimpute,Apache-2.0,2015-11-05 23:39:34.000000,2021-10-21 17:45:20.000000,2021-10-21 17:45:17.000000,160.0,1.0,111.0,1022,202.0,Multivariate imputation and matrix completion algorithms..,12.0,21,2021-03-30 16:22:41.000000,0.5.5,5.0,,fancyimpute,,,,['sklearn'],1104.0,1104.0,https://pypi.org/project/fancyimpute,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +440,Streamz,True,python-streamz/streamz,,time-series-data,https://github.com/python-streamz/streamz,https://github.com/python-streamz/streamz,,2017-04-04 21:45:49.000000,2021-12-15 17:31:34.000000,2021-12-09 21:11:54.000000,128.0,92.0,144.0,1011,779.0,Real-time stream processing for python.,44.0,21,,,15.0,,streamz,conda-forge/streamz,,,,253.0,253.0,https://pypi.org/project/streamz,10211.0,14660.0,https://anaconda.org/conda-forge/streamz,2021-10-04 16:06:59.119000,226900.0,,,,,3.0,,,,,,,,,,,,,,,, +441,keract,True,philipperemy/keract,,interpretability,https://github.com/philipperemy/keract,https://github.com/philipperemy/keract,MIT,2017-05-17 04:50:57.000000,2021-09-24 23:52:45.000000,2021-07-28 09:17:30.000000,183.0,2.0,81.0,945,382.0,Layers Outputs and Gradients in Keras. Made easy.,16.0,21,2021-06-19 16:14:57.000000,4.5.0,10.0,,keract,,,,['tensorflow'],106.0,106.0,https://pypi.org/project/keract,1340.0,1340.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +442,attention-ocr,True,emedvedev/attention-ocr,,ocr,https://github.com/emedvedev/attention-ocr,https://github.com/emedvedev/attention-ocr,MIT,2017-07-21 18:35:19.000000,2021-10-29 14:44:11.000000,2021-10-29 14:44:08.000000,241.0,22.0,126.0,882,205.0,A Tensorflow model for text recognition (CNN + seq2seq with..,27.0,21,2020-10-12 06:56:40.000000,0.7.6,2.0,,aocr,,,,['tensorflow'],18.0,18.0,https://pypi.org/project/aocr,276.0,276.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +443,Madmom,True,CPJKU/madmom,,audio,https://github.com/CPJKU/madmom,https://github.com/CPJKU/madmom,,2015-09-08 08:19:06.000000,2021-12-16 01:15:52.000000,2021-08-23 17:19:35.000000,146.0,52.0,187.0,835,1728.0,Python audio and music signal processing library.,20.0,21,2018-11-14 14:57:41.000000,0.16.1,10.0,,madmom,,,,,168.0,168.0,https://pypi.org/project/madmom,10955.0,10955.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +444,Node2Vec,True,eliorc/node2vec,,graph,https://github.com/eliorc/node2vec,https://github.com/eliorc/node2vec,MIT,2017-12-08 13:30:06.000000,2021-10-09 06:10:48.000000,2021-10-09 06:09:16.000000,181.0,1.0,68.0,821,64.0,Implementation of the node2vec algorithm.,9.0,21,2021-10-09 06:10:48.000000,0.4.4,7.0,,node2vec,conda-forge/node2vec,,,,,,https://pypi.org/project/node2vec,132731.0,133188.0,https://anaconda.org/conda-forge/node2vec,2020-04-25 22:41:13.714000,19651.0,,,,,2.0,,,,,,,,,,,,,,,, +445,Satpy,True,pytroll/satpy,,geospatial-data,https://github.com/pytroll/satpy,https://github.com/pytroll/satpy,GPL-3.0,2016-02-09 20:29:43.000000,2021-12-16 12:11:33.000000,2021-12-16 12:11:32.000000,216.0,282.0,419.0,779,,Python package for earth-observing satellite data processing.,120.0,21,2021-12-10 22:08:53.000000,0.33.0,42.0,,satpy,conda-forge/satpy,,,,54.0,54.0,https://pypi.org/project/satpy,1663.0,3600.0,https://anaconda.org/conda-forge/satpy,2021-12-11 02:55:08.917000,79432.0,,,,,3.0,,,,,,,,,,,,,,,, +446,pythreejs,True,jupyter-widgets/pythreejs,,data-viz,https://github.com/jupyter-widgets/pythreejs,https://github.com/jupyter-widgets/pythreejs,,2013-12-23 17:02:11.000000,2021-12-06 21:48:19.000000,2021-12-06 21:48:19.000000,160.0,67.0,144.0,777,1667.0,A Jupyter - Three.js bridge.,29.0,21,,,15.0,,pythreejs,conda-forge/pythreejs,,,['jupyter'],19.0,19.0,https://pypi.org/project/pythreejs,39030.0,50474.0,https://anaconda.org/conda-forge/pythreejs,2021-03-02 13:32:39.505000,356445.0,,,,,3.0,,jupyter-threejs,https://www.npmjs.com/package/jupyter-threejs,6124.0,,,,,,,,,,,, +447,PFRL,True,pfnet/pfrl,,reinforcement-learning,https://github.com/pfnet/pfrl,https://github.com/pfnet/pfrl,MIT,2020-06-24 09:31:50.000000,2021-12-06 07:44:27.000000,2021-12-06 07:44:27.000000,98.0,23.0,33.0,750,388.0,PFRL: a PyTorch-based deep reinforcement learning library.,15.0,21,2021-07-07 02:43:23.000000,0.3.0,4.0,,pfrl,,,,,27.0,27.0,https://pypi.org/project/pfrl,1780.0,1780.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +448,NeuPy,True,itdxer/neupy,,ml-frameworks,https://github.com/itdxer/neupy,https://github.com/itdxer/neupy,MIT,2015-08-24 19:45:11.000000,2021-09-29 17:25:21.000000,2019-09-02 19:02:38.000000,148.0,30.0,234.0,696,1145.0,NeuPy is a Tensorflow based python library for prototyping and building..,7.0,21,2019-04-04 19:44:59.000000,0.8.2,29.0,,neupy,,,,,117.0,117.0,https://pypi.org/project/neupy,2962.0,2962.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +449,CLTK,True,cltk/cltk,,nlp,https://github.com/cltk/cltk,https://github.com/cltk/cltk,MIT,2014-01-11 23:59:47.000000,2021-12-13 21:01:00.000000,2021-10-21 22:56:32.000000,299.0,22.0,489.0,696,3592.0,The Classical Language Toolkit.,113.0,21,2021-06-10 16:34:40.000000,1.0.15,66.0,,cltk,,,,,185.0,185.0,https://pypi.org/project/cltk,,0.0,,,,,,,,3.0,22.0,,,,,,,,,,,,,,, +450,SMAC3,True,automl/SMAC3,,hyperopt,https://github.com/automl/SMAC3,https://github.com/automl/SMAC3,,2016-08-17 10:58:05.000000,2021-12-16 14:07:49.000000,2021-11-05 09:44:04.000000,163.0,63.0,287.0,638,2048.0,Sequential Model-based Algorithm Configuration.,38.0,21,2021-10-21 07:38:01.000000,1.1.0,28.0,,smac,,,,,,,https://pypi.org/project/smac,29511.0,29511.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +451,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 15:47:02.000000,2021-12-16 07:41:17.000000,2021-12-16 07:41:16.000000,113.0,26.0,109.0,596,703.0,Library for exploring and validating machine learning..,23.0,21,2021-12-01 23:06:45.000000,1.5.0,34.0,,tensorflow-data-validation,,,,"['tensorflow', 'jupyter']",361.0,361.0,https://pypi.org/project/tensorflow-data-validation,,7.0,,,,,,,,3.0,288.0,,,,,,,,,,,,,,, +452,SALib,True,SALib/SALib,,probabilistics,https://github.com/SALib/SALib,https://github.com/SALib/SALib,MIT,2013-05-30 13:38:10.000000,2021-11-25 13:20:11.000000,2021-11-25 13:20:11.000000,162.0,39.0,219.0,548,965.0,"Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,..",34.0,21,2021-09-04 09:49:51.000000,1.4.5,27.0,,salib,conda-forge/salib,,,,,,https://pypi.org/project/salib,,1213.0,https://anaconda.org/conda-forge/salib,2021-09-04 07:03:28.179000,74039.0,,,,,3.0,,,,,,,,,,,,,,,, +453,tinytag,True,devsnd/tinytag,,audio,https://github.com/devsnd/tinytag,https://github.com/devsnd/tinytag,MIT,2014-01-27 15:27:01.000000,2021-12-15 14:07:05.000000,2021-12-15 10:10:52.000000,82.0,10.0,75.0,495,339.0,"Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and..",20.0,21,,,,,tinytag,,,,,447.0,447.0,https://pypi.org/project/tinytag,10958.0,10958.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +454,mpi4py,True,mpi4py/mpi4py,,distributed-ml,https://github.com/mpi4py/mpi4py,https://github.com/mpi4py/mpi4py,BSD-2-Clause,2013-09-05 14:44:25.000000,2021-11-25 23:30:14.783000,2021-11-25 21:50:26.000000,74.0,13.0,41.0,483,2441.0,Python bindings for MPI.,20.0,21,2021-11-25 21:00:09.000000,3.1.3,10.0,,mpi4py,conda-forge/mpi4py,,,,,,https://pypi.org/project/mpi4py,,13871.0,https://anaconda.org/conda-forge/mpi4py,2021-11-25 23:30:14.783000,863759.0,,,,,3.0,2743.0,,,,,,,,,,,,,,, +455,imodels,True,csinva/imodels,,interpretability,https://github.com/csinva/imodels,https://github.com/csinva/imodels,MIT,2019-07-04 15:38:48.000000,2021-12-16 09:24:34.000000,2021-12-16 09:24:31.000000,40.0,3.0,14.0,400,495.0,"Interpretable ML package for concise, transparent, and accurate predictive..",7.0,21,2021-12-06 02:24:05.000000,1.2.0,15.0,,imodels,,,,,10.0,10.0,https://pypi.org/project/imodels,1592.0,1592.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +456,MedPy,True,loli/medpy,,medical-data,https://github.com/loli/medpy,https://github.com/loli/medpy,GPL-3.0,2012-05-11 10:57:34.000000,2020-05-01 15:25:39.000000,2020-05-01 15:25:38.000000,114.0,11.0,67.0,380,324.0,Medical image processing in Python.,13.0,21,2019-02-14 17:09:49.000000,0.4.0,5.0,,MedPy,,,,,453.0,453.0,https://pypi.org/project/MedPy,9990.0,9990.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +457,messytables,True,okfn/messytables,,data-loading,https://github.com/okfn/messytables,https://github.com/okfn/messytables,,2011-07-27 18:08:21.000000,2021-12-13 19:46:22.000000,2019-11-13 07:35:33.000000,102.0,30.0,55.0,376,601.0,Tools for parsing messy tabular data. This is now superseded by..,44.0,21,2016-09-29 14:15:14.000000,0.15.1,1.0,,messytables,,,,,216.0,216.0,https://pypi.org/project/messytables,9183.0,9183.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +458,GeoViews,True,holoviz/geoviews,,geospatial-data,https://github.com/holoviz/geoviews,https://github.com/holoviz/geoviews,BSD-3-Clause,2016-04-19 16:27:01.000000,2021-12-06 16:05:30.000000,2021-12-01 14:42:28.000000,65.0,102.0,188.0,375,670.0,"Simple, concise geographical visualization in Python.",25.0,21,2021-09-30 16:31:39.000000,1.9.2,24.0,,geoviews,conda-forge/geoviews,,,,,,https://pypi.org/project/geoviews,8103.0,10055.0,https://anaconda.org/conda-forge/geoviews,2021-09-29 18:42:51.694000,87866.0,,,,,3.0,,,,,,,,,,,,,,,, +459,EarthPy,True,earthlab/earthpy,,geospatial-data,https://github.com/earthlab/earthpy,https://github.com/earthlab/earthpy,BSD-3-Clause,2018-02-20 03:02:42.000000,2021-12-01 01:34:26.000000,2021-10-11 19:46:23.000000,122.0,16.0,207.0,306,,A package built to support working with spatial data using open source..,40.0,21,2021-10-01 22:50:41.000000,0.9.4,14.0,,earthpy,conda-forge/earthpy,,,,114.0,114.0,https://pypi.org/project/earthpy,4470.0,5712.0,https://anaconda.org/conda-forge/earthpy,2021-10-04 19:35:49.510000,39750.0,,,,,3.0,,,,,,,,,,,,,,,, +460,pysparkling,True,svenkreiss/pysparkling,,data-pipelines,https://github.com/svenkreiss/pysparkling,https://github.com/svenkreiss/pysparkling,,2015-05-09 19:23:20.000000,2021-10-31 16:40:25.000000,2021-02-22 17:29:11.000000,41.0,6.0,21.0,242,1527.0,A pure Python implementation of Apache Spark's RDD and DStream..,10.0,21,2021-01-10 21:14:23.000000,0.6.1,26.0,,pysparkling,,,,,81.0,81.0,https://pypi.org/project/pysparkling,19746.0,19746.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +461,PyText,True,facebookresearch/pytext,,nlp,https://github.com/facebookresearch/pytext,https://github.com/facebookresearch/pytext,,2018-07-31 23:40:46.000000,2021-12-15 19:59:29.000000,2021-12-15 19:59:27.000000,791.0,59.0,74.0,6264,,A natural language modeling framework based on PyTorch.,216.0,20,2020-06-08 23:30:58.000000,0.3.3,9.0,,pytext-nlp,,,,['pytorch'],103.0,103.0,https://pypi.org/project/pytext-nlp,245.0,252.0,,,,,,,,3.0,282.0,,,,,,,,,,,,,,, +462,PyTorch3D,True,facebookresearch/pytorch3d,,image,https://github.com/facebookresearch/pytorch3d,https://github.com/facebookresearch/pytorch3d,,2019-10-25 02:23:45.000000,2021-12-15 16:34:12.000000,2021-12-15 16:34:10.000000,747.0,77.0,766.0,5476,,PyTorch3D is FAIR's library of reusable components for deep..,75.0,20,2021-10-06 13:00:09.000000,0.6.0,10.0,,pytorch3d,pytorch3d/pytorch3d,,,['pytorch'],133.0,133.0,https://pypi.org/project/pytorch3d,,1055.0,https://anaconda.org/pytorch3d/pytorch3d,2021-12-13 19:33:09.797000,26393.0,,,,,3.0,,,,,,,,,,,,,,,, +463,Edward,True,blei-lab/edward,,probabilistics,https://github.com/blei-lab/edward,https://github.com/blei-lab/edward,,2016-02-10 20:06:05.000000,2019-10-22 20:30:48.000000,2018-07-25 01:28:08.000000,753.0,185.0,328.0,4673,1796.0,A probabilistic programming language in TensorFlow. Deep..,87.0,20,2018-01-22 06:03:37.000000,1.3.5,28.0,,edward,,,,['tensorflow'],248.0,248.0,https://pypi.org/project/edward,,0.0,,,,,,,,3.0,15.0,,,,,,,,,,,,,,, +464,Augmentor,True,mdbloice/Augmentor,,image,https://github.com/mdbloice/Augmentor,https://github.com/mdbloice/Augmentor,MIT,2016-03-01 18:29:55.000000,2021-10-15 05:38:50.000000,2021-10-15 05:38:50.000000,809.0,112.0,70.0,4589,537.0,Image augmentation library in Python for machine learning.,22.0,20,,,,,Augmentor,,,,,387.0,387.0,https://pypi.org/project/Augmentor,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +465,mace,True,XiaoMi/mace,,ml-frameworks,https://github.com/XiaoMi/mace,https://github.com/XiaoMi/mace,Apache-2.0,2018-06-27 03:50:12.000000,2021-12-06 07:43:58.000000,2021-12-06 07:43:40.000000,773.0,37.0,612.0,4536,3306.0,MACE is a deep learning inference framework optimized for mobile..,63.0,20,2021-03-18 10:07:32.000000,1.0.4,11.0,,,,,,,,,,,34.0,,,,,,,,3.0,1395.0,,,,,,,,,,,,,,, +466,pyAudioAnalysis,True,tyiannak/pyAudioAnalysis,,audio,https://github.com/tyiannak/pyAudioAnalysis,https://github.com/tyiannak/pyAudioAnalysis,Apache-2.0,2014-08-27 12:43:13.000000,2021-11-12 09:42:45.000000,2021-11-12 09:42:45.000000,1029.0,162.0,114.0,4482,723.0,"Python Audio Analysis Library: Feature Extraction,..",25.0,20,,,,,pyAudioAnalysis,,,,,245.0,245.0,https://pypi.org/project/pyAudioAnalysis,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +467,NeMo,True,NVIDIA/NeMo,,nlp,https://github.com/NVIDIA/NeMo,https://github.com/NVIDIA/NeMo,Apache-2.0,2019-08-05 20:16:42.000000,2021-12-16 06:53:11.000000,2021-12-16 04:09:09.000000,789.0,39.0,827.0,3673,,NeMo: a toolkit for conversational AI.,120.0,20,2021-12-04 00:00:07.000000,1.5.1,21.0,,nemo-toolkit,,,,['pytorch'],,,https://pypi.org/project/nemo-toolkit,6884.0,7497.0,,,,,,,,3.0,16574.0,,,,,,,,,,,,,,, +468,yellowbrick,True,DistrictDataLabs/yellowbrick,,interpretability,https://github.com/DistrictDataLabs/yellowbrick,https://github.com/DistrictDataLabs/yellowbrick,Apache-2.0,2016-05-18 14:12:17.000000,2021-12-10 22:07:08.000000,2021-11-10 14:17:20.000000,490.0,83.0,547.0,3437,,Visual analysis and diagnostic tools to facilitate machine..,102.0,20,2021-02-13 20:31:18.000000,1.3.post1,22.0,,yellowbrick,,,,['sklearn'],,,https://pypi.org/project/yellowbrick,328851.0,328851.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +469,TensorForce,True,tensorforce/tensorforce,,reinforcement-learning,https://github.com/tensorforce/tensorforce,https://github.com/tensorforce/tensorforce,Apache-2.0,2017-03-19 16:24:22.000000,2021-11-10 20:00:27.000000,2021-11-10 20:00:19.000000,490.0,4.0,617.0,3062,2090.0,Tensorforce: a TensorFlow library for applied..,81.0,20,2021-08-30 20:20:58.000000,0.6.5,14.0,,tensorforce,,,,['tensorflow'],,,https://pypi.org/project/tensorforce,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +470,finmarketpy,True,cuemacro/finmarketpy,,financial-data,https://github.com/cuemacro/finmarketpy,https://github.com/cuemacro/finmarketpy,Apache-2.0,2015-02-19 23:32:03.000000,2021-10-07 14:56:30.000000,2021-10-07 14:55:28.000000,418.0,23.0,3.0,2795,678.0,Python library for backtesting trading strategies & analyzing..,14.0,20,2021-10-07 14:56:30.000000,0.11.11,12.0,,finmarketpy,,,,,4.0,4.0,https://pypi.org/project/finmarketpy,103.0,103.0,,,,,,,,3.0,40.0,,,,,,,,,,,,,,, +471,scikit-opt,True,guofei9987/scikit-opt,,sklearn-utils,https://github.com/guofei9987/scikit-opt,https://github.com/guofei9987/scikit-opt,MIT,2017-12-05 10:20:41.000000,2021-12-10 12:26:10.000000,2021-12-04 12:23:59.000000,655.0,28.0,98.0,2785,305.0,"Genetic Algorithm, Particle Swarm Optimization, Simulated..",13.0,20,2021-06-28 12:45:52.000000,0.6.5,20.0,,scikit-opt,,,,['sklearn'],55.0,55.0,https://pypi.org/project/scikit-opt,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +472,dpark,True,douban/dpark,,data-pipelines,https://github.com/douban/dpark,https://github.com/douban/dpark,BSD-3-Clause,2012-04-11 08:35:06.000000,2020-12-25 10:36:06.000000,2020-12-25 10:36:05.000000,543.0,,60.0,2669,1467.0,"Python clone of Spark, a MapReduce alike framework in Python.",35.0,20,2018-07-27 04:05:25.000000,0.5.0,4.0,,dpark,,,,['spark'],4.0,4.0,https://pypi.org/project/dpark,82.0,82.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +473,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 14:40:43.000000,2021-12-16 11:25:53.000000,2021-12-13 12:09:25.000000,733.0,73.0,537.0,2635,,Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning..,87.0,20,2021-10-15 15:52:28.000000,1.8.1,35.0,,adversarial-robustness-toolbox,,,,,173.0,173.0,https://pypi.org/project/adversarial-robustness-toolbox,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +474,StreamAlert,True,airbnb/streamalert,,others,https://github.com/airbnb/streamalert,https://github.com/airbnb/streamalert,Apache-2.0,2017-01-22 01:10:56.000000,2021-12-06 17:56:08.000000,2021-11-04 18:52:02.000000,313.0,83.0,257.0,2631,1900.0,"StreamAlert is a serverless, realtime data analysis framework..",33.0,20,2021-11-04 19:07:51.000000,3.5.0,28.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +475,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 16:41:38.000000,2021-12-16 14:01:46.000000,2021-12-16 13:31:38.000000,483.0,110.0,1225.0,2568,,AI Toolkit for Healthcare Imaging.,84.0,20,2021-11-25 21:19:49.000000,0.8.0,9.0,,monai,,,,['pytorch'],163.0,163.0,https://pypi.org/project/monai,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +476,cleanlab,True,cgnorthcutt/cleanlab,,others,https://github.com/cleanlab/cleanlab,https://github.com/cleanlab/cleanlab,AGPL-3.0,2018-05-11 01:55:21.000000,2021-11-17 00:07:37.000000,2021-11-08 16:11:39.000000,241.0,34.0,47.0,2514,814.0,The standard package for machine learning with noisy labels and..,6.0,20,2021-04-18 19:52:49.000000,1.0,2.0,cleanlab/cleanlab,cleanlab,,,,,24.0,24.0,https://pypi.org/project/cleanlab,5659.0,5659.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +477,Enigma Catalyst,True,enigmampc/catalyst,,financial-data,https://github.com/scrtlabs/catalyst,https://github.com/scrtlabs/catalyst,Apache-2.0,2017-06-13 22:31:34.000000,2021-09-22 15:32:01.000000,2021-09-22 15:31:55.000000,674.0,123.0,358.0,2312,6364.0,An Algorithmic Trading Library for Crypto-Assets in Python.,147.0,20,,,,scrtlabs/catalyst,enigma-catalyst,,,,,23.0,23.0,https://pypi.org/project/enigma-catalyst,972.0,972.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +478,knockknock,True,huggingface/knockknock,,ml-experiments,https://github.com/huggingface/knockknock,https://github.com/huggingface/knockknock,MIT,2019-03-20 13:08:55.000000,2021-09-22 02:27:34.000000,2020-03-16 04:26:47.000000,191.0,14.0,23.0,2304,75.0,Knock Knock: Get notified when your training ends with only two..,18.0,20,,,5.0,,knockknock,conda-forge/knockknock,,,,228.0,228.0,https://pypi.org/project/knockknock,,319.0,https://anaconda.org/conda-forge/knockknock,2020-03-17 01:52:16.317000,8312.0,,,,,3.0,,,,,,,,,,,,,,,, +479,Kashgari,True,BrikerMan/Kashgari,,nlp,https://github.com/BrikerMan/Kashgari,https://github.com/BrikerMan/Kashgari,Apache-2.0,2019-01-19 01:53:28.000000,2021-07-09 03:57:16.000000,2021-07-09 03:57:16.000000,422.0,33.0,326.0,2235,,Kashgari is a production-level NLP Transfer learning framework..,21.0,20,2021-07-04 10:44:36.000000,2.0.2,24.0,,kashgari-tf,,,,['tensorflow'],49.0,49.0,https://pypi.org/project/kashgari-tf,73.0,73.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +480,HiPlot,True,facebookresearch/hiplot,,data-viz,https://github.com/facebookresearch/hiplot,https://github.com/facebookresearch/hiplot,MIT,2019-11-08 13:06:41.000000,2021-11-05 18:04:22.000000,2021-11-05 17:54:23.000000,105.0,10.0,61.0,2219,,HiPlot makes understanding high dimensional data easy.,7.0,20,2021-11-04 14:24:43.000000,0.1.32,34.0,,hiplot,conda-forge/hiplot,,,,3.0,3.0,https://pypi.org/project/hiplot,10414.0,13750.0,https://anaconda.org/conda-forge/hiplot,2021-11-05 06:41:13.441000,73409.0,,,,,3.0,,,,,,,,,,,,,,,, +481,pandas-datareader,True,pydata/pandas-datareader,,data-loading,https://github.com/pydata/pandas-datareader,https://github.com/pydata/pandas-datareader,,2015-01-15 00:34:19.000000,2021-11-28 13:29:47.000000,2021-08-07 12:53:30.000000,546.0,92.0,392.0,2183,,Extract data from a wide range of Internet sources into..,83.0,20,2021-07-13 12:27:15.000000,0.10.0,19.0,,pandas-datareader,conda-forge/pandas-datareader,,,['pandas'],,,https://pypi.org/project/pandas-datareader,244521.0,247310.0,https://anaconda.org/conda-forge/pandas-datareader,2021-07-14 09:19:08.289000,156220.0,,,,,3.0,,,,,,,,,,,,,,,, +482,vidgear,True,abhiTronix/vidgear,,image,https://github.com/abhiTronix/vidgear,https://github.com/abhiTronix/vidgear,Apache-2.0,2019-03-17 02:42:42.000000,2021-12-13 02:51:59.000000,2021-12-05 10:14:09.000000,153.0,2.0,190.0,2042,826.0,High-performance cross-platform Video Processing Python framework..,9.0,20,2021-12-05 12:54:46.000000,idgear-0.2.4,16.0,,vidgear,,,,,156.0,156.0,https://pypi.org/project/vidgear,,15.0,,,,,,,,3.0,505.0,,,,,,,,,,,,,,, +483,Pandaral·lel,True,nalepae/pandarallel,,data-containers,https://github.com/nalepae/pandarallel,https://github.com/nalepae/pandarallel,BSD-3-Clause,2019-03-10 11:58:29.000000,2021-10-17 19:31:25.000000,2021-10-17 19:29:29.000000,125.0,78.0,64.0,1887,128.0,A simple and efficient tool to parallelize Pandas operations on all availableCPUs.,18.0,20,2021-10-17 19:31:25.000000,1.5.4,31.0,,pandarallel,,,,"['pandas', 'jupyter']",359.0,359.0,https://pypi.org/project/pandarallel,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +484,Sweetviz,True,fbdesignpro/sweetviz,,data-viz,https://github.com/fbdesignpro/sweetviz,https://github.com/fbdesignpro/sweetviz,MIT,2020-05-09 15:25:47.000000,2021-10-01 14:11:39.000000,2021-07-08 14:31:20.000000,184.0,20.0,70.0,1849,102.0,"Visualize and compare datasets, target values and associations, with one..",6.0,20,2021-05-28 14:19:52.000000,2.1.2,5.0,,sweetviz,,,,,,,https://pypi.org/project/sweetviz,59692.0,59692.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +485,mljar-supervised,True,mljar/mljar-supervised,,hyperopt,https://github.com/mljar/mljar-supervised,https://github.com/mljar/mljar-supervised,MIT,2018-11-05 12:58:04.000000,2021-12-06 08:40:00.000000,2021-12-06 08:40:00.000000,237.0,75.0,373.0,1701,983.0,Automated Machine Learning Pipeline with Feature Engineering..,14.0,20,2021-09-06 11:25:56.000000,0.11.0,46.0,,mljar-supervised,,,,,33.0,33.0,https://pypi.org/project/mljar-supervised,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +486,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 05:46:52.000000,2021-11-09 17:22:51.512000,2020-08-19 14:58:00.000000,187.0,34.0,21.0,1664,113.0,Parallel t-SNE implementation with Python and Torch..,15.0,20,,,1.0,,MulticoreTSNE,conda-forge/multicore-tsne,,,['pytorch'],265.0,265.0,https://pypi.org/project/MulticoreTSNE,,318.0,https://anaconda.org/conda-forge/multicore-tsne,2021-11-09 17:22:51.512000,11766.0,,,,,3.0,,,,,,,,,,,,,,,, +487,TFX,True,tensorflow/tfx,,data-pipelines,https://github.com/tensorflow/tfx,https://github.com/tensorflow/tfx,Apache-2.0,2019-02-04 17:14:36.000000,2021-12-16 08:44:18.000000,2021-12-16 08:44:14.000000,514.0,230.0,478.0,1653,3995.0,TFX is an end-to-end platform for deploying production ML pipelines.,125.0,20,2021-12-14 19:05:52.000000,1.5.0,64.0,,tfx,,,,['tensorflow'],,,https://pypi.org/project/tfx,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +488,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 07:14:02.000000,2021-12-13 20:26:16.000000,2021-12-02 11:21:00.000000,118.0,24.0,93.0,1582,,JAX-based neural network library.,53.0,20,2021-11-01 13:18:04.000000,0.0.5,7.0,,,,,,,269.0,269.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +489,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 13:05:24.000000,2021-12-16 13:21:19.000000,2021-12-16 10:05:03.000000,226.0,130.0,229.0,1572,1104.0,Time series forecasting with PyTorch.,27.0,20,2021-11-29 19:54:39.000000,0.9.2,26.0,,pytorch-forecasting,,,,,,,https://pypi.org/project/pytorch-forecasting,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +490,auto_ml,True,ClimbsRocks/auto_ml,,hyperopt,https://github.com/ClimbsRocks/auto_ml,https://github.com/ClimbsRocks/auto_ml,MIT,2016-08-07 21:35:08.000000,2021-02-10 07:52:35.000000,2018-03-25 19:46:25.000000,297.0,178.0,216.0,1559,1149.0,[UNMAINTAINED] Automated machine learning for analytics & production.,13.0,20,2017-09-12 03:01:00.000000,2.7.0,12.0,,auto_ml,,,,,,,https://pypi.org/project/auto_ml,1420.0,1420.0,,,,,,,,2.0,38.0,,,,,,,,,,,,,,, +491,hiddenlayer,True,waleedka/hiddenlayer,,ml-experiments,https://github.com/waleedka/hiddenlayer,https://github.com/waleedka/hiddenlayer,MIT,2018-05-18 22:34:51.000000,2021-10-16 05:29:37.000000,2020-04-24 06:58:09.000000,219.0,46.0,34.0,1559,58.0,Neural network graphs and training metrics for..,6.0,20,2018-12-03 04:33:29.000000,0.2,1.0,,hiddenlayer,,,,"['pytorch', 'tensorflow', 'jupyter']",88.0,88.0,https://pypi.org/project/hiddenlayer,1941.0,1941.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +492,lore,True,instacart/lore,,ml-experiments,https://github.com/instacart/lore,https://github.com/instacart/lore,MIT,2017-10-19 21:51:45.000000,2021-11-22 20:05:31.000000,2020-05-11 22:26:45.000000,122.0,16.0,18.0,1536,270.0,Lore makes machine learning approachable for Software Engineers and..,22.0,20,2020-05-05 20:16:54.000000,0.8.3,1.0,,lore,,,,,17.0,17.0,https://pypi.org/project/lore,649.0,649.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +493,DELTA,True,Delta-ML/delta,,nlp,https://github.com/Delta-ML/delta,https://github.com/Delta-ML/delta,Apache-2.0,2019-05-29 08:33:57.000000,2021-11-08 22:20:35.000000,2020-12-17 06:57:15.000000,291.0,1.0,74.0,1480,932.0,DELTA is a deep learning based natural language and speech..,41.0,20,2020-07-16 09:31:45.000000,0.3.3,4.0,,delta-nlp,,zh794390558/delta,,['tensorflow'],,,https://pypi.org/project/delta-nlp,20.0,441.0,,,,https://hub.docker.com/r/zh794390558/delta,2021-08-03 14:50:00.516864,,13065.0,3.0,,,,,,,,,,,,,,,, +494,Talos,True,autonomio/talos,,hyperopt,https://github.com/autonomio/talos,https://github.com/autonomio/talos,MIT,2018-05-04 20:36:41.000000,2021-05-27 09:49:51.000000,2021-05-27 09:49:50.000000,247.0,35.0,354.0,1473,559.0,"Hyperparameter Optimization for TensorFlow, Keras and PyTorch.",19.0,20,2020-11-09 16:48:30.000000,1.0,12.0,,talos,,,,['tensorflow'],131.0,131.0,https://pypi.org/project/talos,813.0,813.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +495,anaGo,True,Hironsan/anago,,nlp,https://github.com/Hironsan/anago,https://github.com/Hironsan/anago,MIT,2017-06-26 21:28:36.000000,2021-08-25 14:45:13.000000,2021-04-01 12:34:50.000000,360.0,37.0,72.0,1424,298.0,"Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-..",11.0,20,2018-06-03 13:51:56.000000,1.0.0,5.0,,anago,,,,['tensorflow'],27.0,27.0,https://pypi.org/project/anago,489.0,489.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +496,Classy Vision,True,facebookresearch/ClassyVision,,image,https://github.com/facebookresearch/ClassyVision,https://github.com/facebookresearch/ClassyVision,MIT,2019-09-13 22:54:44.000000,2021-12-09 18:31:19.000000,2021-12-09 18:31:15.000000,237.0,13.0,61.0,1388,,An end-to-end PyTorch framework for image and video..,66.0,20,2021-07-19 20:08:51.000000,0.6.0,6.0,,classy_vision,conda-forge/classy_vision,,,['pytorch'],,,https://pypi.org/project/classy_vision,1354.0,1819.0,https://anaconda.org/conda-forge/classy_vision,2020-12-11 20:08:25.437000,10703.0,,,,,3.0,,,,,,,,,,,,,,,, +497,TNT,True,pytorch/tnt,,ml-experiments,https://github.com/pytorch/tnt,https://github.com/pytorch/tnt,BSD-3-Clause,2016-12-10 11:49:58.000000,2021-01-22 09:14:29.000000,2021-01-05 19:36:17.000000,190.0,23.0,35.0,1357,156.0,"Simple tools for logging and visualizing, loading and training.",35.0,20,2019-11-15 12:57:59.000000,0.0.5.1,2.0,,torchnet,,,,['pytorch'],,,https://pypi.org/project/torchnet,17382.0,17382.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +498,garage,True,rlworkgroup/garage,,reinforcement-learning,https://github.com/rlworkgroup/garage,https://github.com/rlworkgroup/garage,MIT,2018-06-10 21:31:23.000000,2021-10-20 05:09:03.000000,2021-10-20 05:09:03.000000,240.0,189.0,799.0,1357,1217.0,A toolkit for reproducible reinforcement learning research.,78.0,20,2020-09-14 22:30:57.000000,2020.06.3,21.0,,garage,,,,['tensorflow'],23.0,23.0,https://pypi.org/project/garage,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +499,MLBox,True,AxeldeRomblay/MLBox,,hyperopt,https://github.com/AxeldeRomblay/MLBox,https://github.com/AxeldeRomblay/MLBox,,2017-06-01 16:59:24.000000,2021-08-25 15:38:03.000000,2020-08-25 09:26:27.000000,260.0,16.0,74.0,1272,1121.0,MLBox is a powerful Automated Machine Learning python library.,9.0,20,2019-08-25 22:46:42.000000,0.8.1,7.0,,mlbox,,,,,28.0,28.0,https://pypi.org/project/mlbox,2757.0,2757.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +500,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 01:11:33.000000,2021-11-21 18:51:53.000000,2021-11-21 18:51:52.000000,164.0,2.0,68.0,1213,1794.0,PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021).,12.0,20,2021-09-11 12:03:52.000000,_00041,36.0,,torch-geometric-temporal,,,,['pytorch'],,,https://pypi.org/project/torch-geometric-temporal,1028.0,1028.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +501,Paddle Graph Learning,True,PaddlePaddle/PGL,,graph,https://github.com/PaddlePaddle/PGL,https://github.com/PaddlePaddle/PGL,Apache-2.0,2019-06-11 03:23:28.000000,2021-12-16 11:52:58.000000,2021-12-16 09:12:04.000000,186.0,34.0,62.0,1173,,Paddle Graph Learning (PGL) is an efficient and..,21.0,20,2021-02-02 13:17:55.000000,2.1.1,5.0,,pgl,,,,['paddle'],23.0,23.0,https://pypi.org/project/pgl,980.0,980.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +502,pyts,True,johannfaouzi/pyts,,time-series-data,https://github.com/johannfaouzi/pyts,https://github.com/johannfaouzi/pyts,BSD-3-Clause,2017-07-31 09:23:16.000000,2021-12-09 13:27:33.000000,2021-12-09 13:27:29.000000,113.0,32.0,24.0,1115,,A Python package for time series classification.,10.0,20,2021-10-31 13:50:40.000000,0.12.0,7.0,,pyts,conda-forge/pyts,,,,161.0,161.0,https://pypi.org/project/pyts,,346.0,https://anaconda.org/conda-forge/pyts,2021-10-31 15:13:32.850000,9693.0,,,,,3.0,,,,,,,,,,,,,,,, +503,gplearn,True,trevorstephens/gplearn,,others,https://github.com/trevorstephens/gplearn,https://github.com/trevorstephens/gplearn,BSD-3-Clause,2015-03-26 01:01:14.000000,2021-10-18 05:33:30.000000,2021-10-18 05:33:29.000000,181.0,45.0,127.0,1050,148.0,"Genetic Programming in Python, with a scikit-learn inspired API.",10.0,20,,,,,gplearn,,,,['sklearn'],212.0,212.0,https://pypi.org/project/gplearn,2621.0,2621.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +504,ChainerRL,True,chainer/chainerrl,,reinforcement-learning,https://github.com/chainer/chainerrl,https://github.com/chainer/chainerrl,MIT,2017-01-30 04:58:15.000000,2021-08-10 18:25:48.000000,2021-04-17 06:02:30.000000,209.0,51.0,147.0,1013,3471.0,ChainerRL is a deep reinforcement learning library built on top of..,29.0,20,2020-02-14 05:32:03.000000,0.8.0,8.0,,chainerrl,,,,,107.0,107.0,https://pypi.org/project/chainerrl,,,,,,,,,,2.0,,,,,,,,,,,,,,,, +505,Skater,True,oracle/Skater,,interpretability,https://github.com/oracle/Skater,https://github.com/oracle/Skater,UPL-1.0,2017-01-26 05:45:42.000000,2021-11-15 19:51:51.883000,2020-06-29 20:07:12.000000,162.0,65.0,97.0,1006,1101.0,Python Library for Model Interpretation/Explanations.,34.0,20,2018-09-21 06:46:11.000000,1.1.2,15.0,,skater,conda-forge/skater,,,,,,https://pypi.org/project/skater,2446.0,3291.0,https://anaconda.org/conda-forge/skater,2021-11-15 19:51:51.883000,45683.0,,,,,3.0,,,,,,,,,,,,,,,, +506,DALEX,True,ModelOriented/DALEX,,interpretability,https://github.com/ModelOriented/DALEX,https://github.com/ModelOriented/DALEX,GPL-3.0,2018-02-18 03:24:12.000000,2021-11-08 12:23:05.000000,2021-11-08 12:23:03.000000,117.0,15.0,312.0,971,594.0,moDel Agnostic Language for Exploration and eXplanation.,20.0,20,2021-01-04 17:21:32.000000,1.0.0,3.0,,dalex,,,,,26.0,26.0,https://pypi.org/project/dalex,10899.0,10899.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +507,geoplotlib,True,andrea-cuttone/geoplotlib,,geospatial-data,https://github.com/andrea-cuttone/geoplotlib,https://github.com/andrea-cuttone/geoplotlib,MIT,2015-02-24 13:13:07.000000,2021-10-20 12:00:24.000000,2019-05-06 07:06:50.000000,153.0,25.0,18.0,940,159.0,python toolbox for visualizing geographical data and making maps.,8.0,20,,,,,geoplotlib,,,,,124.0,124.0,https://pypi.org/project/geoplotlib,1505.0,1505.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +508,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 21:48:16.000000,2021-12-16 08:25:17.000000,2021-12-06 22:50:05.000000,162.0,2.0,57.0,888,493.0,Training neural models with structured signals.,30.0,20,2020-08-18 00:30:03.000000,1.3.1,6.0,,neural-structured-learning,,,,['tensorflow'],152.0,152.0,https://pypi.org/project/neural-structured-learning,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +509,pyopencl,True,inducer/pyopencl,,others,https://github.com/inducer/pyopencl,https://github.com/inducer/pyopencl,,2011-04-06 02:51:33.000000,2021-12-13 20:35:04.000000,2021-12-13 20:35:03.000000,212.0,59.0,233.0,858,,"OpenCL integration for Python, plus shiny features.",90.0,20,,,37.0,,pyopencl,conda-forge/pyopencl,,,,593.0,593.0,https://pypi.org/project/pyopencl,15598.0,24334.0,https://anaconda.org/conda-forge/pyopencl,2021-12-06 03:04:41.546000,541634.0,,,,,3.0,,,,,,,,,,,,,,,, +510,mrq,True,pricingassistant/mrq,,data-pipelines,https://github.com/pricingassistant/mrq,https://github.com/pricingassistant/mrq,MIT,2014-02-13 09:32:40.000000,2021-12-13 19:45:34.000000,2020-12-13 18:58:15.000000,112.0,52.0,119.0,858,709.0,Mr. Queue - A distributed worker task queue in Python using Redis & gevent.,37.0,20,2018-08-31 13:59:56.000000,0.9.10,5.0,,mrq,,,,,27.0,27.0,https://pypi.org/project/mrq,262.0,262.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +511,torch-scatter,True,rusty1s/pytorch_scatter,,pytorch-utils,https://github.com/rusty1s/pytorch_scatter,https://github.com/rusty1s/pytorch_scatter,MIT,2017-12-16 16:34:23.000000,2021-11-13 17:38:08.000000,2021-11-13 17:38:07.000000,86.0,20.0,209.0,839,970.0,PyTorch Extension Library of Optimized Scatter Operations.,18.0,20,2021-10-22 09:39:51.000000,2.0.9,20.0,,torch-scatter,,,,['pytorch'],,,https://pypi.org/project/torch-scatter,31870.0,31870.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +512,ploomber,True,ploomber/ploomber,,data-pipelines,https://github.com/ploomber/ploomber,https://github.com/ploomber/ploomber,Apache-2.0,2020-01-20 20:13:06.000000,2021-12-15 20:08:01.000000,2021-12-13 17:31:20.000000,64.0,77.0,323.0,793,2184.0,Lean Data Science workflows: develop and test locally. Deploy to..,23.0,20,,,,,ploomber,,,,,22.0,22.0,https://pypi.org/project/ploomber,2691.0,2691.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +513,explainerdashboard,True,oegedijk/explainerdashboard,,interpretability,https://github.com/oegedijk/explainerdashboard,https://github.com/oegedijk/explainerdashboard,MIT,2019-10-30 08:26:16.000000,2021-12-08 13:50:00.000000,2021-12-08 13:49:58.000000,91.0,21.0,113.0,768,1224.0,Quickly build Explainable AI dashboards that show the inner..,12.0,20,2021-10-24 19:56:27.000000,0.3.7,66.0,,explainerdashboard,,,,,46.0,46.0,https://pypi.org/project/explainerdashboard,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +514,Prince,True,MaxHalford/prince,,others,https://github.com/MaxHalford/prince,https://github.com/MaxHalford/prince,MIT,2016-10-22 12:36:06.000000,2021-12-11 00:12:58.000000,2021-12-11 00:12:58.000000,128.0,34.0,67.0,740,198.0,"Python factor analysis library (PCA, CA, MCA, MFA, FAMD).",10.0,20,,,,,prince,,,,['sklearn'],168.0,168.0,https://pypi.org/project/prince,17542.0,17542.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +515,Objax,True,google/objax,,ml-frameworks,https://github.com/google/objax,https://github.com/google/objax,Apache-2.0,2020-08-20 06:20:40.000000,2021-09-20 23:54:26.000000,2021-09-20 23:54:26.000000,56.0,37.0,56.0,665,414.0,Objax is a machine learning framework that provides an Object..,22.0,20,2021-04-01 00:14:18.000000,1.4.0,6.0,,objax,,,,['jax'],17.0,17.0,https://pypi.org/project/objax,2463.0,2463.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +516,PDPbox,True,SauceCat/PDPbox,,data-viz,https://github.com/SauceCat/PDPbox,https://github.com/SauceCat/PDPbox,MIT,2017-06-26 08:01:54.000000,2021-06-24 15:32:01.000000,2021-03-14 16:01:01.000000,102.0,17.0,38.0,638,227.0,python partial dependence plot toolbox.,7.0,20,2021-03-14 16:07:34.000000,0.2.1,2.0,,pdpbox,conda-forge/pdpbox,,,,457.0,457.0,https://pypi.org/project/pdpbox,,354.0,https://anaconda.org/conda-forge/pdpbox,2021-03-14 19:37:51.465000,10291.0,,,,,3.0,,,,,,,,,,,,,,,, +517,PyKEEN,True,pykeen/pykeen,,graph,https://github.com/pykeen/pykeen,https://github.com/pykeen/pykeen,MIT,2020-02-24 07:26:03.000000,2021-12-16 12:33:15.000000,2021-12-13 19:23:25.000000,90.0,94.0,208.0,633,2503.0,A Python library for learning and evaluating knowledge graph embeddings.,24.0,20,2021-10-18 09:50:50.000000,1.6.0,12.0,,pykeen,,,,,,,https://pypi.org/project/pykeen,900.0,905.0,,,,,,,,2.0,92.0,,,,,,,,,,,,,,, +518,CellProfiler,True,CellProfiler/CellProfiler,,image,https://github.com/CellProfiler/CellProfiler,https://github.com/CellProfiler/CellProfiler,,2011-04-05 12:10:12.000000,2021-11-22 12:29:52.000000,2021-11-05 20:24:04.000000,294.0,196.0,2816.0,633,15358.0,An open-source application for biological image analysis.,121.0,20,2021-07-22 19:01:42.000000,4.2.1,43.0,,cellprofiler,,,,,5.0,5.0,https://pypi.org/project/cellprofiler,,21.0,,,,,,,,3.0,2018.0,,,,,,,,,,,,,,, +519,inflect,True,jaraco/inflect,,nlp,https://github.com/jaraco/inflect,https://github.com/jaraco/inflect,MIT,2010-06-20 13:43:13.000000,2021-12-12 20:37:30.000000,2021-03-23 00:21:53.000000,65.0,17.0,63.0,594,,"Correctly generate plurals, ordinals, indefinite articles; convert numbers..",29.0,20,2021-03-03 01:32:18.000000,5.3.0,12.0,,inflect,conda-forge/inflect,,,,,,https://pypi.org/project/inflect,1288946.0,1292329.0,https://anaconda.org/conda-forge/inflect,2021-11-02 11:19:10.735000,189490.0,,,,,3.0,,,,,,,,,,,,,,,, +520,Caer,True,jasmcaus/caer,,image,https://github.com/jasmcaus/caer,https://github.com/jasmcaus/caer,MIT,2020-08-06 18:36:14.000000,2021-10-13 21:04:50.000000,2021-10-13 21:05:33.000000,63.0,2.0,13.0,576,5078.0,"A lightweight Computer Vision library. Scale your models, not boilerplate.",8.0,20,2021-10-06 07:29:20.000000,2.0.3,13.0,,caer,,,https://caer.rtfd.io,,,,https://pypi.org/project/caer,4092.0,4093.0,,,,,,,,3.0,19.0,,,,,,,,,,,,,,, +521,PyTorch Sparse,True,rusty1s/pytorch_sparse,,pytorch-utils,https://github.com/rusty1s/pytorch_sparse,https://github.com/rusty1s/pytorch_sparse,MIT,2018-07-28 18:46:53.000000,2021-11-13 22:13:04.000000,2021-11-13 22:13:02.000000,68.0,25.0,129.0,537,650.0,PyTorch Extension Library of Optimized Autograd Sparse..,17.0,20,2021-09-08 09:32:15.000000,0.6.12,22.0,,torch-sparse,,,,['pytorch'],,,https://pypi.org/project/torch-sparse,19943.0,19943.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +522,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 18:30:17.000000,2021-12-01 15:33:10.000000,2021-11-09 22:44:59.000000,56.0,6.0,38.0,507,614.0,A simplified framework and utilities for PyTorch.,16.0,20,2021-10-30 18:41:03.000000,1.7,24.0,,poutyne,,,,['pytorch'],73.0,73.0,https://pypi.org/project/poutyne,5752.0,5752.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +523,findspark,True,minrk/findspark,,others,https://github.com/minrk/findspark,https://github.com/minrk/findspark,BSD-3-Clause,2015-06-12 21:34:06.000000,2021-06-14 06:11:28.000000,2021-06-14 06:10:09.000000,66.0,11.0,10.0,424,,Find pyspark to make it importable.,14.0,20,,,4.0,,findspark,conda-forge/findspark,,,['spark'],2116.0,2116.0,https://pypi.org/project/findspark,,9062.0,https://anaconda.org/conda-forge/findspark,2018-07-06 12:57:33.438000,598103.0,,,,,3.0,,,,,,,,,,,,,,,, +524,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 21:02:09.000000,2021-12-16 07:41:13.000000,2021-12-16 07:41:12.000000,75.0,18.0,56.0,410,573.0,For recording and retrieving metadata associated with ML..,13.0,20,2021-11-29 23:48:29.000000,1.5.0,27.0,,ml-metadata,,,,,170.0,170.0,https://pypi.org/project/ml-metadata,,51.0,,,,,,,,3.0,1711.0,,,,,,,,,,,,,,, +525,pyvips,True,libvips/pyvips,,image,https://github.com/libvips/pyvips,https://github.com/libvips/pyvips,MIT,2017-07-28 16:39:43.000000,2021-12-15 10:07:01.000000,2021-12-15 10:05:34.000000,32.0,93.0,163.0,374,411.0,python binding for libvips using cffi.,12.0,20,,,3.0,,pyvips,conda-forge/pyvips,,,,252.0,252.0,https://pypi.org/project/pyvips,,491.0,https://anaconda.org/conda-forge/pyvips,2021-11-22 15:51:16.569000,13759.0,,,,,3.0,,,,,,,,,,,,,,,, +526,lazypredict,True,shankarpandala/lazypredict,,hyperopt,https://github.com/shankarpandala/lazypredict,https://github.com/shankarpandala/lazypredict,MIT,2019-11-16 09:56:35.000000,2021-10-18 15:23:13.000000,2021-10-18 15:23:12.000000,36.0,29.0,30.0,266,195.0,Lazy Predict help build a lot of basic models without much code..,16.0,20,,,,,lazypredict,,,,['sklearn'],207.0,207.0,https://pypi.org/project/lazypredict,7883.0,7883.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +527,pyfasttext,True,vrasneur/pyfasttext,,nlp,https://github.com/vrasneur/pyfasttext,https://github.com/vrasneur/pyfasttext,GPL-3.0,2017-06-30 18:44:42.000000,2018-12-08 15:02:54.000000,2018-12-08 15:02:12.000000,30.0,21.0,28.0,230,153.0,Yet another Python binding for fastText.,4.0,20,2018-12-08 15:02:54.000000,0.4.6,12.0,,pyfasttext,,,,,202.0,202.0,https://pypi.org/project/pyfasttext,5625.0,5631.0,,,,,,,,3.0,345.0,,,,,,,,,,,,,,, +528,py3nvml,True,fbcotter/py3nvml,,gpu-utilities,https://github.com/fbcotter/py3nvml,https://github.com/fbcotter/py3nvml,BSD-3-Clause,2016-11-21 01:07:37.000000,2021-11-19 20:12:42.962000,2021-09-06 14:45:26.000000,28.0,2.0,10.0,200,83.0,Python 3 Bindings for NVML library. Get NVIDIA GPU status inside..,8.0,20,2019-10-11 13:39:49.000000,0.2.4,6.0,,py3nvml,conda-forge/py3nvml,,,,357.0,357.0,https://pypi.org/project/py3nvml,,1033.0,https://anaconda.org/conda-forge/py3nvml,2021-11-19 20:12:42.962000,23778.0,,,,,2.0,,,,,,,,,,,,,,,, +529,Glow,True,projectglow/glow,,medical-data,https://github.com/projectglow/glow,https://github.com/projectglow/glow,Apache-2.0,2019-10-04 21:26:47.000000,2021-12-15 00:42:23.000000,2021-12-01 20:08:47.000000,55.0,45.0,77.0,184,363.0,An open-source toolkit for large-scale genomic analysis.,18.0,20,2021-10-30 01:16:11.000000,1.1.1,14.0,,glow.py,,,,,,,https://pypi.org/project/glow.py,26928.0,26928.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +530,pyexcel-xlsx,True,pyexcel/pyexcel-xlsx,,data-loading,https://github.com/pyexcel/pyexcel-xlsx,https://github.com/pyexcel/pyexcel-xlsx,,2014-12-02 00:03:24.000000,2020-11-28 22:30:58.000000,2020-11-28 22:30:53.000000,17.0,13.0,20.0,95,267.0,"A wrapper library to read, manipulate and write data in xlsx and..",4.0,20,2020-10-10 13:13:09.000000,0.6.0,30.0,,pyexcel-xlsx,conda-forge/pyexcel-xlsx,,,,1429.0,1429.0,https://pypi.org/project/pyexcel-xlsx,109600.0,109971.0,https://anaconda.org/conda-forge/pyexcel-xlsx,2020-10-10 15:53:49.660000,18559.0,,,,,3.0,51.0,,,,,,,,,,,,,,, +531,Recommenders,True,microsoft/recommenders,,recommender-systems,https://github.com/microsoft/recommenders,https://github.com/microsoft/recommenders,MIT,2018-09-19 10:06:07.000000,2021-12-16 13:50:37.000000,2021-09-23 08:42:12.000000,1991.0,148.0,486.0,11804,,Best Practices on Recommendation Systems.,101.0,19,2021-09-23 18:03:12.000000,0.7.0,9.0,,,,,,,5.0,5.0,,,2.0,,,,,,,,3.0,85.0,,,,,,,,,,,,,,, +532,vit-pytorch,True,lucidrains/vit-pytorch,,image,https://github.com/lucidrains/vit-pytorch,https://github.com/lucidrains/vit-pytorch,MIT,2020-10-03 22:47:24.000000,2021-12-04 04:07:18.000000,2021-12-04 04:07:18.000000,1068.0,73.0,80.0,7167,,"Implementation of Vision Transformer, a simple way to..",12.0,19,2021-12-04 03:52:57.000000,0.24.3,100.0,,vit-pytorch,,,,['pytorch'],59.0,59.0,https://pypi.org/project/vit-pytorch,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +533,PaddleDetection,True,PaddlePaddle/PaddleDetection,,image,https://github.com/PaddlePaddle/PaddleDetection,https://github.com/PaddlePaddle/PaddleDetection,Apache-2.0,2019-10-25 07:21:14.000000,2021-12-16 13:35:55.000000,2021-12-09 10:44:04.000000,1441.0,783.0,1963.0,5776,,Object detection and instance segmentation toolkit..,75.0,19,2021-12-09 11:11:05.000000,2.3.0,5.0,,,,,,['paddle'],6.0,6.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +534,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 20:32:44.000000,2021-11-16 17:00:34.000000,2021-08-04 06:54:21.000000,1124.0,48.0,215.0,5409,205.0,2D and 3D Face alignment library build using pytorch.,23.0,19,2021-04-28 22:15:40.000000,1.3.4,10.0,,face-alignment,,,,['pytorch'],,,https://pypi.org/project/face-alignment,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +535,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 03:02:39.000000,2021-12-10 12:36:28.000000,2021-03-15 15:49:05.000000,866.0,175.0,144.0,4466,145.0,Official Kaggle API.,36.0,19,,,8.0,,kaggle,conda-forge/kaggle,,,,,,https://pypi.org/project/kaggle,,2418.0,https://anaconda.org/conda-forge/kaggle,2021-11-15 19:59:06.419000,74983.0,,,,,3.0,,,,,-8.0,,,,,,,,,,, +536,cuDF,True,rapidsai/cudf,,gpu-utilities,https://github.com/rapidsai/cudf,https://github.com/rapidsai/cudf,Apache-2.0,2017-05-07 03:43:37.000000,2021-12-16 13:07:09.000000,2021-12-16 02:50:55.000000,568.0,606.0,3589.0,4365,,cuDF - GPU DataFrame Library.,226.0,19,2021-12-09 18:32:39.000000,21.12.01,20.0,,cudf,,,,,,,https://pypi.org/project/cudf,1092.0,1092.0,,,,,,,,2.0,,,,,,,,,,,,,,,, +537,MindsDB,True,mindsdb/mindsdb,,ml-frameworks,https://github.com/mindsdb/mindsdb,https://github.com/mindsdb/mindsdb,GPL-3.0,2018-08-02 17:56:45.000000,2021-12-16 09:52:20.000000,2021-12-16 07:59:55.000000,552.0,78.0,699.0,4187,,Predictive AI layer for existing databases.,89.0,19,2021-12-10 14:48:52.000000,2.59.0,79.0,,mindsdb,,,,['pytorch'],,,https://pypi.org/project/mindsdb,3168.0,3168.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +538,neon,True,NervanaSystems/neon,,ml-frameworks,https://github.com/NervanaSystems/neon,https://github.com/NervanaSystems/neon,Apache-2.0,2014-10-16 01:00:17.000000,2020-12-23 01:21:42.000000,2019-05-22 18:27:54.000000,807.0,82.0,306.0,3855,1118.0,Intel Nervana reference deep learning framework committed to best..,109.0,19,2018-01-05 21:36:23.000000,2.6.0,32.0,,nervananeon,,,,,,,https://pypi.org/project/nervananeon,99.0,103.0,,,,,,,,3.0,317.0,,,,,,,,,,,,,,, +539,Crypto Signals,True,CryptoSignal/crypto-signal,,financial-data,https://github.com/CryptoSignal/Crypto-Signal,https://github.com/CryptoSignal/Crypto-Signal,MIT,2017-09-16 23:49:24.000000,2021-10-19 20:21:49.000000,2021-06-28 16:44:17.000000,949.0,49.0,198.0,3694,564.0,Github.com/CryptoSignal - #1 Quant Trading & Technical..,28.0,19,,,,,,,shadowreaver/crypto-signal,,,,,,,2752.0,,,,https://hub.docker.com/r/shadowreaver/crypto-signal,2020-09-03 13:00:35.801133,7.0,140399.0,3.0,,,,,,,,,,,,,,,, +540,ArrayFire,True,arrayfire/arrayfire,,gpu-utilities,https://github.com/arrayfire/arrayfire,https://github.com/arrayfire/arrayfire,,2014-10-28 20:58:33.000000,2021-12-13 22:58:44.000000,2021-10-15 20:16:28.000000,479.0,226.0,1262.0,3693,5776.0,ArrayFire: a general purpose GPU library.,81.0,19,2021-01-08 21:41:09.000000,3.8.0,30.0,,arrayfire,,,,,,,https://pypi.org/project/arrayfire,522.0,544.0,,,,,,,,2.0,1734.0,,,,,,,,,,,,,,, +541,AdaNet,True,tensorflow/adanet,,hyperopt,https://github.com/tensorflow/adanet,https://github.com/tensorflow/adanet,Apache-2.0,2018-06-28 20:20:24.000000,2021-08-30 19:33:24.000000,2021-08-30 19:33:24.000000,519.0,65.0,47.0,3341,440.0,Fast and flexible AutoML with learning guarantees.,27.0,19,2020-07-09 20:53:28.000000,0.9.0,11.0,,adanet,,,,['tensorflow'],41.0,41.0,https://pypi.org/project/adanet,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +542,TensorWatch,True,microsoft/tensorwatch,,ml-experiments,https://github.com/microsoft/tensorwatch,https://github.com/microsoft/tensorwatch,MIT,2019-05-15 08:29:34.000000,2021-04-13 09:44:02.000000,2021-01-15 19:46:05.000000,336.0,50.0,15.0,3191,112.0,"Debugging, monitoring and visualization for Python Machine Learning..",13.0,19,,,,,tensorwatch,,,,,65.0,65.0,https://pypi.org/project/tensorwatch,6071.0,6071.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +543,Camelot,True,atlanhq/camelot,,data-loading,https://github.com/atlanhq/camelot,https://github.com/atlanhq/camelot,,2016-06-18 11:48:49.000000,2021-11-24 11:40:44.000000,2019-10-15 05:25:40.000000,326.0,76.0,277.0,3149,446.0,Camelot: PDF Table Extraction for Humans.,23.0,19,2019-01-17 04:21:43.000000,0.7.2,1.0,,camelot-py,,,,,,,https://pypi.org/project/camelot-py,43441.0,43441.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +544,River,True,online-ml/river,,others,https://github.com/online-ml/river,https://github.com/online-ml/river,BSD-3-Clause,2019-01-24 15:18:26.000000,2021-12-16 12:00:07.000000,2021-12-16 11:57:19.000000,319.0,5.0,325.0,2974,,Online machine learning in Python.,70.0,19,2021-12-01 16:11:26.000000,0.9.0,1.0,,,,,,,56.0,56.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +545,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 16:09:50.000000,2021-12-14 22:39:12.000000,2021-12-14 22:39:09.000000,378.0,14.0,18.0,2923,828.0,High-performance TensorFlow library for quantitative..,36.0,19,,,4.0,,tf-quant-finance,,,,['tensorflow'],,,https://pypi.org/project/tf-quant-finance,892.0,892.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +546,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 21:00:13.000000,2021-09-12 08:32:45.000000,2021-09-12 08:29:06.000000,417.0,14.0,112.0,2767,954.0,A model library for exploring state-of-the-art deep learning..,37.0,19,2020-11-17 12:32:37.000000,0.5.5.1,13.0,,nlp-architect,,,,,8.0,8.0,https://pypi.org/project/nlp-architect,480.0,480.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +547,Porcupine,True,Picovoice/Porcupine,,audio,https://github.com/Picovoice/porcupine,https://github.com/Picovoice/porcupine,Apache-2.0,2018-03-08 01:55:25.000000,2021-12-16 00:39:50.000000,2021-12-15 18:52:09.000000,361.0,6.0,336.0,2606,622.0,On-device wake word detection powered by deep learning.,30.0,19,2021-11-25 22:59:03.000000,2.0,11.0,,pvporcupine,,,,,6.0,6.0,https://pypi.org/project/pvporcupine,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +548,Apache Singa,True,apache/singa,,distributed-ml,https://github.com/apache/singa,https://github.com/apache/singa,Apache-2.0,2015-04-02 07:00:05.000000,2021-12-02 04:35:29.000000,2021-08-10 09:12:48.000000,717.0,18.0,49.0,2448,2360.0,a distributed deep learning platform.,76.0,19,2020-04-21 08:01:08.000000,3.0.0,16.0,,,nusdbsystem/singa,apache/singa,,,1.0,1.0,,,8.0,https://anaconda.org/nusdbsystem/singa,2021-08-09 13:10:26.397000,389.0,https://hub.docker.com/r/apache/singa,2019-06-04 04:32:52.195956,4.0,209.0,3.0,,,,,,,,,,,,,,,, +549,pygal,True,Kozea/pygal,,graph,https://github.com/Kozea/pygal,https://github.com/Kozea/pygal,LGPL-3.0,2011-09-23 10:17:50.000000,2021-11-29 10:47:48.000000,2021-11-24 21:04:02.000000,384.0,155.0,244.0,2418,1018.0,PYthon svg GrAph plotting Library.,71.0,19,2015-02-16 16:54:22.000000,1.7.0,2.0,,pygal,conda-forge/pygal,,,,,,https://pypi.org/project/pygal,,316.0,https://anaconda.org/conda-forge/pygal,2019-06-04 02:55:56.728000,9499.0,,,,,3.0,,,,,,,,,,,,,,,, +550,Luminoth,True,tryolabs/luminoth,,image,https://github.com/tryolabs/luminoth,https://github.com/tryolabs/luminoth,BSD-3-Clause,2017-02-16 15:07:46.000000,2021-08-25 16:02:32.000000,2020-01-07 20:53:25.000000,402.0,52.0,128.0,2386,838.0,Deep Learning toolkit for Computer Vision.,15.0,19,,,10.0,,luminoth,,,,['tensorflow'],39.0,39.0,https://pypi.org/project/luminoth,853.0,1093.0,,,,,,,,3.0,12034.0,,,,,,,,,,,,,,, +551,DeepWalk,True,phanein/deepwalk,,graph,https://github.com/phanein/deepwalk,https://github.com/phanein/deepwalk,GPL-3.0,2014-08-23 03:38:20.000000,2021-09-16 12:01:08.000000,2020-04-02 01:05:35.000000,779.0,25.0,80.0,2370,46.0,DeepWalk - Deep Learning for Graphs.,10.0,19,2014-11-19 19:20:33.000000,1.0.2,1.0,,deepwalk,,,,,46.0,46.0,https://pypi.org/project/deepwalk,2477.0,2477.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +552,TF Ranking,True,tensorflow/ranking,,recommender-systems,https://github.com/tensorflow/ranking,https://github.com/tensorflow/ranking,Apache-2.0,2018-12-03 20:48:57.000000,2021-11-22 21:37:02.000000,2021-11-22 21:36:59.000000,408.0,44.0,231.0,2362,442.0,Learning to Rank in TensorFlow.,25.0,19,2021-11-16 23:49:54.000000,0.5.0,15.0,,tensorflow_ranking,,,,['tensorflow'],,,https://pypi.org/project/tensorflow_ranking,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +553,DDSP,True,magenta/ddsp,,audio,https://github.com/magenta/ddsp,https://github.com/magenta/ddsp,Apache-2.0,2020-01-14 18:38:27.000000,2021-12-15 20:55:37.000000,2021-12-06 22:26:09.000000,207.0,20.0,105.0,2017,,DDSP: Differentiable Digital Signal Processing.,29.0,19,2021-11-22 18:43:52.000000,1.7.0,20.0,,ddsp,,,,['tensorflow'],18.0,18.0,https://pypi.org/project/ddsp,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +554,textacy,True,chartbeat-labs/textacy,,nlp,https://github.com/chartbeat-labs/textacy,https://github.com/chartbeat-labs/textacy,,2016-02-03 16:52:45.000000,2021-12-06 14:59:26.000000,2021-12-06 14:45:21.000000,226.0,26.0,219.0,1845,,"NLP, before and after spaCy.",31.0,19,2021-12-06 14:59:26.000000,0.12.0,28.0,,textacy,conda-forge/textacy,,,,,,https://pypi.org/project/textacy,35711.0,37558.0,https://anaconda.org/conda-forge/textacy,2021-04-13 18:57:20.207000,101633.0,,,,,3.0,,,,,,,,,,,,,,,, +555,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 16:48:48.000000,2021-12-14 11:50:25.000000,2021-12-14 11:50:25.000000,184.0,30.0,71.0,1622,,Fast and Easy Infinite Neural Networks in Python.,21.0,19,2021-11-17 06:35:11.000000,0.3.9,10.0,,neural-tangents,,,,,27.0,27.0,https://pypi.org/project/neural-tangents,,10.0,,,,,,,,3.0,185.0,,,,,,,,,,,,,,, +556,FairScale,True,facebookresearch/fairscale,,distributed-ml,https://github.com/facebookresearch/fairscale,https://github.com/facebookresearch/fairscale,BSD-3-Clause,2020-07-07 19:02:01.000000,2021-12-16 06:28:22.000000,2021-12-16 06:28:22.000000,138.0,53.0,196.0,1538,,PyTorch extensions for high performance and large scale training.,51.0,19,2021-11-18 22:57:34.000000,0.4.3,25.0,,fairscale,,,,['pytorch'],123.0,123.0,https://pypi.org/project/fairscale,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +557,Magnitude,True,plasticityai/magnitude,,nn-search,https://github.com/plasticityai/magnitude,https://github.com/plasticityai/magnitude,MIT,2018-02-24 07:28:16.000000,2021-02-23 18:10:43.000000,2020-07-17 20:19:46.000000,103.0,29.0,51.0,1497,350.0,"A fast, efficient universal vector embedding utility package.",4.0,19,2020-05-25 11:26:09.000000,0.1.143,100.0,,pymagnitude,,,,,213.0,213.0,https://pypi.org/project/pymagnitude,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +558,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 20:51:25.000000,2021-09-29 18:48:52.000000,2021-09-29 18:48:52.000000,181.0,10.0,31.0,1464,239.0,pip install antialiased-cnns to improve stability and..,6.0,19,2020-10-23 22:45:52.000000,0.3,4.0,,antialiased-cnns,,,,['pytorch'],12.0,12.0,https://pypi.org/project/antialiased-cnns,1116.0,1116.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +559,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 19:35:56.000000,2021-07-08 19:04:05.000000,2021-07-08 19:03:55.000000,188.0,2.0,49.0,1416,108.0,"Pretrained EfficientNet, EfficientNet-Lite, MixNet,..",5.0,19,,,,,geffnet,,,,['pytorch'],87.0,87.0,https://pypi.org/project/geffnet,7166.0,7166.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +560,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 04:24:04.000000,2021-02-10 05:12:44.000000,2021-02-10 05:12:44.000000,179.0,57.0,145.0,1353,902.0,ThunderSVM: A Fast SVM Library on GPUs and CPUs.,33.0,19,2019-11-17 09:36:51.000000,0.3.4,5.0,,thundersvm,,,,,,,https://pypi.org/project/thundersvm,726.0,763.0,,,,,,,,3.0,2295.0,,,,,,,,,,,,,,, +561,lightly,True,lightly-ai/lightly,,image,https://github.com/lightly-ai/lightly,https://github.com/lightly-ai/lightly,MIT,2020-10-13 13:02:56.000000,2021-12-16 10:59:24.000000,2021-12-16 10:49:20.000000,86.0,62.0,229.0,1345,570.0,A python library for self-supervised learning on images.,14.0,19,2021-12-14 14:30:04.000000,1.2.1,35.0,,lightly,,,,['pytorch'],25.0,25.0,https://pypi.org/project/lightly,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +562,Higher,True,facebookresearch/higher,,pytorch-utils,https://github.com/facebookresearch/higher,https://github.com/facebookresearch/higher,Apache-2.0,2019-09-06 18:58:36.000000,2021-11-30 14:53:11.000000,2021-10-26 07:08:33.000000,95.0,45.0,50.0,1297,,higher is a pytorch library allowing users to obtain higher..,9.0,19,,,,,higher,,,,['pytorch'],101.0,101.0,https://pypi.org/project/higher,32533.0,32533.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +563,fairlearn,True,fairlearn/fairlearn,,interpretability,https://github.com/fairlearn/fairlearn,https://github.com/fairlearn/fairlearn,MIT,2018-05-15 01:51:35.000000,2021-12-15 16:49:59.000000,2021-12-15 16:38:40.000000,267.0,117.0,199.0,1142,,A Python package to assess and improve fairness of machine..,61.0,19,2021-07-07 08:16:09.000000,0.7.0,11.0,,fairlearn,conda-forge/fairlearn,,,['sklearn'],,,https://pypi.org/project/fairlearn,,745.0,https://anaconda.org/conda-forge/fairlearn,2021-07-07 15:56:16.605000,16403.0,,,,,3.0,,,,,,,,,,,,,,,, +564,luminol,True,linkedin/luminol,,time-series-data,https://github.com/linkedin/luminol,https://github.com/linkedin/luminol,Apache-2.0,2015-11-18 23:16:33.000000,2020-12-27 09:54:35.000000,2018-01-09 07:46:55.000000,193.0,24.0,12.0,981,69.0,Anomaly Detection and Correlation library.,8.0,19,,,,,luminol,,,,,47.0,47.0,https://pypi.org/project/luminol,40536.0,40536.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +565,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 18:22:13.000000,2021-04-21 08:39:31.000000,2020-08-19 16:56:56.000000,170.0,172.0,236.0,964,595.0,A Framework for Encrypted Machine Learning in TensorFlow.,28.0,19,,,,,tf-encrypted,,,,['tensorflow'],58.0,58.0,https://pypi.org/project/tf-encrypted,573.0,573.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +566,keras-ocr,True,faustomorales/keras-ocr,,ocr,https://github.com/faustomorales/keras-ocr,https://github.com/faustomorales/keras-ocr,MIT,2019-09-20 23:08:50.000000,2021-11-24 10:16:01.000000,2021-11-24 10:01:11.000000,236.0,47.0,105.0,955,184.0,A packaged and flexible version of the CRAFT text detector and..,12.0,19,2020-09-13 21:05:45.000000,0.8.4,1.0,,keras-ocr,,,,['tensorflow'],,,https://pypi.org/project/keras-ocr,4915.0,18349.0,,,,,,,,3.0,201521.0,,,,,,,,,,,,,,, +567,TensorFrames,True,databricks/tensorframes,,distributed-ml,https://github.com/databricks/tensorframes,https://github.com/databricks/tensorframes,Apache-2.0,2016-03-04 19:25:19.000000,2021-08-25 14:58:55.000000,2019-11-15 21:43:53.000000,157.0,48.0,43.0,761,221.0,[DEPRECATED] Tensorflow wrapper for DataFrames on..,16.0,19,2018-11-16 20:50:02.000000,0.6.0,6.0,,tensorframes,,,,"['tensorflow', 'spark']",,,https://pypi.org/project/tensorframes,21326.0,21326.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +568,Performer Pytorch,True,lucidrains/performer-pytorch,,pytorch-utils,https://github.com/lucidrains/performer-pytorch,https://github.com/lucidrains/performer-pytorch,MIT,2020-10-03 03:41:36.000000,2021-11-07 01:02:45.000000,2021-11-07 01:02:14.000000,99.0,27.0,41.0,758,,"An implementation of Performer, a linear attention-..",6.0,19,2021-11-07 01:02:45.000000,1.1.3,79.0,,performer-pytorch,,,,['pytorch'],34.0,34.0,https://pypi.org/project/performer-pytorch,1394.0,1394.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +569,TreeInterpreter,True,andosa/treeinterpreter,,interpretability,https://github.com/andosa/treeinterpreter,https://github.com/andosa/treeinterpreter,BSD-3-Clause,2015-08-02 20:26:21.000000,2021-02-28 18:33:06.000000,2021-02-28 18:33:06.000000,133.0,19.0,4.0,689,37.0,Package for interpreting scikit-learn's decision tree..,11.0,19,,,,,treeinterpreter,,,,['sklearn'],181.0,181.0,https://pypi.org/project/treeinterpreter,203030.0,203030.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +570,scikit-lego,True,koaning/scikit-lego,,sklearn-utils,https://github.com/koaning/scikit-lego,https://github.com/koaning/scikit-lego,MIT,2019-01-21 15:30:15.000000,2021-12-13 15:23:10.000000,2021-12-09 11:40:28.000000,75.0,32.0,200.0,666,,Extra blocks for scikit-learn pipelines.,48.0,19,2021-12-09 11:34:28.000000,0.6.9,27.0,,scikit-lego,conda-forge/scikit-lego,,,['sklearn'],39.0,39.0,https://pypi.org/project/scikit-lego,,630.0,https://anaconda.org/conda-forge/scikit-lego,2021-12-09 15:20:11.388000,16391.0,,,,,2.0,,,,,,,,,,,,,,,, +571,sklearn-deap,True,rsteca/sklearn-deap,,hyperopt,https://github.com/rsteca/sklearn-deap,https://github.com/rsteca/sklearn-deap,MIT,2015-10-28 22:52:34.000000,2021-07-30 15:07:28.000000,2021-07-30 15:06:27.000000,109.0,16.0,34.0,666,104.0,Use evolutionary algorithms instead of gridsearch in..,22.0,19,2021-07-30 15:07:28.000000,0.3.0,14.0,,sklearn-deap,,,,['sklearn'],30.0,30.0,https://pypi.org/project/sklearn-deap,1040.0,1040.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +572,Guild AI,True,guildai/guildai,,ml-experiments,https://github.com/guildai/guildai,https://github.com/guildai/guildai,Apache-2.0,2017-09-27 18:57:50.000000,2021-12-15 22:35:27.000000,2021-12-15 22:34:59.000000,58.0,117.0,174.0,644,4586.0,"Experiment tracking, ML developer tools.",18.0,19,,,,,guildai,,,,,38.0,38.0,https://pypi.org/project/guildai,2756.0,2756.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +573,Torchbearer,True,pytorchbearer/torchbearer,,ml-frameworks,https://github.com/pytorchbearer/torchbearer,https://github.com/pytorchbearer/torchbearer,MIT,2018-03-12 16:30:42.000000,2021-03-26 19:56:57.000000,2021-03-26 19:56:57.000000,68.0,8.0,237.0,615,430.0,torchbearer: A model fitting library for PyTorch.,13.0,19,2020-01-31 14:07:22.000000,0.5.3,24.0,,torchbearer,,,,['pytorch'],56.0,56.0,https://pypi.org/project/torchbearer,556.0,556.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +574,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 20:26:10.000000,2021-11-01 12:13:56.000000,2021-11-01 12:13:55.000000,117.0,48.0,46.0,611,324.0,Source code/webpage/demos for the What-If Tool.,20.0,19,2021-10-12 17:36:36.000000,1.8.1,3.0,,witwidget,,,,,,,https://pypi.org/project/witwidget,,4284.0,,,,,,,,3.0,,wit-widget,https://www.npmjs.com/package/wit-widget,4284.0,,,,,,,,,,,, +575,deeplift,True,kundajelab/deeplift,,interpretability,https://github.com/kundajelab/deeplift,https://github.com/kundajelab/deeplift,MIT,2016-06-01 02:18:06.000000,2021-11-11 17:50:26.000000,2021-11-11 17:50:26.000000,134.0,33.0,48.0,596,553.0,Public facing deeplift repo.,11.0,19,,,21.0,,deeplift,,,,,52.0,52.0,https://pypi.org/project/deeplift,516.0,516.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +576,Mapbox GL,True,mapbox/mapboxgl-jupyter,,geospatial-data,https://github.com/mapbox/mapboxgl-jupyter,https://github.com/mapbox/mapboxgl-jupyter,MIT,2017-08-08 15:10:51.000000,2021-10-11 17:16:45.000000,2021-04-19 05:00:36.000000,122.0,31.0,67.0,592,221.0,Use Mapbox GL JS to visualize data in a Python Jupyter notebook.,21.0,19,2019-06-03 21:24:10.000000,0.10.2,14.0,,mapboxgl,,,,['jupyter'],123.0,123.0,https://pypi.org/project/mapboxgl,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +577,TensorFlow I/O,True,tensorflow/io,,tensorflow-utils,https://github.com/tensorflow/io,https://github.com/tensorflow/io,Apache-2.0,2018-11-09 22:44:05.000000,2021-12-15 23:04:19.000000,2021-12-15 20:19:44.000000,196.0,153.0,326.0,522,1529.0,"Dataset, streaming, and file system extensions maintained by TensorFlow SIG-IO.",83.0,19,2021-12-15 23:04:19.000000,0.23.1,30.0,,tensorflow-io,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-io,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +578,HpBandSter,True,automl/HpBandSter,,hyperopt,https://github.com/automl/HpBandSter,https://github.com/automl/HpBandSter,BSD-3-Clause,2017-12-17 20:28:20.000000,2021-01-31 10:05:37.000000,2019-03-26 09:26:28.000000,107.0,51.0,35.0,504,187.0,a distributed Hyperband implementation on Steroids.,11.0,19,2019-07-30 12:47:43.000000,1.0,1.0,,hpbandster,,,,,186.0,186.0,https://pypi.org/project/hpbandster,25252.0,25252.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +579,Neuraxle,True,Neuraxio/Neuraxle,,hyperopt,https://github.com/Neuraxio/Neuraxle,https://github.com/Neuraxio/Neuraxle,Apache-2.0,2019-03-26 21:01:54.000000,2021-12-16 13:48:40.000000,2021-11-01 21:10:39.000000,52.0,130.0,181.0,491,1593.0,A Sklearn-like Framework for Hyperparameter Tuning and AutoML in..,7.0,19,2021-10-17 21:12:29.000000,0.6.1,22.0,,neuraxle,,,,,24.0,24.0,https://pypi.org/project/neuraxle,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +580,PyWaffle,True,gyli/PyWaffle,,data-viz,https://github.com/gyli/PyWaffle,https://github.com/gyli/PyWaffle,MIT,2017-11-14 20:03:47.000000,2021-12-10 13:42:36.000000,2021-07-28 14:49:15.000000,80.0,3.0,11.0,459,254.0,Make Waffle Charts in Python.,6.0,19,,,,,pywaffle,,,,,101.0,101.0,https://pypi.org/project/pywaffle,2611.0,2611.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +581,pivottablejs,True,nicolaskruchten/jupyter_pivottablejs,,data-viz,https://github.com/nicolaskruchten/jupyter_pivottablejs,https://github.com/nicolaskruchten/jupyter_pivottablejs,,2015-09-09 13:39:18.000000,2018-12-04 14:43:26.000000,2018-12-04 14:43:25.000000,61.0,16.0,40.0,452,32.0,Dragndrop Pivot Tables and Charts for Jupyter/IPython..,3.0,19,2018-01-15 18:11:51.000000,0.9.0,8.0,,pivottablejs,,,,['jupyter'],206.0,206.0,https://pypi.org/project/pivottablejs,16709.0,16709.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +582,Case Recommender,True,caserec/CaseRecommender,,recommender-systems,https://github.com/caserec/CaseRecommender,https://github.com/caserec/CaseRecommender,MIT,2015-11-12 18:25:39.000000,2021-11-25 23:08:48.000000,2021-11-25 23:08:43.000000,77.0,4.0,20.0,372,204.0,Case Recommender: A Flexible and Extensible Python..,11.0,19,2021-11-25 23:10:34.000000,1.1.1,2.0,,caserecommender,,,,['sklearn'],9.0,9.0,https://pypi.org/project/caserecommender,815.0,815.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +583,MXBoard,True,awslabs/mxboard,,ml-experiments,https://github.com/awslabs/mxboard,https://github.com/awslabs/mxboard,Apache-2.0,2018-02-06 23:03:51.000000,2021-11-30 10:46:24.000000,2020-01-24 23:21:55.000000,47.0,16.0,15.0,333,42.0,Logging MXNet data for visualization in TensorBoard.,9.0,19,2018-05-22 20:20:50.000000,0.1.0,1.0,,mxboard,,,,['mxnet'],126.0,126.0,https://pypi.org/project/mxboard,5231.0,5231.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +584,TensorFlow Cloud,True,tensorflow/cloud,,tensorflow-utils,https://github.com/tensorflow/cloud,https://github.com/tensorflow/cloud,Apache-2.0,2020-02-10 18:51:59.000000,2021-12-13 23:30:59.000000,2021-09-07 17:39:33.000000,64.0,54.0,26.0,318,565.0,The TensorFlow Cloud repository provides APIs that..,25.0,19,2021-06-16 20:29:30.000000,0.1.16,17.0,,tensorflow-cloud,,,,['tensorflow'],115.0,115.0,https://pypi.org/project/tensorflow-cloud,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +585,sklearn-evaluation,True,edublancas/sklearn-evaluation,,interpretability,https://github.com/edublancas/sklearn-evaluation,https://github.com/edublancas/sklearn-evaluation,MIT,2015-09-04 16:33:42.000000,2021-10-17 18:09:38.000000,2021-10-17 18:09:37.000000,25.0,8.0,29.0,315,533.0,"Machine learning model evaluation made easy: plots,..",6.0,19,2021-06-26 14:03:00.000000,0.5.6,8.0,,sklearn-evaluation,,,,['sklearn'],33.0,33.0,https://pypi.org/project/sklearn-evaluation,912.0,912.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +586,NIPY,True,nipy/nipy,,medical-data,https://github.com/nipy/nipy,https://github.com/nipy/nipy,BSD-3-Clause,2010-05-02 10:00:33.000000,2021-12-05 02:53:17.000000,2021-03-29 16:56:48.000000,126.0,38.0,111.0,311,6427.0,Neuroimaging in Python FMRI analysis package.,63.0,19,,,2.0,,nipy,conda-forge/nipy,,,,,,https://pypi.org/project/nipy,1454.0,3140.0,https://anaconda.org/conda-forge/nipy,2020-05-04 19:38:04.112000,89362.0,,,,,3.0,,,,,,,,,,,,,,,, +587,impyute,True,eltonlaw/impyute,,others,https://github.com/eltonlaw/impyute,https://github.com/eltonlaw/impyute,MIT,2017-01-21 09:16:27.000000,2021-11-06 21:15:04.000000,2021-11-06 21:15:04.000000,43.0,27.0,37.0,299,292.0,Data imputations library to preprocess datasets with missing data.,11.0,19,,,,,impyute,,,,,120.0,120.0,https://pypi.org/project/impyute,2542.0,2542.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +588,datatest,True,shawnbrown/datatest,,data-loading,https://github.com/shawnbrown/datatest,https://github.com/shawnbrown/datatest,,2016-05-12 13:16:27.000000,2021-12-05 17:44:33.000000,2021-12-05 17:44:33.000000,12.0,10.0,42.0,253,2173.0,Tools for test driven data-wrangling and data validation.,7.0,19,2021-01-04 03:43:58.000000,0.11.1,16.0,,datatest,,,,,59.0,59.0,https://pypi.org/project/datatest,5649.0,5649.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +589,ivis,True,beringresearch/ivis,,data-viz,https://github.com/beringresearch/ivis,https://github.com/beringresearch/ivis,Apache-2.0,2018-08-13 08:31:01.000000,2021-11-08 17:08:45.000000,2021-11-08 17:08:42.000000,26.0,3.0,50.0,253,611.0,Dimensionality reduction in very large datasets using Siamese..,10.0,19,2021-10-17 09:48:21.000000,2.06,32.0,,ivis,,,,['tensorflow'],19.0,19.0,https://pypi.org/project/ivis,889.0,889.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +590,somoclu,True,peterwittek/somoclu,,distributed-ml,https://github.com/peterwittek/somoclu,https://github.com/peterwittek/somoclu,MIT,2013-01-16 06:33:16.000000,2021-11-15 19:51:57.895000,2021-10-31 08:28:12.000000,61.0,25.0,107.0,229,619.0,Massively parallel self-organizing maps: accelerate training on..,19.0,19,2021-10-31 08:33:47.000000,1.7.6,13.0,,somoclu,conda-forge/somoclu,,,,,,https://pypi.org/project/somoclu,2147.0,3265.0,https://anaconda.org/conda-forge/somoclu,2021-11-15 19:51:57.895000,57238.0,,,,,3.0,1541.0,,,,,,,,,,,,,,, +591,scikit-posthocs,True,maximtrp/scikit-posthocs,,probabilistics,https://github.com/maximtrp/scikit-posthocs,https://github.com/maximtrp/scikit-posthocs,MIT,2017-06-22 19:41:37.000000,2021-11-26 21:39:34.000000,2021-11-26 21:39:28.000000,23.0,4.0,39.0,224,466.0,Multiple Pairwise Comparisons (Post Hoc) Tests in Python.,8.0,19,2021-03-17 06:05:28.000000,0.6.7,5.0,,scikit-posthocs,,,,['sklearn'],,,https://pypi.org/project/scikit-posthocs,37695.0,37695.0,,,,,,,,3.0,23.0,,,,,,,,,,,,,,, +592,fletcher,True,xhochy/fletcher,,data-containers,https://github.com/xhochy/fletcher,https://github.com/xhochy/fletcher,MIT,2018-03-04 16:44:22.000000,2021-11-04 09:30:27.570000,2021-02-18 14:46:18.000000,34.0,33.0,40.0,219,520.0,Pandas ExtensionDType/Array backed by Apache Arrow.,24.0,19,2021-01-17 20:04:41.000000,0.7.2,14.0,,fletcher,conda-forge/fletcher,,,['pandas'],3.0,3.0,https://pypi.org/project/fletcher,,865.0,https://anaconda.org/conda-forge/fletcher,2021-11-04 09:30:27.570000,35473.0,,,,,3.0,13.0,,,,,,,,,,,,,,, +593,Dopamine,True,google/dopamine,,reinforcement-learning,https://github.com/google/dopamine,https://github.com/google/dopamine,Apache-2.0,2018-07-26 09:58:36.000000,2021-12-14 17:59:05.000000,2021-12-14 17:59:04.000000,1270.0,60.0,82.0,9679,282.0,Dopamine is a research framework for fast prototyping of..,14.0,18,2019-09-26 14:58:33.000000,2,2.0,,dopamine-rl,,,,['tensorflow'],,,https://pypi.org/project/dopamine-rl,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +594,TensorLayer,True,tensorlayer/tensorlayer,,reinforcement-learning,https://github.com/tensorlayer/TensorLayer,https://github.com/tensorlayer/TensorLayer,,2016-06-07 15:55:16.000000,2021-12-03 08:14:02.000000,2021-10-29 08:29:08.000000,1484.0,18.0,437.0,6793,3350.0,Deep Learning and Reinforcement Learning Library for..,132.0,18,2021-01-06 07:16:21.000000,2.2.4,76.0,,tensorlayer,,,,['tensorflow'],,,https://pypi.org/project/tensorlayer,,20.0,,,,,,,,3.0,1289.0,,,,,,,,,,,,,,, +595,TTS,True,mozilla/TTS,,audio,https://github.com/mozilla/TTS,https://github.com/mozilla/TTS,MPL-2.0,2018-01-23 14:22:06.000000,2021-08-10 18:22:41.000000,2021-02-12 10:36:31.000000,851.0,15.0,506.0,5421,2184.0,Deep learning for Text to Speech (Discussion forum:..,56.0,18,2021-01-29 00:03:56.000000,0.0.9,1.0,,,,,,,,,,,139.0,,,,,,,,3.0,1531.0,,,,,,,,,,,,,,, +596,MMF,True,facebookresearch/mmf,,image,https://github.com/facebookresearch/mmf,https://github.com/facebookresearch/mmf,BSD-3-Clause,2018-06-27 04:52:40.000000,2021-12-16 07:49:22.000000,2021-12-14 21:47:29.000000,778.0,151.0,416.0,4712,,A modular framework for vision & language multimodal research from..,89.0,18,2019-08-26 19:04:21.000000,0.3.1,2.0,,mmf,,,,['pytorch'],10.0,10.0,https://pypi.org/project/mmf,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +597,TensorFlowOnSpark,True,yahoo/TensorFlowOnSpark,,distributed-ml,https://github.com/yahoo/TensorFlowOnSpark,https://github.com/yahoo/TensorFlowOnSpark,Apache-2.0,2017-01-20 18:15:57.000000,2021-10-15 23:08:42.000000,2021-10-15 23:08:39.000000,921.0,5.0,354.0,3747,628.0,TensorFlowOnSpark brings TensorFlow programs to..,33.0,18,2021-05-25 22:25:31.000000,2.2.4,22.0,,tensorflowonspark,,,,"['tensorflow', 'spark']",,,https://pypi.org/project/tensorflowonspark,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +598,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 20:00:52.000000,2021-10-18 02:38:38.000000,2021-10-18 01:45:21.000000,570.0,141.0,93.0,2834,143.0,Python package to easily retrain OpenAI's GPT-2 text-..,18.0,18,2021-10-18 02:38:39.000000,0.8.1,17.0,,gpt-2-simple,,,,['tensorflow'],,,https://pypi.org/project/gpt-2-simple,6363.0,6371.0,,,,,,,,3.0,281.0,,,,,,,,,,,,,,, +599,cuML,True,rapidsai/cuml,,gpu-utilities,https://github.com/rapidsai/cuml,https://github.com/rapidsai/cuml,Apache-2.0,2018-10-11 15:45:35.000000,2021-12-16 13:08:07.000000,2021-12-16 08:32:06.000000,367.0,613.0,1285.0,2499,,cuML - RAPIDS Machine Learning Library.,144.0,18,2021-12-08 19:17:51.000000,21.12.00,19.0,,cuml,,,,,,,https://pypi.org/project/cuml,751.0,751.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +600,PARL,True,PaddlePaddle/PARL,,reinforcement-learning,https://github.com/PaddlePaddle/PARL,https://github.com/PaddlePaddle/PARL,Apache-2.0,2018-04-25 17:54:22.000000,2021-12-15 02:24:20.000000,2021-12-15 02:22:19.000000,593.0,62.0,223.0,2346,1.0,A high-performance distributed training framework for Reinforcement..,28.0,18,2021-06-03 09:31:59.000000,2.0.0,7.0,,parl,,,,['paddle'],84.0,84.0,https://pypi.org/project/parl,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +601,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 03:11:32.000000,2021-12-13 01:36:04.000000,2021-12-13 01:32:56.000000,407.0,39.0,227.0,1960,249.0,Backtest trading strategies in Python.,15.0,18,,,,,backtesting,,,,,,,https://pypi.org/project/backtesting,12790.0,12790.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +602,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 22:01:20.000000,2021-09-23 12:14:23.000000,2021-08-31 13:59:28.000000,325.0,147.0,94.0,1678,,Super easy library for BERT based NLP models.,35.0,18,2020-07-09 12:05:40.000000,1.8.0,5.0,utterworks/fast-bert,fast-bert,,,,,,,https://pypi.org/project/fast-bert,1855.0,1855.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +603,AmpliGraph,True,Accenture/AmpliGraph,,graph,https://github.com/Accenture/AmpliGraph,https://github.com/Accenture/AmpliGraph,Apache-2.0,2019-01-09 14:52:05.000000,2021-09-24 18:27:27.000000,2021-05-25 16:49:48.000000,190.0,20.0,181.0,1660,947.0,Python library for Representation Learning on Knowledge..,19.0,18,2021-05-25 16:57:42.000000,1.4.0,11.0,,ampligraph,,,,['tensorflow'],16.0,16.0,https://pypi.org/project/ampligraph,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +604,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 09:25:46.000000,2021-12-16 10:09:47.000000,2021-12-16 08:59:29.000000,83.0,4.0,45.0,1488,,ZenML : MLOps framework to create reproducible ML pipelines for..,21.0,18,2021-12-14 01:39:49.000000,0.5.5,19.0,zenml-io/zenml,zenml,,,,,,,https://pypi.org/project/zenml,455.0,455.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +605,tensorrec,True,jfkirk/tensorrec,,recommender-systems,https://github.com/jfkirk/tensorrec,https://github.com/jfkirk/tensorrec,Apache-2.0,2017-02-28 18:51:11.000000,2021-09-07 23:58:55.000000,2020-02-04 21:10:25.000000,218.0,35.0,90.0,1168,334.0,A TensorFlow recommendation algorithm and framework in..,9.0,18,,,,,tensorrec,,,,['tensorflow'],26.0,26.0,https://pypi.org/project/tensorrec,306.0,306.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +606,Optimus,True,ironmussa/Optimus,,data-pipelines,https://github.com/hi-primus/optimus,https://github.com/hi-primus/optimus,Apache-2.0,2017-07-13 02:31:18.000000,2021-12-13 20:56:17.000000,2021-12-09 01:20:57.000000,205.0,30.0,195.0,1147,1.0,"Agile Data Preparation Workflows madeeasy with pandas, dask,..",23.0,18,2020-07-19 03:05:40.000000,2.2.32,73.0,hi-primus/optimus,optimuspyspark,,,,['spark'],,,https://pypi.org/project/optimuspyspark,7391.0,7391.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +607,sklearn-porter,True,nok/sklearn-porter,,model-serialisation,https://github.com/nok/sklearn-porter,https://github.com/nok/sklearn-porter,MIT,2016-06-22 22:21:34.000000,2021-11-23 15:46:59.000000,2019-12-18 13:31:50.000000,142.0,38.0,29.0,1111,699.0,"Transpile trained scikit-learn estimators to C, Java,..",11.0,18,2019-01-20 13:14:03.000000,0.7.2,15.0,,sklearn-porter,,,,['sklearn'],,,https://pypi.org/project/sklearn-porter,524.0,524.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +608,Sockeye,True,awslabs/sockeye,,nlp,https://github.com/awslabs/sockeye,https://github.com/awslabs/sockeye,Apache-2.0,2017-06-08 07:44:30.000000,2021-12-16 08:36:07.000000,2021-12-14 14:48:58.000000,279.0,5.0,252.0,1034,,Sequence-to-sequence framework with a focus on Neural Machine..,54.0,18,2021-12-13 17:39:31.000000,3.0.4,59.0,,sockeye,,,,['mxnet'],,,https://pypi.org/project/sockeye,468.0,468.0,,,,,,,,3.0,12.0,,,,,,,,,,,,,,, +609,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 16:53:56.000000,2021-11-30 17:18:08.000000,2021-04-29 14:20:17.000000,118.0,19.0,18.0,907,188.0,"Standard for moving data between databases, web APIs, files, queues, and just about anything else you can think of.",26.0,18,,,,,singer-python,,,,,,,https://pypi.org/project/singer-python,126211.0,126211.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +610,Labml,True,lab-ml/labml,,ml-experiments,https://github.com/labmlai/labml,https://github.com/labmlai/labml,MIT,2018-11-16 09:34:48.000000,2021-09-06 14:08:38.000000,2021-09-06 14:08:28.000000,58.0,15.0,10.0,890,1139.0,Monitor deep learning model training and hardware usage from your mobile..,6.0,18,2021-08-27 10:19:56.000000,0.4.132,3.0,labmlai/labml,labml,,,,,39.0,39.0,https://pypi.org/project/labml,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +611,FiftyOne,True,voxel51/fiftyone,,data-viz,https://github.com/voxel51/fiftyone,https://github.com/voxel51/fiftyone,,2020-04-22 13:43:28.000000,2021-12-15 22:01:52.000000,2021-11-30 16:18:01.000000,98.0,181.0,420.0,861,5467.0,"Visualize, create, and debug image and video datasets and model predictions.",20.0,18,2021-11-24 16:30:30.000000,0.14.2,23.0,,fiftyone,,,,"['tensorflow', 'pytorch', 'jupyter']",64.0,64.0,https://pypi.org/project/fiftyone,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +612,Orbit,True,uber/orbit,,probabilistics,https://github.com/uber/orbit,https://github.com/uber/orbit,,2020-01-07 18:20:37.000000,2021-12-15 04:27:39.000000,2021-12-15 04:27:38.000000,61.0,36.0,262.0,837,684.0,A Python package for Bayesian forecasting with object-oriented design..,14.0,18,2021-08-30 17:57:34.000000,1.0.17,15.0,,orbit-ml,,,,,5.0,5.0,https://pypi.org/project/orbit-ml,3116.0,3116.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +613,rows,True,turicas/rows,,data-loading,https://github.com/turicas/rows,https://github.com/turicas/rows,LGPL-3.0,2014-05-07 05:43:11.000000,2021-12-13 03:26:36.000000,2021-12-13 03:03:24.000000,133.0,142.0,149.0,779,738.0,"A common, beautiful interface to tabular data, no matter the format.",30.0,18,2019-02-14 21:20:15.000000,0.4.1,7.0,,rows,,,,,129.0,129.0,https://pypi.org/project/rows,,0.0,,,,,,,,3.0,37.0,,,,,,,,,,,,,,, +614,Tez,True,abhishekkrthakur/tez,,pytorch-utils,https://github.com/abhishekkrthakur/tez,https://github.com/abhishekkrthakur/tez,Apache-2.0,2020-11-13 10:19:22.000000,2021-10-01 10:49:27.000000,2021-09-27 14:42:42.000000,106.0,16.0,10.0,728,,Tez is a super-simple and lightweight Trainer for PyTorch. It..,,18,2021-08-16 18:42:17.000000,0.1.8,1.0,,tez,,,,['pytorch'],17.0,17.0,https://pypi.org/project/tez,1492.0,1492.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +615,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 13:05:44.000000,2020-06-30 10:19:46.000000,2019-05-21 11:29:06.000000,128.0,72.0,94.0,707,487.0,A scikit-learn based module for multi-label et. al...,15.0,18,2018-12-10 10:51:36.000000,0.2.0,4.0,,scikit-multilearn,,,,['sklearn'],607.0,607.0,https://pypi.org/project/scikit-multilearn,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +616,Test Tube,True,williamFalcon/test-tube,,hyperopt,https://github.com/williamFalcon/test-tube,https://github.com/williamFalcon/test-tube,MIT,2017-09-06 02:14:57.000000,2021-10-14 18:44:27.000000,2020-03-17 22:44:47.000000,64.0,23.0,21.0,703,642.0,Python library to easily log experiments and parallelize..,16.0,18,2019-06-29 19:21:43.000000,0.64,3.0,,test_tube,,,,,,,https://pypi.org/project/test_tube,12790.0,12790.0,,,,,,,,3.0,10.0,,,,,,,,,,,,,,, +617,AlphaPy,True,ScottfreeLLC/AlphaPy,,hyperopt,https://github.com/ScottfreeLLC/AlphaPy,https://github.com/ScottfreeLLC/AlphaPy,Apache-2.0,2016-02-14 00:47:32.000000,2021-10-23 07:17:16.000000,2021-10-23 07:17:16.000000,142.0,11.0,29.0,676,413.0,"Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,..",3.0,18,2020-08-29 18:48:20.000000,2.5.0,11.0,,alphapy,,,,,3.0,3.0,https://pypi.org/project/alphapy,177.0,177.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +618,finetune,True,IndicoDataSolutions/finetune,,nlp,https://github.com/IndicoDataSolutions/finetune,https://github.com/IndicoDataSolutions/finetune,MPL-2.0,2018-06-12 17:02:16.000000,2021-12-16 07:22:11.000000,2021-11-18 10:57:22.000000,69.0,22.0,116.0,656,1201.0,Scikit-learn style model finetuning for NLP.,19.0,18,2019-01-18 20:10:51.000000,0.5.14,14.0,,finetune,,,,"['tensorflow', 'sklearn']",9.0,9.0,https://pypi.org/project/finetune,75.0,75.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +619,robustness,True,MadryLab/robustness,,adversarial,https://github.com/MadryLab/robustness,https://github.com/MadryLab/robustness,MIT,2019-08-21 09:26:33.000000,2021-11-30 00:11:07.000000,2021-11-30 00:11:07.000000,120.0,13.0,54.0,635,141.0,"A library for experimenting with, training and evaluating neural..",13.0,18,2020-12-01 06:11:12.000000,1.2.1.post2,7.0,,robustness,,,,,67.0,67.0,https://pypi.org/project/robustness,877.0,877.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +620,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 00:32:10.000000,2021-11-11 01:20:14.000000,2021-11-11 01:20:14.000000,56.0,4.0,15.0,613,55.0,scikit-learn cross validators for iterative..,6.0,18,2021-10-03 18:24:15.000000,0.1.7,3.0,,iterative-stratification,,,,['sklearn'],178.0,178.0,https://pypi.org/project/iterative-stratification,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +621,Baal,True,ElementAI/baal,,probabilistics,https://github.com/ElementAI/baal,https://github.com/ElementAI/baal,Apache-2.0,2019-09-30 20:16:26.000000,2021-12-14 14:15:31.000000,2021-12-14 14:15:31.000000,48.0,18.0,44.0,491,149.0,Using approximate bayesian posteriors in deep nets for active learning.,11.0,18,2021-12-13 13:46:51.000000,1.5.0,7.0,,baal,,,,,,,https://pypi.org/project/baal,529.0,529.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +622,aequitas,True,dssg/aequitas,,interpretability,https://github.com/dssg/aequitas,https://github.com/dssg/aequitas,MIT,2018-02-13 19:40:30.000000,2021-07-13 10:19:56.000000,2021-05-27 09:45:10.000000,84.0,37.0,21.0,441,857.0,Bias and Fairness Audit Toolkit.,16.0,18,,,,,aequitas,,,,,87.0,87.0,https://pypi.org/project/aequitas,1223.0,1223.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +623,animatplot,True,t-makaro/animatplot,,data-viz,https://github.com/t-makaro/animatplot,https://github.com/t-makaro/animatplot,MIT,2017-04-03 00:54:04.000000,2021-04-07 10:46:25.000000,2020-10-05 06:14:18.000000,35.0,13.0,17.0,385,178.0,A python package for animating plots build on matplotlib.,7.0,18,2019-03-05 21:32:47.000000,0.4.1,7.0,,animatplot,conda-forge/animatplot,,,,29.0,29.0,https://pypi.org/project/animatplot,270.0,481.0,https://anaconda.org/conda-forge/animatplot,2020-10-06 02:02:00.460000,7176.0,,,,,3.0,,,,,,,,,,,,,,,, +624,joypy,True,sbebo/joypy,,data-viz,https://github.com/leotac/joypy,https://github.com/leotac/joypy,MIT,2017-07-30 17:18:50.000000,2021-12-14 22:27:57.000000,2021-12-13 22:30:34.000000,43.0,9.0,36.0,366,117.0,Joyplots in Python with matplotlib & pandas.,5.0,18,,,5.0,leotac/joypy,joypy,conda-forge/joypy,,,,112.0,112.0,https://pypi.org/project/joypy,,364.0,https://anaconda.org/conda-forge/joypy,2020-12-28 14:07:53.760000,12028.0,,,,,3.0,,,,,,,,,,,,,,,, +625,Pywick,True,achaiah/pywick,,pytorch-utils,https://github.com/achaiah/pywick,https://github.com/achaiah/pywick,,2019-03-25 15:42:47.000000,2021-12-14 22:07:33.000000,2021-10-22 03:09:17.000000,38.0,1.0,12.0,364,149.0,High-level batteries-included neural network training library for..,4.0,18,2021-10-22 03:16:49.000000,0.6.5,8.0,,pywick,,,,['pytorch'],5.0,5.0,https://pypi.org/project/pywick,5102.0,5102.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +626,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 10:59:08.000000,2020-08-11 12:36:43.000000,2020-06-15 12:01:36.000000,81.0,54.0,164.0,363,413.0,"Module for statistical learning, with a particular emphasis on time-..",16.0,18,2019-09-11 11:25:15.000000,0.6,5.0,,tick,,,,,46.0,46.0,https://pypi.org/project/tick,889.0,892.0,,,,,,,,3.0,188.0,,,,,,,,,,,,,,, +627,recmetrics,True,statisticianinstilettos/recmetrics,,recommender-systems,https://github.com/statisticianinstilettos/recmetrics,https://github.com/statisticianinstilettos/recmetrics,MIT,2018-10-15 15:29:49.000000,2021-10-27 14:22:31.000000,2021-10-27 14:16:34.000000,74.0,6.0,10.0,330,237.0,A library of metrics for evaluating recommender systems.,13.0,18,,,,,recmetrics,,,,,20.0,20.0,https://pypi.org/project/recmetrics,1133.0,1133.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +628,vega,True,vega/ipyvega,,data-viz,https://github.com/vega/ipyvega,https://github.com/vega/ipyvega,BSD-3-Clause,2015-08-04 03:22:47.000000,2021-12-07 22:16:34.000000,2021-12-02 08:13:40.000000,52.0,11.0,81.0,318,541.0,IPython/Jupyter notebook module for Vega and Vega-Lite.,10.0,18,,,26.0,,vega,conda-forge/vega,,,['jupyter'],,,https://pypi.org/project/vega,20907.0,28010.0,https://anaconda.org/conda-forge/vega,2021-11-18 16:21:37.805000,468830.0,,,,,3.0,,,,,,,,,,,,,,,, +629,Brainiak,True,brainiak/brainiak,,medical-data,https://github.com/brainiak/brainiak,https://github.com/brainiak/brainiak,Apache-2.0,2016-02-08 23:19:27.000000,2021-12-03 01:07:31.000000,2021-05-28 01:21:58.000000,121.0,68.0,123.0,260,393.0,Brain Imaging Analysis Kit.,33.0,18,,,,,brainiak,,brainiak/brainiak,,,15.0,15.0,https://pypi.org/project/brainiak,193.0,202.0,,,,https://hub.docker.com/r/brainiak/brainiak,2020-10-15 21:11:03.379549,1.0,680.0,3.0,,,,,,,,,,,,,,,, +630,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 04:28:03.000000,2021-11-28 17:12:07.000000,2021-11-28 17:12:04.000000,58.0,2.0,30.0,222,,pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef..,10.0,18,2021-11-22 06:36:42.000000,2.7.3,51.0,,pymap3d,conda-forge/pymap3d,,,,,,https://pypi.org/project/pymap3d,42724.0,43488.0,https://anaconda.org/conda-forge/pymap3d,2021-10-19 05:47:09.404000,16046.0,,,,,3.0,,,,,,,,,,,,,,,, +631,Muda,True,bmcfee/muda,,audio,https://github.com/bmcfee/muda,https://github.com/bmcfee/muda,ISC,2014-11-07 21:21:22.000000,2021-05-03 14:04:37.000000,2021-05-03 14:04:36.000000,34.0,5.0,44.0,196,293.0,A library for augmenting annotated audio data.,7.0,18,2019-11-15 15:46:12.000000,0.4.1,11.0,,muda,,,,,13.0,13.0,https://pypi.org/project/muda,165.0,165.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +632,Dejavu,True,worldveil/dejavu,,audio,https://github.com/worldveil/dejavu,https://github.com/worldveil/dejavu,MIT,2013-11-19 02:50:35.000000,2020-10-29 17:40:17.000000,2020-06-03 05:58:03.000000,1238.0,74.0,129.0,5609,146.0,Audio fingerprinting and recognition in Python.,23.0,17,,,,,PyDejavu,,,,,19.0,19.0,https://pypi.org/project/PyDejavu,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +633,DALI,True,NVIDIA/DALI,,gpu-utilities,https://github.com/NVIDIA/DALI,https://github.com/NVIDIA/DALI,Apache-2.0,2018-06-01 22:18:01.000000,2021-12-16 12:09:49.000000,2021-12-16 12:09:00.000000,453.0,141.0,926.0,3623,,A GPU-accelerated library containing highly optimized building blocks..,67.0,17,2021-11-22 18:51:41.000000,1.8.0,46.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +634,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 14:28:59.000000,2021-08-25 09:25:32.000000,2021-08-25 09:25:32.000000,653.0,100.0,798.0,3378,838.0,"A fork of OpenAI Baselines, implementations of reinforcement..",112.0,17,2020-08-05 19:45:11.000000,2.10.1,21.0,,stable-baselines,,,,,,,https://pypi.org/project/stable-baselines,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +635,ReAgent,True,facebookresearch/ReAgent,,reinforcement-learning,https://github.com/facebookresearch/ReAgent,https://github.com/facebookresearch/ReAgent,BSD-3-Clause,2017-07-27 17:53:21.000000,2021-12-08 23:34:16.000000,2021-12-08 23:33:50.000000,424.0,22.0,75.0,3077,1339.0,"A platform for Reasoning systems (Reinforcement Learning,..",122.0,17,,,,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +636,Spotlight,True,maciejkula/spotlight,,recommender-systems,https://github.com/maciejkula/spotlight,https://github.com/maciejkula/spotlight,MIT,2017-06-25 18:52:19.000000,2020-11-15 08:21:28.000000,2020-02-09 21:03:48.000000,389.0,61.0,48.0,2622,299.0,Deep recommender models using PyTorch.,11.0,17,2019-09-08 10:19:53.000000,0.1.6,7.0,,,maciejkula/spotlight,,,['pytorch'],,,,,121.0,https://anaconda.org/maciejkula/spotlight,2018-05-27 18:32:12.235000,6537.0,,,,,3.0,,,,,,,,,,,,,,,, +637,tensorflow-graphics,True,tensorflow/graphics,,image,https://github.com/tensorflow/graphics,https://github.com/tensorflow/graphics,Apache-2.0,2019-01-08 10:39:44.000000,2021-12-15 23:30:31.000000,2021-12-06 14:39:04.000000,317.0,69.0,89.0,2566,741.0,TensorFlow Graphics: Differentiable Graphics Layers..,34.0,17,2019-05-09 10:06:22.000000,1.0.0,1.0,,tensorflow-graphics,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-graphics,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +638,Coach,True,IntelLabs/coach,,reinforcement-learning,https://github.com/IntelLabs/coach,https://github.com/IntelLabs/coach,Apache-2.0,2017-10-01 19:27:43.000000,2021-08-21 06:45:37.000000,2021-06-28 07:40:53.000000,407.0,78.0,183.0,2083,521.0,Reinforcement Learning Coach by Intel AI Lab enables easy..,35.0,17,2019-07-24 13:14:28.000000,1.0.0,9.0,,rl_coach,,,,,,,https://pypi.org/project/rl_coach,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +639,PyFlux,True,RJT1990/pyflux,,time-series-data,https://github.com/RJT1990/pyflux,https://github.com/RJT1990/pyflux,BSD-3-Clause,2016-02-16 20:12:02.000000,2019-03-19 10:45:02.000000,2018-12-16 15:30:13.000000,218.0,82.0,65.0,1932,118.0,Open source time series library for Python.,6.0,17,,,,,pyflux,,,,,206.0,206.0,https://pypi.org/project/pyflux,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +640,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 17:30:28.000000,2021-09-26 02:36:04.000000,2021-08-19 02:08:33.000000,455.0,75.0,27.0,1901,136.0,Deep Learning Pipelines for Apache Spark.,16.0,17,2020-01-08 19:50:31.000000,1.6.0,9.0,,,,,,['spark'],19.0,19.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +641,BlazingSQL,True,BlazingDB/blazingsql,,gpu-utilities,https://github.com/BlazingDB/blazingsql,https://github.com/BlazingDB/blazingsql,Apache-2.0,2018-09-24 18:25:45.000000,2021-10-08 18:42:47.000000,2021-09-30 21:51:09.000000,159.0,123.0,586.0,1650,,"BlazingSQL is a lightweight, GPU accelerated, SQL engine for..",47.0,17,2021-08-16 15:40:43.000000,21.08.00,19.0,,,blazingsql/blazingsql-protocol,,,,,,,,34.0,https://anaconda.org/blazingsql/blazingsql-protocol,2019-11-11 19:54:17.621000,939.0,,,,,3.0,,,,,,,,,,,,,,,, +642,datatable,True,h2oai/datatable,,data-containers,https://github.com/h2oai/datatable,https://github.com/h2oai/datatable,MPL-2.0,2017-03-03 02:32:59.000000,2021-12-15 23:46:39.000000,2021-12-10 23:49:03.000000,122.0,136.0,1249.0,1418,,A Python package for manipulating 2-dimensional tabular data..,32.0,17,2021-07-02 00:15:35.000000,1.0.0,16.0,,datatable,,,,,,,https://pypi.org/project/datatable,,23.0,,,,,,,,3.0,1197.0,,,,,,,,,,,,,,, +643,doc2text,True,jlsutherland/doc2text,,ocr,https://github.com/jlsutherland/doc2text,https://github.com/jlsutherland/doc2text,MIT,2016-08-28 19:30:02.000000,2020-12-01 22:56:27.000000,2020-12-01 22:56:26.000000,94.0,12.0,9.0,1252,62.0,Detect text blocks and OCR poorly scanned PDFs in bulk. Python module..,5.0,17,,,,,doc2text,,,,,50.0,50.0,https://pypi.org/project/doc2text,383.0,383.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +644,PyCUDA,True,inducer/pycuda,,gpu-utilities,https://github.com/inducer/pycuda,https://github.com/inducer/pycuda,,2011-04-06 02:53:31.000000,2021-12-07 05:24:20.000000,2021-12-07 05:24:19.000000,243.0,56.0,152.0,1247,,"CUDA integration for Python, plus shiny features.",74.0,17,,,,,pycuda,,,,,1096.0,1096.0,https://pypi.org/project/pycuda,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +645,Norfair,True,tryolabs/norfair,,image,https://github.com/tryolabs/norfair,https://github.com/tryolabs/norfair,BSD-3-Clause,2020-07-01 20:15:44.000000,2021-10-01 22:03:27.000000,2021-10-01 22:03:26.000000,88.0,8.0,31.0,1153,283.0,Lightweight Python library for adding real-time 2D object tracking to..,9.0,17,2021-07-29 15:46:57.000000,0.3.1,6.0,,norfair,,,,,,,https://pypi.org/project/norfair,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +646,TensorNets,True,taehoonlee/tensornets,,tensorflow-utils,https://github.com/taehoonlee/tensornets,https://github.com/taehoonlee/tensornets,MIT,2017-09-19 05:19:01.000000,2021-01-02 06:28:10.000000,2021-01-02 06:26:24.000000,186.0,16.0,42.0,998,284.0,High level network definitions with pre-trained weights in..,6.0,17,2020-03-31 04:38:27.000000,0.4.6,12.0,,tensornets,,,,['tensorflow'],42.0,42.0,https://pypi.org/project/tensornets,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +647,CrypTen,True,facebookresearch/CrypTen,,privacy-ml,https://github.com/facebookresearch/CrypTen,https://github.com/facebookresearch/CrypTen,MIT,2019-08-15 00:00:31.000000,2021-12-15 16:36:18.000000,2021-12-15 16:36:16.000000,156.0,19.0,93.0,973,,A framework for Privacy Preserving Machine Learning.,25.0,17,2020-04-21 13:59:37.000000,0.1,1.0,,crypten,,,,['pytorch'],12.0,12.0,https://pypi.org/project/crypten,308.0,308.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +648,fastFM,True,ibayer/fastFM,,recommender-systems,https://github.com/ibayer/fastFM,https://github.com/ibayer/fastFM,,2014-10-27 12:25:51.000000,2021-12-06 14:42:35.000000,2021-03-24 12:22:31.000000,190.0,46.0,60.0,955,297.0,fastFM: A Library for Factorization Machines.,20.0,17,2017-11-22 16:13:16.000000,0.2.11,10.0,,fastfm,,,,,91.0,91.0,https://pypi.org/project/fastfm,,5.0,,,,,,,,3.0,424.0,,,,,,,,,,,,,,, +649,stockstats,True,jealous/stockstats,,financial-data,https://github.com/jealous/stockstats,https://github.com/jealous/stockstats,BSD-3-Clause,2016-06-05 15:21:22.000000,2021-11-20 06:22:47.000000,2021-11-20 06:22:44.000000,243.0,30.0,42.0,910,28.0,Supply a wrapper ``StockDataFrame`` based on the..,8.0,17,,,,,stockstats,,,,,361.0,361.0,https://pypi.org/project/stockstats,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +650,calamari,True,Calamari-OCR/calamari,,ocr,https://github.com/Calamari-OCR/calamari,https://github.com/Calamari-OCR/calamari,Apache-2.0,2018-03-20 15:22:29.000000,2021-10-28 09:18:45.000000,2021-10-02 08:17:09.000000,185.0,39.0,191.0,882,405.0,Line based ATR Engine based on OCRopy.,19.0,17,2021-10-02 07:50:30.000000,2.1.4,30.0,,calamari_ocr,,,,,,,https://pypi.org/project/calamari_ocr,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +651,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 13:50:19.000000,2021-12-16 14:08:51.000000,2021-12-16 13:45:36.000000,57.0,37.0,69.0,879,467.0,Decentralized deep learning in PyTorch. Built to train models on..,19.0,17,2021-08-26 08:46:51.000000,0.10.0,12.0,,hivemind,,,,,4.0,4.0,https://pypi.org/project/hivemind,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +652,cuGraph,True,rapidsai/cugraph,,gpu-utilities,https://github.com/rapidsai/cugraph,https://github.com/rapidsai/cugraph,Apache-2.0,2018-11-15 18:07:11.000000,2021-12-16 13:06:45.000000,2021-12-15 09:01:39.000000,167.0,63.0,664.0,871,,cuGraph - RAPIDS Graph Analytics Library.,70.0,17,2021-12-08 19:15:16.000000,21.12.00,16.0,,cugraph,,,,,,,https://pypi.org/project/cugraph,197.0,197.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +653,scikit-cuda,True,lebedov/scikit-cuda,,gpu-utilities,https://github.com/lebedov/scikit-cuda,https://github.com/lebedov/scikit-cuda,,2010-09-27 02:02:07.000000,2021-07-13 12:58:06.000000,2021-07-13 12:58:06.000000,166.0,50.0,167.0,868,1032.0,Python interface to GPU-powered libraries.,45.0,17,2015-12-29 15:56:39.000000,0.5.1,7.0,,scikit-cuda,,,,,149.0,149.0,https://pypi.org/project/scikit-cuda,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +654,ADTK,True,arundo/adtk,,time-series-data,https://github.com/arundo/adtk,https://github.com/arundo/adtk,MPL-2.0,2019-09-27 00:34:22.000000,2021-07-18 06:52:12.000000,2020-04-17 02:27:44.000000,94.0,26.0,34.0,760,78.0,A Python toolkit for rule-based/unsupervised anomaly detection in time..,11.0,17,2020-04-17 02:17:35.000000,0.6.2,12.0,,adtk,,,,,,,https://pypi.org/project/adtk,54968.0,54968.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +655,gmaps,True,pbugnion/gmaps,,geospatial-data,https://github.com/pbugnion/gmaps,https://github.com/pbugnion/gmaps,BSD-3-Clause,2014-12-01 09:12:06.000000,2020-10-13 07:09:18.000000,2019-07-22 06:22:45.000000,143.0,62.0,136.0,726,1380.0,Google maps for Jupyter notebooks.,16.0,17,2016-01-02 19:06:03.000000,0.2,20.0,,gmaps,conda-forge/gmaps,,,['jupyter'],1.0,1.0,https://pypi.org/project/gmaps,,6415.0,https://anaconda.org/conda-forge/gmaps,2019-08-02 11:56:50.940000,249905.0,,,,,3.0,,jupyter-gmaps,https://www.npmjs.com/package/jupyter-gmaps,1872.0,,,,,,,,,,,, +656,RLax,True,deepmind/rlax,,reinforcement-learning,https://github.com/deepmind/rlax,https://github.com/deepmind/rlax,Apache-2.0,2020-02-18 07:14:59.000000,2021-12-02 17:18:58.000000,2021-12-02 17:18:54.000000,56.0,3.0,9.0,723,144.0,A library of reinforcement learning building blocks in JAX.,16.0,17,2021-11-19 12:34:03.000000,0.1.1,3.0,,rlax,,,,['jax'],32.0,32.0,https://pypi.org/project/rlax,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +657,lets-plot,True,JetBrains/lets-plot,,data-viz,https://github.com/JetBrains/lets-plot,https://github.com/JetBrains/lets-plot,,2019-03-20 16:13:03.000000,2021-12-16 11:09:44.000000,2021-12-15 21:34:09.000000,29.0,71.0,150.0,705,2310.0,An open-source plotting library for statistical data.,16.0,17,2021-12-10 17:04:12.000000,2.2.1,45.0,,lets-plot,,,,,12.0,12.0,https://pypi.org/project/lets-plot,,5.0,,,,,,,,3.0,140.0,,,,,,,,,,,,,,, +658,bambi,True,bambinos/bambi,,probabilistics,https://github.com/bambinos/bambi,https://github.com/bambinos/bambi,MIT,2016-05-16 03:21:00.000000,2021-12-01 12:18:02.000000,2021-12-01 12:18:01.000000,67.0,31.0,179.0,704,,BAyesian Model-Building Interface (Bambi) in Python.,21.0,17,2021-09-17 11:44:04.000000,0.6.3,12.0,,bambi,,,,,18.0,18.0,https://pypi.org/project/bambi,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +659,Vulkan Kompute,True,EthicalML/vulkan-kompute,,gpu-utilities,https://github.com/KomputeProject/kompute,https://github.com/KomputeProject/kompute,Apache-2.0,2020-07-29 05:23:33.000000,2021-12-15 17:06:43.000000,2021-12-15 17:06:41.000000,49.0,51.0,106.0,621,965.0,General purpose GPU compute framework for cross vendor..,16.0,17,2021-09-16 04:09:57.000000,0.8.0,12.0,KomputeProject/kompute,kp,,,,,2.0,2.0,https://pypi.org/project/kp,96.0,102.0,,,,,,,,3.0,105.0,,,,,,,,,,,,,,, +660,Dragonfly,True,dragonfly/dragonfly,,hyperopt,https://github.com/dragonfly/dragonfly,https://github.com/dragonfly/dragonfly,MIT,2018-04-20 22:19:50.000000,2021-07-31 04:54:26.000000,2020-07-03 18:01:17.000000,199.0,31.0,18.0,610,397.0,An open source python library for scalable Bayesian optimisation.,12.0,17,,,,,dragonfly-opt,,,,,,,https://pypi.org/project/dragonfly-opt,34106.0,34106.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +661,combo,True,yzhao062/combo,,sklearn-utils,https://github.com/yzhao062/combo,https://github.com/yzhao062/combo,BSD-2-Clause,2019-07-14 01:13:36.000000,2021-10-02 13:57:54.000000,2021-10-02 13:57:52.000000,93.0,9.0,3.0,557,207.0,(AAAI' 20) A Python Toolbox for Machine Learning Model..,,17,2020-02-19 02:11:55.000000,V0.1.0,1.0,,combo,,,,"['sklearn', 'xgboost']",435.0,435.0,https://pypi.org/project/combo,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +662,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 19:20:13.000000,2021-01-30 21:50:08.000000,2021-01-30 21:50:02.000000,107.0,6.0,28.0,487,249.0,Code to compute permutation and drop-column..,14.0,17,2021-01-28 23:23:17.000000,1.3.7,5.0,,rfpimp,,,,['sklearn'],88.0,88.0,https://pypi.org/project/rfpimp,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +663,seglearn,True,dmbee/seglearn,,time-series-data,https://github.com/dmbee/seglearn,https://github.com/dmbee/seglearn,BSD-3-Clause,2018-03-05 20:53:59.000000,2021-03-12 17:13:13.000000,2021-03-12 17:12:50.000000,52.0,5.0,23.0,481,268.0,Python module for machine learning time series:.,13.0,17,,,,,seglearn,,,,,11.0,11.0,https://pypi.org/project/seglearn,1467.0,1467.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +664,optunity,True,claesenm/optunity,,hyperopt,https://github.com/claesenm/optunity,https://github.com/claesenm/optunity,BSD-3-Clause,2014-05-28 17:29:11.000000,2020-05-11 14:32:39.000000,2020-05-11 14:32:38.000000,73.0,47.0,48.0,378,782.0,optimization routines for hyperparameter tuning.,9.0,17,2015-09-30 04:59:38.000000,1.1.1,3.0,,optunity,,,,,68.0,68.0,https://pypi.org/project/optunity,,0.0,,,,,,,,3.0,67.0,,,,,,,,,,,,,,, +665,Studio.ml,True,studioml/studio,,ml-experiments,https://github.com/studioml/studio,https://github.com/studioml/studio,Apache-2.0,2017-05-15 01:49:28.000000,2021-09-14 22:54:36.000000,2021-09-14 22:26:21.000000,51.0,57.0,195.0,374,2409.0,Studio: Simplify and expedite model building process.,21.0,17,2020-02-19 22:50:45.000000,0.0.15,4.0,,studioml,,,,,5.0,5.0,https://pypi.org/project/studioml,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +666,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 15:23:32.000000,2021-12-07 02:37:12.000000,2021-12-07 02:36:42.000000,65.0,8.0,49.0,346,242.0,"Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost..",6.0,17,,,2.0,,auto-ts,,,,,,,https://pypi.org/project/auto-ts,2634.0,2634.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +667,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 13:09:15.000000,2021-12-06 01:39:22.000000,2021-12-06 01:38:51.000000,69.0,4.0,14.0,314,293.0,Automatically Build Multiple ML Models with a Single Line of Code...,6.0,17,,,,,autoviml,,,,,15.0,15.0,https://pypi.org/project/autoviml,926.0,926.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +668,Sherpa,True,sherpa-ai/sherpa,,hyperopt,https://github.com/sherpa-ai/sherpa,https://github.com/sherpa-ai/sherpa,,2018-05-16 21:41:54.000000,2020-10-18 07:57:50.000000,2020-10-18 07:57:48.000000,48.0,15.0,41.0,307,823.0,"Hyperparameter optimization that enables researchers to experiment,..",43.0,17,2020-07-31 05:29:09.000000,1.0.7,4.0,,parameter-sherpa,,,,,17.0,17.0,https://pypi.org/project/parameter-sherpa,419.0,419.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +669,textpipe,True,textpipe/textpipe,,nlp,https://github.com/textpipe/textpipe,https://github.com/textpipe/textpipe,MIT,2018-06-21 16:23:32.000000,2021-06-09 11:55:53.000000,2021-06-09 11:55:53.000000,22.0,15.0,25.0,291,371.0,Textpipe: clean and extract metadata from text.,28.0,17,,,,,textpipe,,,,,8.0,8.0,https://pypi.org/project/textpipe,1812.0,1812.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +670,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 16:48:58.000000,2021-12-10 22:18:21.000000,2021-12-10 22:18:17.000000,41.0,4.0,2.0,241,176.0,a tool that leverages rich metadata and lineage..,11.0,17,2021-09-02 22:08:38.000000,1.1.0,4.0,,model-card-toolkit,,,,,5.0,5.0,https://pypi.org/project/model-card-toolkit,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +671,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 22:56:45.000000,2021-12-03 20:24:45.000000,2021-12-03 19:26:37.000000,66.0,2.0,8.0,240,279.0,Tensorflow's Fairness Evaluation and Visualization..,25.0,17,2021-12-03 20:24:45.000000,0.36.0,15.0,,fairness-indicators,,,,"['tensorflow', 'jupyter']",,,https://pypi.org/project/fairness-indicators,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +672,gokart,True,m3dev/gokart,,ml-experiments,https://github.com/m3dev/gokart,https://github.com/m3dev/gokart,MIT,2018-12-23 07:40:27.000000,2021-11-16 10:27:07.000000,2021-11-16 10:27:07.000000,38.0,11.0,51.0,227,449.0,A wrapper of the data pipeline library luigi.,29.0,17,2021-10-15 10:18:50.000000,1.0.6,41.0,,gokart,,,,,,,https://pypi.org/project/gokart,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +673,Orion,True,Epistimio/orion,,hyperopt,https://github.com/Epistimio/orion,https://github.com/Epistimio/orion,,2017-09-07 06:05:21.000000,2021-12-15 21:26:22.000000,2021-12-01 17:47:52.000000,41.0,61.0,143.0,208,3037.0,Asynchronous Distributed Hyperparameter Optimization.,24.0,17,,,20.0,,orion,,,,,47.0,47.0,https://pypi.org/project/orion,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +674,Funsor,True,pyro-ppl/funsor,,probabilistics,https://github.com/pyro-ppl/funsor,https://github.com/pyro-ppl/funsor,Apache-2.0,2019-01-30 23:13:39.000000,2021-12-13 22:24:52.000000,2021-12-13 22:24:28.000000,14.0,65.0,73.0,184,561.0,Functional tensors for probabilistic programming.,9.0,17,2021-12-13 22:52:43.000000,0.4.2,8.0,,funsor,,,,['pytorch'],20.0,20.0,https://pypi.org/project/funsor,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +675,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 15:02:43.000000,2021-12-16 13:20:30.000000,2021-12-15 22:15:13.000000,28.0,12.0,115.0,177,,Highly optimized inference engine for Binarized..,18.0,17,2021-09-08 13:40:14.000000,0.6.2,15.0,,larq-compute-engine,,,,,4.0,4.0,https://pypi.org/project/larq-compute-engine,545.0,559.0,,,,,,,,3.0,327.0,,,,,,,,,,,,,,, +676,BatchFlow,True,analysiscenter/batchflow,,data-pipelines,https://github.com/analysiscenter/batchflow,https://github.com/analysiscenter/batchflow,Apache-2.0,2017-03-13 14:22:53.000000,2021-12-16 12:38:57.000000,2021-12-14 13:06:41.000000,37.0,34.0,67.0,168,4874.0,BatchFlow helps you conveniently work with random or sequential..,30.0,17,2021-06-10 10:49:35.000000,0.5.0,7.0,,batchflow,,,,,,,https://pypi.org/project/batchflow,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +677,pyRDF2Vec,True,IBCNServices/pyRDF2Vec,,graph,https://github.com/IBCNServices/pyRDF2Vec,https://github.com/IBCNServices/pyRDF2Vec,MIT,2019-06-13 11:36:12.000000,2021-11-08 12:31:08.000000,2021-11-08 12:31:08.000000,24.0,3.0,41.0,136,1143.0,Python Implementation and Extension of RDF2Vec.,5.0,17,2021-06-09 10:55:19.000000,0.2.3,6.0,,pyrdf2vec,,,,,,,https://pypi.org/project/pyrdf2vec,174.0,174.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +678,DE⫶TR,True,facebookresearch/detr,,image,https://github.com/facebookresearch/detr,https://github.com/facebookresearch/detr,Apache-2.0,2020-05-26 23:54:52.000000,2021-11-28 09:13:56.000000,2021-10-18 10:06:31.000000,1364.0,129.0,266.0,8068,42.0,End-to-End Object Detection with Transformers.,24.0,16,2020-06-29 16:41:01.000000,0.2,1.0,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +679,DeepMind Lab,True,deepmind/lab,,reinforcement-learning,https://github.com/deepmind/lab,https://github.com/deepmind/lab,GPL-2.0,2016-11-30 13:41:26.000000,2021-11-01 21:58:46.000000,2021-07-21 17:50:32.000000,1304.0,50.0,160.0,6593,488.0,A customisable 3D platform for agent-based AI research.,7.0,16,2020-12-07 11:26:33.000000,release-2020-12-07,8.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +680,tinygrad,True,geohot/tinygrad,,pytorch-utils,https://github.com/geohot/tinygrad,https://github.com/geohot/tinygrad,MIT,2020-10-18 16:23:12.000000,2021-12-12 18:45:12.000000,2021-12-12 18:45:10.000000,568.0,3.0,83.0,5110,641.0,You like pytorch? You like micrograd? You love tinygrad!.,52.0,16,,,,,,,,,['pytorch'],1.0,1.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +681,TRFL,True,deepmind/trfl,,reinforcement-learning,https://github.com/deepmind/trfl,https://github.com/deepmind/trfl,Apache-2.0,2018-08-08 14:44:11.000000,2021-08-16 11:47:43.000000,2021-08-16 11:45:18.000000,369.0,4.0,16.0,3100,123.0,TensorFlow Reinforcement Learning.,13.0,16,,,,,trfl,,,,['tensorflow'],68.0,68.0,https://pypi.org/project/trfl,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +682,BytePS,True,bytedance/byteps,,distributed-ml,https://github.com/bytedance/byteps,https://github.com/bytedance/byteps,Apache-2.0,2019-06-25 07:00:13.000000,2021-10-12 17:02:08.000000,2021-10-12 16:17:49.000000,423.0,92.0,155.0,3028,427.0,A high performance and generic framework for distributed DNN training.,19.0,16,2020-02-19 23:44:20.000000,0.2,1.0,,byteps,,bytepsimage/tensorflow,,,,,https://pypi.org/project/byteps,,39.0,,,,https://hub.docker.com/r/bytepsimage/tensorflow,2020-03-03 02:33:23.358610,,1199.0,3.0,,,,,,,,,,,,,,,, +683,PyTorch-BigGraph,True,facebookresearch/PyTorch-BigGraph,,graph,https://github.com/facebookresearch/PyTorch-BigGraph,https://github.com/facebookresearch/PyTorch-BigGraph,,2018-10-01 20:41:16.000000,2021-11-28 17:50:14.000000,2021-10-27 14:34:36.000000,397.0,52.0,119.0,2965,,Generate embeddings from large-scale graph-structured..,24.0,16,2019-10-14 16:45:11.000000,1.0.0,3.0,,torchbiggraph,,,,['pytorch'],,,https://pypi.org/project/torchbiggraph,809.0,812.0,,,,,,,,3.0,122.0,,,,,,,,,,,,,,, +684,AdaBound,True,Luolc/AdaBound,,pytorch-utils,https://github.com/Luolc/AdaBound,https://github.com/Luolc/AdaBound,Apache-2.0,2019-02-15 18:05:20.000000,2019-03-06 17:01:52.000000,2019-03-06 17:01:45.000000,320.0,17.0,7.0,2881,27.0,An optimizer that trains as fast as Adam and as good as SGD.,2.0,16,2019-03-06 16:44:42.000000,0.0.5,1.0,,adabound,,,,['pytorch'],123.0,123.0,https://pypi.org/project/adabound,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +685,LIT,True,PAIR-code/lit,,interpretability,https://github.com/PAIR-code/lit,https://github.com/PAIR-code/lit,Apache-2.0,2020-07-28 13:07:26.000000,2021-12-14 19:23:31.000000,2021-11-14 21:25:56.000000,269.0,25.0,61.0,2719,,The Language Interpretability Tool: Interactively analyze NLP models for..,17.0,16,2021-11-09 03:06:04.000000,0.4,5.0,,lit-nlp,,,,,7.0,7.0,https://pypi.org/project/lit-nlp,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +686,GraphEmbedding,True,shenweichen/GraphEmbedding,,graph,https://github.com/shenweichen/GraphEmbedding,https://github.com/shenweichen/GraphEmbedding,MIT,2019-02-11 16:27:20.000000,2021-10-08 04:42:07.000000,2020-10-18 09:32:47.000000,745.0,38.0,14.0,2458,28.0,Implementation and experiments of graph embedding algorithms.,8.0,16,,,,,,,,,['sklearn'],12.0,12.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +687,opencv-python,True,skvark/opencv-python,,image,https://github.com/opencv/opencv-python,https://github.com/opencv/opencv-python,,2016-04-08 13:36:40.000000,2021-12-16 06:11:34.000000,2021-12-16 06:03:15.000000,471.0,26.0,464.0,2405,817.0,"Automated CI toolchain to produce precompiled opencv-python, opencv-python-headless, opencv-contrib-python and opencv-..",36.0,16,2021-11-19 15:28:16.000000,60,59.0,opencv/opencv-python,opencv-python,,,,,,,https://pypi.org/project/opencv-python,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +688,aim,True,aimhubio/aim,,ml-experiments,https://github.com/aimhubio/aim,https://github.com/aimhubio/aim,Apache-2.0,2019-05-31 18:25:07.000000,2021-12-16 14:28:01.000000,2021-12-16 14:23:25.000000,107.0,88.0,172.0,1880,,"Aim a super-easy way to record, search and compare 1000s of ML training..",22.0,16,,,,,aim,,,,,44.0,44.0,https://pypi.org/project/aim,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +689,Mara Pipelines,True,mara/mara-pipelines,,data-pipelines,https://github.com/mara/mara-pipelines,https://github.com/mara/mara-pipelines,MIT,2018-03-31 20:37:22.000000,2021-10-27 08:01:17.000000,2021-09-18 06:45:18.000000,85.0,6.0,12.0,1840,141.0,"A lightweight opinionated ETL framework, halfway between plain..",16.0,16,2020-07-31 19:31:29.000000,3.1.1,7.0,,mara-pipelines,,,,,8.0,8.0,https://pypi.org/project/mara-pipelines,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +690,Pillow-SIMD,True,uploadcare/pillow-simd,,image,https://github.com/uploadcare/pillow-simd,https://github.com/uploadcare/pillow-simd,PIL,2014-11-12 15:33:02.000000,2021-08-02 11:34:58.000000,2020-06-02 14:50:14.000000,70.0,12.0,57.0,1693,,The friendly PIL fork.,310.0,16,,,,,pillow-simd,,,,,498.0,498.0,https://pypi.org/project/pillow-simd,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +691,riko,True,nerevu/riko,,data-pipelines,https://github.com/nerevu/riko,https://github.com/nerevu/riko,MIT,2016-06-02 12:22:51.000000,2020-08-14 16:48:23.000000,2020-08-14 16:47:45.000000,67.0,21.0,8.0,1571,1257.0,A Python stream processing engine modeled after Yahoo! Pipes.,18.0,16,,,,,riko,,,,,,,https://pypi.org/project/riko,268.0,268.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +692,Lambda Networks,True,lucidrains/lambda-networks,,pytorch-utils,https://github.com/lucidrains/lambda-networks,https://github.com/lucidrains/lambda-networks,MIT,2020-10-08 19:01:15.000000,2020-11-18 19:54:34.000000,2020-11-18 19:54:30.000000,150.0,12.0,15.0,1497,,"Implementation of LambdaNetworks, a new approach to..",3.0,16,2020-11-18 08:18:54.000000,0.4.0,11.0,,lambda-networks,,,,['pytorch'],3.0,3.0,https://pypi.org/project/lambda-networks,85.0,85.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +693,DLTK,True,DLTK/DLTK,,medical-data,https://github.com/DLTK/DLTK,https://github.com/DLTK/DLTK,Apache-2.0,2017-05-02 15:40:36.000000,2021-08-25 14:40:15.000000,2019-01-21 14:01:28.000000,389.0,7.0,24.0,1287,379.0,Deep Learning Toolkit for Medical Image Analysis.,9.0,16,,,,,dltk,,,,['tensorflow'],21.0,21.0,https://pypi.org/project/dltk,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +694,advertorch,True,BorealisAI/advertorch,,adversarial,https://github.com/BorealisAI/advertorch,https://github.com/BorealisAI/advertorch,GPL-3.0,2018-11-29 22:17:33.000000,2021-12-09 19:16:53.000000,2021-07-30 15:59:28.000000,156.0,15.0,33.0,982,273.0,A Toolbox for Adversarial Robustness Research.,18.0,16,,,,,advertorch,,,,['pytorch'],57.0,57.0,https://pypi.org/project/advertorch,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +695,Fiber,True,uber/fiber,,distributed-ml,https://github.com/uber/fiber,https://github.com/uber/fiber,Apache-2.0,2020-01-07 18:16:24.000000,2021-06-30 02:02:42.000000,2021-03-15 07:00:08.000000,101.0,16.0,8.0,946,66.0,Distributed Computing for AI Made Simple.,5.0,16,,,,,fiber,,,,,30.0,30.0,https://pypi.org/project/fiber,1840.0,1840.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +696,Bounter,True,RaRe-Technologies/bounter,,data-containers,https://github.com/RaRe-Technologies/bounter,https://github.com/RaRe-Technologies/bounter,MIT,2017-07-18 07:24:15.000000,2021-09-19 00:43:46.000000,2021-05-24 07:29:54.000000,45.0,14.0,9.0,930,156.0,Efficient Counter that uses a limited (bounded) amount of memory..,8.0,16,2019-01-17 09:38:28.000000,1.1.0,3.0,,bounter,,,,,25.0,25.0,https://pypi.org/project/bounter,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +697,nude.py,True,hhatto/nude.py,,image,https://github.com/hhatto/nude.py,https://github.com/hhatto/nude.py,MIT,2013-06-09 06:55:55.000000,2020-11-23 13:49:32.000000,2020-11-23 13:49:02.000000,132.0,7.0,3.0,825,79.0,Nudity detection with Python.,12.0,16,,,,,nudepy,,,,,1343.0,1343.0,https://pypi.org/project/nudepy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +698,AstroML,True,astroML/astroML,,others,https://github.com/astroML/astroML,https://github.com/astroML/astroML,BSD-2-Clause,2012-10-17 22:33:50.000000,2021-08-04 16:00:40.000000,2021-04-07 06:12:17.000000,261.0,52.0,86.0,786,,"Machine learning, statistics, and data mining for astronomy and..",30.0,16,,,4.0,,astroML,conda-forge/astroml,,,['sklearn'],,,https://pypi.org/project/astroML,1132.0,1645.0,https://anaconda.org/conda-forge/astroml,2020-02-16 04:18:54.678000,26679.0,,,,,3.0,,,,,,,,,,,,,,,, +699,YouTokenToMe,True,vkcom/youtokentome,,nlp,https://github.com/VKCOM/YouTokenToMe,https://github.com/VKCOM/YouTokenToMe,MIT,2019-06-06 11:38:28.000000,2021-01-28 23:05:01.000000,2021-01-28 19:04:09.000000,55.0,27.0,23.0,780,79.0,Unsupervised text tokenizer focused on computational efficiency.,6.0,16,2020-02-13 09:57:47.000000,1.0.6,4.0,,youtokentome,,,,,183.0,183.0,https://pypi.org/project/youtokentome,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +700,pytorch2keras,True,nerox8664/pytorch2keras,,model-serialisation,https://github.com/gmalivenko/pytorch2keras,https://github.com/gmalivenko/pytorch2keras,MIT,2017-11-16 20:21:43.000000,2021-09-28 21:39:06.000000,2021-08-06 08:18:46.000000,127.0,50.0,67.0,764,282.0,PyTorch to Keras model convertor.,13.0,16,,,1.0,gmalivenko/pytorch2keras,pytorch2keras,,,,,26.0,26.0,https://pypi.org/project/pytorch2keras,711.0,711.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +701,MedicalTorch,True,perone/medicaltorch,,medical-data,https://github.com/perone/medicaltorch,https://github.com/perone/medicaltorch,Apache-2.0,2018-02-27 02:50:07.000000,2021-12-04 23:52:48.000000,2021-04-16 18:50:54.000000,112.0,13.0,9.0,757,57.0,A medical imaging framework for Pytorch.,8.0,16,2018-11-24 00:33:11.000000,0.2,1.0,,medicaltorch,,,,['pytorch'],11.0,11.0,https://pypi.org/project/medicaltorch,202.0,202.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +702,XAI,True,EthicalML/xai,,interpretability,https://github.com/EthicalML/xai,https://github.com/EthicalML/xai,MIT,2019-01-11 20:00:09.000000,2021-10-30 06:35:19.000000,2021-10-30 06:30:12.000000,113.0,1.0,7.0,744,91.0,XAI - An eXplainability toolbox for machine learning.,3.0,16,2021-10-30 06:35:19.000000,0.1.0,1.0,,xai,,,,,11.0,11.0,https://pypi.org/project/xai,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +703,DiCE,True,interpretml/DiCE,,interpretability,https://github.com/interpretml/DiCE,https://github.com/interpretml/DiCE,MIT,2019-05-02 09:51:02.000000,2021-12-13 19:36:24.000000,2021-12-11 00:04:19.000000,96.0,40.0,50.0,731,476.0,Generate Diverse Counterfactual Explanations for any machine..,12.0,16,2021-09-27 06:59:35.000000,0.7.2,8.0,,dice-ml,,,,"['tensorflow', 'pytorch']",,,https://pypi.org/project/dice-ml,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +704,NearPy,True,pixelogik/NearPy,,nn-search,https://github.com/pixelogik/NearPy,https://github.com/pixelogik/NearPy,MIT,2013-04-25 09:10:26.000000,2021-09-26 01:44:54.000000,2018-10-21 17:54:28.000000,141.0,24.0,38.0,693,159.0,Python framework for fast (approximated) nearest neighbour search in..,18.0,16,2016-09-27 13:04:44.000000,1.0.0,1.0,,NearPy,,,,,63.0,63.0,https://pypi.org/project/NearPy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +705,pdpipe,True,pdpipe/pdpipe,,data-pipelines,https://github.com/pdpipe/pdpipe,https://github.com/pdpipe/pdpipe,,2017-01-24 20:37:22.000000,2021-12-14 14:42:38.000000,2021-12-14 14:42:35.000000,29.0,15.0,23.0,629,370.0,Easy pipelines for pandas DataFrames.,9.0,16,2021-12-10 10:52:16.000000,0.0.69,30.0,,pdpipe,,,,['pandas'],38.0,38.0,https://pypi.org/project/pdpipe,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +706,pickleDB,True,patx/pickledb,,data-containers,https://github.com/patx/pickledb,https://github.com/patx/pickledb,BSD-3-Clause,2011-10-28 00:04:40.000000,2021-11-09 10:02:37.000000,2019-11-15 03:38:30.000000,105.0,15.0,39.0,622,105.0,pickleDB is an open source key-value store using Python's json..,12.0,16,,,,,pickledb,,,,,788.0,788.0,https://pypi.org/project/pickledb,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +707,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 09:58:08.000000,2021-11-23 01:55:15.000000,2021-01-05 04:22:15.000000,80.0,30.0,30.0,616,606.0,ThunderGBM: Fast GBDTs and Random Forests on GPUs.,10.0,16,2019-05-07 08:47:56.000000,0.3.2,3.0,,thundergbm,,,,,,,https://pypi.org/project/thundergbm,81.0,81.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +708,Tensor Sensor,True,parrt/tensor-sensor,,pytorch-utils,https://github.com/parrt/tensor-sensor,https://github.com/parrt/tensor-sensor,MIT,2020-08-28 22:54:04.000000,2021-12-13 18:54:27.000000,2021-12-13 18:54:25.000000,31.0,8.0,15.0,615,234.0,The goal of this library is to generate more helpful..,3.0,16,2021-12-11 21:24:11.000000,1.0,15.0,,tensor-sensor,,,,['pytorch'],7.0,7.0,https://pypi.org/project/tensor-sensor,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +709,Auto Tune Models,True,HDI-Project/ATM,,hyperopt,https://github.com/HDI-Project/ATM,https://github.com/HDI-Project/ATM,MIT,2016-10-14 18:03:00.000000,2020-02-21 17:44:07.000000,2020-02-21 17:40:58.000000,129.0,17.0,71.0,513,775.0,"Auto Tune Models - A multi-tenant, multi-data system for..",16.0,16,2019-07-30 09:28:26.000000,0.2.2,6.0,,atm,,,,,8.0,8.0,https://pypi.org/project/atm,97.0,97.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +710,pyhsmm,True,mattjj/pyhsmm,,probabilistics,https://github.com/mattjj/pyhsmm,https://github.com/mattjj/pyhsmm,MIT,2012-03-18 17:40:13.000000,2020-09-29 20:58:26.000000,2020-08-24 17:03:59.000000,158.0,35.0,60.0,504,1426.0,Bayesian inference in HSMMs and HMMs.,13.0,16,,,,,pyhsmm,,,,,23.0,23.0,https://pypi.org/project/pyhsmm,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +711,tcav,True,tensorflow/tcav,,interpretability,https://github.com/tensorflow/tcav,https://github.com/tensorflow/tcav,Apache-2.0,2018-07-03 17:45:35.000000,2021-11-10 19:43:31.000000,2021-09-16 17:56:31.000000,118.0,3.0,52.0,500,171.0,Code for the TCAV ML interpretability project.,19.0,16,2018-11-21 15:34:40.000000,0.2,2.0,,tcav,,,,['tensorflow'],11.0,11.0,https://pypi.org/project/tcav,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +712,N2,True,kakao/n2,,nn-search,https://github.com/kakao/n2,https://github.com/kakao/n2,Apache-2.0,2017-11-23 02:27:59.000000,2021-05-20 05:41:36.000000,2021-05-20 05:39:44.000000,61.0,10.0,20.0,498,242.0,TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast..,18.0,16,2020-10-16 03:43:47.000000,0.1.7,4.0,,n2,,,,,22.0,22.0,https://pypi.org/project/n2,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +713,kglib,True,graknlabs/kglib,,graph,https://github.com/vaticle/kglib,https://github.com/vaticle/kglib,Apache-2.0,2018-09-16 16:46:48.000000,2021-10-22 14:09:11.000000,2021-10-22 14:09:00.000000,86.0,9.0,49.0,482,488.0,Grakn Knowledge Graph Library (ML R&D).,7.0,16,2020-08-19 15:32:49.000000,0.2.2,7.0,vaticle/kglib,grakn-kglib,,,,,,,https://pypi.org/project/grakn-kglib,73.0,79.0,,,,,,,,3.0,211.0,,,,,,,,,,,,,,, +714,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 13:36:52.000000,2021-12-11 08:22:06.000000,2021-12-07 08:14:03.000000,57.0,60.0,99.0,428,501.0,"SoundFile is an audio library based on libsndfile, CFFI, and..",23.0,16,2019-12-04 10:03:39.000000,0.10.3post1,7.0,,soundfile,,,,,,,https://pypi.org/project/soundfile,,29.0,,,,,,,,3.0,2751.0,,,,,,,,,,,,,,, +715,BioPandas,True,rasbt/biopandas,,others,https://github.com/rasbt/biopandas,https://github.com/rasbt/biopandas,BSD-3-Clause,2015-11-21 00:00:14.000000,2021-09-24 00:11:37.000000,2021-09-24 00:11:37.000000,89.0,15.0,24.0,400,,Working with molecular structures in pandas DataFrames.,8.0,16,2021-08-30 11:48:10.000000,0.2.9,12.0,,biopandas,conda-forge/biopandas,,,['pandas'],,,https://pypi.org/project/biopandas,2496.0,4047.0,https://anaconda.org/conda-forge/biopandas,2021-08-31 18:19:35.536000,93095.0,,,,,3.0,,,,,,,,,,,,,,,, +716,DeepMatcher,True,anhaidgroup/deepmatcher,,nlp,https://github.com/anhaidgroup/deepmatcher,https://github.com/anhaidgroup/deepmatcher,BSD-3-Clause,2017-12-01 19:01:11.000000,2021-06-13 01:13:43.000000,2021-06-13 00:22:13.000000,88.0,54.0,22.0,385,176.0,Python package for performing Entity and Text Matching using..,7.0,16,,,,,deepmatcher,,,,,14.0,14.0,https://pypi.org/project/deepmatcher,479.0,479.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +717,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 21:15:41.000000,2021-10-27 17:57:56.000000,2019-12-05 08:17:22.000000,175.0,30.0,23.0,385,46.0,scikit-learn inspired API for CRFsuite.,6.0,16,,,,,sklearn-crfsuite,,,,['sklearn'],3336.0,3336.0,https://pypi.org/project/sklearn-crfsuite,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +718,Camphr,True,PKSHATechnology-Research/camphr,,nlp,https://github.com/PKSHATechnology-Research/camphr,https://github.com/PKSHATechnology-Research/camphr,Apache-2.0,2020-02-10 03:39:58.000000,2021-08-18 06:06:52.000000,2021-08-18 06:06:51.000000,17.0,2.0,25.0,342,1404.0,"spaCy plugin for Transformers , Udify, ELmo, etc.",7.0,16,2020-08-21 04:45:06.000000,0.7.0,21.0,,camphr,,,,['spacy'],,,https://pypi.org/project/camphr,201.0,201.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +719,pdvega,True,altair-viz/pdvega,,data-viz,https://github.com/altair-viz/pdvega,https://github.com/altair-viz/pdvega,MIT,2018-01-11 21:30:27.000000,2019-03-29 16:09:14.000000,2019-03-29 16:09:13.000000,30.0,16.0,10.0,338,177.0,Interactive plotting for Pandas using Vega-Lite.,9.0,16,,,,,pdvega,,,,,59.0,59.0,https://pypi.org/project/pdvega,145.0,145.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +720,SUOD,True,yzhao062/SUOD,,others,https://github.com/yzhao062/SUOD,https://github.com/yzhao062/SUOD,BSD-2-Clause,2019-11-20 00:23:54.000000,2021-10-02 14:00:14.000000,2021-10-02 14:00:01.000000,36.0,4.0,2.0,300,144.0,(MLSys' 21) An Acceleration System for Large-scare Unsupervised..,,16,,,,,suod,,,,,403.0,403.0,https://pypi.org/project/suod,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +721,quinn,True,MrPowers/quinn,,ml-experiments,https://github.com/MrPowers/quinn,https://github.com/MrPowers/quinn,,2017-09-15 13:02:42.000000,2021-03-27 14:31:44.000000,2021-02-09 04:48:07.000000,40.0,14.0,9.0,300,110.0,pyspark methods to enhance developer productivity.,6.0,16,2017-10-17 03:04:48.000000,0.2.0,1.0,,quinn,,,,['spark'],,,https://pypi.org/project/quinn,464373.0,464373.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +722,elegy,True,poets-ai/elegy,,ml-frameworks,https://github.com/poets-ai/elegy,https://github.com/poets-ai/elegy,MIT,2020-06-30 14:00:37.000000,2021-12-14 13:57:24.000000,2021-12-14 13:55:52.000000,21.0,18.0,62.0,298,324.0,Elegy is a framework-agnostic Trainer interface for the Jax..,14.0,16,2021-12-14 13:57:24.000000,0.8.4,19.0,,elegy,,,,"['tensorflow', 'jax']",,,https://pypi.org/project/elegy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +723,skggm,True,skggm/skggm,,sklearn-utils,https://github.com/skggm/skggm,https://github.com/skggm/skggm,MIT,2016-06-11 18:35:56.000000,2021-10-01 04:11:05.000000,2020-12-24 05:43:15.000000,34.0,28.0,47.0,190,691.0,Scikit-learn compatible estimation of general graphical models.,5.0,16,2018-09-12 01:11:31.000000,0.2.8,6.0,,skggm,,,,['sklearn'],8.0,8.0,https://pypi.org/project/skggm,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +724,featurewiz,True,AutoViML/featurewiz,,hyperopt,https://github.com/AutoViML/featurewiz,https://github.com/AutoViML/featurewiz,Apache-2.0,2020-11-29 16:46:16.000000,2021-12-10 22:34:27.000000,2021-12-10 22:33:30.000000,27.0,5.0,2.0,99,,Use advanced feature engineering strategies and select the..,3.0,16,,,,,featurewiz,,,,,3.0,3.0,https://pypi.org/project/featurewiz,118167.0,118167.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +725,PySlowFast,True,facebookresearch/SlowFast,,image,https://github.com/facebookresearch/SlowFast,https://github.com/facebookresearch/SlowFast,Apache-2.0,2019-08-20 22:47:26.000000,2021-11-03 07:05:48.000000,2021-10-28 14:20:52.000000,825.0,234.0,237.0,4425,,PySlowFast: video understanding codebase from FAIR for..,25.0,15,,,,,,,,,['pytorch'],5.0,5.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +726,OpenNRE,True,thunlp/OpenNRE,,nlp,https://github.com/thunlp/OpenNRE,https://github.com/thunlp/OpenNRE,MIT,2017-02-26 07:37:12.000000,2021-12-09 19:53:22.000000,2021-12-09 19:53:22.000000,904.0,10.0,320.0,3439,161.0,An Open-Source Package for Neural Relation Extraction (NRE).,10.0,15,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +727,pdftabextract,True,WZBSocialScienceCenter/pdftabextract,,ocr,https://github.com/WZBSocialScienceCenter/pdftabextract,https://github.com/WZBSocialScienceCenter/pdftabextract,Apache-2.0,2016-07-08 11:44:46.000000,2020-12-28 00:52:23.000000,2018-10-26 13:57:02.000000,339.0,3.0,18.0,1969,168.0,A set of tools for extracting tables from PDF files..,2.0,15,,,,,pdftabextract,,,,,37.0,37.0,https://pypi.org/project/pdftabextract,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +728,pycls,True,facebookresearch/pycls,,image,https://github.com/facebookresearch/pycls,https://github.com/facebookresearch/pycls,MIT,2019-06-10 22:47:17.000000,2021-10-14 20:53:57.000000,2021-08-19 02:33:54.000000,203.0,22.0,55.0,1803,,"Codebase for Image Classification Research, written in PyTorch.",13.0,15,2021-05-21 00:29:47.000000,0.2,2.0,,,,,,['pytorch'],4.0,4.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +729,automl-gs,True,minimaxir/automl-gs,,hyperopt,https://github.com/minimaxir/automl-gs,https://github.com/minimaxir/automl-gs,MIT,2019-01-13 18:57:44.000000,2019-10-22 11:20:40.000000,2019-04-05 06:48:14.000000,158.0,24.0,6.0,1766,102.0,"Provide an input CSV and a target field to predict, generate a..",7.0,15,2019-04-05 06:51:04.000000,0.2.1,2.0,,automl_gs,,,,,,,https://pypi.org/project/automl_gs,19.0,19.0,,,,,,,,3.0,27.0,,,,,,,,,,,,,,, +730,Advisor,True,tobegit3hub/advisor,,hyperopt,https://github.com/tobegit3hub/advisor,https://github.com/tobegit3hub/advisor,Apache-2.0,2017-09-14 03:50:33.000000,2019-11-11 07:09:57.869705,2019-11-11 06:59:31.000000,255.0,19.0,13.0,1421,165.0,Open-source implementation of Google Vizier for hyper parameters..,11.0,15,,,,,advisor,,tobegit3hub/advisor,,,,,https://pypi.org/project/advisor,62.0,94.0,,,,https://hub.docker.com/r/tobegit3hub/advisor,2019-11-11 07:09:57.869705,,1637.0,3.0,,,,,,,,,,,,,,,, +731,Pypeline,True,cgarciae/pypeln,,data-pipelines,https://github.com/cgarciae/pypeln,https://github.com/cgarciae/pypeln,MIT,2018-09-01 13:43:31.000000,2021-05-01 11:58:40.000000,2021-04-13 00:55:39.000000,73.0,14.0,38.0,1290,235.0,Concurrent data pipelines in Python .,10.0,15,2021-01-05 17:59:01.000000,0.4.7,13.0,,pypeln,,,,,,,https://pypi.org/project/pypeln,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +732,Xcessiv,True,reiinakano/xcessiv,,hyperopt,https://github.com/reiinakano/xcessiv,https://github.com/reiinakano/xcessiv,Apache-2.0,2017-03-07 18:18:25.000000,2018-06-06 22:23:37.000000,2017-08-21 00:51:15.000000,106.0,21.0,13.0,1260,316.0,"A web-based application for quick, scalable, and automated..",6.0,15,2017-08-21 00:53:25.000000,0.5.1,20.0,,xcessiv,,,,,1.0,1.0,https://pypi.org/project/xcessiv,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +733,Databolt Flow,True,d6t/d6tflow,,data-pipelines,https://github.com/d6t/d6tflow,https://github.com/d6t/d6tflow,MIT,2019-02-03 01:51:22.000000,2021-10-06 00:53:28.000000,2021-09-28 02:59:00.000000,68.0,9.0,13.0,935,266.0,Python library for building highly effective data science workflows.,12.0,15,,,,,d6tflow,,,,,17.0,17.0,https://pypi.org/project/d6tflow,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +734,iNNvestigate,True,albermax/innvestigate,,interpretability,https://github.com/albermax/innvestigate,https://github.com/albermax/innvestigate,BSD-2-Clause,2017-12-13 18:11:20.000000,2021-08-03 15:45:16.000000,2021-08-03 15:45:16.000000,199.0,65.0,163.0,924,943.0,A toolbox to iNNvestigate neural networks' predictions!.,19.0,15,,,,,innvestigate,,,,['tensorflow'],,,https://pypi.org/project/innvestigate,451.0,451.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +735,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 23:13:11.000000,2021-07-26 13:59:41.000000,2021-07-26 13:59:38.000000,96.0,7.0,34.0,882,157.0,Differentiable SDE solvers with GPU support and efficient..,5.0,15,2021-01-05 18:31:38.000000,0.2.4,4.0,,,,,,['pytorch'],9.0,9.0,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +736,Translate,True,pytorch/translate,,nlp,https://github.com/pytorch/translate,https://github.com/pytorch/translate,BSD-3-Clause,2018-04-24 16:44:04.000000,2021-10-06 18:21:48.000000,2021-10-06 18:21:42.000000,171.0,11.0,27.0,716,810.0,Translate - a PyTorch Language Library.,87.0,15,,,,,pytorch-translate,,,,['pytorch'],,,https://pypi.org/project/pytorch-translate,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +737,Anchor,True,marcotcr/anchor,,interpretability,https://github.com/marcotcr/anchor,https://github.com/marcotcr/anchor,BSD-2-Clause,2018-02-02 23:38:50.000000,2021-11-17 21:38:50.000000,2021-11-17 21:38:50.000000,93.0,16.0,51.0,675,45.0,Code for High-Precision Model-Agnostic Explanations paper.,10.0,15,,,,,anchor_exp,,,,,,,https://pypi.org/project/anchor_exp,1773.0,1773.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +738,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 17:37:36.000000,2021-12-15 13:53:15.000000,2021-12-15 13:53:14.000000,97.0,24.0,26.0,656,492.0,Machine learning framework for both deep learning and traditional..,25.0,15,2021-06-22 05:25:53.000000,NeoML-master_2.0.5.0,2.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +739,AutoViz,True,AutoViML/AutoViz,,data-viz,https://github.com/AutoViML/AutoViz,https://github.com/AutoViML/AutoViz,Apache-2.0,2019-07-17 17:14:06.000000,2021-12-13 01:34:23.000000,2021-12-13 01:34:06.000000,86.0,7.0,34.0,575,114.0,"Automatically Visualize any dataset, any size with a single line of..",11.0,15,,,,,autoviz,,,,,125.0,125.0,https://pypi.org/project/autoviz,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +740,TF Compression,True,tensorflow/compression,,tensorflow-utils,https://github.com/tensorflow/compression,https://github.com/tensorflow/compression,Apache-2.0,2018-05-15 23:32:19.000000,2021-12-07 10:23:50.000000,2021-10-26 22:08:24.000000,198.0,3.0,73.0,552,175.0,Data compression in TensorFlow.,10.0,15,2021-05-14 00:38:32.000000,2.2,11.0,,tensorflow-compression,,,,['tensorflow'],,,https://pypi.org/project/tensorflow-compression,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +741,SKLL,True,EducationalTestingService/skll,,ml-experiments,https://github.com/EducationalTestingService/skll,https://github.com/EducationalTestingService/skll,,2013-08-02 14:31:46.000000,2021-12-16 00:15:48.000000,2021-12-09 16:41:20.000000,63.0,35.0,358.0,527,,SciKit-Learn Laboratory (SKLL) makes it easy to run machine..,36.0,15,2021-02-26 03:01:01.000000,2.5,64.0,,skll,,,,['sklearn'],34.0,34.0,https://pypi.org/project/skll,396.0,396.0,,,,,,,,3.0,11.0,,,,,,,,,,,,,,, +742,Submit it,True,facebookincubator/submitit,,distributed-ml,https://github.com/facebookincubator/submitit,https://github.com/facebookincubator/submitit,MIT,2020-04-24 07:41:09.000000,2021-12-09 11:50:36.000000,2021-12-09 11:50:36.000000,48.0,22.0,31.0,513,,Python 3.6+ toolbox for submitting jobs to Slurm.,17.0,15,2021-02-01 10:18:48.000000,1.2.0,6.0,,submitit,conda-forge/submitit,,,,,,https://pypi.org/project/submitit,,316.0,https://anaconda.org/conda-forge/submitit,2021-02-10 12:48:57.745000,5063.0,,,,,3.0,,,,,,,,,,,,,,,, +743,torch-cluster,True,rusty1s/pytorch_cluster,,graph,https://github.com/rusty1s/pytorch_cluster,https://github.com/rusty1s/pytorch_cluster,MIT,2018-01-12 20:56:06.000000,2021-12-14 09:26:14.000000,2021-12-14 09:26:13.000000,84.0,9.0,82.0,452,563.0,PyTorch Extension Library of Optimized Graph Cluster..,19.0,15,2021-03-01 13:58:47.000000,1.5.9,28.0,,torch-cluster,,,,['pytorch'],,,https://pypi.org/project/torch-cluster,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +744,LOFO,True,aerdem4/lofo-importance,,interpretability,https://github.com/aerdem4/lofo-importance,https://github.com/aerdem4/lofo-importance,MIT,2019-01-14 10:46:46.000000,2021-10-04 13:21:14.000000,2021-10-04 13:20:39.000000,50.0,4.0,13.0,423,26.0,Leave One Feature Out Importance.,3.0,15,,,,,lofo-importance,,,,,6.0,6.0,https://pypi.org/project/lofo-importance,327.0,327.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +745,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 22:49:49.000000,2021-10-10 00:13:26.000000,2021-10-10 00:13:26.000000,56.0,12.0,129.0,366,273.0,A Python library for dynamic classifier and ensemble selection.,13.0,15,,,,,deslib,,,,['sklearn'],22.0,22.0,https://pypi.org/project/deslib,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +746,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 21:00:31.000000,2021-10-01 15:05:45.000000,2021-08-03 00:21:54.000000,38.0,12.0,4.0,320,60.0,Topological Data Analysis for Python.,3.0,15,2021-08-03 00:22:58.000000,1.0.0,4.0,,scikit-tda,,,,['sklearn'],24.0,24.0,https://pypi.org/project/scikit-tda,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +747,ExplainX.ai,True,explainX/explainx,,interpretability,https://github.com/explainX/explainx,https://github.com/explainX/explainx,MIT,2020-06-16 14:27:15.000000,2021-02-07 11:06:21.000000,2021-02-02 09:03:57.000000,36.0,7.0,17.0,253,184.0,Explainable AI framework for data scientists. Explain & debug any..,4.0,15,2021-02-07 11:06:21.000000,2.407,21.0,,explainx,,,,,,,https://pypi.org/project/explainx,598.0,598.0,,,,,,,,3.0,2.0,,,,,,,,,,,,,,, +748,DeepGraph,True,deepgraph/deepgraph,,graph,https://github.com/deepgraph/deepgraph,https://github.com/deepgraph/deepgraph,,2015-10-27 12:28:45.000000,2021-11-08 16:53:47.290000,2021-06-14 10:58:10.000000,36.0,9.0,5.0,247,162.0,Analyze Data with Pandas-based Networks. Documentation:.,2.0,15,2020-10-01 13:20:38.000000,0.2.3,12.0,,deepgraph,conda-forge/deepgraph,,,['pandas'],2.0,2.0,https://pypi.org/project/deepgraph,304.0,2505.0,https://anaconda.org/conda-forge/deepgraph,2021-11-08 16:53:47.290000,114460.0,,,,,3.0,,,,,,,,,,,,,,,, +749,Julius,True,adefossez/julius,,audio,https://github.com/adefossez/julius,https://github.com/adefossez/julius,MIT,2020-10-26 10:54:21.000000,2021-10-20 08:30:09.000000,2021-10-20 08:28:45.000000,12.0,1.0,8.0,243,,Fast PyTorch based DSP for audio and 1D signals.,2.0,15,,,,,julius,,,,['pytorch'],49.0,49.0,https://pypi.org/project/julius,8075.0,8075.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +750,NeuralQA,True,victordibia/neuralqa,,nlp,https://github.com/victordibia/neuralqa,https://github.com/victordibia/neuralqa,MIT,2020-05-19 03:55:56.000000,2021-11-10 19:59:22.000000,2020-12-16 17:41:37.000000,31.0,20.0,8.0,218,312.0,NeuralQA: A Usable Library for Question Answering on Large Datasets with..,3.0,15,,,,,neuralqa,,,,,3.0,3.0,https://pypi.org/project/neuralqa,87.0,87.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +751,Parfit,True,jmcarpenter2/parfit,,hyperopt,https://github.com/jmcarpenter2/parfit,https://github.com/jmcarpenter2/parfit,MIT,2017-11-22 20:17:51.000000,2020-04-04 19:26:44.000000,2020-04-04 19:26:37.000000,25.0,6.0,5.0,199,127.0,A package for parallelizing the fit and flexibly scoring of..,2.0,15,,,,,parfit,,,,['sklearn'],9.0,9.0,https://pypi.org/project/parfit,16204.0,16204.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +752,ONNX-T5,True,abelriboulot/onnxt5,,nlp,https://github.com/abelriboulot/onnxt5,https://github.com/abelriboulot/onnxt5,Apache-2.0,2020-08-01 09:38:35.000000,2021-01-28 09:24:53.000000,2021-01-28 09:24:52.000000,24.0,6.0,8.0,189,74.0,"Summarization, translation, sentiment-analysis, text-generation and..",3.0,15,2021-01-28 09:24:24.000000,0.1.9,9.0,,onnxt5,,,,,,,https://pypi.org/project/onnxt5,171.0,171.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +753,nx-altair,True,Zsailer/nx_altair,,data-viz,https://github.com/Zsailer/nx_altair,https://github.com/Zsailer/nx_altair,MIT,2018-05-13 00:10:12.000000,2021-12-14 21:34:25.000000,2020-06-02 21:10:26.000000,22.0,6.0,4.0,183,51.0,Draw interactive NetworkX graphs with Altair.,3.0,15,,,,,nx-altair,,,,['jupyter'],,,https://pypi.org/project/nx-altair,3147.0,3147.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +754,PyStan,True,stan-dev/pystan,,probabilistics,https://github.com/stan-dev/pystan,https://github.com/stan-dev/pystan,ISC,2017-03-06 19:56:42.094000,2021-10-27 08:33:56.000000,2021-10-21 11:47:11.000000,34.0,6.0,150.0,143,,"PyStan, a Python interface to Stan, a platform for statistical modeling...",10.0,15,,,9.0,,pystan,conda-forge/pystan,,,,,,https://pypi.org/project/pystan,,23470.0,https://anaconda.org/conda-forge/pystan,2021-09-21 02:32:24.465000,1337817.0,,,,,3.0,,,,,,,,,,,,,,,, +755,openpyxl,True,,,data-loading,,https://foss.heptapod.net/openpyxl/openpyxl,MIT,2015-11-03 00:22:17.154000,2021-10-05 11:52:53.531000,,0.0,230.0,1541.0,31,,A Python library to read/write Excel 2010 xlsx/xlsm files.,,15,,,41.0,,openpyxl,openpyxl,openpyxl/openpyxl-ci,https://openpyxl.readthedocs.io/en/stable/,,,,https://pypi.org/project/openpyxl,19982070.0,19982954.0,https://anaconda.org/anaconda/openpyxl,2021-10-05 11:52:53.531000,63403.0,https://hub.docker.com/r/openpyxl/openpyxl-ci,2018-09-13 18:04:17.646261,,1193.0,3.0,,,,,,,,,,,,,,,https://foss.heptapod.net/api/graphql::openpyxl/openpyxl,https://foss.heptapod.net/openpyxl/openpyxl +756,Euler,True,alibaba/euler,,graph,https://github.com/alibaba/euler,https://github.com/alibaba/euler,Apache-2.0,2019-01-10 06:32:32.000000,2021-04-19 11:30:28.000000,2020-07-29 05:53:01.000000,541.0,213.0,102.0,2701,8.0,A distributed graph deep learning framework.,3.0,14,2020-07-07 02:24:18.000000,2.0.0,2.0,,euler-gl,,,,['tensorflow'],,,https://pypi.org/project/euler-gl,11.0,11.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +757,image-match,True,EdjoLabs/image-match,,image,https://github.com/ProvenanceLabs/image-match,https://github.com/ProvenanceLabs/image-match,,2016-03-08 18:16:45.000000,2021-09-21 13:07:59.000000,2021-09-21 13:07:59.000000,368.0,51.0,48.0,2658,405.0,Quickly search over billions of images.,19.0,14,2017-02-06 08:12:01.000000,1.1.2,10.0,ProvenanceLabs/image-match,image_match,,,,,,,https://pypi.org/project/image_match,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +758,ZhuSuan,True,thu-ml/zhusuan,,probabilistics,https://github.com/thu-ml/zhusuan,https://github.com/thu-ml/zhusuan,MIT,2016-07-18 13:31:38.000000,2020-01-09 14:51:27.000000,2019-08-05 10:00:04.000000,401.0,7.0,53.0,2093,439.0,"A probabilistic programming library for Bayesian deep learning,..",20.0,14,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +759,NeuroNER,True,Franck-Dernoncourt/NeuroNER,,nlp,https://github.com/Franck-Dernoncourt/NeuroNER,https://github.com/Franck-Dernoncourt/NeuroNER,MIT,2017-03-07 01:24:15.000000,2021-10-16 02:17:23.000000,2019-10-02 23:26:11.000000,447.0,82.0,67.0,1579,132.0,Named-entity recognition using neural networks. Easy-to-use and..,7.0,14,2019-03-13 20:28:15.000000,1.0-dev2,1.0,,pyneuroner,,,,,,,https://pypi.org/project/pyneuroner,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +760,AdvBox,True,advboxes/AdvBox,,adversarial,https://github.com/advboxes/AdvBox,https://github.com/advboxes/AdvBox,Apache-2.0,2018-08-08 08:55:41.000000,2021-09-08 00:05:01.000000,2021-05-03 22:51:52.000000,241.0,6.0,29.0,1187,375.0,Advbox is a toolbox to generate adversarial examples that fool..,19.0,14,,,,,advbox,,,,,,,https://pypi.org/project/advbox,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +761,Torch-Struct,True,harvardnlp/pytorch-struct,,pytorch-utils,https://github.com/harvardnlp/pytorch-struct,https://github.com/harvardnlp/pytorch-struct,MIT,2019-08-26 19:34:30.000000,2021-11-15 13:42:41.000000,2021-11-04 18:34:31.000000,76.0,21.0,28.0,1007,268.0,"Fast, general, and tested differentiable structured prediction..",13.0,14,2021-02-15 20:20:59.000000,0.5,2.0,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +762,NGT,True,yahoojapan/NGT,,nn-search,https://github.com/yahoojapan/NGT,https://github.com/yahoojapan/NGT,Apache-2.0,2016-09-01 07:36:57.000000,2021-11-06 00:02:46.000000,2021-10-25 04:48:23.000000,82.0,8.0,75.0,829,132.0,Nearest Neighbor Search with Neighborhood Graph and Tree for High-..,12.0,14,2021-04-14 00:31:14.000000,1.13.7,50.0,,ngt,,,,,,,https://pypi.org/project/ngt,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +763,tffm,True,geffy/tffm,,tensorflow-utils,https://github.com/geffy/tffm,https://github.com/geffy/tffm,MIT,2016-05-02 17:06:07.000000,2020-05-22 21:40:58.000000,2020-05-22 21:40:57.000000,180.0,17.0,22.0,774,106.0,TensorFlow implementation of an arbitrary order Factorization Machine.,10.0,14,,,,,tffm,,,,['tensorflow'],11.0,11.0,https://pypi.org/project/tffm,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +764,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 22:07:35.000000,2021-07-28 22:22:28.000000,2021-07-28 22:22:27.000000,158.0,,26.0,748,79.0,Framework-agnostic implementation for state-of-the-art saliency..,14.0,14,,,,,saliency,,,,['tensorflow'],19.0,19.0,https://pypi.org/project/saliency,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +765,AutoGL,True,THUMNLab/AutoGL,,graph,https://github.com/THUMNLab/AutoGL,https://github.com/THUMNLab/AutoGL,Apache-2.0,2020-11-30 14:26:22.000000,2021-12-16 14:03:49.000000,2021-11-23 02:46:46.000000,72.0,3.0,11.0,723,,An autoML framework & toolkit for machine learning on graphs.,9.0,14,2020-12-23 08:15:15.000000,0.1.1,2.0,,auto-graph-learning,,,,['pytorch'],,,https://pypi.org/project/auto-graph-learning,28.0,28.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +766,HyperparameterHunter,True,HunterMcGushion/hyperparameter_hunter,,hyperopt,https://github.com/HunterMcGushion/hyperparameter_hunter,https://github.com/HunterMcGushion/hyperparameter_hunter,MIT,2018-06-01 23:17:00.000000,2021-01-20 03:52:41.000000,2021-01-20 03:52:40.000000,87.0,32.0,84.0,680,1096.0,Easy hyperparameter optimization and automatic result..,4.0,14,2019-08-06 09:09:45.000000,3.0.0,16.0,,hyperparameter-hunter,,,,,,,https://pypi.org/project/hyperparameter-hunter,,8.0,,,,,,,,3.0,329.0,,,,,,,,,,,,,,, +767,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 19:03:34.000000,2020-04-25 18:38:20.000000,2020-04-25 18:37:42.000000,92.0,19.0,34.0,668,198.0,A Python library for detecting patterns and anomalies..,15.0,14,,,,,matrixprofile-ts,,,,,17.0,17.0,https://pypi.org/project/matrixprofile-ts,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +768,cuSignal,True,rapidsai/cusignal,,gpu-utilities,https://github.com/rapidsai/cusignal,https://github.com/rapidsai/cusignal,Apache-2.0,2019-08-22 14:27:27.000000,2021-12-08 17:57:36.000000,2021-12-08 17:57:35.000000,80.0,12.0,110.0,552,,GPU accelerated signal processing.,36.0,14,2021-12-08 17:04:15.000000,21.12.00,10.0,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +769,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 13:42:47.000000,2021-05-12 08:25:18.000000,2020-10-23 14:31:57.000000,69.0,22.0,5.0,422,247.0,machine learning with logical rules in Python.,18.0,14,2020-12-11 09:37:02.000000,1.0.1,1.0,,skope-rules,,,,['sklearn'],58.0,58.0,https://pypi.org/project/skope-rules,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +770,pydlm,True,wwrechard/pydlm,,time-series-data,https://github.com/wwrechard/pydlm,https://github.com/wwrechard/pydlm,BSD-3-Clause,2016-06-29 07:58:53.000000,2021-02-24 14:21:28.000000,2019-10-22 07:18:40.000000,87.0,35.0,8.0,404,362.0,A python library for Bayesian time series modeling.,6.0,14,,,,,pydlm,,,,,24.0,24.0,https://pypi.org/project/pydlm,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +771,tfdeploy,True,riga/tfdeploy,,model-serialisation,https://github.com/riga/tfdeploy,https://github.com/riga/tfdeploy,BSD-3-Clause,2016-03-07 13:08:21.000000,2021-01-08 09:52:54.000000,2021-01-08 09:52:49.000000,37.0,11.0,23.0,345,170.0,Deploy tensorflow graphs for fast evaluation and export to..,4.0,14,2016-12-23 10:46:31.000000,0.3.3,10.0,,tfdeploy,,,,['tensorflow'],,,https://pypi.org/project/tfdeploy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +772,TransferNLP,True,feedly/transfer-nlp,,nlp,https://github.com/feedly/transfer-nlp,https://github.com/feedly/transfer-nlp,MIT,2019-03-12 20:00:31.000000,2020-05-28 17:32:42.000000,2020-05-28 17:31:53.000000,17.0,3.0,20.0,287,465.0,NLP library designed for reproducible experimentation..,7.0,14,2020-05-28 17:32:42.000000,0.1.6,8.0,,transfer-nlp,,,,['pytorch'],,,https://pypi.org/project/transfer-nlp,81.0,81.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +773,skift,True,shaypal5/skift,,nlp,https://github.com/shaypal5/skift,https://github.com/shaypal5/skift,,2018-02-03 11:37:21.000000,2021-12-13 07:34:41.000000,2021-12-13 07:27:35.000000,21.0,2.0,9.0,224,131.0,scikit-learn wrappers for Python fastText.,8.0,14,2021-12-13 07:35:28.000000,0.0.21,1.0,,skift,,,,['sklearn'],10.0,10.0,https://pypi.org/project/skift,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +774,flupy,True,olirice/flupy,,data-pipelines,https://github.com/olirice/flupy,https://github.com/olirice/flupy,,2018-01-06 16:46:04.000000,2021-11-05 17:01:59.000000,2021-11-05 17:01:56.000000,12.0,,9.0,167,195.0,Fluent data pipelines for python and your shell.,6.0,14,,,,,flupy,,,,,,,https://pypi.org/project/flupy,35667.0,35667.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +775,steppy,True,minerva-ml/steppy,,ml-experiments,https://github.com/minerva-ml/steppy,https://github.com/minerva-ml/steppy,MIT,2018-01-15 09:40:49.000000,2018-11-23 09:48:51.000000,2018-11-23 09:47:34.000000,33.0,13.0,50.0,132,69.0,"Lightweight, Python library for fast and reproducible experimentation.",5.0,14,2018-11-23 09:48:51.000000,0.1.16,16.0,,steppy,,,,,42.0,42.0,https://pypi.org/project/steppy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +776,celer,True,mathurinm/celer,,sklearn-utils,https://github.com/mathurinm/celer,https://github.com/mathurinm/celer,BSD-3-Clause,2018-02-20 19:37:31.000000,2021-12-10 09:56:59.000000,2021-12-10 09:44:45.000000,23.0,14.0,55.0,127,,"Fast solver for L1-type problems: Lasso, sparse Logisitic regression,..",9.0,14,2020-10-12 12:26:09.000000,0.5.1,3.0,,celer,,,,['sklearn'],10.0,10.0,https://pypi.org/project/celer,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +777,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 08:19:28.000000,2020-12-04 17:43:48.000000,2020-12-04 17:43:47.000000,764.0,3.0,120.0,5050,47.0,Build Graph Nets in Tensorflow.,10.0,13,,,,,graph-nets,,,,['tensorflow'],,,https://pypi.org/project/graph-nets,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +778,StarSpace,True,facebookresearch/StarSpace,,ml-frameworks,https://github.com/facebookresearch/StarSpace,https://github.com/facebookresearch/StarSpace,MIT,2017-06-28 17:50:18.000000,2021-11-03 16:23:46.000000,2019-12-13 19:03:25.000000,500.0,48.0,148.0,3707,,"Learning embeddings for classification, retrieval and ranking.",17.0,13,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +779,GraphSAGE,True,williamleif/GraphSAGE,,graph,https://github.com/williamleif/GraphSAGE,https://github.com/williamleif/GraphSAGE,MIT,2017-05-29 15:36:22.000000,2021-08-25 15:01:46.000000,2018-09-19 19:27:00.000000,717.0,89.0,59.0,2580,59.0,Representation learning on large graphs using stochastic..,9.0,13,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +780,ENAS,True,carpedm20/ENAS-pytorch,,hyperopt,https://github.com/carpedm20/ENAS-pytorch,https://github.com/carpedm20/ENAS-pytorch,Apache-2.0,2018-02-15 04:54:37.000000,2020-12-09 18:13:03.000000,2020-06-16 07:23:32.000000,461.0,37.0,7.0,2504,53.0,PyTorch implementation of Efficient Neural Architecture Search via..,6.0,13,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +781,OpenNE,True,thunlp/OpenNE,,graph,https://github.com/thunlp/OpenNE,https://github.com/thunlp/OpenNE,MIT,2017-10-08 04:58:20.000000,2021-09-15 14:38:30.000000,2019-08-12 10:56:27.000000,466.0,2.0,94.0,1526,98.0,An Open-Source Package for Network Embedding (NE).,10.0,13,,,,,,,,,['tensorflow'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +782,MedicalNet,True,Tencent/MedicalNet,,medical-data,https://github.com/Tencent/MedicalNet,https://github.com/Tencent/MedicalNet,MIT,2019-07-17 09:53:10.000000,2021-09-16 22:05:49.000000,2020-08-27 13:37:26.000000,333.0,48.0,14.0,1285,26.0,Many studies have shown that the performance on deep learning is..,,13,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +783,SpeedTorch,True,Santosh-Gupta/SpeedTorch,,gpu-utilities,https://github.com/Santosh-Gupta/SpeedTorch,https://github.com/Santosh-Gupta/SpeedTorch,MIT,2019-09-07 18:57:52.000000,2020-02-21 23:13:29.000000,2020-02-21 23:13:28.000000,39.0,4.0,2.0,644,170.0,Library for faster pinned CPU - GPU transfer in Pytorch.,3.0,13,,,,,SpeedTorch,,,,['pytorch'],3.0,3.0,https://pypi.org/project/SpeedTorch,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +784,FlashTorch,True,MisaOgura/flashtorch,,interpretability,https://github.com/MisaOgura/flashtorch,https://github.com/MisaOgura/flashtorch,MIT,2019-03-22 13:00:57.000000,2021-06-30 12:46:02.000000,2021-04-27 11:10:20.000000,77.0,7.0,22.0,635,127.0,Visualization toolkit for neural networks in PyTorch! Demo --.,2.0,13,2020-05-29 14:39:38.000000,0.1.3,5.0,,flashtorch,,,,['pytorch'],8.0,8.0,https://pypi.org/project/flashtorch,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +785,Pandas Summary,True,mouradmourafiq/pandas-summary,,data-containers,https://github.com/polyaxon/datatile,https://github.com/polyaxon/datatile,Apache-2.0,2016-03-25 21:59:32.000000,2021-12-02 15:32:38.000000,2021-12-02 15:32:38.000000,37.0,7.0,6.0,373,26.0,An extension to pandas dataframes describe function.,7.0,13,,,,polyaxon/datatile,pandas-summary,,,,['pandas'],3.0,3.0,https://pypi.org/project/pandas-summary,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +786,Sematch,True,gsi-upm/sematch,,graph,https://github.com/gsi-upm/sematch,https://github.com/gsi-upm/sematch,Apache-2.0,2012-11-30 11:11:53.000000,2020-11-05 21:20:52.000000,2019-03-27 03:17:24.000000,101.0,12.0,19.0,369,122.0,semantic similarity framework for knowledge graph.,5.0,13,,,,,sematch,,,,,29.0,29.0,https://pypi.org/project/sematch,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +787,datmo,True,datmo/datmo,,ml-experiments,https://github.com/datmo/datmo,https://github.com/datmo/datmo,MIT,2017-11-03 05:46:43.000000,2021-06-01 22:48:33.000000,2019-11-29 00:48:44.000000,28.0,27.0,149.0,338,1051.0,Open source production model management tool for data scientists.,6.0,13,,,,,datmo,,,,,5.0,5.0,https://pypi.org/project/datmo,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +788,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 17:58:14.000000,2021-11-30 05:04:57.000000,2021-11-19 06:05:15.000000,15.0,69.0,175.0,287,700.0,datadescribe: Pythonic EDA Accelerator for Data Science.,14.0,13,,,5.0,,data-describe,,,,,,,https://pypi.org/project/data-describe,312.0,312.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +789,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 01:08:37.000000,2021-11-10 20:14:57.000000,2021-03-03 01:30:06.000000,21.0,,5.0,180,79.0,An automatic ML model optimization tool.,11.0,13,2021-03-03 02:00:23.000000,2.0,3.0,,auptimizer,,,,,,,https://pypi.org/project/auptimizer,33.0,33.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +790,ModelChimp,True,ModelChimp/modelchimp,,ml-experiments,https://github.com/ModelChimp/modelchimp,https://github.com/ModelChimp/modelchimp,BSD-2-Clause,2018-11-05 08:39:03.000000,2021-12-15 19:55:39.000000,2021-08-01 07:11:57.000000,12.0,4.0,10.0,122,363.0,Experiment tracking for machine and deep learning projects.,3.0,13,2019-04-09 10:43:15.000000,0.4.0,3.0,,modelchimp,,modelchimp/modelchimp-server,,,,,https://pypi.org/project/modelchimp,,17.0,,,,https://hub.docker.com/r/modelchimp/modelchimp-server,2019-04-09 10:15:09.532793,,648.0,3.0,,,,,,,,,,,,,,,, +791,micrograd,True,karpathy/micrograd,,pytorch-utils,https://github.com/karpathy/micrograd,https://github.com/karpathy/micrograd,MIT,2020-04-13 04:31:18.000000,2021-06-24 12:28:13.000000,2020-04-18 19:15:25.000000,143.0,2.0,3.0,1846,24.0,A tiny scalar-valued autograd engine and a neural net library..,2.0,12,,,,,micrograd,,,,['pytorch'],4.0,4.0,https://pypi.org/project/micrograd,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +792,surpriver,True,tradytics/surpriver,,financial-data,https://github.com/tradytics/surpriver,https://github.com/tradytics/surpriver,GPL-3.0,2020-08-30 07:56:22.000000,2021-08-13 08:02:31.000000,2020-09-21 04:32:05.000000,251.0,9.0,6.0,1379,64.0,Find big moving stocks before they move using machine..,6.0,12,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +793,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 12:34:57.000000,2021-09-09 14:14:09.000000,2021-09-09 14:14:04.000000,272.0,37.0,85.0,1070,40.0,The Medical Detection Toolkit contains 2D + 3D..,3.0,12,,,,,,,,,['pytorch'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +794,GraphVite,True,DeepGraphLearning/graphvite,,graph,https://github.com/DeepGraphLearning/graphvite,https://github.com/DeepGraphLearning/graphvite,Apache-2.0,2019-07-16 15:48:20.000000,2021-01-14 02:19:03.000000,2021-01-14 02:18:46.000000,130.0,35.0,56.0,976,15.0,GraphVite: A General and High-performance Graph Embedding System.,,12,,,4.0,,,milagraph/graphvite,,,,,,,,144.0,https://anaconda.org/milagraph/graphvite,2020-03-19 18:21:30.972000,4054.0,,,,,3.0,,,,,,,,,,,,,,,, +795,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 14:02:25.000000,2021-11-15 17:46:29.000000,2019-10-21 07:52:07.000000,50.0,8.0,15.0,619,46.0,Log TensorBoard events without touching TensorFlow.,5.0,12,,,,,tensorboard_logger,,,,,,,https://pypi.org/project/tensorboard_logger,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +796,VizSeq,True,facebookresearch/vizseq,,nlp,https://github.com/facebookresearch/vizseq,https://github.com/facebookresearch/vizseq,MIT,2019-08-26 13:19:38.000000,2021-09-14 21:59:53.000000,2021-09-02 03:19:31.000000,43.0,6.0,9.0,372,,"An Analysis Toolkit for Natural Language Generation (Translation,..",3.0,12,,,,,vizseq,,,,,3.0,3.0,https://pypi.org/project/vizseq,68.0,68.0,,,,,,,,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 11:38:17.000000,2021-12-12 23:37:19.000000,2021-07-05 08:09:48.000000,14.0,12.0,43.0,312,467.0,MLOps tool for deploying machine learning projects to..,4.0,12,,,,,bodywork-core,,,,,9.0,9.0,https://pypi.org/project/bodywork-core,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +798,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 21:07:17.000000,2021-07-07 00:44:10.000000,2021-07-07 00:44:07.000000,46.0,7.0,10.0,270,58.0,Distributed scikit-learn meta-estimators in PySpark.,7.0,12,,,,,sk-dist,,,,"['sklearn', 'spark']",8.0,8.0,https://pypi.org/project/sk-dist,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +799,textvec,True,textvec/textvec,,nlp,https://github.com/textvec/textvec,https://github.com/textvec/textvec,MIT,2018-04-12 14:03:53.000000,2020-12-03 14:23:11.000000,2020-12-03 14:23:04.000000,21.0,3.0,6.0,179,70.0,Text vectorization tool to outperform TFIDF for classification tasks.,4.0,12,2019-09-12 07:41:04.000000,2.0,1.0,,textvec,,,,['sklearn'],4.0,4.0,https://pypi.org/project/textvec,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +800,dabl,True,amueller/dabl,,sklearn-utils,https://github.com/amueller/dabl,https://github.com/amueller/dabl,BSD-3-Clause,2020-01-30 18:26:49.000000,2021-07-09 20:34:09.000000,2021-07-09 18:47:52.000000,9.0,,,114,,Data Analysis Baseline Library.,21.0,12,,,,,dabl,,,,['sklearn'],,,https://pypi.org/project/dabl,2090.0,2090.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +801,DeepNeuro,True,QTIM-Lab/DeepNeuro,,medical-data,https://github.com/QTIM-Lab/DeepNeuro,https://github.com/QTIM-Lab/DeepNeuro,MIT,2017-06-01 19:36:34.000000,2020-06-24 13:00:15.000000,2020-06-24 13:00:14.000000,34.0,25.0,16.0,108,285.0,A deep learning python package for neuroimaging data. Made by:.,6.0,12,,,,,deepneuro,,,,,1.0,1.0,https://pypi.org/project/deepneuro,33.0,33.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +802,Hypermax,True,electricbrainio/hypermax,,hyperopt,https://github.com/electricbrainio/hypermax,https://github.com/electricbrainio/hypermax,BSD-3-Clause,2018-07-27 18:43:01.000000,2020-08-02 18:08:50.000000,2020-08-02 18:08:46.000000,13.0,3.0,2.0,97,207.0,"Better, faster hyper-parameter optimization.",9.0,12,,,,,hypermax,,,,,4.0,4.0,https://pypi.org/project/hypermax,31.0,31.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +803,Attribution Priors,True,suinleelab/attributionpriors,,interpretability,https://github.com/suinleelab/attributionpriors,https://github.com/suinleelab/attributionpriors,MIT,2019-06-24 23:54:24.000000,2021-03-19 19:43:58.000000,2021-03-19 19:43:51.000000,10.0,1.0,3.0,90,72.0,Tools for training explainable models using..,6.0,12,2021-03-16 17:47:18.000000,1.0.0,1.0,,attributionpriors,,,,"['tensorflow', 'pytorch']",3.0,3.0,https://pypi.org/project/attributionpriors,27.0,27.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +804,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 07:15:56.000000,2021-11-11 10:54:41.000000,2021-11-11 10:53:33.000000,9.0,1.0,11.0,74,630.0,Contextual AI adds explainability to different stages of..,12.0,12,,,2.0,,contextual-ai,,,,,,,https://pypi.org/project/contextual-ai,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +805,bias-detector,True,intuit/bias-detector,,interpretability,https://github.com/intuit/bias-detector,https://github.com/intuit/bias-detector,MIT,2021-02-02 16:58:52.000000,2021-10-27 10:28:48.000000,2021-10-27 10:28:48.000000,9.0,,,36,,Bias Detector is a python package for detecting bias in machine..,4.0,12,2021-04-22 15:15:27.000000,0.0.12,10.0,,bias-detector,,,,,,,https://pypi.org/project/bias-detector,40.0,40.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +806,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 19:43:35.639000,2021-11-09 20:33:15.000000,2021-08-06 12:03:40.000000,6.0,,,9,,Feature engineering package with sklearn like functionality.,24.0,12,,,9.0,,feature_engine,conda-forge/feature_engine,,,,,,https://pypi.org/project/feature_engine,,419.0,https://anaconda.org/conda-forge/feature_engine,2021-09-01 07:47:26.156000,6711.0,,,,,3.0,,,,,,,,,,,,,,,, +807,OpenKE,True,thunlp/OpenKE,,graph,https://github.com/thunlp/OpenKE,https://github.com/thunlp/OpenKE,,2017-10-08 11:20:23.000000,2021-09-29 09:46:39.000000,2021-04-06 08:24:50.000000,828.0,18.0,308.0,2849,97.0,An Open-Source Package for Knowledge Embedding (KE).,10.0,11,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +808,Botflow,True,kkyon/botflow,,data-pipelines,https://github.com/kkyon/botflow,https://github.com/kkyon/botflow,,2018-08-20 03:13:31.000000,2020-12-31 09:03:22.000000,2019-05-23 14:40:50.000000,100.0,2.0,2.0,1178,192.0,Python Fast Dataflow programming framework for Data pipeline work(..,11.0,11,,,,,botflow,,,,,1.0,1.0,https://pypi.org/project/botflow,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +809,Devol,True,joeddav/devol,,hyperopt,https://github.com/joeddav/devol,https://github.com/joeddav/devol,MIT,2017-02-10 03:07:54.000000,2020-07-05 21:56:59.000000,2020-07-05 21:56:58.000000,109.0,7.0,20.0,935,116.0,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 20:43:42.000000,2020-10-02 06:01:01.000000,2018-01-31 16:50:23.000000,146.0,15.0,14.0,891,147.0,Approximate Nearest Neighbor Search for Sparse Data in Python!.,5.0,11,,,,,,,,,,,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +811,PandaPy,True,firmai/pandapy,,data-containers,https://github.com/firmai/pandapy,https://github.com/firmai/pandapy,,2020-01-15 18:21:23.000000,2021-10-20 11:36:04.000000,2021-10-20 11:36:04.000000,56.0,1.0,1.0,487,85.0,PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x..,3.0,11,2020-11-12 16:12:54.000000,zen,1.0,,pandapy,,,,['pandas'],1.0,1.0,https://pypi.org/project/pandapy,67.0,67.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +812,Headliner,True,as-ideas/headliner,,nlp,https://github.com/as-ideas/headliner,https://github.com/as-ideas/headliner,,2019-09-30 11:33:28.000000,2021-03-26 07:19:57.000000,2020-02-14 09:03:27.000000,40.0,1.0,13.0,230,276.0,Easy training and deployment of seq2seq models.,2.0,11,,,,,headliner,,,,,3.0,3.0,https://pypi.org/project/headliner,127.0,127.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +813,Hypertunity,True,gdikov/hypertunity,,hyperopt,https://github.com/gdikov/hypertunity,https://github.com/gdikov/hypertunity,Apache-2.0,2019-06-02 12:04:55.000000,2020-01-26 23:14:49.000000,2020-01-26 22:53:29.000000,9.0,,2.0,120,64.0,A toolset for black-box hyperparameter optimisation.,2.0,11,2020-01-26 23:01:09.000000,1.0.1,7.0,,hypertunity,,,,,2.0,2.0,https://pypi.org/project/hypertunity,25.0,25.0,,,,,,,,3.0,,,,,,,,,,,,,,,, +814,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 07:47:03.000000,2019-03-06 20:41:10.000000,2019-03-06 20:41:09.000000,15.0,2.0,,71,5.0,Python 3 Bindings for the NVIDIA Management Library.,2.0,11,,,,,nvidia-ml-py3,,,,,4617.0,4617.0,https://pypi.org/project/nvidia-ml-py3,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +815,nptsne,True,biovault/nptsne,,data-viz,https://github.com/biovault/nptsne,https://github.com/biovault/nptsne,Apache-2.0,2019-06-28 08:40:25.000000,2021-12-15 15:24:03.000000,2021-02-03 08:52:27.000000,2.0,7.0,5.0,27,857.0,nptsne is a numpy compatible python binary package that offers a number..,3.0,11,,,,,nptsne,,,,,3.0,3.0,https://pypi.org/project/nptsne,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +816,atspy,True,firmai/atspy,,time-series-data,https://github.com/firmai/atspy,https://github.com/firmai/atspy,,2020-01-28 05:00:10.000000,2021-08-30 13:03:29.000000,2021-08-30 13:03:29.000000,78.0,18.0,2.0,397,98.0,AtsPy: Automated Time Series Models in Python (by @firmai).,5.0,10,2020-11-12 16:10:48.000000,zen,1.0,,atspy,,,,,3.0,3.0,https://pypi.org/project/atspy,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +817,Mozart,True,aashrafh/Mozart,,ocr,https://github.com/aashrafh/Mozart,https://github.com/aashrafh/Mozart,Apache-2.0,2020-12-14 11:49:14.000000,2021-05-05 17:21:44.000000,2021-05-05 17:21:44.000000,47.0,3.0,6.0,342,,An optical music recognition (OMR) system. Converts sheet..,5.0,10,,,,,,,,,['sklearn'],,,,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +818,ipyexperiments,True,stas00/ipyexperiments,,gpu-utilities,https://github.com/stas00/ipyexperiments,https://github.com/stas00/ipyexperiments,,2018-11-15 01:19:40.000000,2021-12-07 18:50:39.000000,2021-12-07 18:50:38.000000,10.0,,5.0,142,203.0,jupyter/ipython experiment containers for GPU and..,3.0,10,,,,,ipyexperiments,,,,['jupyter'],5.0,5.0,https://pypi.org/project/ipyexperiments,,,,,,,,,,3.0,,,,,,,,,,,,,,,, +819,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 08:05:13.000000,2021-09-16 02:14:06.000000,2021-08-19 13:59:11.000000,8.0,,,43,,Distributed machine learning made simple.,2.0,10,2020-12-14 15:25:59.000000,0.2.4,2.0,,lazycluster,,,,,7.0,7.0,https://pypi.org/project/lazycluster,,,,,,,,,,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 22:23:05.000000,2021-03-12 01:44:04.000000,2021-03-12 01:43:14.000000,1.0,,,9,122.0,Train off-the-shelf machine learning models in one..,,7,,,,,traintool,,,,"['pytorch', 'tensorflow', 'sklearn']",,,https://pypi.org/project/traintool,20.0,20.0,,,,,,,,3.0,,,,,,,,,,,,,,,, diff --git a/latest-changes.md b/latest-changes.md index 1a0c82d..e1ea810 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._ -- Jina (🥈30 · ⭐ 12K · 📈) - An easier way to build neural search on the cloud. Apache-2 -- Milvus (🥈27 · ⭐ 8.3K · 📈) - An open source embedding vector similarity search engine powered.. Apache-2 -- Tensor Sensor (🥉20 · ⭐ 600 · 📈) - The goal of this library is to generate more helpful.. MIT -- Tez (🥉18 · ⭐ 700 · 📈) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 -- DeepMind Lab (🥉16 · ⭐ 6.5K · 📈) - A customisable 3D platform for agent-based AI research. ❗️GPL-2.0 +- 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 ## 📉 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._ -- DVC (🥈27 · ⭐ 8.7K · 📉) - Data Version Control | Git for Data & Models. Apache-2 -- fairseq (🥈23 · ⭐ 14K · 📉) - Facebook AI Research Sequence-to-Sequence Toolkit written in.. MIT -- TensorFlow Text (🥉22 · ⭐ 830 · 📉) - Making text a first-class citizen in TensorFlow. Apache-2 -- Flax (🥉20 · ⭐ 2.2K · 📉) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax -- DeepSpeech (🥉4 · 📉) - DeepSpeech is an open source embedded (offline, on-.. ❗Unlicensed +- 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 From ea2e268b91bfeb6b55714417a14ee34b65a30efe Mon Sep 17 00:00:00 2001 From: HanXinzi2020 Date: Thu, 30 Dec 2021 11:34:05 +0800 Subject: [PATCH 2/2] Update README.md --- README.md | 1924 ++++++++++++++++++++++++++--------------------------- 1 file changed, 962 insertions(+), 962 deletions(-) diff --git a/README.md b/README.md index 9200938..9583ca9 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3.1M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。 -## 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 · ⭐ 160K) - An Open Source Machine Learning Framework for Everyone. Apache-2 +
Tensorflow (🥇44 · ⭐ 160K) - 适用于所有人的开源机器学习框架。Apache-2 - [GitHub](https://github.com/tensorflow/tensorflow) (👨‍💻 3.9K · 🔀 69K · 📦 170K · 📋 34K - 7% open · ⏱️ 16.12.2021): @@ -103,7 +103,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull tensorflow/tensorflow ```
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scikit-learn (🥇38 · ⭐ 48K) - scikit-learn: machine learning in Python. BSD-3 +
scikit-learn (🥇38 · ⭐ 48K) - scikit-learn：基于Python的机器学习工具库。BSD-3 - [GitHub](https://github.com/scikit-learn/scikit-learn) (👨‍💻 2.4K · 🔀 22K · 📥 760 · 📦 290K · 📋 9K - 18% open · ⏱️ 15.12.2021): @@ -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 · ⭐ 22K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. Apache-2 +
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 - [GitHub](https://github.com/dmlc/xgboost) (👨‍💻 540 · 🔀 7.7K · 📥 3.5K · 📦 25K · 📋 4.2K - 6% open · ⏱️ 16.12.2021): @@ -135,7 +135,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge xgboost ```
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LightGBM (🥇36 · ⭐ 13K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. MIT +
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 - [GitHub](https://github.com/microsoft/LightGBM) (👨‍💻 250 · 🔀 3.4K · 📥 130K · 📦 10K · 📋 2.5K - 5% open · ⏱️ 15.12.2021): @@ -151,7 +151,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge lightgbm ```
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pytorch-lightning (🥇35 · ⭐ 17K) - The lightweight PyTorch wrapper for high-performance.. Apache-2 +
pytorch-lightning (🥇35 · ⭐ 17K) - 轻巧而具备高性能的PyTorch上层封装工具库。Apache-2 - [GitHub](https://github.com/PyTorchLightning/pytorch-lightning) (👨‍💻 590 · 🔀 2K · 📥 4.9K · 📦 6K · 📋 4.3K - 8% open · ⏱️ 16.12.2021): @@ -167,7 +167,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge pytorch-lightning ```
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Thinc (🥇34 · ⭐ 2.4K) - A refreshing functional take on deep learning, compatible with your favorite.. MIT +
Thinc (🥇34 · ⭐ 2.4K) - 深度学习工具库。MIT - [GitHub](https://github.com/explosion/thinc) (👨‍💻 42 · 🔀 220 · 📦 18K · 📋 110 - 13% open · ⏱️ 16.12.2021): @@ -183,7 +183,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge thinc ```
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PyTorch (🥈33 · ⭐ 53K) - Tensors and Dynamic neural networks in Python with strong GPU.. BSD-3 +
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 - [GitHub](https://github.com/pytorch/pytorch) (👨‍💻 3K · 🔀 14K · 📥 600 · 📋 24K - 31% open · ⏱️ 16.12.2021): @@ -199,7 +199,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c pytorch pytorch ```
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StatsModels (🥈33 · ⭐ 6.9K) - Statsmodels: statistical modeling and econometrics in Python. BSD-3 +
StatsModels (🥈33 · ⭐ 6.9K) - 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) (👨‍💻 350 · 🔀 2.2K · 📥 26 · 📦 55K · 📋 4.5K - 46% open · ⏱️ 15.12.2021): @@ -215,7 +215,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge statsmodels ```
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PaddlePaddle (🥈32 · ⭐ 17K) - PArallel Distributed Deep LEarning: Machine Learning.. Apache-2 +
PaddlePaddle (🥈32 · ⭐ 17K) - paddlepaddle机器学习与深度学习工具库。Apache-2 - [GitHub](https://github.com/PaddlePaddle/Paddle) (👨‍💻 670 · 🔀 4K · 📥 15K · 📦 83 · 📋 14K - 14% open · ⏱️ 16.12.2021): @@ -227,7 +227,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install paddlepaddle ```
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PySpark (🥈31 · ⭐ 32K) - Apache Spark Python API. Apache-2 +
PySpark (🥈31 · ⭐ 32K) - Apache Spark Python API。Apache-2 - [GitHub](https://github.com/apache/spark) (👨‍💻 2.6K · 🔀 24K · ⏱️ 16.12.2021): @@ -243,7 +243,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge pyspark ```
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dlib (🥈31 · ⭐ 11K) - A toolkit for making real world machine learning and data analysis.. ❗️BSL-1.0 +
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 - [GitHub](https://github.com/davisking/dlib) (👨‍💻 170 · 🔀 2.6K · 📥 25K · 📦 12K · 📋 2K - 1% open · ⏱️ 16.12.2021): @@ -259,7 +259,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge dlib ```
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Theano (🥈31 · ⭐ 9.5K) - Theano is a Python library that allows you to define, optimize,.. ❗Unlicensed +
Theano (🥈31 · ⭐ 9.5K) - Theano是一个Python神经网络工具库。❗Unlicensed - [GitHub](https://github.com/Theano/Theano) (👨‍💻 380 · 🔀 2.4K · 📦 12K · 📋 2.7K - 21% open · ⏱️ 23.11.2021): @@ -275,7 +275,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge theano ```
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jax (🥈30 · ⭐ 16K) - Composable transformations of Python+NumPy programs: differentiate,.. Apache-2 +
jax (🥈30 · ⭐ 16K) - Python + NumPy程序工具库。Apache-2 - [GitHub](https://github.com/google/jax) (👨‍💻 340 · 🔀 1.4K · 📦 3.1K · 📋 2.8K - 28% open · ⏱️ 16.12.2021): @@ -291,7 +291,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge jaxlib ```
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Chainer (🥈30 · ⭐ 5.7K) - A flexible framework of neural networks for deep learning. MIT +
Chainer (🥈30 · ⭐ 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 · 📦 2.4K · 📋 2K - 0% open · ⏱️ 10.06.2021): @@ -303,7 +303,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install chainer ```
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Keras (🥈29 · ⭐ 53K) - Deep Learning for humans. ❗Unlicensed +
Keras (🥈29 · ⭐ 53K) - 易上手的深度学习工具库。❗Unlicensed - [GitHub](https://github.com/keras-team/keras) (👨‍💻 1K · 🔀 18K · 📋 11K - 1% open · ⏱️ 16.12.2021): @@ -319,7 +319,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge keras ```
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Jina (🥈29 · ⭐ 13K) - An easier way to build neural search on the cloud. Apache-2 +
Jina (🥈29 · ⭐ 13K) - 在云端构建神经搜索的简便方法库。Apache-2 - [GitHub](https://github.com/jina-ai/jina) (👨‍💻 130 · 🔀 1.7K · 📦 190 · 📋 1.2K - 5% open · ⏱️ 16.12.2021): @@ -335,7 +335,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull jinaai/jina ```
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Catboost (🥈29 · ⭐ 6.3K) - A fast, scalable, high performance Gradient Boosting on Decision.. Apache-2 +
Catboost (🥈29 · ⭐ 6.3K) - 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) (👨‍💻 930 · 🔀 910 · 📥 70K · 📋 1.7K - 19% open · ⏱️ 16.12.2021): @@ -351,7 +351,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge catboost ```
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einops (🥈29 · ⭐ 4K) - Deep learning operations reinvented (for pytorch, tensorflow, jax and.. MIT +
einops (🥈29 · ⭐ 4K) - 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) (👨‍💻 13 · 🔀 160 · 📦 1.6K · 📋 87 - 33% open · ⏱️ 14.12.2021): @@ -367,7 +367,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge einops ```
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Fastai (🥈28 · ⭐ 22K) - The fastai deep learning library. Apache-2 +
Fastai (🥈28 · ⭐ 22K) - Fastai深度学习库。Apache-2 - [GitHub](https://github.com/fastai/fastai) (👨‍💻 180 · 🔀 7K · 📋 1.5K - 5% open · ⏱️ 29.11.2021): @@ -379,7 +379,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install fastai ```
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MXNet (🥈28 · ⭐ 20K) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning.. Apache-2 +
MXNet (🥈28 · ⭐ 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) (👨‍💻 970 · 🔀 6.5K · 📥 24K · 📋 9.4K - 18% open · ⏱️ 16.12.2021): @@ -395,7 +395,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c anaconda mxnet ```
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tensorpack (🥈28 · ⭐ 6.1K) - A Neural Net Training Interface on TensorFlow, with focus.. Apache-2 +
tensorpack (🥈28 · ⭐ 6.1K) - TensorFlow上的神经网络训练接口。Apache-2 - [GitHub](https://github.com/tensorpack/tensorpack) (👨‍💻 58 · 🔀 1.8K · 📥 130 · 📦 920 · 📋 1.3K - 0% open · ⏱️ 27.11.2021): @@ -407,7 +407,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tensorpack ```
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PyFlink (🥈27 · ⭐ 18K) - Apache Flink Python API. Apache-2 +
PyFlink (🥈27 · ⭐ 18K) - Apache Flink Python API。Apache-2 - [GitHub](https://github.com/apache/flink) (👨‍💻 1.4K · 🔀 9.8K · ⏱️ 16.12.2021): @@ -419,7 +419,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install apache-flink ```
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Sonnet (🥈27 · ⭐ 9.1K) - TensorFlow-based neural network library. Apache-2 +
Sonnet (🥈27 · ⭐ 9.1K) - 基于TensorFlow的神经网络库。Apache-2 - [GitHub](https://github.com/deepmind/sonnet) (👨‍💻 53 · 🔀 1.2K · 📦 730 · 📋 170 - 11% open · ⏱️ 15.12.2021): @@ -435,7 +435,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge sonnet ```
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Vowpal Wabbit (🥈27 · ⭐ 7.8K) - Vowpal Wabbit is a machine learning system which pushes the.. BSD-3 +
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 - [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (👨‍💻 310 · 🔀 1.7K · 📋 1.1K - 12% open · ⏱️ 15.12.2021): @@ -447,7 +447,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install vowpalwabbit ```
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skorch (🥈27 · ⭐ 4.2K) - A scikit-learn compatible neural network library that wraps.. BSD-3 +
skorch (🥈27 · ⭐ 4.2K) - 封装成scikit-learn接口模式的神经网络库。BSD-3 - [GitHub](https://github.com/skorch-dev/skorch) (👨‍💻 47 · 🔀 290 · 📦 420 · 📋 420 - 11% open · ⏱️ 28.11.2021): @@ -463,7 +463,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge skorch ```
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dyNET (🥈27 · ⭐ 3.3K · 💤) - DyNet: The Dynamic Neural Network Toolkit. Apache-2 +
dyNET (🥈27 · ⭐ 3.3K · 💤) - DyNet：动态神经网络工具包。Apache-2 - [GitHub](https://github.com/clab/dynet) (👨‍💻 160 · 🔀 670 · 📥 4.3K · 📦 200 · 📋 920 - 27% open · ⏱️ 27.01.2021): @@ -475,7 +475,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install dyNET ```
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Flax (🥈27 · ⭐ 2.4K · 📈) - Flax is a neural network library for JAX that is designed for.. Apache-2 jax +
Flax (🥈27 · ⭐ 2.4K · 📈) - 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) (👨‍💻 120 · 🔀 270 · 📥 31 · 📦 560 · 📋 410 - 32% open · ⏱️ 13.12.2021): @@ -487,7 +487,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install flax ```
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TFlearn (🥉26 · ⭐ 9.6K · 💀) - Deep learning library featuring a higher-level API for.. ❗Unlicensed +
TFlearn (🥉26 · ⭐ 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 · 📦 3.7K · 📋 910 - 60% open · ⏱️ 30.11.2020): @@ -499,7 +499,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tflearn ```
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Ignite (🥉26 · ⭐ 3.8K) - High-level library to help with training and evaluating neural.. BSD-3 +
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 - [GitHub](https://github.com/pytorch/ignite) (👨‍💻 160 · 🔀 500 · 📋 950 - 11% open · ⏱️ 15.12.2021): @@ -515,7 +515,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c pytorch ignite ```
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ktrain (🥉26 · ⭐ 930) - ktrain is a Python library that makes deep learning and AI more.. Apache-2 +
ktrain (🥉26 · ⭐ 930) - 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) (👨‍💻 12 · 🔀 220 · 📦 240 · 📋 380 - 1% open · ⏱️ 23.11.2021): @@ -527,7 +527,7 @@ _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 learning.. 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) (👨‍💻 82 · 🔀 1.1K · 📥 4.9K · 📦 280 · 📋 1.8K - 26% open · ⏱️ 29.11.2021): @@ -539,7 +539,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install turicreate ```
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Ludwig (🥉24 · ⭐ 8K) - Ludwig is a toolbox that allows to train and evaluate deep.. Apache-2 +
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 - [GitHub](https://github.com/ludwig-ai/ludwig) (👨‍💻 110 · 🔀 910 · 📦 98 · 📋 630 - 23% open · ⏱️ 16.12.2021): @@ -551,7 +551,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install ludwig ```
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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): @@ -563,7 +563,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nupic ```
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xLearn (🥉24 · ⭐ 3K · 💀) - High performance, easy-to-use, and scalable machine learning (ML).. Apache-2 +
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 - [GitHub](https://github.com/aksnzhy/xlearn) (👨‍💻 30 · 🔀 510 · 📥 3K · 📦 72 · 📋 300 - 62% open · ⏱️ 03.03.2020): @@ -575,7 +575,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install xlearn ```
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tensorflow-upstream (🥉24 · ⭐ 580) - TensorFlow ROCm port. Apache-2 +
tensorflow-upstream (🥉24 · ⭐ 580) - TensorFlow ROCm端口。Apache-2 - [GitHub](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) (👨‍💻 3.9K · 🔀 66 · 📥 17 · 📋 310 - 15% open · ⏱️ 14.12.2021): @@ -587,7 +587,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install tensorflow-rocm ```
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mlpack (🥉23 · ⭐ 3.9K) - mlpack: a scalable C++ machine learning library --. ❗Unlicensed +
mlpack (🥉23 · ⭐ 3.9K) - mlpack：可扩展的C++机器学习库-。❗Unlicensed - [GitHub](https://github.com/mlpack/mlpack) (👨‍💻 280 · 🔀 1.4K · 📋 1.4K - 3% open · ⏱️ 15.12.2021): @@ -603,7 +603,7 @@ _General-purpose machine learning and deep learning frameworks._ conda install -c conda-forge mlpack ```
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Neural Network Libraries (🥉23 · ⭐ 2.5K) - Neural Network Libraries. Apache-2 +
Neural Network Libraries (🥉23 · ⭐ 2.5K) - 神经网络工具库。Apache-2 - [GitHub](https://github.com/sony/nnabla) (👨‍💻 63 · 🔀 300 · 📥 530 · 📋 61 - 27% open · ⏱️ 16.12.2021): @@ -615,7 +615,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nnabla ```
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fklearn (🥉23 · ⭐ 1.4K) - fklearn: Functional Machine Learning. Apache-2 +
fklearn (🥉23 · ⭐ 1.4K) - fklearn：机器学习工具库。Apache-2 - [GitHub](https://github.com/nubank/fklearn) (👨‍💻 40 · 🔀 150 · 📦 10 · 📋 40 - 47% open · ⏱️ 06.12.2021): @@ -627,7 +627,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install fklearn ```
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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): @@ -639,7 +639,7 @@ _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 · 🔀 940 · 📦 880 · 📋 520 - 22% open · ⏱️ 20.11.2019): @@ -651,7 +651,7 @@ _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): @@ -667,7 +667,7 @@ _General-purpose machine learning and deep learning frameworks._ docker pull shogun/shogun ```
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NeuPy (🥉21 · ⭐ 700 · 💀) - NeuPy is a Tensorflow based python library for prototyping and building.. MIT +
NeuPy (🥉21 · ⭐ 700 · 💀) - 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 · 📦 120 · 📋 260 - 11% open · ⏱️ 02.09.2019): @@ -679,7 +679,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install neupy ```
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mace (🥉20 · ⭐ 4.5K) - MACE is a deep learning inference framework optimized for mobile.. Apache-2 +
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 - [GitHub](https://github.com/XiaoMi/mace) (👨‍💻 63 · 🔀 770 · 📥 1.4K · 📋 650 - 5% open · ⏱️ 06.12.2021): @@ -687,7 +687,7 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/XiaoMi/mace ```
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Haiku (🥉20 · ⭐ 1.6K) - JAX-based neural network library. Apache-2 +
Haiku (🥉20 · ⭐ 1.6K) - 基于JAX的神经网络库。Apache-2 - [GitHub](https://github.com/deepmind/dm-haiku) (👨‍💻 53 · 🔀 120 · 📦 270 · 📋 120 - 20% open · ⏱️ 02.12.2021): @@ -695,7 +695,7 @@ _General-purpose machine learning and deep learning frameworks._ git clone https://github.com/deepmind/dm-haiku ```
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Objax (🥉20 · ⭐ 660) - Objax is a machine learning framework that provides an Object.. Apache-2 jax +
Objax (🥉20 · ⭐ 660) - 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) (👨‍💻 22 · 🔀 56 · 📦 17 · 📋 93 - 39% open · ⏱️ 20.09.2021): @@ -707,7 +707,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install objax ```
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MindsDB (🥉19 · ⭐ 4.2K) - Predictive AI layer for existing databases. ❗️GPL-3.0 +
MindsDB (🥉19 · ⭐ 4.2K) - 为各种现有数据库提供预测性AI层。❗️GPL-3.0 - [GitHub](https://github.com/mindsdb/mindsdb) (👨‍💻 89 · 🔀 550 · 📋 780 - 10% open · ⏱️ 16.12.2021): @@ -719,7 +719,7 @@ _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 · 🔀 810 · 📥 320 · 📋 390 - 21% open · ⏱️ 22.05.2019): @@ -731,7 +731,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install nervananeon ```
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Neural Tangents (🥉19 · ⭐ 1.6K) - Fast and Easy Infinite Neural Networks in Python. Apache-2 +
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): @@ -743,7 +743,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install neural-tangents ```
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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) (👨‍💻 33 · 🔀 180 · 📥 2.3K · 📋 200 - 28% open · ⏱️ 10.02.2021): @@ -755,7 +755,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install thundersvm ```
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Torchbearer (🥉19 · ⭐ 620 · 💤) - torchbearer: A model fitting library for PyTorch. MIT +
Torchbearer (🥉19 · ⭐ 620 · 💤) - torchbearer：PyTorch的模型拟合库。MIT - [GitHub](https://github.com/pytorchbearer/torchbearer) (👨‍💻 13 · 🔀 68 · 📦 56 · 📋 240 - 3% open · ⏱️ 26.03.2021): @@ -767,7 +767,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install torchbearer ```
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ThunderGBM (🥉16 · ⭐ 620 · 💤) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. Apache-2 +
ThunderGBM (🥉16 · ⭐ 620 · 💤) - ThunderGBM：GPU上的快速GBDT和随机森林。Apache-2 - [GitHub](https://github.com/Xtra-Computing/thundergbm) (👨‍💻 10 · 🔀 80 · 📋 60 - 50% open · ⏱️ 05.01.2021): @@ -779,7 +779,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install thundergbm ```
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elegy (🥉16 · ⭐ 300) - Elegy is a framework-agnostic Trainer interface for the Jax.. MIT jax +
elegy (🥉16 · ⭐ 300) - Elegy是Jax的与框架无关的Trainer工具。MIT jax - [GitHub](https://github.com/poets-ai/elegy) (👨‍💻 14 · 🔀 21 · 📋 80 - 22% open · ⏱️ 14.12.2021): @@ -791,7 +791,7 @@ _General-purpose machine learning and deep learning frameworks._ pip install elegy ```
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NeoML (🥉15 · ⭐ 660) - Machine learning framework for both deep learning and traditional.. Apache-2 +
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 - [GitHub](https://github.com/neoml-lib/neoml) (👨‍💻 25 · 🔀 97 · 📋 50 - 48% open · ⏱️ 15.12.2021): @@ -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 (🥉13 · ⭐ 3.7K · 💀) - Learning embeddings for classification, retrieval and ranking. MIT +
StarSpace (🥉13 · ⭐ 3.7K · 💀) - 学习embedding嵌入用于分类，检索和排序。MIT - [GitHub](https://github.com/facebookresearch/StarSpace) (👨‍💻 17 · 🔀 500 · 📋 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。_ -
Seaborn (🥇35 · ⭐ 9K) - Statistical data visualization using matplotlib. BSD-3 +
Seaborn (🥇35 · ⭐ 9K) - 使用matplotlib进行统计数据可视化。BSD-3 - [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 160 · 🔀 1.5K · 📥 210 · 📦 130K · 📋 1.9K - 4% open · ⏱️ 27.11.2021): @@ -831,7 +831,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge seaborn ```
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Matplotlib (🥇33 · ⭐ 15K · 📉) - matplotlib: plotting with Python. ❗Unlicensed +
Matplotlib (🥇33 · ⭐ 15K · 📉) - matplotlib：Python绘图工具库。❗Unlicensed - [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.3K · 🔀 6K · 📦 470K · 📋 8.2K - 17% open · ⏱️ 16.12.2021): @@ -847,7 +847,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge matplotlib ```
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pandas-profiling (🥇33 · ⭐ 8.3K) - Create HTML profiling reports from pandas DataFrame.. MIT +
pandas-profiling (🥇33 · ⭐ 8.3K) - 从pandas DataFrame创建HTML分析报告。MIT - [GitHub](https://github.com/pandas-profiling/pandas-profiling) (👨‍💻 83 · 🔀 1.2K · 📦 6.1K · 📋 530 - 17% open · ⏱️ 06.12.2021): @@ -863,7 +863,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pandas-profiling ```
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Altair (🥇33 · ⭐ 7.1K) - Declarative statistical visualization library for Python. BSD-3 +
Altair (🥇33 · ⭐ 7.1K) - 用于Python的声明式统计可视化库。BSD-3 - [GitHub](https://github.com/altair-viz/altair) (👨‍💻 130 · 🔀 600 · 📦 20K · 📋 1.6K - 14% open · ⏱️ 13.12.2021): @@ -879,7 +879,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge altair ```
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UMAP (🥇32 · ⭐ 5.3K) - Uniform Manifold Approximation and Projection. BSD-3 +
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): @@ -891,7 +891,7 @@ _General-purpose and task-specific data visualization libraries._ pip install umap-learn ```
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Bokeh (🥈31 · ⭐ 16K) - Interactive Data Visualization in the browser, from Python. BSD-3 +
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): @@ -907,7 +907,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge bokeh ```
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dash (🥈31 · ⭐ 16K) - Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript.. MIT +
dash (🥈31 · ⭐ 16K) - 适用于Python，R，Julia和Jupyter的分析型Web应用程序。MIT - [GitHub](https://github.com/plotly/dash) (👨‍💻 100 · 🔀 1.6K · 📦 160 · 📋 1.1K - 46% open · ⏱️ 15.12.2021): @@ -923,7 +923,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dash ```
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pyecharts (🥈29 · ⭐ 12K) - Python Echarts Plotting Library. MIT +
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): @@ -935,7 +935,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pyecharts ```
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Plotly (🥈29 · ⭐ 11K) - The interactive graphing library for Python (includes Plotly Express). MIT +
Plotly (🥈29 · ⭐ 11K) - 适用于Python的交互式图形库（包括Plotly Express）。MIT - [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 190 · 🔀 2K · 📦 9 · 📋 2.1K - 46% open · ⏱️ 16.12.2021): @@ -955,7 +955,7 @@ _General-purpose and task-specific data visualization libraries._ npm install plotlywidget ```
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missingno (🥈29 · ⭐ 3K) - Missing data visualization module for Python. MIT +
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 - [GitHub](https://github.com/ResidentMario/missingno) (👨‍💻 17 · 🔀 380 · 📦 5.7K · 📋 110 - 9% open · ⏱️ 04.07.2021): @@ -971,7 +971,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge missingno ```
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plotnine (🥈27 · ⭐ 2.9K) - A grammar of graphics for Python. ❗️GPL-2.0 +
plotnine (🥈27 · ⭐ 2.9K) - Python的图形语法。❗️GPL-2.0 - [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 89 · 🔀 150 · 📦 2.8K · 📋 460 - 16% open · ⏱️ 14.12.2021): @@ -987,7 +987,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge plotnine ```
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datashader (🥈27 · ⭐ 2.7K) - Quickly and accurately render even the largest data. ❗Unlicensed +
datashader (🥈27 · ⭐ 2.7K) - 快速准确地渲染大数据。❗Unlicensed - [GitHub](https://github.com/holoviz/datashader) (👨‍💻 45 · 🔀 330 · 📦 900 · 📋 480 - 26% open · ⏱️ 29.11.2021): @@ -1003,7 +1003,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge datashader ```
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Cufflinks (🥈27 · ⭐ 2.4K · 💤) - Productivity Tools for Plotly + Pandas. MIT +
Cufflinks (🥈27 · ⭐ 2.4K · 💤) - Plotly + Pandas的生产力工具。MIT - [GitHub](https://github.com/santosjorge/cufflinks) (👨‍💻 38 · 🔀 560 · 📦 4.8K · 📋 200 - 39% open · ⏱️ 25.02.2021): @@ -1015,7 +1015,7 @@ _General-purpose and task-specific data visualization libraries._ pip install cufflinks ```
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PyVista (🥈27 · ⭐ 1K) - 3D plotting and mesh analysis through a streamlined interface for the.. MIT +
PyVista (🥈27 · ⭐ 1K) - 通过简化的界面进行3D绘图和网格分析。MIT - [GitHub](https://github.com/pyvista/pyvista) (👨‍💻 64 · 🔀 200 · 📥 380 · 📦 540 · 📋 640 - 27% open · ⏱️ 15.12.2021): @@ -1031,7 +1031,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pyvista ```
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hvPlot (🥈27 · ⭐ 490) - A high-level plotting API for pandas, dask, xarray, and networkx built on.. BSD-3 +
hvPlot (🥈27 · ⭐ 490) - 用于构建的pandas，dask，xarray和networkx的高级绘图API。BSD-3 - [GitHub](https://github.com/holoviz/hvplot) (👨‍💻 33 · 🔀 62 · 📦 940 · 📋 400 - 34% open · ⏱️ 16.12.2021): @@ -1047,7 +1047,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge hvplot ```
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wordcloud (🥈26 · ⭐ 8.5K) - A little word cloud generator in Python. MIT +
wordcloud (🥈26 · ⭐ 8.5K) - Python中的词云生成器。MIT - [GitHub](https://github.com/amueller/word_cloud) (👨‍💻 64 · 🔀 2.1K · 📋 450 - 20% open · ⏱️ 13.11.2021): @@ -1063,7 +1063,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge wordcloud ```
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Facets Overview (🥈26 · ⭐ 6.7K · 💤) - Visualizations for machine learning datasets. Apache-2 +
Facets Overview (🥈26 · ⭐ 6.7K · 💤) - 机器学习数据集的可视化。Apache-2 - [GitHub](https://github.com/PAIR-code/facets) (👨‍💻 28 · 🔀 820 · 📦 92 · 📋 150 - 50% open · ⏱️ 06.05.2021): @@ -1075,7 +1075,7 @@ _General-purpose and task-specific data visualization libraries._ pip install facets-overview ```
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bqplot (🥈26 · ⭐ 3.2K) - Plotting library for IPython/Jupyter notebooks. Apache-2 +
bqplot (🥈26 · ⭐ 3.2K) - 用于IPython / Jupyter笔记本的绘图库。Apache-2 - [GitHub](https://github.com/bqplot/bqplot) (👨‍💻 55 · 🔀 430 · 📦 28 · 📋 550 - 35% open · ⏱️ 10.12.2021): @@ -1095,7 +1095,7 @@ _General-purpose and task-specific data visualization libraries._ npm install bqplot ```
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D-Tale (🥈25 · ⭐ 2.9K) - Visualizer for pandas data structures. ❗️LGPL-2.1 +
D-Tale (🥈25 · ⭐ 2.9K) - pandas数据结构的可视化工具。❗️LGPL-2.1 - [GitHub](https://github.com/man-group/dtale) (👨‍💻 18 · 🔀 220 · 📦 270 · 📋 440 - 8% open · ⏱️ 12.12.2021): @@ -1111,7 +1111,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge dtale ```
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HoloViews (🥈25 · ⭐ 2.1K) - With Holoviews, your data visualizes itself. BSD-3 +
HoloViews (🥈25 · ⭐ 2.1K) - 使用Holoviews，您的数据可以可视化。BSD-3 - [GitHub](https://github.com/holoviz/holoviews) (👨‍💻 120 · 🔀 330 · 📋 2.7K - 29% open · ⏱️ 15.12.2021): @@ -1131,7 +1131,7 @@ _General-purpose and task-specific data visualization libraries._ npm install @pyviz/jupyterlab_pyviz ```
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Perspective (🥉24 · ⭐ 4K) - Streaming pivot visualization via WebAssembly. Apache-2 +
Perspective (🥉24 · ⭐ 4K) - 通过WebAssembly进行流式透视显示。Apache-2 - [GitHub](https://github.com/finos/perspective) (👨‍💻 65 · 🔀 410 · 📦 220 · 📋 470 - 12% open · ⏱️ 16.12.2021): @@ -1147,7 +1147,7 @@ _General-purpose and task-specific data visualization libraries._ npm install @finos/perspective-jupyterlab ```
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VisPy (🥉24 · ⭐ 2.8K) - High-performance interactive 2D/3D data visualization library. ❗Unlicensed +
VisPy (🥉24 · ⭐ 2.8K) - 高性能交互式2D / 3D数据可视化库。❗Unlicensed - [GitHub](https://github.com/vispy/vispy) (👨‍💻 170 · 🔀 570 · 📦 650 · 📋 1.3K - 20% open · ⏱️ 10.12.2021): @@ -1167,7 +1167,7 @@ _General-purpose and task-specific data visualization libraries._ npm install vispy ```
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HyperTools (🥉23 · ⭐ 1.7K) - A Python toolbox for gaining geometric insights into high-dimensional.. MIT +
HyperTools (🥉23 · ⭐ 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 · 🔀 160 · 📥 8 · 📦 160 · 📋 190 - 35% open · ⏱️ 19.07.2021): @@ -1179,7 +1179,7 @@ _General-purpose and task-specific data visualization libraries._ pip install hypertools ```
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Graphviz (🥉23 · ⭐ 1.1K) - Simple Python interface for Graphviz. MIT +
Graphviz (🥉23 · ⭐ 1.1K) - Graphviz的简单Python界面。MIT - [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 17 · 🔀 160 · 📦 26K · 📋 120 - 3% open · ⏱️ 15.12.2021): @@ -1191,7 +1191,7 @@ _General-purpose and task-specific data visualization libraries._ pip install graphviz ```
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Pandas-Bokeh (🥉23 · ⭐ 740 · 💤) - Bokeh Plotting Backend for Pandas and GeoPandas. MIT +
Pandas-Bokeh (🥉23 · ⭐ 740 · 💤) - pandas和GeoPandas的Bokeh绘图后端。MIT - [GitHub](https://github.com/PatrikHlobil/Pandas-Bokeh) (👨‍💻 12 · 🔀 93 · 📦 260 · 📋 93 - 29% open · ⏱️ 10.05.2021): @@ -1203,7 +1203,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pandas-bokeh ```
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python-ternary (🥉23 · ⭐ 500) - Ternary plotting library for python with matplotlib. MIT +
python-ternary (🥉23 · ⭐ 500) - 带有matplotlib的python三元绘图库。MIT - [GitHub](https://github.com/marcharper/python-ternary) (👨‍💻 27 · 🔀 130 · 📥 17 · 📦 76 · 📋 120 - 21% open · ⏱️ 21.10.2021): @@ -1219,7 +1219,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge python-ternary ```
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Chartify (🥉22 · ⭐ 3.1K · 💤) - Python library that makes it easy for data scientists to create.. Apache-2 +
Chartify (🥉22 · ⭐ 3.1K · 💤) - Python库，使数据科学家可以轻松创建。Apache-2 - [GitHub](https://github.com/spotify/chartify) (👨‍💻 21 · 🔀 270 · 📦 61 · 📋 71 - 56% open · ⏱️ 05.02.2021): @@ -1235,7 +1235,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge chartify ```
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PandasGUI (🥉22 · ⭐ 2.5K) - A GUI for Pandas DataFrames. MIT +
PandasGUI (🥉22 · ⭐ 2.5K) - pandas Dataframe的GUI。MIT - [GitHub](https://github.com/adamerose/PandasGUI) (👨‍💻 10 · 🔀 150 · 📦 120 · 📋 140 - 22% open · ⏱️ 25.09.2021): @@ -1247,7 +1247,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pandasgui ```
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openTSNE (🥉22 · ⭐ 930) - Extensible, parallel implementations of t-SNE. BSD-3 +
openTSNE (🥉22 · ⭐ 930) - t-SNE的可扩展并行实现。BSD-3 - [GitHub](https://github.com/pavlin-policar/openTSNE) (👨‍💻 10 · 🔀 97 · 📦 270 · 📋 98 - 3% open · ⏱️ 25.10.2021): @@ -1263,7 +1263,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge opentsne ```
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PyQtGraph (🥉21 · ⭐ 2.7K) - Fast data visualization and GUI tools for scientific /.. ❗Unlicensed +
PyQtGraph (🥉21 · ⭐ 2.7K) - 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) (👨‍💻 210 · 🔀 880 · 📋 950 - 29% open · ⏱️ 15.12.2021): @@ -1279,7 +1279,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pyqtgraph ```
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pythreejs (🥉21 · ⭐ 780) - A Jupyter - Three.js bridge. ❗Unlicensed +
pythreejs (🥉21 · ⭐ 780) - Jupyter-Three.js桥。❗Unlicensed - [GitHub](https://github.com/jupyter-widgets/pythreejs) (👨‍💻 29 · 🔀 160 · 📦 19 · 📋 210 - 31% open · ⏱️ 06.12.2021): @@ -1299,7 +1299,7 @@ _General-purpose and task-specific data visualization libraries._ npm install jupyter-threejs ```
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data-validation (🥉21 · ⭐ 600) - Library for exploring and validating machine learning.. Apache-2 +
data-validation (🥉21 · ⭐ 600) - 用于探索和验证机器学习的库。Apache-2 - [GitHub](https://github.com/tensorflow/data-validation) (👨‍💻 23 · 🔀 110 · 📥 290 · 📦 360 · 📋 140 - 19% open · ⏱️ 16.12.2021): @@ -1311,7 +1311,7 @@ _General-purpose and task-specific data visualization libraries._ pip install tensorflow-data-validation ```
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HiPlot (🥉20 · ⭐ 2.2K) - HiPlot makes understanding high dimensional data easy. MIT +
HiPlot (🥉20 · ⭐ 2.2K) - HiPlot使理解高维数据变得容易。MIT - [GitHub](https://github.com/facebookresearch/hiplot) (👨‍💻 7 · 🔀 100 · 📦 3 · 📋 71 - 14% open · ⏱️ 05.11.2021): @@ -1327,7 +1327,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge hiplot ```
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Sweetviz (🥉20 · ⭐ 1.8K) - Visualize and compare datasets, target values and associations, with one.. MIT +
Sweetviz (🥉20 · ⭐ 1.8K) - 可视化和比较数据集，目标值和相关性。MIT - [GitHub](https://github.com/fbdesignpro/sweetviz) (👨‍💻 6 · 🔀 180 · 📋 90 - 22% open · ⏱️ 08.07.2021): @@ -1339,7 +1339,7 @@ _General-purpose and task-specific data visualization libraries._ pip install sweetviz ```
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Multicore-TSNE (🥉20 · ⭐ 1.7K · 💀) - Parallel t-SNE implementation with Python and Torch.. BSD-3 +
Multicore-TSNE (🥉20 · ⭐ 1.7K · 💀) - 使用Python和Torch并行执行t-SNE。BSD-3 - [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (👨‍💻 15 · 🔀 190 · 📦 260 · 📋 55 - 61% 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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PDPbox (🥉20 · ⭐ 640 · 💤) - python partial dependence plot toolbox. MIT +
PDPbox (🥉20 · ⭐ 640 · 💤) - python部分依赖图工具箱。MIT - [GitHub](https://github.com/SauceCat/PDPbox) (👨‍💻 7 · 🔀 100 · 📦 460 · 📋 55 - 30% open · ⏱️ 14.03.2021): @@ -1371,7 +1371,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge pdpbox ```
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PyWaffle (🥉19 · ⭐ 460) - Make Waffle Charts in Python. MIT +
PyWaffle (🥉19 · ⭐ 460) - 用Python作图。MIT - [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 80 · 📦 100 · 📋 14 - 21% open · ⏱️ 28.07.2021): @@ -1383,7 +1383,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pywaffle ```
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pivottablejs (🥉19 · ⭐ 450 · 💀) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. ❗Unlicensed +
pivottablejs (🥉19 · ⭐ 450 · 💀) - Jupyter/IPython的Dragndrop数据透视表和图表。❗Unlicensed - [GitHub](https://github.com/nicolaskruchten/jupyter_pivottablejs) (👨‍💻 3 · 🔀 61 · 📦 210 · 📋 56 - 28% open · ⏱️ 04.12.2018): @@ -1395,7 +1395,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pivottablejs ```
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ivis (🥉19 · ⭐ 250) - Dimensionality reduction in very large datasets using Siamese.. Apache-2 +
ivis (🥉19 · ⭐ 250) - 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 · 🔀 26 · 📦 19 · 📋 53 - 5% open · ⏱️ 08.11.2021): @@ -1407,7 +1407,7 @@ _General-purpose and task-specific data visualization libraries._ pip install ivis ```
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FiftyOne (🥉18 · ⭐ 860) - Visualize, create, and debug image and video datasets.. ❗Unlicensed +
FiftyOne (🥉18 · ⭐ 860) - 可视化，创建和调试图像和视频数据集。❗Unlicensed - [GitHub](https://github.com/voxel51/fiftyone) (👨‍💻 20 · 🔀 98 · 📦 64 · 📋 600 - 30% open · ⏱️ 30.11.2021): @@ -1419,7 +1419,7 @@ _General-purpose and task-specific data visualization libraries._ pip install fiftyone ```
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animatplot (🥉18 · ⭐ 380 · 💀) - A python package for animating plots build on matplotlib. MIT +
animatplot (🥉18 · ⭐ 380 · 💀) - 用于在patpliblib上构建动画图的python程序包。MIT - [GitHub](https://github.com/t-makaro/animatplot) (👨‍💻 7 · 🔀 35 · 📦 29 · 📋 30 - 43% open · ⏱️ 05.10.2020): @@ -1435,7 +1435,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge animatplot ```
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joypy (🥉18 · ⭐ 370) - Joyplots in Python with matplotlib & pandas. MIT +
joypy (🥉18 · ⭐ 370) - 带有matplotlib和pandas的Python中的Joyplots。MIT - [GitHub](https://github.com/leotac/joypy) (👨‍💻 5 · 🔀 43 · 📦 110 · 📋 45 - 20% open · ⏱️ 13.12.2021): @@ -1451,7 +1451,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge joypy ```
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vega (🥉18 · ⭐ 320) - IPython/Jupyter notebook module for Vega and Vega-Lite. BSD-3 +
vega (🥉18 · ⭐ 320) - 适用于Vega和Vega-Lite的IPython/Jupyter笔记本模块。BSD-3 - [GitHub](https://github.com/vega/ipyvega) (👨‍💻 10 · 🔀 52 · 📋 92 - 11% open · ⏱️ 02.12.2021): @@ -1467,7 +1467,7 @@ _General-purpose and task-specific data visualization libraries._ conda install -c conda-forge vega ```
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lets-plot (🥉17 · ⭐ 700) - An open-source plotting library for statistical data. ❗Unlicensed +
lets-plot (🥉17 · ⭐ 700) - 一个用于统计数据的开源绘图库。❗Unlicensed - [GitHub](https://github.com/JetBrains/lets-plot) (👨‍💻 16 · 🔀 29 · 📥 140 · 📦 12 · 📋 220 - 32% open · ⏱️ 15.12.2021): @@ -1479,7 +1479,7 @@ _General-purpose and task-specific data visualization libraries._ pip install lets-plot ```
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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 · 🔀 30 · 📦 59 · 📋 26 - 61% open · ⏱️ 29.03.2019): @@ -1491,7 +1491,7 @@ _General-purpose and task-specific data visualization libraries._ pip install pdvega ```
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AutoViz (🥉15 · ⭐ 580) - Automatically Visualize any dataset, any size with a single line of.. Apache-2 +
AutoViz (🥉15 · ⭐ 580) - 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) (👨‍💻 11 · 🔀 86 · 📦 120 · 📋 41 - 17% open · ⏱️ 13.12.2021): @@ -1503,7 +1503,7 @@ _General-purpose and task-specific data visualization libraries._ pip install autoviz ```
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nx-altair (🥉15 · ⭐ 180 · 💀) - Draw interactive NetworkX graphs with Altair. MIT +
nx-altair (🥉15 · ⭐ 180 · 💀) - 使用Altair绘制交互式NetworkX图形。MIT - [GitHub](https://github.com/Zsailer/nx_altair) (👨‍💻 3 · 🔀 22 · 📋 10 - 60% open · ⏱️ 02.06.2020): @@ -1515,7 +1515,7 @@ _General-purpose and task-specific data visualization libraries._ pip install nx-altair ```
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data-describe (🥉13 · ⭐ 290) - datadescribe: Pythonic EDA Accelerator for Data Science. ❗Unlicensed +
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): @@ -1527,7 +1527,7 @@ _General-purpose and task-specific data visualization libraries._ pip install data-describe ```
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nptsne (🥉11 · ⭐ 27 · 💤) - nptsne is a numpy compatible python binary package that offers a.. Apache-2 +
nptsne (🥉11 · ⭐ 27 · 💤) - nptsne是numpy兼容的python二进制包。Apache-2 - [GitHub](https://github.com/biovault/nptsne) (👨‍💻 3 · 🔀 2 · 📦 3 · 📋 12 - 58% 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。_ -
transformers (🥇38 · ⭐ 56K) - Transformers: State-of-the-art Natural Language.. Apache-2 +
transformers (🥇38 · ⭐ 56K) - transformers：先进的自然语言模型库。Apache-2 - [GitHub](https://github.com/huggingface/transformers) (👨‍💻 1.1K · 🔀 13K · 📥 1.4K · 📦 20K · 📋 8.3K - 3% open · ⏱️ 16.12.2021): @@ -1563,7 +1563,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge transformers ```
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spaCy (🥇38 · ⭐ 22K) - Industrial-strength Natural Language Processing (NLP) in Python. MIT +
spaCy (🥇38 · ⭐ 22K) - Python中的工业级自然语言处理（NLP）工具包。MIT - [GitHub](https://github.com/explosion/spaCy) (👨‍💻 640 · 🔀 3.6K · 📥 3.1K · 📦 33K · 📋 5K - 1% open · ⏱️ 16.12.2021): @@ -1579,7 +1579,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge spacy ```
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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) (👨‍💻 420 · 🔀 3.9K · 📥 3.5K · 📦 29K · 📋 1.7K - 20% open · ⏱️ 13.12.2021): @@ -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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nltk (🥇33 · ⭐ 10K) - Suite of libraries and programs for symbolic and statistical natural.. Apache-2 +
nltk (🥇33 · ⭐ 10K) - 用于符号和统计自然的库和程序套件。Apache-2 - [GitHub](https://github.com/nltk/nltk) (👨‍💻 410 · 🔀 2.4K · 📦 120K · 📋 1.6K - 12% open · ⏱️ 16.12.2021): @@ -1611,7 +1611,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge nltk ```
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AllenNLP (🥇32 · ⭐ 11K) - An open-source NLP research library, built on PyTorch. Apache-2 +
AllenNLP (🥇32 · ⭐ 11K) - 基于PyTorch的开源NLP研究库。Apache-2 - [GitHub](https://github.com/allenai/allennlp) (👨‍💻 250 · 🔀 2.1K · 📥 43 · 📦 2.1K · 📋 2.5K - 3% open · ⏱️ 14.12.2021): @@ -1623,7 +1623,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install allennlp ```
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fastText (🥇31 · ⭐ 23K · 💀) - Library for fast text representation and classification. MIT +
fastText (🥇31 · ⭐ 23K · 💀) - 用于快速文本表示和分类的库。MIT - [GitHub](https://github.com/facebookresearch/fastText) (👨‍💻 58 · 🔀 4.3K · 📦 2.4K · 📋 1K - 40% open · ⏱️ 18.07.2020): @@ -1639,7 +1639,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge fasttext ```
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ChatterBot (🥇31 · ⭐ 12K) - ChatterBot is a machine learning, conversational dialog engine.. BSD-3 +
ChatterBot (🥇31 · ⭐ 12K) - ChatterBot是机器学习的对话引擎。BSD-3 - [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 100 · 🔀 3.8K · 📦 4K · 📋 1.5K - 18% open · ⏱️ 01.06.2021): @@ -1651,7 +1651,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install chatterbot ```
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fuzzywuzzy (🥇31 · ⭐ 8.6K) - Fuzzy String Matching in Python. ❗️GPL-2.0 +
fuzzywuzzy (🥇31 · ⭐ 8.6K) - Python中的模糊字符串匹配。❗️GPL-2.0 - [GitHub](https://github.com/seatgeek/fuzzywuzzy) (👨‍💻 70 · 🔀 860 · 📦 11K · 📋 180 - 43% open · ⏱️ 09.09.2021): @@ -1667,7 +1667,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge fuzzywuzzy ```
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sentence-transformers (🥇31 · ⭐ 6.7K) - Sentence Embeddings with BERT & XLNet. Apache-2 +
sentence-transformers (🥇31 · ⭐ 6.7K) - BERT和XLNet的句子嵌入。Apache-2 - [GitHub](https://github.com/UKPLab/sentence-transformers) (👨‍💻 67 · 🔀 1.3K · 📦 2.1K · 📋 1.2K - 49% open · ⏱️ 15.12.2021): @@ -1679,7 +1679,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sentence-transformers ```
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sentencepiece (🥇31 · ⭐ 5.5K) - Unsupervised text tokenizer for Neural Network-based text.. Apache-2 +
sentencepiece (🥇31 · ⭐ 5.5K) - 用于基于神经网络的文本的预处理器。Apache-2 - [GitHub](https://github.com/google/sentencepiece) (👨‍💻 57 · 🔀 730 · 📥 19K · 📦 12K · 📋 490 - 9% open · ⏱️ 02.07.2021): @@ -1695,7 +1695,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge sentencepiece ```
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flair (🥈30 · ⭐ 11K) - A very simple framework for state-of-the-art Natural Language.. ❗Unlicensed +
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 - [GitHub](https://github.com/flairNLP/flair) (👨‍💻 210 · 🔀 1.5K · 📦 1.1K · 📋 1.7K - 4% open · ⏱️ 16.12.2021): @@ -1707,7 +1707,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install flair ```
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TextBlob (🥈30 · ⭐ 8K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. MIT +
TextBlob (🥈30 · ⭐ 8K) - 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 · 📥 97 · 📦 16K · 📋 240 - 36% open · ⏱️ 22.10.2021): @@ -1723,7 +1723,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textblob ```
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ParlAI (🥈29 · ⭐ 8.5K) - A framework for training and evaluating AI models on a variety of.. MIT +
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): @@ -1735,7 +1735,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install parlai ```
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DeepPavlov (🥈28 · ⭐ 5.5K) - An open source library for deep learning end-to-end dialog.. Apache-2 +
DeepPavlov (🥈28 · ⭐ 5.5K) - 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 · 🔀 970 · 📦 240 · 📋 600 - 16% open · ⏱️ 28.09.2021): @@ -1747,7 +1747,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install deeppavlov ```
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Tokenizers (🥈28 · ⭐ 5.1K) - Fast State-of-the-Art Tokenizers optimized for Research and.. Apache-2 +
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 - [GitHub](https://github.com/huggingface/tokenizers) (👨‍💻 46 · 🔀 410 · 📦 38 · 📋 530 - 27% open · ⏱️ 15.12.2021): @@ -1763,7 +1763,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge tokenizers ```
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ftfy (🥈28 · ⭐ 3.1K · 💤) - Fixes mojibake and other glitches in Unicode text, after the fact. MIT +
ftfy (🥈28 · ⭐ 3.1K · 💤) - 修复Unicode文本中的故障功能的工具库。MIT - [GitHub](https://github.com/rspeer/python-ftfy) (👨‍💻 18 · 🔀 100 · 📦 4.5K · 📋 120 - 9% open · ⏱️ 17.05.2021): @@ -1779,7 +1779,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge ftfy ```
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GluonNLP (🥈27 · ⭐ 2.3K) - Toolkit that enables easy text preprocessing, datasets loading.. Apache-2 +
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 - [GitHub](https://github.com/dmlc/gluon-nlp) (👨‍💻 82 · 🔀 490 · 📦 680 · 📋 530 - 44% open · ⏱️ 24.08.2021): @@ -1791,7 +1791,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install gluonnlp ```
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Dedupe (🥈26 · ⭐ 3.2K) - A python library for accurate and scalable fuzzy matching, record.. MIT +
Dedupe (🥈26 · ⭐ 3.2K) - 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) (👨‍💻 61 · 🔀 440 · 📦 210 · 📋 670 - 9% open · ⏱️ 14.10.2021): @@ -1803,7 +1803,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install dedupe ```
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TextDistance (🥈26 · ⭐ 2.6K) - Compute distance between sequences. 30+ algorithms, pure python.. MIT +
TextDistance (🥈26 · ⭐ 2.6K) - 计算序列之间的距离，包含30多种算法。MIT - [GitHub](https://github.com/life4/textdistance) (👨‍💻 11 · 🔀 200 · 📥 410 · 📦 1.4K · ⏱️ 29.11.2021): @@ -1819,7 +1819,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textdistance ```
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spacy-transformers (🥈26 · ⭐ 1.1K) - Use pretrained transformers like BERT, XLNet and GPT-2.. MIT spacy +
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 - [GitHub](https://github.com/explosion/spacy-transformers) (👨‍💻 18 · 🔀 130 · 📦 340 · ⏱️ 16.12.2021): @@ -1831,7 +1831,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install spacy-transformers ```
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Rasa (🥈25 · ⭐ 13K) - Open source machine learning framework to automate text- and voice-.. Apache-2 +
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 - [GitHub](https://github.com/RasaHQ/rasa) (👨‍💻 520 · 🔀 3.7K · 📋 6.3K - 13% open · ⏱️ 16.12.2021): @@ -1843,7 +1843,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install rasa ```
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OpenNMT (🥈25 · ⭐ 5.4K) - Open Source Neural Machine Translation in PyTorch. MIT +
OpenNMT (🥈25 · ⭐ 5.4K) - PyTorch中的开源神经机器翻译。MIT - [GitHub](https://github.com/OpenNMT/OpenNMT-py) (👨‍💻 170 · 🔀 1.9K · 📦 120 · 📋 1.3K - 6% open · ⏱️ 08.12.2021): @@ -1855,7 +1855,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install OpenNMT-py ```
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haystack (🥈25 · ⭐ 3.4K) - End-to-end Python framework for building natural language search.. Apache-2 +
haystack (🥈25 · ⭐ 3.4K) - 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) (👨‍💻 87 · 🔀 580 · 📦 94 · 📋 1K - 13% open · ⏱️ 16.12.2021): @@ -1867,7 +1867,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install haystack ```
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neuralcoref (🥈25 · ⭐ 2.5K) - Fast Coreference Resolution in spaCy with Neural Networks. MIT +
neuralcoref (🥈25 · ⭐ 2.5K) - 基于SpaCy的神经网络实现快速共指解析。MIT - [GitHub](https://github.com/huggingface/neuralcoref) (👨‍💻 21 · 🔀 420 · 📥 300 · 📦 430 · 📋 290 - 20% open · ⏱️ 22.06.2021): @@ -1883,7 +1883,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge neuralcoref ```
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fastNLP (🥈25 · ⭐ 2.4K) - fastNLP: A Modularized and Extensible NLP Framework. Currently still.. Apache-2 +
fastNLP (🥈25 · ⭐ 2.4K) - fastNLP：模块化和可扩展的NLP框架。Apache-2 - [GitHub](https://github.com/fastnlp/fastNLP) (👨‍💻 54 · 🔀 400 · 📥 65 · 📦 52 · 📋 180 - 19% open · ⏱️ 06.12.2021): @@ -1895,7 +1895,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fastnlp ```
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jellyfish (🥈25 · ⭐ 1.6K) - a python library for doing approximate and phonetic matching of.. BSD-2 +
jellyfish (🥈25 · ⭐ 1.6K) - 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 · 📦 3K · 📋 110 - 8% open · ⏱️ 16.11.2021): @@ -1911,7 +1911,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge jellyfish ```
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Ciphey (🥈24 · ⭐ 9.1K) - Automatically decrypt encryptions without knowing the key or cipher,.. MIT +
Ciphey (🥈24 · ⭐ 9.1K) - 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 · 🔀 560 · 📋 270 - 15% open · ⏱️ 03.11.2021): @@ -1927,7 +1927,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we docker pull remnux/ciphey ```
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stanza (🥈24 · ⭐ 5.9K) - Official Stanford NLP Python Library for Many Human Languages. ❗Unlicensed +
stanza (🥈24 · ⭐ 5.9K) - 斯坦福NLP官方Python语言库，支持多种语言。❗Unlicensed - [GitHub](https://github.com/stanfordnlp/stanza) (👨‍💻 41 · 🔀 740 · 📦 780 · 📋 610 - 11% open · ⏱️ 18.11.2021): @@ -1943,7 +1943,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c stanfordnlp stanza ```
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torchtext (🥈24 · ⭐ 2.9K) - Data loaders and abstractions for text and NLP. BSD-3 +
torchtext (🥈24 · ⭐ 2.9K) - 文本和NLP的数据加载器和抽象。BSD-3 - [GitHub](https://github.com/pytorch/text) (👨‍💻 120 · 🔀 640 · 📋 590 - 43% open · ⏱️ 13.12.2021): @@ -1955,7 +1955,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install torchtext ```
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PyTextRank (🥈24 · ⭐ 1.7K) - Python implementation of TextRank for phrase extraction and.. MIT +
PyTextRank (🥈24 · ⭐ 1.7K) - TextRank的Python实现。MIT - [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 17 · 🔀 290 · 📦 220 · 📋 79 - 27% open · ⏱️ 10.10.2021): @@ -1967,7 +1967,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytextrank ```
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pyahocorasick (🥈24 · ⭐ 660) - Python module (C extension and plain python) implementing Aho-.. BSD-3 +
pyahocorasick (🥈24 · ⭐ 660) - Python文本工具库。BSD-3 - [GitHub](https://github.com/WojciechMula/pyahocorasick) (👨‍💻 23 · 🔀 95 · 📦 840 · 📋 110 - 34% open · ⏱️ 22.11.2021): @@ -1983,7 +1983,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge pyahocorasick ```
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fairseq (🥈23 · ⭐ 15K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. MIT +
fairseq (🥈23 · ⭐ 15K) - 用Python编写的Facebook AI Research Sequence-to-Sequence工具包。MIT - [GitHub](https://github.com/pytorch/fairseq) (👨‍💻 370 · 🔀 3.8K · 📥 160 · 📦 610 · 📋 3.1K - 34% open · ⏱️ 16.12.2021): @@ -1995,7 +1995,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fairseq ```
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flashtext (🥈23 · ⭐ 5K · 💀) - Extract Keywords from sentence or Replace keywords in sentences. MIT +
flashtext (🥈23 · ⭐ 5K · 💀) - 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 · 🔀 550 · 📦 650 · 📋 96 - 46% open · ⏱️ 03.05.2020): @@ -2007,7 +2007,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install flashtext ```
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vaderSentiment (🥈23 · ⭐ 3.3K · 💤) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. MIT +
vaderSentiment (🥈23 · ⭐ 3.3K · 💤) - VADER情感分析。MIT - [GitHub](https://github.com/cjhutto/vaderSentiment) (👨‍💻 10 · 🔀 820 · 📦 3.3K · 📋 100 - 28% open · ⏱️ 15.03.2021): @@ -2019,7 +2019,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install vadersentiment ```
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pytorch-nlp (🥈23 · ⭐ 2K) - Basic Utilities for PyTorch Natural Language Processing (NLP). BSD-3 +
pytorch-nlp (🥈23 · ⭐ 2K) - 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 · 🔀 240 · 📦 310 · 📋 66 - 25% open · ⏱️ 10.07.2021): @@ -2031,7 +2031,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytorch-nlp ```
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polyglot (🥈23 · ⭐ 1.9K · 💀) - Multilingual text (NLP) processing toolkit. ❗️GPL-3.0 +
polyglot (🥈23 · ⭐ 1.9K · 💀) - 多语言文本（NLP）处理工具包。❗️GPL-3.0 - [GitHub](https://github.com/aboSamoor/polyglot) (👨‍💻 26 · 🔀 300 · 📦 620 · 📋 200 - 68% open · ⏱️ 22.09.2020): @@ -2043,7 +2043,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install polyglot ```
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scattertext (🥈23 · ⭐ 1.7K) - Beautiful visualizations of how language differs among document.. Apache-2 +
scattertext (🥈23 · ⭐ 1.7K) - 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 · 🔀 230 · 📦 250 · 📋 82 - 20% open · ⏱️ 15.11.2021): @@ -2059,7 +2059,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge scattertext ```
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TensorFlow Text (🥈23 · ⭐ 860) - Making text a first-class citizen in TensorFlow. Apache-2 +
TensorFlow Text (🥈23 · ⭐ 860) - TensorFlow文本处理。Apache-2 - [GitHub](https://github.com/tensorflow/text) (👨‍💻 66 · 🔀 160 · 📦 1.2K · 📋 140 - 17% open · ⏱️ 08.12.2021): @@ -2071,7 +2071,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install tensorflow-text ```
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snowballstemmer (🥈23 · ⭐ 530) - Snowball compiler and stemming algorithms. BSD-3 +
snowballstemmer (🥈23 · ⭐ 530) - Snowball编译器和词干算法。BSD-3 - [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 28 · 🔀 140 · 📦 4 · 📋 57 - 22% open · ⏱️ 16.11.2021): @@ -2087,7 +2087,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge snowballstemmer ```
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T5 (🥉22 · ⭐ 3.8K) - Code for the paper Exploring the Limits of Transfer Learning with a.. Apache-2 +
T5 (🥉22 · ⭐ 3.8K) - 探索迁移学习的论文源码Apache-2 - [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (👨‍💻 44 · 🔀 530 · 📦 72 · 📋 370 - 10% open · ⏱️ 13.12.2021): @@ -2099,7 +2099,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install t5 ```
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Snips NLU (🥉22 · ⭐ 3.6K · 💤) - Snips Python library to extract meaning from text. Apache-2 +
Snips NLU (🥉22 · ⭐ 3.6K · 💤) - 从文本中提取含义的Python库。Apache-2 - [GitHub](https://github.com/snipsco/snips-nlu) (👨‍💻 22 · 🔀 480 · 📋 250 - 21% open · ⏱️ 03.05.2021): @@ -2111,7 +2111,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install snips-nlu ```
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Sumy (🥉22 · ⭐ 2.7K) - Module for automatic summarization of text documents and HTML pages. Apache-2 +
Sumy (🥉22 · ⭐ 2.7K) - 自动汇总文本文档和HTML页面的模块。Apache-2 - [GitHub](https://github.com/miso-belica/sumy) (👨‍💻 21 · 🔀 450 · 📦 1K · 📋 93 - 13% open · ⏱️ 23.11.2021): @@ -2123,7 +2123,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sumy ```
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Texar (🥉22 · ⭐ 2.2K · 💀) - Toolkit for Machine Learning, Natural Language Processing, and.. Apache-2 +
Texar (🥉22 · ⭐ 2.2K · 💀) - 机器学习，自然语言处理等工具包。Apache-2 - [GitHub](https://github.com/asyml/texar) (👨‍💻 43 · 🔀 360 · 📦 17 · 📋 160 - 19% open · ⏱️ 29.07.2020): @@ -2135,7 +2135,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install texar ```
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langid (🥉22 · ⭐ 1.9K · 💀) - Stand-alone language identification system. ❗Unlicensed +
langid (🥉22 · ⭐ 1.9K · 💀) - 独立的语言识别系统。❗Unlicensed - [GitHub](https://github.com/saffsd/langid.py) (👨‍💻 9 · 🔀 280 · 📦 870 · 📋 71 - 36% open · ⏱️ 15.07.2017): @@ -2147,7 +2147,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install langid ```
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sense2vec (🥉22 · ⭐ 1.3K) - Contextually-keyed word vectors. MIT +
sense2vec (🥉22 · ⭐ 1.3K) - 上下文相关性构建词向量。MIT - [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 17 · 🔀 220 · 📥 23K · 📦 100 · 📋 100 - 15% open · ⏱️ 16.08.2021): @@ -2163,7 +2163,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge sense2vec ```
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pySBD (🥉22 · ⭐ 390 · 💤) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. MIT +
pySBD (🥉22 · ⭐ 390 · 💤) - pySBD（Python句子边界歧义消除）。MIT - [GitHub](https://github.com/nipunsadvilkar/pySBD) (👨‍💻 6 · 🔀 42 · 📦 250 · 📋 60 - 20% open · ⏱️ 11.02.2021): @@ -2175,7 +2175,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pysbd ```
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stop-words (🥉22 · ⭐ 130 · 💀) - Get list of common stop words in various languages in Python. BSD-3 +
stop-words (🥉22 · ⭐ 130 · 💀) - 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 · 🔀 24 · 📦 1.4K · 📋 12 - 25% open · ⏱️ 23.07.2018): @@ -2187,7 +2187,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install stop-words ```
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textgenrnn (🥉21 · ⭐ 4.6K · 💀) - Easily train your own text-generating neural network.. ❗Unlicensed +
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): @@ -2199,7 +2199,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textgenrnn ```
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MatchZoo (🥉21 · ⭐ 3.6K) - Facilitating the design, comparison and sharing of deep.. Apache-2 +
MatchZoo (🥉21 · ⭐ 3.6K) - 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 · 🔀 890 · 📦 10 · 📋 460 - 6% open · ⏱️ 02.06.2021): @@ -2211,7 +2211,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install matchzoo ```
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phonenumbers (🥉21 · ⭐ 2.9K) - Python port of Google's libphonenumber. Apache-2 +
phonenumbers (🥉21 · ⭐ 2.9K) - Google的libphonenumber的Python端口。Apache-2 - [GitHub](https://github.com/daviddrysdale/python-phonenumbers) (👨‍💻 25 · 🔀 350 · 📋 130 - 2% open · ⏱️ 14.12.2021): @@ -2227,7 +2227,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge phonenumbers ```
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spark-nlp (🥉21 · ⭐ 2.5K) - State of the Art Natural Language Processing. Apache-2 +
spark-nlp (🥉21 · ⭐ 2.5K) - 最先进的自然语言处理。Apache-2 - [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (👨‍💻 100 · 🔀 510 · 📋 600 - 12% open · ⏱️ 16.12.2021): @@ -2239,7 +2239,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install spark-nlp ```
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Texthero (🥉21 · ⭐ 2.4K) - Text preprocessing, representation and visualization from zero to hero. MIT +
Texthero (🥉21 · ⭐ 2.4K) - 文本预处理，表示和可视化从入门到精通。MIT - [GitHub](https://github.com/jbesomi/texthero) (👨‍💻 18 · 🔀 200 · 📥 87 · 📋 110 - 44% open · ⏱️ 19.07.2021): @@ -2251,7 +2251,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install texthero ```
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FARM (🥉21 · ⭐ 1.4K) - Fast & easy transfer learning for NLP. Harvesting language models.. Apache-2 +
FARM (🥉21 · ⭐ 1.4K) - NLP的快速和轻松迁移学习。Apache-2 - [GitHub](https://github.com/deepset-ai/FARM) (👨‍💻 36 · 🔀 210 · 📋 400 - 3% open · ⏱️ 23.11.2021): @@ -2263,7 +2263,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install farm ```
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SciSpacy (🥉21 · ⭐ 1.1K) - A full spaCy pipeline and models for scientific/biomedical.. Apache-2 +
SciSpacy (🥉21 · ⭐ 1.1K) - 完整的科学/生物医学的SpaCy应用案例。Apache-2 - [GitHub](https://github.com/allenai/scispacy) (👨‍💻 21 · 🔀 140 · 📦 370 · 📋 230 - 15% open · ⏱️ 15.07.2021): @@ -2275,7 +2275,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install scispacy ```
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CLTK (🥉21 · ⭐ 700) - The Classical Language Toolkit. MIT +
CLTK (🥉21 · ⭐ 700) - 古典语言工具包。MIT - [GitHub](https://github.com/cltk/cltk) (👨‍💻 110 · 🔀 300 · 📥 22 · 📦 180 · 📋 510 - 4% open · ⏱️ 21.10.2021): @@ -2287,7 +2287,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install cltk ```
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PyText (🥉20 · ⭐ 6.3K) - A natural language modeling framework based on PyTorch. ❗Unlicensed +
PyText (🥉20 · ⭐ 6.3K) - 基于PyTorch的自然语言建模框架。❗Unlicensed - [GitHub](https://github.com/facebookresearch/pytext) (👨‍💻 220 · 🔀 790 · 📥 280 · 📦 100 · 📋 130 - 44% open · ⏱️ 15.12.2021): @@ -2299,7 +2299,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pytext-nlp ```
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NeMo (🥉20 · ⭐ 3.7K) - NeMo: a toolkit for conversational AI. Apache-2 +
NeMo (🥉20 · ⭐ 3.7K) - NeMo：用于智能对话的工具包。Apache-2 - [GitHub](https://github.com/NVIDIA/NeMo) (👨‍💻 120 · 🔀 790 · 📥 17K · 📋 870 - 4% open · ⏱️ 16.12.2021): @@ -2311,7 +2311,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install nemo-toolkit ```
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Kashgari (🥉20 · ⭐ 2.2K) - Kashgari is a production-level NLP Transfer learning framework.. Apache-2 +
Kashgari (🥉20 · ⭐ 2.2K) - Kashgari是工业级的NLP迁移学习框架。Apache-2 - [GitHub](https://github.com/BrikerMan/Kashgari) (👨‍💻 21 · 🔀 420 · 📦 49 · 📋 360 - 9% open · ⏱️ 09.07.2021): @@ -2323,7 +2323,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install kashgari-tf ```
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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): @@ -2339,7 +2339,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we docker pull zh794390558/delta ```
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anaGo (🥉20 · ⭐ 1.4K · 💤) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. MIT +
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 - [GitHub](https://github.com/Hironsan/anago) (👨‍💻 11 · 🔀 360 · 📦 27 · 📋 110 - 33% open · ⏱️ 01.04.2021): @@ -2351,7 +2351,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install anago ```
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inflect (🥉20 · ⭐ 590 · 💤) - Correctly generate plurals, ordinals, indefinite articles; convert.. MIT +
inflect (🥉20 · ⭐ 590 · 💤) - 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) (👨‍💻 29 · 🔀 65 · 📋 80 - 21% open · ⏱️ 23.03.2021): @@ -2367,7 +2367,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge inflect ```
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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 · 📥 340 · 📦 200 · 📋 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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NLP Architect (🥉19 · ⭐ 2.8K) - A model library for exploring state-of-the-art deep learning.. Apache-2 +
NLP Architect (🥉19 · ⭐ 2.8K) - 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 · 🔀 420 · 📦 8 · 📋 130 - 11% open · ⏱️ 12.09.2021): @@ -2391,7 +2391,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install nlp-architect ```
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textacy (🥉19 · ⭐ 1.8K) - NLP, before and after spaCy. ❗Unlicensed +
textacy (🥉19 · ⭐ 1.8K) - spaCy之前和之后的NLP。❗Unlicensed - [GitHub](https://github.com/chartbeat-labs/textacy) (👨‍💻 31 · 🔀 230 · 📋 240 - 10% open · ⏱️ 06.12.2021): @@ -2407,7 +2407,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we conda install -c conda-forge textacy ```
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gpt-2-simple (🥉18 · ⭐ 2.8K) - Python package to easily retrain OpenAI's GPT-2 text-.. ❗Unlicensed +
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 - [GitHub](https://github.com/minimaxir/gpt-2-simple) (👨‍💻 18 · 🔀 570 · 📥 280 · 📋 230 - 60% open · ⏱️ 18.10.2021): @@ -2419,7 +2419,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install gpt-2-simple ```
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fast-bert (🥉18 · ⭐ 1.7K) - Super easy library for BERT based NLP models. Apache-2 +
fast-bert (🥉18 · ⭐ 1.7K) - 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) (👨‍💻 35 · 🔀 320 · 📋 240 - 60% open · ⏱️ 31.08.2021): @@ -2431,7 +2431,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install fast-bert ```
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Sockeye (🥉18 · ⭐ 1K) - Sequence-to-sequence framework with a focus on Neural Machine.. Apache-2 +
Sockeye (🥉18 · ⭐ 1K) - 序列到序列框架。Apache-2 - [GitHub](https://github.com/awslabs/sockeye) (👨‍💻 54 · 🔀 280 · 📥 12 · 📋 260 - 1% open · ⏱️ 14.12.2021): @@ -2443,7 +2443,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install sockeye ```
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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 · 🔀 69 · 📦 9 · 📋 140 - 15% open · ⏱️ 18.11.2021): @@ -2455,7 +2455,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install finetune ```
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textpipe (🥉17 · ⭐ 290) - Textpipe: clean and extract metadata from text. MIT +
textpipe (🥉17 · ⭐ 290) - Textpipe：从文本中清理并提取元数据。MIT - [GitHub](https://github.com/textpipe/textpipe) (👨‍💻 28 · 🔀 22 · 📦 8 · 📋 40 - 37% open · ⏱️ 09.06.2021): @@ -2467,7 +2467,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textpipe ```
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YouTokenToMe (🥉16 · ⭐ 780 · 💤) - Unsupervised text tokenizer focused on computational efficiency. MIT +
YouTokenToMe (🥉16 · ⭐ 780 · 💤) - 用于基于神经网络的文本的预处理器。MIT - [GitHub](https://github.com/VKCOM/YouTokenToMe) (👨‍💻 6 · 🔀 55 · 📦 180 · 📋 50 - 54% open · ⏱️ 28.01.2021): @@ -2479,7 +2479,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install youtokentome ```
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DeepMatcher (🥉16 · ⭐ 380) - Python package for performing Entity and Text Matching using.. BSD-3 +
DeepMatcher (🥉16 · ⭐ 380) - 用于实体和文本匹配的Python包。BSD-3 - [GitHub](https://github.com/anhaidgroup/deepmatcher) (👨‍💻 7 · 🔀 88 · 📦 14 · 📋 76 - 71% 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 · 🔀 17 · 📋 27 - 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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OpenNRE (🥉15 · ⭐ 3.4K) - An Open-Source Package for Neural Relation Extraction (NRE). MIT +
OpenNRE (🥉15 · ⭐ 3.4K) - 神经关系提取（NRE）的开源软件包。MIT - [GitHub](https://github.com/thunlp/OpenNRE) (👨‍💻 10 · 🔀 900 · 📋 330 - 3% open · ⏱️ 09.12.2021): @@ -2511,7 +2511,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we git clone https://github.com/thunlp/OpenNRE ```
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Translate (🥉15 · ⭐ 720) - Translate - a PyTorch Language Library. BSD-3 +
Translate (🥉15 · ⭐ 720) - Translate-PyTorch NLP库。BSD-3 - [GitHub](https://github.com/pytorch/translate) (👨‍💻 87 · 🔀 170 · 📋 38 - 28% open · ⏱️ 06.10.2021): @@ -2523,7 +2523,7 @@ _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 · 🔀 31 · 📦 3 · 📋 28 - 71% open · ⏱️ 16.12.2020): @@ -2535,7 +2535,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install neuralqa ```
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ONNX-T5 (🥉15 · ⭐ 190 · 💤) - Summarization, translation, sentiment-analysis, text-generation.. Apache-2 +
ONNX-T5 (🥉15 · ⭐ 190 · 💤) - 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 · 🔀 24 · 📋 14 - 42% open · ⏱️ 28.01.2021): @@ -2547,7 +2547,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install onnxt5 ```
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NeuroNER (🥉14 · ⭐ 1.6K · 💀) - Named-entity recognition using neural networks. Easy-to-use and.. MIT +
NeuroNER (🥉14 · ⭐ 1.6K · 💀) - 使用神经网络的命名实体识别。MIT - [GitHub](https://github.com/Franck-Dernoncourt/NeuroNER) (👨‍💻 7 · 🔀 450 · 📋 150 - 55% open · ⏱️ 02.10.2019): @@ -2559,7 +2559,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install pyneuroner ```
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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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skift (🥉14 · ⭐ 220) - scikit-learn wrappers for Python fastText. ❗Unlicensed +
skift (🥉14 · ⭐ 220) - 适用于Python fastText的scikit-learn包装器。❗Unlicensed - [GitHub](https://github.com/shaypal5/skift) (👨‍💻 8 · 🔀 21 · 📦 10 · 📋 11 - 18% open · ⏱️ 13.12.2021): @@ -2583,7 +2583,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install skift ```
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VizSeq (🥉12 · ⭐ 370) - An Analysis Toolkit for Natural Language Generation (Translation,.. MIT +
VizSeq (🥉12 · ⭐ 370) - 用于自然语言生成的分析工具包。MIT - [GitHub](https://github.com/facebookresearch/vizseq) (👨‍💻 3 · 🔀 43 · 📦 3 · 📋 15 - 40% open · ⏱️ 02.09.2021): @@ -2595,7 +2595,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install vizseq ```
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textvec (🥉12 · ⭐ 180 · 💤) - Text vectorization tool to outperform TFIDF for classification.. MIT +
textvec (🥉12 · ⭐ 180 · 💤) - 胜过TF-IDF文本向量化工具。MIT - [GitHub](https://github.com/textvec/textvec) (👨‍💻 4 · 🔀 21 · 📦 4 · 📋 9 - 33% open · ⏱️ 03.12.2020): @@ -2607,7 +2607,7 @@ _Libraries for processing, cleaning, manipulating, and analyzing text data as we pip install textvec ```
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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 · 🔀 40 · 📦 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。_ -
imgaug (🥇32 · ⭐ 12K · 💀) - Image augmentation for machine learning experiments. MIT +
imgaug (🥇32 · ⭐ 12K · 💀) - 用于机器学习实验的图像增强。MIT - [GitHub](https://github.com/aleju/imgaug) (👨‍💻 36 · 🔀 2.2K · 📦 8.4K · 📋 480 - 53% open · ⏱️ 01.06.2020): @@ -2643,7 +2643,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imgaug ```
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Albumentations (🥇32 · ⭐ 9.3K) - Fast image augmentation library and an easy-to-use wrapper.. MIT +
Albumentations (🥇32 · ⭐ 9.3K) - 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) (👨‍💻 98 · 🔀 1.2K · 📦 6K · 📋 540 - 39% open · ⏱️ 14.12.2021): @@ -2659,7 +2659,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge albumentations ```
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MoviePy (🥇32 · ⭐ 8.8K) - Video editing with Python. MIT +
MoviePy (🥇32 · ⭐ 8.8K) - 使用Python进行视频编辑。MIT - [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 140 · 🔀 1.1K · 📦 12K · 📋 1.1K - 29% open · ⏱️ 12.11.2021): @@ -2675,7 +2675,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge moviepy ```
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PyTorch Image Models (🥇30 · ⭐ 15K) - PyTorch image models, scripts, pretrained weights --.. Apache-2 +
PyTorch Image Models (🥇30 · ⭐ 15K) - PyTorch图像模型，脚本，预训练权重。Apache-2 - [GitHub](https://github.com/rwightman/pytorch-image-models) (👨‍💻 62 · 🔀 2.4K · 📥 780K · 📦 1.6K · 📋 420 - 10% open · ⏱️ 14.12.2021): @@ -2683,7 +2683,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/rwightman/pytorch-image-models ```
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imageio (🥇30 · ⭐ 960) - Python library for reading and writing image data. BSD-2 +
imageio (🥇30 · ⭐ 960) - 用于读取和写入图像数据的Python库。BSD-2 - [GitHub](https://github.com/imageio/imageio) (👨‍💻 83 · 🔀 190 · 📥 45 · 📦 53K · 📋 400 - 17% open · ⏱️ 08.12.2021): @@ -2699,7 +2699,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imageio ```
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GluonCV (🥈29 · ⭐ 5K) - Gluon CV Toolkit. Apache-2 +
GluonCV (🥈29 · ⭐ 5K) - Gluon CV工具包。Apache-2 - [GitHub](https://github.com/dmlc/gluon-cv) (👨‍💻 110 · 🔀 1.1K · 📦 640 · 📋 790 - 6% open · ⏱️ 14.11.2021): @@ -2711,7 +2711,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install gluoncv ```
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scikit-image (🥈29 · ⭐ 4.7K) - Image processing in Python. ❗Unlicensed +
scikit-image (🥈29 · ⭐ 4.7K) - Python中的图像处理。❗Unlicensed - [GitHub](https://github.com/scikit-image/scikit-image) (👨‍💻 540 · 🔀 1.8K · 📦 88K · 📋 2.2K - 6% open · ⏱️ 15.12.2021): @@ -2727,7 +2727,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge scikit-image ```
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ImageHash (🥈29 · ⭐ 2.2K) - A Python Perceptual Image Hashing Module. BSD-2 +
ImageHash (🥈29 · ⭐ 2.2K) - Python感知图像哈希模块。BSD-2 - [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 20 · 🔀 280 · 📦 3.9K · 📋 100 - 10% open · ⏱️ 07.09.2021): @@ -2743,7 +2743,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imagehash ```
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imutils (🥈28 · ⭐ 3.9K · 💤) - A series of convenience functions to make basic image processing.. MIT +
imutils (🥈28 · ⭐ 3.9K · 💤) - 图像处理库。MIT - [GitHub](https://github.com/PyImageSearch/imutils) (👨‍💻 20 · 🔀 930 · 📦 21K · 📋 160 - 52% open · ⏱️ 15.01.2021): @@ -2759,7 +2759,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge imutils ```
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MMDetection (🥈27 · ⭐ 18K) - OpenMMLab Detection Toolbox and Benchmark. Apache-2 +
MMDetection (🥈27 · ⭐ 18K) - OpenMMLab检测工具箱。Apache-2 - [GitHub](https://github.com/open-mmlab/mmdetection) (👨‍💻 290 · 🔀 5.8K · 📦 200 · 📋 4.9K - 7% open · ⏱️ 16.12.2021): @@ -2767,7 +2767,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/open-mmlab/mmdetection ```
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glfw (🥈27 · ⭐ 8.4K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. ❗️Zlib +
glfw (🥈27 · ⭐ 8.4K) - 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 · 🔀 3K · 📥 2.6M · 📦 1 · 📋 1.5K - 27% open · ⏱️ 14.12.2021): @@ -2783,7 +2783,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge glfw ```
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Kornia (🥈27 · ⭐ 5.6K) - Open Source Differentiable Computer Vision Library for.. ❗Unlicensed +
Kornia (🥈27 · ⭐ 5.6K) - PyTorch的开源可微分计算机视觉库。❗Unlicensed - [GitHub](https://github.com/kornia/kornia) (👨‍💻 140 · 🔀 540 · 📥 160 · 📦 830 · 📋 490 - 22% open · ⏱️ 12.12.2021): @@ -2795,7 +2795,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install kornia ```
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Wand (🥈27 · ⭐ 1.1K) - The ctypes-based simple ImageMagick binding for Python. MIT +
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): @@ -2807,7 +2807,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install wand ```
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detectron2 (🥈26 · ⭐ 19K) - Detectron2 is FAIR's next-generation platform for object.. Apache-2 +
detectron2 (🥈26 · ⭐ 19K) - Detectron2是Facebook FAIR的高级目标检测平台。Apache-2 - [GitHub](https://github.com/facebookresearch/detectron2) (👨‍💻 200 · 🔀 4.9K · 📦 440 · 📋 2.8K - 4% open · ⏱️ 08.12.2021): @@ -2819,7 +2819,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge detectron2 ```
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InsightFace (🥈26 · ⭐ 11K) - Face Analysis Project on MXNet and PyTorch. MIT +
InsightFace (🥈26 · ⭐ 11K) - MXNet和PyTorch上的人脸分析项目。MIT - [GitHub](https://github.com/deepinsight/insightface) (👨‍💻 31 · 🔀 3.5K · 📦 120 · 📋 1.8K - 53% open · ⏱️ 03.12.2021): @@ -2831,7 +2831,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install insightface ```
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imageai (🥈26 · ⭐ 6.7K · 💤) - A python library built to empower developers to build applications.. MIT +
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): @@ -2843,7 +2843,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install imageai ```
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Face Recognition (🥈25 · ⭐ 43K) - The world's simplest facial recognition api for.. MIT +
Face Recognition (🥈25 · ⭐ 43K) - 简单的面部识别API。MIT - [GitHub](https://github.com/ageitgey/face_recognition) (👨‍💻 47 · 🔀 12K · 📥 450 · 📋 1.2K - 53% open · ⏱️ 14.06.2021): @@ -2855,7 +2855,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install face_recognition ```
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Pillow (🥈24 · ⭐ 9.2K · 📉) - The friendly PIL fork (Python Imaging Library). ❗️PIL +
Pillow (🥈24 · ⭐ 9.2K · 📉) - 友好的PIL分支（Python Imaging Library）。❗️PIL - [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 380 · 🔀 1.6K · 📋 2.4K - 5% open · ⏱️ 15.12.2021): @@ -2871,7 +2871,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge pillow ```
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facenet-pytorch (🥈24 · ⭐ 2.6K) - Pretrained Pytorch face detection (MTCNN) and recognition.. MIT +
facenet-pytorch (🥈24 · ⭐ 2.6K) - 预训练的Pytorch人脸检测（MTCNN）和识别。MIT - [GitHub](https://github.com/timesler/facenet-pytorch) (👨‍💻 14 · 🔀 550 · 📥 180K · 📦 570 · 📋 140 - 36% open · ⏱️ 13.12.2021): @@ -2883,7 +2883,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install facenet-pytorch ```
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torchvision (🥈23 · ⭐ 11K) - Datasets, Transforms and Models specific to Computer Vision. BSD-3 +
torchvision (🥈23 · ⭐ 11K) - 计算机视觉的数据集，转换和模型。BSD-3 - [GitHub](https://github.com/pytorch/vision) (👨‍💻 440 · 🔀 5.3K · 📋 2K - 23% open · ⏱️ 16.12.2021): @@ -2899,7 +2899,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge torchvision ```
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mtcnn (🥈23 · ⭐ 1.7K) - MTCNN face detection implementation for TensorFlow, as a PIP package. MIT +
mtcnn (🥈23 · ⭐ 1.7K) - TensorFlow的MTCNN人脸检测实现。MIT - [GitHub](https://github.com/ipazc/mtcnn) (👨‍💻 15 · 🔀 430 · 📦 1.7K · 📋 97 - 61% open · ⏱️ 09.07.2021): @@ -2911,7 +2911,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install mtcnn ```
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Image Deduplicator (🥉22 · ⭐ 3.9K · 💀) - Finding duplicate images made easy!. Apache-2 +
Image Deduplicator (🥉22 · ⭐ 3.9K · 💀) - 图像查重。Apache-2 - [GitHub](https://github.com/idealo/imagededup) (👨‍💻 10 · 🔀 330 · 📦 21 · 📋 87 - 32% open · ⏱️ 23.11.2020): @@ -2923,7 +2923,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install imagededup ```
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Image Super-Resolution (🥉22 · ⭐ 3.3K) - Super-scale your images and run experiments with.. Apache-2 +
Image Super-Resolution (🥉22 · ⭐ 3.3K) - 图像超精度变换。Apache-2 - [GitHub](https://github.com/idealo/image-super-resolution) (👨‍💻 10 · 🔀 570 · 📦 68 · 📋 190 - 42% open · ⏱️ 02.06.2021): @@ -2939,7 +2939,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well docker pull idealo/image-super-resolution-gpu ```
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Torch Points 3D (🥉22 · ⭐ 1.6K) - Pytorch framework for doing deep learning on point clouds. BSD-3 +
Torch Points 3D (🥉22 · ⭐ 1.6K) - 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 · 🔀 260 · 📦 4 · 📋 300 - 29% open · ⏱️ 10.12.2021): @@ -2951,7 +2951,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install torch-points3d ```
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chainercv (🥉22 · ⭐ 1.5K · 💀) - ChainerCV: a Library for Deep Learning in Computer Vision. MIT +
chainercv (🥉22 · ⭐ 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 · 🔀 310 · 📦 270 · 📋 200 - 18% open · ⏱️ 07.01.2020): @@ -2963,7 +2963,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install chainercv ```
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mahotas (🥉22 · ⭐ 720) - Computer Vision in Python. ❗Unlicensed +
mahotas (🥉22 · ⭐ 720) - Python中的计算机视觉。❗Unlicensed - [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 32 · 🔀 140 · 📦 720 · 📋 76 - 19% open · ⏱️ 07.12.2021): @@ -2991,7 +2991,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install segmentation_models ```
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PyTorch3D (🥉20 · ⭐ 5.5K) - PyTorch3D is FAIR's library of reusable components for.. ❗Unlicensed +
PyTorch3D (🥉20 · ⭐ 5.5K) - PyTorch3D是FAIR的深度学习可重用组件库。❗Unlicensed - [GitHub](https://github.com/facebookresearch/pytorch3d) (👨‍💻 75 · 🔀 750 · 📦 130 · 📋 840 - 9% open · ⏱️ 15.12.2021): @@ -3007,7 +3007,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c pytorch3d pytorch3d ```
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Augmentor (🥉20 · ⭐ 4.6K) - Image augmentation library in Python for machine learning. MIT +
Augmentor (🥉20 · ⭐ 4.6K) - Python中的图像增强库，用于机器学习。MIT - [GitHub](https://github.com/mdbloice/Augmentor) (👨‍💻 22 · 🔀 810 · 📦 390 · 📋 180 - 61% open · ⏱️ 15.10.2021): @@ -3019,7 +3019,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install Augmentor ```
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vidgear (🥉20 · ⭐ 2K) - High-performance cross-platform Video Processing Python framework.. Apache-2 +
vidgear (🥉20 · ⭐ 2K) - 高性能跨平台视频处理Python框架。Apache-2 - [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 9 · 🔀 150 · 📥 500 · 📦 160 · 📋 190 - 1% open · ⏱️ 05.12.2021): @@ -3031,7 +3031,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install vidgear ```
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Classy Vision (🥉20 · ⭐ 1.4K) - An end-to-end PyTorch framework for image and video.. MIT +
Classy Vision (🥉20 · ⭐ 1.4K) - 用于图像和视频的端到端PyTorch框架。MIT - [GitHub](https://github.com/facebookresearch/ClassyVision) (👨‍💻 66 · 🔀 240 · 📋 74 - 17% open · ⏱️ 09.12.2021): @@ -3047,7 +3047,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge classy_vision ```
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CellProfiler (🥉20 · ⭐ 630) - An open-source application for biological image analysis. ❗Unlicensed +
CellProfiler (🥉20 · ⭐ 630) - 生物图像分析的开源应用程序。❗Unlicensed - [GitHub](https://github.com/CellProfiler/CellProfiler) (👨‍💻 120 · 🔀 290 · 📥 2K · 📦 5 · 📋 3K - 6% open · ⏱️ 05.11.2021): @@ -3059,7 +3059,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install cellprofiler ```
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Caer (🥉20 · ⭐ 580) - A lightweight Computer Vision library. Scale your models, not boilerplate. MIT +
Caer (🥉20 · ⭐ 580) - 轻量级的计算机视觉库。MIT - [GitHub](https://github.com/jasmcaus/caer) (👨‍💻 8 · 🔀 63 · 📥 19 · 📋 15 - 13% open · ⏱️ 13.10.2021): @@ -3071,7 +3071,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install caer ```
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pyvips (🥉20 · ⭐ 370) - python binding for libvips using cffi. MIT +
pyvips (🥉20 · ⭐ 370) - 使用cffi的libvips的python接口。MIT - [GitHub](https://github.com/libvips/pyvips) (👨‍💻 12 · 🔀 32 · 📦 250 · 📋 260 - 36% open · ⏱️ 15.12.2021): @@ -3087,7 +3087,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well conda install -c conda-forge pyvips ```
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vit-pytorch (🥉19 · ⭐ 7.2K) - Implementation of Vision Transformer, a simple way to.. MIT +
vit-pytorch (🥉19 · ⭐ 7.2K) - 实现视觉transformer，一种简单的方法。MIT - [GitHub](https://github.com/lucidrains/vit-pytorch) (👨‍💻 12 · 🔀 1.1K · 📦 59 · 📋 150 - 47% open · ⏱️ 04.12.2021): @@ -3099,7 +3099,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install vit-pytorch ```
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PaddleDetection (🥉19 · ⭐ 5.8K) - Object detection and instance segmentation toolkit.. Apache-2 +
PaddleDetection (🥉19 · ⭐ 5.8K) - 对象检测和实例分割工具箱。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (👨‍💻 75 · 🔀 1.4K · 📦 6 · 📋 2.7K - 28% open · ⏱️ 09.12.2021): @@ -3107,7 +3107,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/PaddlePaddle/PaddleDetection ```
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Face Alignment (🥉19 · ⭐ 5.4K) - 2D and 3D Face alignment library build using pytorch. BSD-3 +
Face Alignment (🥉19 · ⭐ 5.4K) - 使用pytorch构建2D和3D人脸对齐库。BSD-3 - [GitHub](https://github.com/1adrianb/face-alignment) (👨‍💻 23 · 🔀 1.1K · 📋 260 - 18% open · ⏱️ 04.08.2021): @@ -3119,7 +3119,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install face-alignment ```
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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 · 📥 12K · 📦 39 · 📋 180 - 28% open · ⏱️ 07.01.2020): @@ -3131,7 +3131,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install luminoth ```
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lightly (🥉19 · ⭐ 1.3K) - A python library for self-supervised learning on images. MIT +
lightly (🥉19 · ⭐ 1.3K) - 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) (👨‍💻 14 · 🔀 86 · 📦 25 · 📋 290 - 21% open · ⏱️ 16.12.2021): @@ -3143,7 +3143,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install lightly ```
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MMF (🥉18 · ⭐ 4.7K) - A modular framework for vision & language multimodal research from.. BSD-3 +
MMF (🥉18 · ⭐ 4.7K) - 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) (👨‍💻 89 · 🔀 780 · 📦 10 · 📋 570 - 26% open · ⏱️ 14.12.2021): @@ -3155,7 +3155,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install mmf ```
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tensorflow-graphics (🥉17 · ⭐ 2.6K) - TensorFlow Graphics: Differentiable Graphics Layers.. Apache-2 +
tensorflow-graphics (🥉17 · ⭐ 2.6K) - TensorFlow图神经网络：可微分的图layerApache-2 - [GitHub](https://github.com/tensorflow/graphics) (👨‍💻 34 · 🔀 320 · 📋 160 - 43% open · ⏱️ 06.12.2021): @@ -3167,7 +3167,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install tensorflow-graphics ```
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Norfair (🥉17 · ⭐ 1.2K) - Lightweight Python library for adding real-time 2D object tracking to.. BSD-3 +
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 - [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 9 · 🔀 88 · 📋 39 - 20% open · ⏱️ 01.10.2021): @@ -3187,7 +3187,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/facebookresearch/detr ```
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opencv-python (🥉16 · ⭐ 2.4K) - Automated CI toolchain to produce precompiled opencv-.. ❗Unlicensed +
opencv-python (🥉16 · ⭐ 2.4K) - 自动化的CI工具链可生成预编译的opencv-python。❗Unlicensed - [GitHub](https://github.com/opencv/opencv-python) (👨‍💻 36 · 🔀 470 · 📋 490 - 5% open · ⏱️ 16.12.2021): @@ -3199,7 +3199,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install opencv-python ```
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Pillow-SIMD (🥉16 · ⭐ 1.7K · 💀) - The friendly PIL fork. ❗️PIL +
Pillow-SIMD (🥉16 · ⭐ 1.7K · 💀) - 友好的PIL fork。❗️PIL - [GitHub](https://github.com/uploadcare/pillow-simd) (👨‍💻 310 · 🔀 70 · 📦 500 · 📋 69 - 17% open · ⏱️ 02.06.2020): @@ -3211,7 +3211,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install pillow-simd ```
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nude.py (🥉16 · ⭐ 820 · 💀) - Nudity detection with Python. MIT +
nude.py (🥉16 · ⭐ 820 · 💀) - 使用Python进行裸露检测。MIT - [GitHub](https://github.com/hhatto/nude.py) (👨‍💻 12 · 🔀 130 · 📦 1.3K · 📋 10 - 70% open · ⏱️ 23.11.2020): @@ -3223,7 +3223,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well pip install nudepy ```
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PySlowFast (🥉15 · ⭐ 4.4K) - PySlowFast: video understanding codebase from FAIR for.. Apache-2 +
PySlowFast (🥉15 · ⭐ 4.4K) - PySlowFast：来自FAIR的视频理解代码库。Apache-2 - [GitHub](https://github.com/facebookresearch/SlowFast) (👨‍💻 25 · 🔀 820 · 📦 5 · 📋 470 - 49% open · ⏱️ 28.10.2021): @@ -3231,7 +3231,7 @@ _Libraries for image & video processing, manipulation, and augmentation as well git clone https://github.com/facebookresearch/SlowFast ```
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pycls (🥉15 · ⭐ 1.8K) - Codebase for Image Classification Research, written in PyTorch. MIT +
pycls (🥉15 · ⭐ 1.8K) - 用PyTorch编写的图像分类研究代码库。MIT - [GitHub](https://github.com/facebookresearch/pycls) (👨‍💻 13 · 🔀 200 · 📦 4 · 📋 77 - 28% open · ⏱️ 19.08.2021): @@ -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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image-match (🥉14 · ⭐ 2.7K) - Quickly search over billions of images. ❗Unlicensed +
image-match (🥉14 · ⭐ 2.7K) - 快速搜索数十亿张图像。❗Unlicensed - [GitHub](https://github.com/ProvenanceLabs/image-match) (👨‍💻 19 · 🔀 370 · 📋 99 - 51% open · ⏱️ 21.09.2021): @@ -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 · ⭐ 10K) - Network Analysis in Python. ❗Unlicensed +
networkx (🥇32 · ⭐ 10K) - Python中的网络分析。❗Unlicensed - [GitHub](https://github.com/networkx/networkx) (👨‍💻 560 · 🔀 2.4K · 📥 57 · 📦 93K · 📋 2.6K - 6% open · ⏱️ 13.12.2021): @@ -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 (🥇28 · ⭐ 8.6K) - Python package built to ease deep learning on graph, on top of existing.. Apache-2 +
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 - [GitHub](https://github.com/dmlc/dgl) (👨‍💻 180 · 🔀 1.9K · 📋 1.3K - 21% open · ⏱️ 15.12.2021): @@ -3287,7 +3287,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install dgl ```
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igraph (🥇27 · ⭐ 900) - Python interface for igraph. ❗️GPL-2.0 +
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): @@ -3303,7 +3303,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge igraph ```
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PyTorch Geometric (🥈23 · ⭐ 13K) - Geometric Deep Learning Extension Library for PyTorch. MIT +
PyTorch Geometric (🥈23 · ⭐ 13K) - PyTorch的几何深度学习扩展库。MIT - [GitHub](https://github.com/pyg-team/pytorch_geometric) (👨‍💻 230 · 🔀 2.3K · 📋 2.3K - 37% open · ⏱️ 16.12.2021): @@ -3315,7 +3315,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-geometric ```
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Karate Club (🥈23 · ⭐ 1.5K) - Karate Club: An API Oriented Open-source Python Framework for.. ❗️GPL-3.0 +
Karate Club (🥈23 · ⭐ 1.5K) - 面向API的开源Python框架。❗️GPL-3.0 - [GitHub](https://github.com/benedekrozemberczki/karateclub) (👨‍💻 13 · 🔀 170 · 📦 65 · 📋 65 - 1% open · ⏱️ 21.11.2021): @@ -3327,7 +3327,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install karateclub ```
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StellarGraph (🥈22 · ⭐ 2.2K) - StellarGraph - Machine Learning on Graphs. Apache-2 +
StellarGraph (🥈22 · ⭐ 2.2K) - StellarGraph-图机器学习库。Apache-2 - [GitHub](https://github.com/stellargraph/stellargraph) (👨‍💻 36 · 🔀 320 · 📦 100 · 📋 980 - 25% 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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ogb (🥈22 · ⭐ 1.2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. MIT +
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 - [GitHub](https://github.com/snap-stanford/ogb) (👨‍💻 18 · 🔀 240 · 📦 190 · ⏱️ 06.12.2021): @@ -3351,7 +3351,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install ogb ```
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Spektral (🥈21 · ⭐ 1.9K) - Graph Neural Networks with Keras and Tensorflow 2. MIT +
Spektral (🥈21 · ⭐ 1.9K) - 使用Keras和Tensorflow 2的图神经网络。MIT - [GitHub](https://github.com/danielegrattarola/spektral) (👨‍💻 19 · 🔀 260 · 📦 87 · 📋 200 - 18% open · ⏱️ 26.10.2021): @@ -3363,7 +3363,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install spektral ```
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Node2Vec (🥈21 · ⭐ 820) - Implementation of the node2vec algorithm. MIT +
Node2Vec (🥈21 · ⭐ 820) - node2vec算法的实现。MIT - [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 9 · 🔀 180 · 📋 69 - 1% open · ⏱️ 09.10.2021): @@ -3391,7 +3391,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-geometric-temporal ```
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Paddle Graph Learning (🥈20 · ⭐ 1.2K) - Paddle Graph Learning (PGL) is an efficient and.. Apache-2 +
Paddle Graph Learning (🥈20 · ⭐ 1.2K) - paddle图机器学习。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PGL) (👨‍💻 21 · 🔀 190 · 📦 23 · 📋 96 - 35% open · ⏱️ 16.12.2021): @@ -3403,7 +3403,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pgl ```
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PyKEEN (🥈20 · ⭐ 630) - A Python library for learning and evaluating knowledge graph embeddings. MIT +
PyKEEN (🥈20 · ⭐ 630) - 一个用于学习和评估知识图嵌入的Python库。MIT - [GitHub](https://github.com/pykeen/pykeen) (👨‍💻 24 · 🔀 90 · 📥 92 · 📋 300 - 31% open · ⏱️ 13.12.2021): @@ -3415,7 +3415,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pykeen ```
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pygal (🥉19 · ⭐ 2.4K) - PYthon svg GrAph plotting Library. ❗️LGPL-3.0 +
pygal (🥉19 · ⭐ 2.4K) - PYthon svg GrAph绘图库。❗️LGPL-3.0 - [GitHub](https://github.com/Kozea/pygal) (👨‍💻 71 · 🔀 380 · 📋 400 - 38% open · ⏱️ 24.11.2021): @@ -3431,7 +3431,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge pygal ```
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DeepWalk (🥉19 · ⭐ 2.4K · 💀) - DeepWalk - Deep Learning for Graphs. ❗️GPL-3.0 +
DeepWalk (🥉19 · ⭐ 2.4K · 💀) - DeepWalk-图的深度学习。❗️GPL-3.0 - [GitHub](https://github.com/phanein/deepwalk) (👨‍💻 10 · 🔀 780 · 📦 46 · 📋 100 - 23% open · ⏱️ 02.04.2020): @@ -3443,7 +3443,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install deepwalk ```
-
AmpliGraph (🥉18 · ⭐ 1.7K · 💤) - Python library for Representation Learning on Knowledge.. Apache-2 +
AmpliGraph (🥉18 · ⭐ 1.7K · 💤) - 用于知识表示学习的Python库。Apache-2 - [GitHub](https://github.com/Accenture/AmpliGraph) (👨‍💻 19 · 🔀 190 · 📦 16 · 📋 200 - 9% open · ⏱️ 25.05.2021): @@ -3455,7 +3455,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install ampligraph ```
-
pyRDF2Vec (🥉17 · ⭐ 140) - Python Implementation and Extension of RDF2Vec. MIT +
pyRDF2Vec (🥉17 · ⭐ 140) - RDF2Vec的Python实现和扩展。MIT - [GitHub](https://github.com/IBCNServices/pyRDF2Vec) (👨‍💻 5 · 🔀 24 · 📋 44 - 6% open · ⏱️ 08.11.2021): @@ -3467,7 +3467,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install pyrdf2vec ```
-
PyTorch-BigGraph (🥉16 · ⭐ 3K) - Generate embeddings from large-scale graph-structured.. ❗Unlicensed +
PyTorch-BigGraph (🥉16 · ⭐ 3K) - 从大型图网络结构生成embedding嵌入。❗Unlicensed - [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (👨‍💻 24 · 🔀 400 · 📥 120 · 📋 170 - 30% open · ⏱️ 27.10.2021): @@ -3479,7 +3479,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torchbiggraph ```
-
GraphEmbedding (🥉16 · ⭐ 2.5K · 💀) - Implementation and experiments of graph embedding.. MIT +
GraphEmbedding (🥉16 · ⭐ 2.5K · 💀) - 图嵌入算法的实现和实验。MIT - [GitHub](https://github.com/shenweichen/GraphEmbedding) (👨‍💻 8 · 🔀 740 · 📦 12 · 📋 52 - 73% open · ⏱️ 18.10.2020): @@ -3487,7 +3487,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/shenweichen/GraphEmbedding ```
-
kglib (🥉16 · ⭐ 480) - Grakn Knowledge Graph Library (ML R&D). Apache-2 +
kglib (🥉16 · ⭐ 480) - Grakn知识图库（ML R＆D）。Apache-2 - [GitHub](https://github.com/vaticle/kglib) (👨‍💻 7 · 🔀 86 · 📥 210 · 📋 58 - 15% open · ⏱️ 22.10.2021): @@ -3499,7 +3499,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install grakn-kglib ```
-
torch-cluster (🥉15 · ⭐ 450) - PyTorch Extension Library of Optimized Graph Cluster.. MIT +
torch-cluster (🥉15 · ⭐ 450) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_cluster) (👨‍💻 19 · 🔀 84 · 📋 91 - 9% open · ⏱️ 14.12.2021): @@ -3511,7 +3511,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install torch-cluster ```
-
DeepGraph (🥉15 · ⭐ 250) - Analyze Data with Pandas-based Networks. Documentation:. ❗Unlicensed +
DeepGraph (🥉15 · ⭐ 250) - 使用基于pandas的网络分析数据。❗Unlicensed - [GitHub](https://github.com/deepgraph/deepgraph) (👨‍💻 2 · 🔀 36 · 📦 2 · 📋 14 - 64% open · ⏱️ 14.06.2021): @@ -3527,7 +3527,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas conda install -c conda-forge deepgraph ```
-
Euler (🥉14 · ⭐ 2.7K · 💀) - A distributed graph deep learning framework. Apache-2 +
Euler (🥉14 · ⭐ 2.7K · 💀) - 分布式图深度学习框架。Apache-2 - [GitHub](https://github.com/alibaba/euler) (👨‍💻 3 · 🔀 540 · 📋 320 - 67% open · ⏱️ 29.07.2020): @@ -3539,7 +3539,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install euler-gl ```
-
AutoGL (🥉14 · ⭐ 720) - An autoML framework & toolkit for machine learning on graphs. Apache-2 +
AutoGL (🥉14 · ⭐ 720) - 用于图上机器学习的autoML框架和工具包。Apache-2 - [GitHub](https://github.com/THUMNLab/AutoGL) (👨‍💻 9 · 🔀 72 · 📋 14 - 21% open · ⏱️ 23.11.2021): @@ -3551,7 +3551,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install auto-graph-learning ```
-
graph-nets (🥉13 · ⭐ 5K · 💤) - Build Graph Nets in Tensorflow. Apache-2 +
graph-nets (🥉13 · ⭐ 5K · 💤) - 在Tensorflow中构建图神经网络。Apache-2 - [GitHub](https://github.com/deepmind/graph_nets) (👨‍💻 10 · 🔀 760 · 📋 120 - 2% open · ⏱️ 04.12.2020): @@ -3563,7 +3563,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install graph-nets ```
-
GraphSAGE (🥉13 · ⭐ 2.6K · 💀) - Representation learning on large graphs using stochastic.. MIT +
GraphSAGE (🥉13 · ⭐ 2.6K · 💀) - 大型图上的表示学习。MIT - [GitHub](https://github.com/williamleif/GraphSAGE) (👨‍💻 9 · 🔀 720 · 📋 150 - 60% open · ⏱️ 19.09.2018): @@ -3571,7 +3571,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/williamleif/GraphSAGE ```
-
OpenNE (🥉13 · ⭐ 1.5K · 💀) - An Open-Source Package for Network Embedding (NE). MIT +
OpenNE (🥉13 · ⭐ 1.5K · 💀) - 神经关系提取（NRE）的开源软件包。MIT - [GitHub](https://github.com/thunlp/OpenNE) (👨‍💻 10 · 🔀 470 · 📋 96 - 2% open · ⏱️ 12.08.2019): @@ -3579,7 +3579,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas git clone https://github.com/thunlp/OpenNE ```
-
Sematch (🥉13 · ⭐ 370 · 💀) - semantic similarity framework for knowledge graph. Apache-2 +
Sematch (🥉13 · ⭐ 370 · 💀) - 知识图的语义相似性框架。Apache-2 - [GitHub](https://github.com/gsi-upm/sematch) (👨‍💻 5 · 🔀 100 · 📦 29 · 📋 31 - 38% open · ⏱️ 27.03.2019): @@ -3591,7 +3591,7 @@ _Libraries for graph processing, clustering, embedding, and machine learning tas pip install sematch ```
-
GraphVite (🥉12 · ⭐ 980 · 💤) - GraphVite: A General and High-performance Graph Embedding.. Apache-2 +
GraphVite (🥉12 · ⭐ 980 · 💤) - GraphVite：通用的高性能图形嵌入系统。Apache-2 - [GitHub](https://github.com/DeepGraphLearning/graphvite) (🔀 130 · 📋 91 - 38% 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 · ⭐ 2.8K · 💤) - An Open-Source Package for Knowledge Embedding (KE). ❗Unlicensed +
OpenKE (🥉11 · ⭐ 2.8K · 💤) - 神经关系提取（NRE）的开源软件包。❗Unlicensed - [GitHub](https://github.com/thunlp/OpenKE) (👨‍💻 10 · 🔀 830 · 📋 330 - 5% 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 · ⭐ 19K · 📈) - DeepSpeech is an open source embedded (offline, on-.. MPL-2.0 +
DeepSpeech (🥇30 · ⭐ 19K · 📈) - DeepSpeech是开源的语音转文本引擎。MPL-2.0 - [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 160 · 🔀 3.2K · 📥 770K · 📦 640 · 📋 2K - 5% open · ⏱️ 17.11.2021): @@ -3631,7 +3631,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install deepspeech ```
-
Pydub (🥇30 · ⭐ 5.8K) - Manipulate audio with a simple and easy high level interface. MIT +
Pydub (🥇30 · ⭐ 5.8K) - 使用简单易用的高级界面处理音频。MIT - [GitHub](https://github.com/jiaaro/pydub) (👨‍💻 90 · 🔀 770 · 📦 9.9K · 📋 450 - 43% open · ⏱️ 08.06.2021): @@ -3647,7 +3647,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge pydub ```
-
audioread (🥇27 · ⭐ 380) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio decoding.. MIT +
audioread (🥇27 · ⭐ 380) - 跨库（GStreamer + Core Audio + MAD + FFmpeg）音频编解码。MIT - [GitHub](https://github.com/beetbox/audioread) (👨‍💻 21 · 🔀 89 · 📦 6.9K · 📋 75 - 38% open · ⏱️ 03.12.2021): @@ -3663,7 +3663,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge audioread ```
-
Magenta (🥈26 · ⭐ 17K) - Magenta: Music and Art Generation with Machine Intelligence. Apache-2 +
Magenta (🥈26 · ⭐ 17K) - 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 · 📦 330 · 📋 860 - 33% open · ⏱️ 30.06.2021): @@ -3675,7 +3675,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install magenta ```
-
aubio (🥈26 · ⭐ 2.6K · 💤) - a library for audio and music analysis. ❗️GPL-3.0 +
aubio (🥈26 · ⭐ 2.6K · 💤) - 用于音频和音乐分析的库。❗️GPL-3.0 - [GitHub](https://github.com/aubio/aubio) (👨‍💻 24 · 🔀 330 · 📦 280 · 📋 300 - 40% open · ⏱️ 19.01.2021): @@ -3691,7 +3691,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge aubio ```
-
torchaudio (🥈25 · ⭐ 1.5K) - Data manipulation and transformation for audio signal.. BSD-2 +
torchaudio (🥈25 · ⭐ 1.5K) - 音频信号的数据处理和转换。BSD-2 - [GitHub](https://github.com/pytorch/audio) (👨‍💻 140 · 🔀 360 · 📋 550 - 20% open · ⏱️ 15.12.2021): @@ -3703,7 +3703,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install torchaudio ```
-
spleeter (🥈24 · ⭐ 18K) - Deezer source separation library including pretrained models. MIT +
spleeter (🥈24 · ⭐ 18K) - Deezer源分离库，包括预训练的模型。MIT - [GitHub](https://github.com/deezer/spleeter) (👨‍💻 18 · 🔀 1.9K · 📥 1.3M · 📋 600 - 17% open · ⏱️ 08.12.2021): @@ -3719,7 +3719,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge spleeter ```
-
Essentia (🥈24 · ⭐ 2K) - C++ library for audio and music analysis, description and.. ❗️AGPL-3.0 +
Essentia (🥈24 · ⭐ 2K) - C++库，用于音频和音乐分析，描述等。❗️AGPL-3.0 - [GitHub](https://github.com/MTG/essentia) (👨‍💻 73 · 🔀 420 · 📦 260 · 📋 920 - 34% open · ⏱️ 16.12.2021): @@ -3731,7 +3731,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install essentia ```
-
espnet (🥈23 · ⭐ 4.5K) - End-to-End Speech Processing Toolkit. Apache-2 +
espnet (🥈23 · ⭐ 4.5K) - 端到端语音处理工具包。Apache-2 - [GitHub](https://github.com/espnet/espnet) (👨‍💻 210 · 🔀 1.3K · 📥 74 · 📦 25 · 📋 1.6K - 14% open · ⏱️ 16.12.2021): @@ -3743,7 +3743,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install espnet ```
-
kapre (🥈23 · ⭐ 790) - kapre: Keras Audio Preprocessors. MIT +
kapre (🥈23 · ⭐ 790) - kapre：Keras音频预处理器。MIT - [GitHub](https://github.com/keunwoochoi/kapre) (👨‍💻 13 · 🔀 140 · 📥 19 · 📦 1.2K · 📋 93 - 11% open · ⏱️ 14.11.2021): @@ -3755,7 +3755,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install kapre ```
-
SpeechRecognition (🥉22 · ⭐ 6K) - Speech recognition module for Python, supporting.. ❗Unlicensed +
SpeechRecognition (🥉22 · ⭐ 6K) - 适用于Python的语音识别模块。❗Unlicensed - [GitHub](https://github.com/Uberi/speech_recognition) (👨‍💻 41 · 🔀 1.9K · 📋 490 - 43% open · ⏱️ 14.12.2021): @@ -3771,7 +3771,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as conda install -c conda-forge speechrecognition ```
-
librosa (🥉22 · ⭐ 4.9K) - Python library for audio and music analysis. ISC +
librosa (🥉22 · ⭐ 4.9K) - 用于音频和音乐分析的Python库。ISC - [GitHub](https://github.com/librosa/librosa) (👨‍💻 92 · 🔀 760 · 📋 920 - 3% open · ⏱️ 13.12.2021): @@ -3799,7 +3799,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install python_speech_features ```
-
Madmom (🥉21 · ⭐ 840) - Python audio and music signal processing library. ❗Unlicensed +
Madmom (🥉21 · ⭐ 840) - Python音频和音乐信号处理库。❗Unlicensed - [GitHub](https://github.com/CPJKU/madmom) (👨‍💻 20 · 🔀 150 · 📦 170 · 📋 240 - 21% open · ⏱️ 23.08.2021): @@ -3811,7 +3811,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install madmom ```
-
tinytag (🥉21 · ⭐ 500) - Read music meta data and length of MP3, OGG, OPUS, MP4, M4A, FLAC, WMA and.. MIT +
tinytag (🥉21 · ⭐ 500) - 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) (👨‍💻 20 · 🔀 82 · 📦 450 · 📋 85 - 11% open · ⏱️ 15.12.2021): @@ -3823,7 +3823,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install tinytag ```
-
pyAudioAnalysis (🥉20 · ⭐ 4.5K) - Python Audio Analysis Library: Feature Extraction,.. Apache-2 +
pyAudioAnalysis (🥉20 · ⭐ 4.5K) - Python音频分析库。Apache-2 - [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 25 · 🔀 1K · 📦 240 · 📋 280 - 58% open · ⏱️ 12.11.2021): @@ -3835,7 +3835,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install pyAudioAnalysis ```
-
Porcupine (🥉19 · ⭐ 2.6K) - On-device wake word detection powered by deep learning. Apache-2 +
Porcupine (🥉19 · ⭐ 2.6K) - 深度学习支持的设备上唤醒词识别。Apache-2 - [GitHub](https://github.com/Picovoice/porcupine) (👨‍💻 30 · 🔀 360 · 📦 6 · 📋 340 - 1% open · ⏱️ 15.12.2021): @@ -3847,7 +3847,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install pvporcupine ```
-
DDSP (🥉19 · ⭐ 2K) - DDSP: Differentiable Digital Signal Processing. Apache-2 +
DDSP (🥉19 · ⭐ 2K) - DDSP：微分数字信号处理。Apache-2 - [GitHub](https://github.com/magenta/ddsp) (👨‍💻 29 · 🔀 210 · 📦 18 · 📋 120 - 16% open · ⏱️ 06.12.2021): @@ -3859,7 +3859,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install ddsp ```
-
TTS (🥉18 · ⭐ 5.4K · 💤) - Deep learning for Text to Speech (Discussion forum:.. MPL-2.0 +
TTS (🥉18 · ⭐ 5.4K · 💤) - 文本到语音的深度学习。MPL-2.0 - [GitHub](https://github.com/mozilla/TTS) (👨‍💻 56 · 🔀 850 · 📥 1.5K · 📋 520 - 2% open · ⏱️ 12.02.2021): @@ -3867,7 +3867,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as git clone https://github.com/mozilla/TTS ```
-
Muda (🥉18 · ⭐ 200 · 💤) - A library for augmenting annotated audio data. ISC +
Muda (🥉18 · ⭐ 200 · 💤) - 用于扩充带注释的音频数据的库。ISC - [GitHub](https://github.com/bmcfee/muda) (👨‍💻 7 · 🔀 34 · 📦 13 · 📋 49 - 10% open · ⏱️ 03.05.2021): @@ -3879,7 +3879,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install muda ```
-
Dejavu (🥉17 · ⭐ 5.6K · 💀) - Audio fingerprinting and recognition in Python. MIT +
Dejavu (🥉17 · ⭐ 5.6K · 💀) - Python中的音频指纹识别。MIT - [GitHub](https://github.com/worldveil/dejavu) (👨‍💻 23 · 🔀 1.2K · 📦 19 · 📋 200 - 36% open · ⏱️ 03.06.2020): @@ -3891,7 +3891,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install PyDejavu ```
-
python-soundfile (🥉16 · ⭐ 430) - SoundFile is an audio library based on libsndfile, CFFI, and.. BSD-3 +
python-soundfile (🥉16 · ⭐ 430) - SoundFile是基于libsndfile，CFFI等的音频库。BSD-3 - [GitHub](https://github.com/bastibe/python-soundfile) (👨‍💻 23 · 🔀 57 · 📥 2.8K · 📋 160 - 37% open · ⏱️ 07.12.2021): @@ -3903,7 +3903,7 @@ _Libraries for audio analysis, manipulation, transformation, and extraction, as pip install soundfile ```
-
Julius (🥉15 · ⭐ 240) - Fast PyTorch based DSP for audio and 1D signals. MIT +
Julius (🥉15 · ⭐ 240) - 基于PyTorch的快速DSP，用于音频和一维信号。MIT - [GitHub](https://github.com/adefossez/julius) (👨‍💻 2 · 🔀 12 · 📦 49 · 📋 9 - 11% open · ⏱️ 20.10.2021): @@ -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 (🥇34 · ⭐ 9.3K) - WebGL2 powered geospatial visualization layers. MIT +
pydeck (🥇34 · ⭐ 9.3K) - WebGL2支持的地理空间可视化图层。MIT - [GitHub](https://github.com/visgl/deck.gl) (👨‍💻 180 · 🔀 1.6K · 📦 2.1K · 📋 2.3K - 4% open · ⏱️ 13.12.2021): @@ -3943,7 +3943,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra npm install deck.gl ```
-
geopy (🥇33 · ⭐ 3.5K) - Geocoding library for Python. MIT +
geopy (🥇33 · ⭐ 3.5K) - 适用于Python的地址解析库。MIT - [GitHub](https://github.com/geopy/geopy) (👨‍💻 120 · 🔀 540 · 📦 30K · 📋 250 - 9% open · ⏱️ 26.09.2021): @@ -3959,7 +3959,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopy ```
-
GeoPandas (🥇33 · ⭐ 2.9K) - Python tools for geographic data. BSD-3 +
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): @@ -3975,7 +3975,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geopandas ```
-
Shapely (🥈31 · ⭐ 2.6K) - Manipulation and analysis of geometric objects. BSD-3 +
Shapely (🥈31 · ⭐ 2.6K) - 操作和分析几何对象。BSD-3 - [GitHub](https://github.com/shapely/shapely) (👨‍💻 130 · 🔀 440 · 📦 25K · 📋 800 - 17% open · ⏱️ 13.12.2021): @@ -3991,7 +3991,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge shapely ```
-
Geocoder (🥈30 · ⭐ 1.4K · 💀) - Python Geocoder. MIT +
Geocoder (🥈30 · ⭐ 1.4K · 💀) - Python Geocoder。MIT - [GitHub](https://github.com/DenisCarriere/geocoder) (👨‍💻 74 · 🔀 260 · 📦 4.2K · 📋 290 - 24% open · ⏱️ 12.10.2018): @@ -4007,7 +4007,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geocoder ```
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folium (🥈29 · ⭐ 5.5K) - Python Data. Leaflet.js Maps. MIT +
folium (🥈29 · ⭐ 5.5K) - Leaflet.js地图的Python数据。MIT - [GitHub](https://github.com/python-visualization/folium) (👨‍💻 120 · 🔀 2K · 📦 13K · 📋 890 - 19% open · ⏱️ 30.11.2021): @@ -4023,7 +4023,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge folium ```
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Rasterio (🥈29 · ⭐ 1.6K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed +
Rasterio (🥈29 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed - [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): @@ -4039,7 +4039,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge rasterio ```
-
ipyleaflet (🥈29 · ⭐ 1.2K) - A Jupyter - Leaflet.js bridge. MIT +
ipyleaflet (🥈29 · ⭐ 1.2K) - Jupyter-Leaflet.js桥。MIT - [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (👨‍💻 72 · 🔀 300 · 📦 1.3K · 📋 460 - 38% open · ⏱️ 13.12.2021): @@ -4059,7 +4059,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra npm install jupyter-leaflet ```
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pyproj (🥈29 · ⭐ 690) - Python interface to PROJ (cartographic projections and coordinate.. MIT +
pyproj (🥈29 · ⭐ 690) - 与PROJ的Python界面（图形投影和坐标。MIT - [GitHub](https://github.com/pyproj4/pyproj) (👨‍💻 44 · 🔀 170 · 📦 12K · 📋 460 - 1% open · ⏱️ 06.12.2021): @@ -4075,7 +4075,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pyproj ```
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Cartopy (🥉28 · ⭐ 1.6K) - Rasterio reads and writes geospatial raster datasets. ❗Unlicensed +
Cartopy (🥉28 · ⭐ 1.6K) - Rasterio读写地理空间栅格数据集。❗Unlicensed - [GitHub](https://github.com/rasterio/rasterio) (👨‍💻 120 · 🔀 440 · 📥 740 · 📦 4.1K · 📋 1.5K - 9% open · ⏱️ 15.12.2021): @@ -4091,7 +4091,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge cartopy ```
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Fiona (🥉27 · ⭐ 870) - Fiona reads and writes geographic data files. ❗Unlicensed +
Fiona (🥉27 · ⭐ 870) - Fiona读写地理数据文件。❗Unlicensed - [GitHub](https://github.com/Toblerity/Fiona) (👨‍💻 65 · 🔀 170 · 📦 7.3K · 📋 640 - 11% open · ⏱️ 09.12.2021): @@ -4107,7 +4107,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge fiona ```
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geojson (🥉27 · ⭐ 680) - Python bindings and utilities for GeoJSON. BSD-3 +
geojson (🥉27 · ⭐ 680) - GeoJSON的Python接口。BSD-3 - [GitHub](https://github.com/jazzband/geojson) (👨‍💻 45 · 🔀 85 · 📦 8.2K · 📋 77 - 24% open · ⏱️ 11.11.2021): @@ -4123,7 +4123,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geojson ```
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ArcGIS API (🥉24 · ⭐ 1.2K) - Documentation and samples for ArcGIS API for Python. Apache-2 +
ArcGIS API (🥉24 · ⭐ 1.2K) - ArcGIS API for Python的文档和示例。Apache-2 - [GitHub](https://github.com/Esri/arcgis-python-api) (👨‍💻 73 · 🔀 820 · 📥 1K · 📋 380 - 24% open · ⏱️ 09.12.2021): @@ -4139,7 +4139,7 @@ _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 · ⭐ 950) - PySAL: Python Spatial Analysis Library Meta-Package. BSD-3 +
PySAL (🥉23 · ⭐ 950) - PySAL：Python空间分析库元包。BSD-3 - [GitHub](https://github.com/pysal/pysal) (👨‍💻 73 · 🔀 250 · 📋 600 - 1% open · ⏱️ 18.10.2021): @@ -4155,7 +4155,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pysal ```
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Sentinelsat (🥉23 · ⭐ 700) - Search and download Copernicus Sentinel satellite images. ❗️GPL-3.0 +
Sentinelsat (🥉23 · ⭐ 700) - 搜索和下载哥白尼前哨卫星图像。❗️GPL-3.0 - [GitHub](https://github.com/sentinelsat/sentinelsat) (👨‍💻 42 · 🔀 190 · 📥 230 · 📦 260 · 📋 310 - 2% open · ⏱️ 02.12.2021): @@ -4167,7 +4167,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install sentinelsat ```
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Satpy (🥉21 · ⭐ 780) - Python package for earth-observing satellite data processing. ❗️GPL-3.0 +
Satpy (🥉21 · ⭐ 780) - 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) (👨‍💻 120 · 🔀 220 · 📦 54 · 📋 700 - 40% open · ⏱️ 16.12.2021): @@ -4183,7 +4183,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge satpy ```
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GeoViews (🥉21 · ⭐ 380) - Simple, concise geographical visualization in Python. BSD-3 +
GeoViews (🥉21 · ⭐ 380) - 使用Python进行简单，简洁的地理可视化。BSD-3 - [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 25 · 🔀 65 · 📋 290 - 35% open · ⏱️ 01.12.2021): @@ -4199,7 +4199,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge geoviews ```
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EarthPy (🥉21 · ⭐ 310) - A package built to support working with spatial data using open source.. BSD-3 +
EarthPy (🥉21 · ⭐ 310) - 使用开放源代码处理空间数据。BSD-3 - [GitHub](https://github.com/earthlab/earthpy) (👨‍💻 40 · 🔀 120 · 📦 110 · 📋 220 - 7% open · ⏱️ 11.10.2021): @@ -4215,7 +4215,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge earthpy ```
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geoplotlib (🥉20 · ⭐ 940 · 💀) - python toolbox for visualizing geographical data and making maps. MIT +
geoplotlib (🥉20 · ⭐ 940 · 💀) - 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 · 🔀 150 · 📦 120 · 📋 43 - 58% open · ⏱️ 06.05.2019): @@ -4227,7 +4227,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install geoplotlib ```
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Mapbox GL (🥉19 · ⭐ 590 · 💤) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. MIT +
Mapbox GL (🥉19 · ⭐ 590 · 💤) - 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 · 🔀 120 · 📦 120 · 📋 98 - 31% open · ⏱️ 19.04.2021): @@ -4239,7 +4239,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra pip install mapboxgl ```
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pymap3d (🥉18 · ⭐ 220) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. BSD-2 +
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): @@ -4255,7 +4255,7 @@ _Libraries to load, process, analyze, and write geographic data as well as libra conda install -c conda-forge pymap3d ```
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gmaps (🥉17 · ⭐ 730 · 💀) - Google maps for Jupyter notebooks. BSD-3 +
gmaps (🥉17 · ⭐ 730 · 💀) - Google为Jupyter笔记本电脑映射。BSD-3 - [GitHub](https://github.com/pbugnion/gmaps) (👨‍💻 16 · 🔀 140 · 📦 1 · 📋 200 - 31% open · ⏱️ 22.07.2019): @@ -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 (🥇29 · ⭐ 15K · 💀) - Zipline, a Pythonic Algorithmic Trading Library. Apache-2 +
zipline (🥇29 · ⭐ 15K · 💀) - Zipline，一个Pythonic算法交易库。Apache-2 - [GitHub](https://github.com/quantopian/zipline) (👨‍💻 150 · 🔀 3.9K · 📦 800 · 📋 960 - 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 (🥇29 · ⭐ 6.1K) - Yahoo! Finance market data downloader (+faster Pandas Datareader). Apache-2 +
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 - [GitHub](https://github.com/ranaroussi/yfinance) (👨‍💻 49 · 🔀 1.4K · 📦 8.4K · 📋 700 - 54% open · ⏱️ 21.11.2021): @@ -4311,7 +4311,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c ranaroussi yfinance ```
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pyfolio (🥇26 · ⭐ 4.2K · 💀) - Portfolio and risk analytics in Python. Apache-2 +
pyfolio (🥇26 · ⭐ 4.2K · 💀) - Python中的投资组合和风险分析。Apache-2 - [GitHub](https://github.com/quantopian/pyfolio) (👨‍💻 55 · 🔀 1.3K · 📦 340 · 📋 400 - 33% open · ⏱️ 15.07.2020): @@ -4327,7 +4327,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge pyfolio ```
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backtrader (🥈25 · ⭐ 7.8K) - Python Backtesting library for trading strategies. ❗️GPL-3.0 +
backtrader (🥈25 · ⭐ 7.8K) - 用于交易策略的Python Backtesting库。❗️GPL-3.0 - [GitHub](https://github.com/mementum/backtrader) (👨‍💻 52 · 🔀 2.3K · 📦 840 · ⏱️ 17.07.2021): @@ -4339,7 +4339,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install backtrader ```
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Alphalens (🥈25 · ⭐ 2.1K · 💀) - Performance analysis of predictive (alpha) stock factors. Apache-2 +
Alphalens (🥈25 · ⭐ 2.1K · 💀) - 股票因子预测分析。Apache-2 - [GitHub](https://github.com/quantopian/alphalens) (👨‍💻 25 · 🔀 790 · 📦 470 · 📋 180 - 20% open · ⏱️ 27.04.2020): @@ -4355,7 +4355,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge alphalens ```
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bt (🥈24 · ⭐ 1.2K · 💤) - bt - flexible backtesting for Python. MIT +
bt (🥈24 · ⭐ 1.2K · 💤) - bt-Python的灵活回测。MIT - [GitHub](https://github.com/pmorissette/bt) (👨‍💻 24 · 🔀 290 · 📦 88 · 📋 270 - 17% open · ⏱️ 15.05.2021): @@ -4367,7 +4367,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install bt ```
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empyrical (🥈24 · ⭐ 870 · 💀) - Common financial risk and performance metrics. Used by zipline.. Apache-2 +
empyrical (🥈24 · ⭐ 870 · 💀) - 常见的金融风险和绩效指标。Apache-2 - [GitHub](https://github.com/quantopian/empyrical) (👨‍💻 22 · 🔀 270 · 📦 760 · 📋 49 - 46% open · ⏱️ 14.10.2020): @@ -4383,7 +4383,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge empyrical ```
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arch (🥈24 · ⭐ 840) - ARCH models in Python. ❗️NCSA +
arch (🥈24 · ⭐ 840) - Python中的ARCH模型。❗️NCSA - [GitHub](https://github.com/bashtage/arch) (👨‍💻 30 · 🔀 190 · 📦 420 · 📋 160 - 7% open · ⏱️ 19.11.2021): @@ -4395,7 +4395,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install arch ```
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ffn (🥈23 · ⭐ 1K · 💤) - ffn - a financial function library for Python. MIT +
ffn (🥈23 · ⭐ 1K · 💤) - ffn-Python的金融函数库。MIT - [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 26 · 🔀 190 · 📦 160 · 📋 96 - 16% open · ⏱️ 24.04.2021): @@ -4407,7 +4407,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install ffn ```
-
Qlib (🥉22 · ⭐ 7.6K) - Qlib is an AI-oriented quantitative investment platform, which aims to.. MIT +
Qlib (🥉22 · ⭐ 7.6K) - Qlib是一个面向AI的量化投资平台。MIT - [GitHub](https://github.com/microsoft/qlib) (👨‍💻 72 · 🔀 1.2K · 📥 270 · 📦 8 · 📋 370 - 33% open · ⏱️ 14.12.2021): @@ -4419,7 +4419,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install pyqlib ```
-
TensorTrade (🥉22 · ⭐ 3.6K) - An open source reinforcement learning framework for training,.. Apache-2 +
TensorTrade (🥉22 · ⭐ 3.6K) - 一个开放源代码的强化学习框架。Apache-2 - [GitHub](https://github.com/tensortrade-org/tensortrade) (👨‍💻 57 · 🔀 820 · 📦 27 · 📋 190 - 11% open · ⏱️ 07.12.2021): @@ -4431,7 +4431,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install tensortrade ```
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PyAlgoTrade (🥉22 · ⭐ 3.6K · 💀) - Python Algorithmic Trading Library. Apache-2 +
PyAlgoTrade (🥉22 · ⭐ 3.6K · 💀) - Python算法交易库。Apache-2 - [GitHub](https://github.com/gbeced/pyalgotrade) (👨‍💻 11 · 🔀 1.2K · 📦 98 · 📋 120 - 30% open · ⏱️ 21.08.2018): @@ -4443,7 +4443,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install pyalgotrade ```
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Alpha Vantage (🥉22 · ⭐ 3.6K) - A python wrapper for Alpha Vantage API for financial data. MIT +
Alpha Vantage (🥉22 · ⭐ 3.6K) - 用于金融数据的Alpha Vantage API的python包装器。MIT - [GitHub](https://github.com/RomelTorres/alpha_vantage) (👨‍💻 39 · 🔀 630 · 📋 250 - 1% open · ⏱️ 14.06.2021): @@ -4455,7 +4455,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install alpha_vantage ```
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FinTA (🥉22 · ⭐ 1.4K) - Common financial technical indicators implemented in Pandas. ❗️LGPL-3.0 +
FinTA (🥉22 · ⭐ 1.4K) - 基于pandas实现的通用金融技术指标。❗️LGPL-3.0 - [GitHub](https://github.com/peerchemist/finta) (👨‍💻 27 · 🔀 440 · 📦 140 · 📋 80 - 21% open · ⏱️ 19.10.2021): @@ -4467,7 +4467,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install finta ```
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ta (🥉21 · ⭐ 2.6K) - Technical Analysis Library using Pandas and Numpy. MIT +
ta (🥉21 · ⭐ 2.6K) - 使用Pandas和Numpy的技术分析库。MIT - [GitHub](https://github.com/bukosabino/ta) (👨‍💻 24 · 🔀 630 · 📦 900 · 📋 180 - 51% open · ⏱️ 08.12.2021): @@ -4479,7 +4479,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install ta ```
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IB-insync (🥉21 · ⭐ 1.6K) - Python sync/async framework for Interactive Brokers API. BSD-2 +
IB-insync (🥉21 · ⭐ 1.6K) - 用于Interactive Brokers API的Python同步/异步框架。BSD-2 - [GitHub](https://github.com/erdewit/ib_insync) (👨‍💻 29 · 🔀 460 · 📋 360 - 2% open · ⏱️ 28.11.2021): @@ -4495,7 +4495,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te conda install -c conda-forge ib-insync ```
-
finmarketpy (🥉20 · ⭐ 2.8K) - Python library for backtesting trading strategies & analyzing.. Apache-2 +
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): @@ -4507,7 +4507,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install finmarketpy ```
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Enigma Catalyst (🥉20 · ⭐ 2.3K) - An Algorithmic Trading Library for Crypto-Assets in Python. Apache-2 +
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): @@ -4519,7 +4519,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install enigma-catalyst ```
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Crypto Signals (🥉19 · ⭐ 3.7K) - Github.com/CryptoSignal - #1 Quant Trading & Technical.. MIT +
Crypto Signals (🥉19 · ⭐ 3.7K) - CryptoSignal量化交易技术。MIT - [GitHub](https://github.com/CryptoSignal/Crypto-Signal) (👨‍💻 28 · 🔀 950 · 📋 250 - 19% open · ⏱️ 28.06.2021): @@ -4531,7 +4531,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te docker pull shadowreaver/crypto-signal ```
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tf-quant-finance (🥉19 · ⭐ 2.9K) - High-performance TensorFlow library for quantitative.. Apache-2 +
tf-quant-finance (🥉19 · ⭐ 2.9K) - 用于量化投资的高性能TensorFlow库。Apache-2 - [GitHub](https://github.com/google/tf-quant-finance) (👨‍💻 36 · 🔀 380 · 📋 32 - 43% open · ⏱️ 14.12.2021): @@ -4543,7 +4543,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install tf-quant-finance ```
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Backtesting.py (🥉18 · ⭐ 2K) - Backtest trading strategies in Python. ❗️AGPL-3.0 +
Backtesting.py (🥉18 · ⭐ 2K) - 回溯Python中的交易策略。❗️AGPL-3.0 - [GitHub](https://github.com/kernc/backtesting.py) (👨‍💻 15 · 🔀 410 · 📋 270 - 14% open · ⏱️ 13.12.2021): @@ -4555,7 +4555,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install backtesting ```
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stockstats (🥉17 · ⭐ 910) - Supply a wrapper ``StockDataFrame`` based on the.. BSD-3 +
stockstats (🥉17 · ⭐ 910) - 提供StockDataFrame包装器BSD-3 - [GitHub](https://github.com/jealous/stockstats) (👨‍💻 8 · 🔀 240 · 📦 360 · 📋 72 - 41% open · ⏱️ 20.11.2021): @@ -4567,7 +4567,7 @@ _Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, te pip install stockstats ```
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surpriver (🥉12 · ⭐ 1.4K · 💀) - Find big moving stocks before they move using machine.. ❗️GPL-3.0 +
surpriver (🥉12 · ⭐ 1.4K · 💀) - 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 · 🔀 250 · 📋 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。_ -
sktime (🥇26 · ⭐ 4.7K) - A unified framework for machine learning with time series. BSD-3 +
sktime (🥇26 · ⭐ 4.7K) - 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) (👨‍💻 130 · 🔀 700 · 📥 64 · 📦 310 · 📋 780 - 31% open · ⏱️ 13.12.2021): @@ -4595,7 +4595,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install sktime ```
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tslearn (🥇26 · ⭐ 1.9K) - A machine learning toolkit dedicated to time-series data. BSD-2 +
tslearn (🥇26 · ⭐ 1.9K) - 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) (👨‍💻 36 · 🔀 250 · 📦 360 · 📋 250 - 27% open · ⏱️ 06.12.2021): @@ -4611,7 +4611,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge tslearn ```
-
Darts (🥈24 · ⭐ 3.2K) - A python library for easy manipulation and forecasting of time series. Apache-2 +
Darts (🥈24 · ⭐ 3.2K) - 一个易于操作和预测时间序列的python库。Apache-2 - [GitHub](https://github.com/unit8co/darts) (👨‍💻 41 · 🔀 280 · 📦 22 · 📋 290 - 36% open · ⏱️ 14.12.2021): @@ -4627,7 +4627,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l docker pull unit8/darts ```
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GluonTS (🥈24 · ⭐ 2.4K) - Probabilistic time series modeling in Python. Apache-2 +
GluonTS (🥈24 · ⭐ 2.4K) - Python中的概率时间序列建模。Apache-2 - [GitHub](https://github.com/awslabs/gluon-ts) (👨‍💻 79 · 🔀 480 · 📋 640 - 34% open · ⏱️ 13.12.2021): @@ -4639,7 +4639,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install gluonts ```
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Prophet (🥈23 · ⭐ 14K) - Tool for producing high quality forecasts for time series data that has.. MIT +
Prophet (🥈23 · ⭐ 14K) - 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) (👨‍💻 140 · 🔀 3.9K · 📥 640 · 📋 1.7K - 9% open · ⏱️ 03.10.2021): @@ -4651,7 +4651,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install fbprophet ```
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tsfresh (🥈23 · ⭐ 6.1K) - Automatic extraction of relevant features from time series:. MIT +
tsfresh (🥈23 · ⭐ 6.1K) - 从时间序列中自动提取相关特征。MIT - [GitHub](https://github.com/blue-yonder/tsfresh) (👨‍💻 80 · 🔀 930 · 📋 470 - 8% open · ⏱️ 15.12.2021): @@ -4667,7 +4667,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge tsfresh ```
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STUMPY (🥈22 · ⭐ 2K) - STUMPY is a powerful and scalable Python library for computing a Matrix.. BSD-3 +
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 - [GitHub](https://github.com/TDAmeritrade/stumpy) (👨‍💻 26 · 🔀 190 · 📋 270 - 10% open · ⏱️ 15.12.2021): @@ -4683,7 +4683,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge stumpy ```
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pmdarima (🥈22 · ⭐ 1.1K) - A statistical library designed to fill the void in Python's time series.. MIT +
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): @@ -4695,7 +4695,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pmdarima ```
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Streamz (🥉21 · ⭐ 1K) - Real-time stream processing for python. ❗Unlicensed +
Streamz (🥉21 · ⭐ 1K) - python的实时流处理。❗Unlicensed - [GitHub](https://github.com/python-streamz/streamz) (👨‍💻 44 · 🔀 130 · 📦 250 · 📋 240 - 38% open · ⏱️ 09.12.2021): @@ -4711,7 +4711,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge streamz ```
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pytorch-forecasting (🥉20 · ⭐ 1.6K) - Time series forecasting with PyTorch. MIT +
pytorch-forecasting (🥉20 · ⭐ 1.6K) - 使用PyTorch进行时间序列预测。MIT - [GitHub](https://github.com/jdb78/pytorch-forecasting) (👨‍💻 27 · 🔀 230 · 📋 360 - 36% open · ⏱️ 16.12.2021): @@ -4723,7 +4723,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pytorch-forecasting ```
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pyts (🥉20 · ⭐ 1.1K) - A Python package for time series classification. BSD-3 +
pyts (🥉20 · ⭐ 1.1K) - 用于时间序列分类的Python软件包。BSD-3 - [GitHub](https://github.com/johannfaouzi/pyts) (👨‍💻 10 · 🔀 110 · 📦 160 · 📋 56 - 57% open · ⏱️ 09.12.2021): @@ -4739,7 +4739,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l conda install -c conda-forge pyts ```
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luminol (🥉19 · ⭐ 980 · 💀) - Anomaly Detection and Correlation library. Apache-2 +
luminol (🥉19 · ⭐ 980 · 💀) - 异常检测和相关库。Apache-2 - [GitHub](https://github.com/linkedin/luminol) (👨‍💻 8 · 🔀 190 · 📦 47 · 📋 36 - 66% open · ⏱️ 09.01.2018): @@ -4751,7 +4751,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install luminol ```
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tick (🥉18 · ⭐ 360 · 💀) - Module for statistical learning, with a particular emphasis on time-.. BSD-3 +
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): @@ -4763,7 +4763,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install tick ```
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PyFlux (🥉17 · ⭐ 1.9K · 💀) - Open source time series library for Python. BSD-3 +
PyFlux (🥉17 · ⭐ 1.9K · 💀) - 适用于Python的开源时间序列库。BSD-3 - [GitHub](https://github.com/RJT1990/pyflux) (👨‍💻 6 · 🔀 220 · 📦 210 · 📋 150 - 55% open · ⏱️ 16.12.2018): @@ -4775,7 +4775,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pyflux ```
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ADTK (🥉17 · ⭐ 760 · 💀) - A Python toolkit for rule-based/unsupervised anomaly detection in time.. MPL-2.0 +
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 - [GitHub](https://github.com/arundo/adtk) (👨‍💻 11 · 🔀 94 · 📋 60 - 43% open · ⏱️ 17.04.2020): @@ -4787,7 +4787,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install adtk ```
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seglearn (🥉17 · ⭐ 480 · 💤) - Python module for machine learning time series:. BSD-3 +
seglearn (🥉17 · ⭐ 480 · 💤) - 机器学习时间序列的Python模块。BSD-3 - [GitHub](https://github.com/dmbee/seglearn) (👨‍💻 13 · 🔀 52 · 📦 11 · 📋 28 - 17% open · ⏱️ 12.03.2021): @@ -4799,7 +4799,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install seglearn ```
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Auto TS (🥉17 · ⭐ 350) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. Apache-2 +
Auto TS (🥉17 · ⭐ 350) - 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 · 🔀 65 · 📋 57 - 14% open · ⏱️ 07.12.2021): @@ -4811,7 +4811,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install auto-ts ```
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matrixprofile-ts (🥉14 · ⭐ 670 · 💀) - A Python library for detecting patterns and anomalies.. Apache-2 +
matrixprofile-ts (🥉14 · ⭐ 670 · 💀) - 一个用于检测模式和异常的Python库。Apache-2 - [GitHub](https://github.com/target/matrixprofile-ts) (👨‍💻 15 · 🔀 92 · 📦 17 · 📋 53 - 35% open · ⏱️ 25.04.2020): @@ -4823,7 +4823,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install matrixprofile-ts ```
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pydlm (🥉14 · ⭐ 400 · 💀) - A python library for Bayesian time series modeling. BSD-3 +
pydlm (🥉14 · ⭐ 400 · 💀) - 用于贝叶斯时间序列建模的python库。BSD-3 - [GitHub](https://github.com/wwrechard/pydlm) (👨‍💻 6 · 🔀 87 · 📦 24 · 📋 43 - 81% open · ⏱️ 22.10.2019): @@ -4835,7 +4835,7 @@ _Libraries for forecasting, anomaly detection, feature extraction, and machine l pip install pydlm ```
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atspy (🥉10 · ⭐ 400) - AtsPy: Automated Time Series Models in Python (by @firmai). ❗Unlicensed +
atspy (🥉10 · ⭐ 400) - AtsPy：Python中的自动时间序列模型。❗Unlicensed - [GitHub](https://github.com/firmai/atspy) (👨‍💻 5 · 🔀 78 · 📦 3 · 📋 20 - 90% open · ⏱️ 30.08.2021): @@ -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。_ -
Lifelines (🥇29 · ⭐ 1.8K) - Survival analysis in Python. MIT +
Lifelines (🥇29 · ⭐ 1.8K) - Python中的生存分析。MIT - [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 98 · 🔀 440 · 📦 730 · 📋 830 - 25% open · ⏱️ 30.11.2021): @@ -4871,7 +4871,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge lifelines ```
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NIPYPE (🥇29 · ⭐ 600) - Workflows and interfaces for neuroimaging packages. Apache-2 +
NIPYPE (🥇29 · ⭐ 600) - 神经影像软件包的工作流程和接口。Apache-2 - [GitHub](https://github.com/nipy/nipype) (👨‍💻 230 · 🔀 440 · 📦 810 · 📋 1.2K - 27% open · ⏱️ 15.12.2021): @@ -4887,7 +4887,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nipype ```
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MNE (🥈27 · ⭐ 1.8K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. BSD-3 +
MNE (🥈27 · ⭐ 1.8K) - MNE：Python中的磁脑图（MEG）和脑电图（EEG）。BSD-3 - [GitHub](https://github.com/mne-tools/mne-python) (👨‍💻 280 · 🔀 940 · 📦 1.3K · 📋 3.9K - 8% open · ⏱️ 16.12.2021): @@ -4903,7 +4903,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge mne ```
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NiBabel (🥈27 · ⭐ 450) - Python package to access a cacophony of neuro-imaging file formats. ❗Unlicensed +
NiBabel (🥈27 · ⭐ 450) - Python软件包，用于访问神经影像文件格式。❗Unlicensed - [GitHub](https://github.com/nipy/nibabel) (👨‍💻 93 · 🔀 220 · 📦 5.9K · 📋 410 - 25% open · ⏱️ 30.09.2021): @@ -4919,7 +4919,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nibabel ```
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Hail (🥈26 · ⭐ 770) - Scalable genomic data analysis. MIT +
Hail (🥈26 · ⭐ 770) - 可扩展的基因组数据分析。MIT - [GitHub](https://github.com/hail-is/hail) (👨‍💻 76 · 🔀 200 · 📦 45 · 📋 2K - 1% open · ⏱️ 16.12.2021): @@ -4931,7 +4931,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install hail ```
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Nilearn (🥈24 · ⭐ 790) - Machine learning for NeuroImaging in Python. ❗Unlicensed +
Nilearn (🥈24 · ⭐ 790) - Python中NeuroImaging的机器学习。❗Unlicensed - [GitHub](https://github.com/nilearn/nilearn) (👨‍💻 180 · 🔀 420 · 📥 14 · 📦 1.3K · 📋 1.5K - 15% open · ⏱️ 16.12.2021): @@ -4947,7 +4947,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nilearn ```
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DIPY (🥈24 · ⭐ 480) - DIPY is the paragon 3D/4D+ imaging library in Python. Contains.. ❗Unlicensed +
DIPY (🥈24 · ⭐ 480) - DIPY是Python中的Paragon 3D/4D +影像库。❗Unlicensed - [GitHub](https://github.com/dipy/dipy) (👨‍💻 130 · 🔀 320 · 📦 480 · 📋 740 - 13% open · ⏱️ 03.12.2021): @@ -4963,7 +4963,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge dipy ```
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DeepVariant (🥈22 · ⭐ 2.4K) - DeepVariant is an analysis pipeline that uses a deep neural.. BSD-3 +
DeepVariant (🥈22 · ⭐ 2.4K) - DeepVariant是使用深度神经网络的分析管道。BSD-3 - [GitHub](https://github.com/google/deepvariant) (👨‍💻 21 · 🔀 580 · 📥 3.7K · 📋 450 - 0% open · ⏱️ 10.12.2021): @@ -4975,7 +4975,7 @@ _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) (👨‍💻 58 · 🔀 390 · 📦 37 · 📋 320 - 30% open · ⏱️ 21.04.2020): @@ -4987,7 +4987,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install niftynet ```
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MedPy (🥉21 · ⭐ 380 · 💀) - Medical image processing in Python. ❗️GPL-3.0 +
MedPy (🥉21 · ⭐ 380 · 💀) - Python中的医学图像处理。❗️GPL-3.0 - [GitHub](https://github.com/loli/medpy) (👨‍💻 13 · 🔀 110 · 📦 450 · 📋 78 - 14% open · ⏱️ 01.05.2020): @@ -4999,7 +4999,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install MedPy ```
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MONAI (🥉20 · ⭐ 2.6K) - AI Toolkit for Healthcare Imaging. Apache-2 +
MONAI (🥉20 · ⭐ 2.6K) - 用于医疗成像的AI工具包。Apache-2 - [GitHub](https://github.com/Project-MONAI/MONAI) (👨‍💻 84 · 🔀 480 · 📦 160 · 📋 1.3K - 8% open · ⏱️ 16.12.2021): @@ -5011,7 +5011,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install monai ```
-
Glow (🥉20 · ⭐ 180) - An open-source toolkit for large-scale genomic analysis. Apache-2 +
Glow (🥉20 · ⭐ 180) - 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) (👨‍💻 18 · 🔀 55 · 📋 120 - 36% open · ⏱️ 01.12.2021): @@ -5023,7 +5023,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install glow.py ```
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NIPY (🥉19 · ⭐ 310 · 💤) - Neuroimaging in Python FMRI analysis package. BSD-3 +
NIPY (🥉19 · ⭐ 310 · 💤) - Python FMRI分析软件包中的Neuroimaging。BSD-3 - [GitHub](https://github.com/nipy/nipy) (👨‍💻 63 · 🔀 130 · 📋 150 - 25% open · ⏱️ 29.03.2021): @@ -5039,7 +5039,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic conda install -c conda-forge nipy ```
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Brainiak (🥉18 · ⭐ 260 · 💤) - Brain Imaging Analysis Kit. Apache-2 +
Brainiak (🥉18 · ⭐ 260 · 💤) - 脑成像分析套件。Apache-2 - [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 33 · 🔀 120 · 📦 15 · 📋 190 - 35% open · ⏱️ 28.05.2021): @@ -5055,7 +5055,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic docker pull brainiak/brainiak ```
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DLTK (🥉16 · ⭐ 1.3K · 💀) - Deep Learning Toolkit for Medical Image Analysis. Apache-2 +
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): @@ -5067,7 +5067,7 @@ _Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic pip install dltk ```
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MedicalTorch (🥉16 · ⭐ 760 · 💤) - A medical imaging framework for Pytorch. Apache-2 +
MedicalTorch (🥉16 · ⭐ 760 · 💤) - Pytorch的医学成像框架。Apache-2 - [GitHub](https://github.com/perone/medicaltorch) (👨‍💻 8 · 🔀 110 · 📦 11 · 📋 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 (🥉13 · ⭐ 1.3K · 💀) - Many studies have shown that the performance on deep learning is.. MIT +
MedicalNet (🥉13 · ⭐ 1.3K · 💀) - Transfer Learning for 3D Medical Image Analysis的论文实现。MIT - [GitHub](https://github.com/Tencent/MedicalNet) (🔀 330 · 📋 62 - 77% 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 (🥉12 · ⭐ 1.1K) - The Medical Detection Toolkit contains 2D + 3D.. Apache-2 +
Medical Detection Toolkit (🥉12 · ⭐ 1.1K) - Medical Detection Toolkit包含2D + 3D。Apache-2 - [GitHub](https://github.com/MIC-DKFZ/medicaldetectiontoolkit) (👨‍💻 3 · 🔀 270 · 📋 120 - 30% open · ⏱️ 09.09.2021): @@ -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 (🥉12 · ⭐ 110 · 💀) - A deep learning python package for neuroimaging data. Made by:. MIT +
DeepNeuro (🥉12 · ⭐ 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 (🥇30 · ⭐ 13K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. Apache-2 +
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 - [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 90 · 🔀 1.7K · 📥 870K · 📦 750 · 📋 470 - 29% open · ⏱️ 15.10.2021): @@ -5127,7 +5127,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install easyocr ```
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PaddleOCR (🥇26 · ⭐ 18K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. Apache-2 +
PaddleOCR (🥇26 · ⭐ 18K) - 基于PaddlePaddle的多语言OCR工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (👨‍💻 58 · 🔀 3.6K · 📦 450 · 📋 3.5K - 25% open · ⏱️ 10.12.2021): @@ -5139,7 +5139,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install paddleocr ```
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tesserocr (🥈25 · ⭐ 1.6K) - A Python wrapper for the tesseract-ocr API. MIT +
tesserocr (🥈25 · ⭐ 1.6K) - 用于tesseract-ocr API的Python包装器。MIT - [GitHub](https://github.com/sirfz/tesserocr) (👨‍💻 26 · 🔀 200 · 📦 580 · 📋 230 - 31% open · ⏱️ 09.11.2021): @@ -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 (🥈24 · ⭐ 3.9K) - Python-tesseract is an optical character recognition (OCR) tool.. Apache-2 +
Tesseract (🥈24 · ⭐ 3.9K) - Python-tesseract是一种光学字符识别（OCR）工具。Apache-2 - [GitHub](https://github.com/madmaze/pytesseract) (👨‍💻 38 · 🔀 550 · 📋 280 - 3% open · ⏱️ 08.12.2021): @@ -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 · ⭐ 5.5K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. MPL-2.0 +
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 - [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 58 · 🔀 510 · 📋 780 - 11% open · ⏱️ 11.12.2021): @@ -5183,7 +5183,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install ocrmypdf ```
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attention-ocr (🥉21 · ⭐ 880) - A Tensorflow model for text recognition (CNN + seq2seq with.. MIT +
attention-ocr (🥉21 · ⭐ 880) - 用于文本识别的Tensorflow模型。MIT - [GitHub](https://github.com/emedvedev/attention-ocr) (👨‍💻 27 · 🔀 240 · 📦 18 · 📋 150 - 14% open · ⏱️ 29.10.2021): @@ -5195,7 +5195,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install aocr ```
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keras-ocr (🥉19 · ⭐ 960) - A packaged and flexible version of the CRAFT text detector and.. MIT +
keras-ocr (🥉19 · ⭐ 960) - CRAFT文本检测器。MIT - [GitHub](https://github.com/faustomorales/keras-ocr) (👨‍💻 12 · 🔀 240 · 📥 200K · 📋 150 - 30% open · ⏱️ 24.11.2021): @@ -5207,7 +5207,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install keras-ocr ```
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doc2text (🥉17 · ⭐ 1.3K · 💤) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. MIT +
doc2text (🥉17 · ⭐ 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 · 🔀 94 · 📦 50 · 📋 21 - 57% open · ⏱️ 01.12.2020): @@ -5219,7 +5219,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install doc2text ```
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calamari (🥉17 · ⭐ 880) - Line based ATR Engine based on OCRopy. Apache-2 +
calamari (🥉17 · ⭐ 880) - 基于OCRopy的基于行的ATR引擎。Apache-2 - [GitHub](https://github.com/Calamari-OCR/calamari) (👨‍💻 19 · 🔀 180 · 📋 230 - 16% open · ⏱️ 02.10.2021): @@ -5231,7 +5231,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install calamari_ocr ```
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pdftabextract (🥉15 · ⭐ 2K · 💀) - A set of tools for extracting tables from PDF files.. Apache-2 +
pdftabextract (🥉15 · ⭐ 2K · 💀) - 一组用于从PDF文件提取表格的工具。Apache-2 - [GitHub](https://github.com/WZBSocialScienceCenter/pdftabextract) (👨‍💻 2 · 🔀 340 · 📦 37 · 📋 21 - 14% open · ⏱️ 26.10.2018): @@ -5243,7 +5243,7 @@ _Libraries for optical character recognition (OCR) and text extraction from imag pip install pdftabextract ```
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Mozart (🥉10 · ⭐ 340 · 💤) - An optical music recognition (OMR) system. Converts sheet.. Apache-2 +
Mozart (🥉10 · ⭐ 340 · 💤) - 光学音乐识别（OMR）系统。Apache-2 - [GitHub](https://github.com/aashrafh/Mozart) (👨‍💻 5 · 🔀 47 · 📋 9 - 33% open · ⏱️ 05.05.2021): @@ -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 (🥇43 · ⭐ 32K) - Flexible and powerful data analysis / manipulation library for.. BSD-3 +
pandas (🥇43 · ⭐ 32K) - 灵活而强大的数据分析/操作库。BSD-3 - [GitHub](https://github.com/pandas-dev/pandas) (👨‍💻 2.9K · 🔀 13K · 📥 130K · 📦 600K · 📋 22K - 15% open · ⏱️ 16.12.2021): @@ -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 · ⭐ 19K) - The fundamental package for scientific computing with Python. BSD-3 +
numpy (🥇38 · ⭐ 19K) - 使用Python进行科学计算的基本软件包。BSD-3 - [GitHub](https://github.com/numpy/numpy) (👨‍💻 1.4K · 🔀 6.1K · 📥 430K · 📦 910K · 📋 10K - 20% open · ⏱️ 16.12.2021): @@ -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 (🥇34 · ⭐ 1.6K) - HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5.. BSD-3 +
h5py (🥇34 · ⭐ 1.6K) - 适用于Python的HDF5-h5py软件包，HDF5的Pythonic接口。BSD-3 - [GitHub](https://github.com/h5py/h5py) (👨‍💻 170 · 🔀 420 · 📥 1.6K · 📦 140K · 📋 1.3K - 16% open · ⏱️ 11.12.2021): @@ -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 · ⭐ 8.8K) - Apache Arrow is a cross-language development platform for in-.. Apache-2 +
Arrow (🥈33 · ⭐ 8.8K) - 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) (👨‍💻 780 · 🔀 2K · 📦 57 · 📋 700 - 1% open · ⏱️ 15.12.2021): @@ -5323,7 +5323,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge arrow ```
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xarray (🥈30 · ⭐ 2.4K) - N-D labeled arrays and datasets in Python. Apache-2 +
xarray (🥈30 · ⭐ 2.4K) - Python中带有N-D标签的数组和数据集。Apache-2 - [GitHub](https://github.com/pydata/xarray) (👨‍💻 350 · 🔀 740 · 📦 8.5K · 📋 3K - 27% open · ⏱️ 13.12.2021): @@ -5339,7 +5339,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge xarray ```
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Koalas (🥈29 · ⭐ 3K) - Koalas: pandas API on Apache Spark. Apache-2 +
Koalas (🥈29 · ⭐ 3K) - Apache Spark上的pandas API。Apache-2 - [GitHub](https://github.com/databricks/koalas) (👨‍💻 51 · 🔀 320 · 📥 1K · 📦 160 · 📋 570 - 15% open · ⏱️ 21.10.2021): @@ -5355,7 +5355,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge koalas ```
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sklearn-pandas (🥈28 · ⭐ 2.5K · 💤) - Pandas integration with sklearn. ❗️Zlib +
sklearn-pandas (🥈28 · ⭐ 2.5K · 💤) - pandas与sklearn集成。❗️Zlib - [GitHub](https://github.com/scikit-learn-contrib/sklearn-pandas) (👨‍💻 37 · 🔀 370 · 📦 3.2K · 📋 150 - 13% open · ⏱️ 08.05.2021): @@ -5367,7 +5367,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install sklearn-pandas ```
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zarr (🥈27 · ⭐ 820) - An implementation of chunked, compressed, N-dimensional arrays for Python. MIT +
zarr (🥈27 · ⭐ 820) - Python的分块，压缩N维数组的实现。MIT - [GitHub](https://github.com/zarr-developers/zarr-python) (👨‍💻 52 · 🔀 130 · 📦 970 · 📋 440 - 37% open · ⏱️ 14.12.2021): @@ -5383,7 +5383,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge zarr ```
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Bottleneck (🥈27 · ⭐ 680 · 💤) - Fast NumPy array functions written in C. BSD-2 +
Bottleneck (🥈27 · ⭐ 680 · 💤) - 用C编写的快速NumPy数组函数。BSD-2 - [GitHub](https://github.com/pydata/bottleneck) (👨‍💻 21 · 🔀 74 · 📦 29K · 📋 220 - 17% open · ⏱️ 24.01.2021): @@ -5399,7 +5399,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge bottleneck ```
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Blaze (🥈26 · ⭐ 3K · 💀) - NumPy and Pandas interface to Big Data. ❗Unlicensed +
Blaze (🥈26 · ⭐ 3K · 💀) - NumPy和Pandas连接到大数据。❗Unlicensed - [GitHub](https://github.com/blaze/blaze) (👨‍💻 64 · 🔀 360 · 📦 8K · 📋 750 - 33% open · ⏱️ 15.08.2019): @@ -5415,7 +5415,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge blaze ```
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Modin (🥈25 · ⭐ 6.6K) - Modin: Speed up your Pandas workflows by changing a single.. ❗Unlicensed +
Modin (🥈25 · ⭐ 6.6K) - Modin：通过更改一行来加快Pandas工作流程。❗Unlicensed - [GitHub](https://github.com/modin-project/modin) (👨‍💻 85 · 🔀 460 · 📥 200K · 📦 520 · 📋 2.2K - 28% open · ⏱️ 16.12.2021): @@ -5427,7 +5427,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install modin ```
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bcolz (🥉23 · ⭐ 940 · 💀) - A columnar data container that can be compressed. ❗Unlicensed +
bcolz (🥉23 · ⭐ 940 · 💀) - 可以压缩的列式数据容器。❗Unlicensed - [GitHub](https://github.com/Blosc/bcolz) (👨‍💻 33 · 🔀 120 · 📦 1.7K · 📋 240 - 50% open · ⏱️ 10.09.2020): @@ -5443,7 +5443,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge bcolz ```
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Vaex (🥉22 · ⭐ 6.8K) - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualize and.. MIT +
Vaex (🥉22 · ⭐ 6.8K) - 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) (👨‍💻 62 · 🔀 520 · 📥 220 · 📋 890 - 31% open · ⏱️ 16.12.2021): @@ -5459,7 +5459,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge vaex ```
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TinyDB (🥉22 · ⭐ 4.7K) - TinyDB is a lightweight document oriented database optimized for your.. MIT +
TinyDB (🥉22 · ⭐ 4.7K) - TinyDB：轻型面向文档的数据库。MIT - [GitHub](https://github.com/msiemens/tinydb) (👨‍💻 70 · 🔀 410 · 📋 270 - 2% open · ⏱️ 04.12.2021): @@ -5475,7 +5475,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge tinydb ```
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Arctic (🥉22 · ⭐ 2.5K) - Arctic is a high performance datastore for numeric data. ❗️LGPL-2.1 +
Arctic (🥉22 · ⭐ 2.5K) - 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) (👨‍💻 72 · 🔀 490 · 📥 180 · 📦 140 · 📋 520 - 15% open · ⏱️ 09.12.2021): @@ -5491,7 +5491,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge arctic ```
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swifter (🥉22 · ⭐ 1.8K) - A package which efficiently applies any function to a pandas.. MIT +
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 - [GitHub](https://github.com/jmcarpenter2/swifter) (👨‍💻 14 · 🔀 84 · 📦 440 · 📋 110 - 21% open · ⏱️ 25.06.2021): @@ -5507,7 +5507,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge swifter ```
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numexpr (🥉22 · ⭐ 1.7K) - Fast numerical array expression evaluator for Python, NumPy, PyTables,.. MIT +
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 - [GitHub](https://github.com/pydata/numexpr) (👨‍💻 59 · 🔀 160 · 📋 310 - 17% open · ⏱️ 10.12.2021): @@ -5523,7 +5523,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge numexpr ```
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datasketch (🥉22 · ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog,.. MIT +
datasketch (🥉22 · ⭐ 1.6K) - MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog等实现。MIT - [GitHub](https://github.com/ekzhu/datasketch) (👨‍💻 20 · 🔀 230 · 📥 18 · 📦 330 · 📋 120 - 21% open · ⏱️ 16.12.2021): @@ -5535,7 +5535,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install datasketch ```
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PyTables (🥉22 · ⭐ 1.1K) - A Python package to manage extremely large amounts of data. BSD-3 +
PyTables (🥉22 · ⭐ 1.1K) - 一个Python包，用于管理大量数据。BSD-3 - [GitHub](https://github.com/PyTables/PyTables) (👨‍💻 100 · 🔀 200 · 📥 160 · 📋 630 - 26% open · ⏱️ 15.12.2021): @@ -5551,7 +5551,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge pytables ```
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pandasql (🥉22 · ⭐ 1.1K · 💀) - sqldf for pandas. MIT +
pandasql (🥉22 · ⭐ 1.1K · 💀) - pandas的sqldf。MIT - [GitHub](https://github.com/yhat/pandasql) (👨‍💻 15 · 🔀 150 · 📦 1K · 📋 65 - 64% open · ⏱️ 01.02.2017): @@ -5563,7 +5563,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandasql ```
-
StaticFrame (🥉22 · ⭐ 260) - Immutable and grow-only Pandas-like DataFrames with a more explicit.. MIT +
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 - [GitHub](https://github.com/InvestmentSystems/static-frame) (👨‍💻 16 · 🔀 23 · 📦 10 · 📋 360 - 10% open · ⏱️ 16.12.2021): @@ -5591,7 +5591,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandarallel ```
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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 · 🔀 34 · 📥 13 · 📦 3 · 📋 73 - 45% open · ⏱️ 18.02.2021): @@ -5607,7 +5607,7 @@ _General-purpose data containers & structures as well as utilities & extensions conda install -c conda-forge fletcher ```
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datatable (🥉17 · ⭐ 1.4K) - A Python package for manipulating 2-dimensional tabular data.. MPL-2.0 +
datatable (🥉17 · ⭐ 1.4K) - 一个用于处理二维表格数据的Python包。MPL-2.0 - [GitHub](https://github.com/h2oai/datatable) (👨‍💻 32 · 🔀 120 · 📥 1.2K · 📋 1.4K - 9% open · ⏱️ 10.12.2021): @@ -5619,7 +5619,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install datatable ```
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Bounter (🥉16 · ⭐ 930 · 💤) - Efficient Counter that uses a limited (bounded) amount of memory.. MIT +
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): @@ -5631,7 +5631,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install bounter ```
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pickleDB (🥉16 · ⭐ 620 · 💀) - pickleDB is an open source key-value store using Python's json.. BSD-3 +
pickleDB (🥉16 · ⭐ 620 · 💀) - pickleDB是使用Python的json的开源键值存储。BSD-3 - [GitHub](https://github.com/patx/pickledb) (👨‍💻 12 · 🔀 100 · 📦 790 · 📋 54 - 27% open · ⏱️ 15.11.2019): @@ -5643,7 +5643,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pickledb ```
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Pandas Summary (🥉13 · ⭐ 370) - An extension to pandas dataframes describe function. Apache-2 +
Pandas Summary (🥉13 · ⭐ 370) - pandas Dataframe的describe函数功能扩展。Apache-2 - [GitHub](https://github.com/polyaxon/datatile) (👨‍💻 7 · 🔀 37 · 📦 3 · 📋 13 - 53% open · ⏱️ 02.12.2021): @@ -5655,7 +5655,7 @@ _General-purpose data containers & structures as well as utilities & extensions pip install pandas-summary ```
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PandaPy (🥉11 · ⭐ 490) - PandaPy has the speed of NumPy and the usability of Pandas.. ❗Unlicensed +
PandaPy (🥉11 · ⭐ 490) - 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 · 🔀 56 · 📦 1 · 📋 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 · ⭐ 13K) - Faker is a Python package that generates fake data for you. MIT +
Faker (🥇37 · ⭐ 13K) - Faker是一个Python软件包，可为您生成伪造数据。MIT - [GitHub](https://github.com/joke2k/faker) (👨‍💻 430 · 🔀 1.5K · 📦 45K · 📋 530 - 24% open · ⏱️ 07.12.2021): @@ -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 (🥇34 · ⭐ 12K) - The largest hub of ready-to-use NLP datasets for ML models with.. Apache-2 +
Datasets (🥇34 · ⭐ 12K) - 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) (👨‍💻 360 · 🔀 1.3K · 📦 2.4K · 📋 1.2K - 34% open · ⏱️ 14.12.2021): @@ -5703,7 +5703,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install datasets ```
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xmltodict (🥇31 · ⭐ 4.6K · 💀) - Python module that makes working with XML feel like you are.. MIT +
xmltodict (🥇31 · ⭐ 4.6K · 💀) - 像处理JSON一样处理XML。MIT - [GitHub](https://github.com/martinblech/xmltodict) (👨‍💻 41 · 🔀 420 · 📦 34K · 📋 200 - 32% open · ⏱️ 26.04.2020): @@ -5719,7 +5719,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge xmltodict ```
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Tablib (🥈29 · ⭐ 4.1K) - Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c. MIT +
Tablib (🥈29 · ⭐ 4.1K) - 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 · 🔀 550 · 📦 13K · 📋 240 - 11% open · ⏱️ 04.11.2021): @@ -5735,7 +5735,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge tablib ```
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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 · 🔀 410 · 📦 86K · ⏱️ 21.08.2021): @@ -5751,7 +5751,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge xlrd ```
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TensorFlow Datasets (🥈28 · ⭐ 3.1K) - TFDS is a collection of datasets ready to use with.. Apache-2 +
TensorFlow Datasets (🥈28 · ⭐ 3.1K) - TFDS是一个高级数据集合。Apache-2 - [GitHub](https://github.com/tensorflow/datasets) (👨‍💻 240 · 🔀 1.1K · 📋 910 - 33% open · ⏱️ 16.12.2021): @@ -5763,7 +5763,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install tensorflow-datasets ```
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snorkel (🥈27 · ⭐ 5K) - A system for quickly generating training data with weak supervision. Apache-2 +
snorkel (🥈27 · ⭐ 5K) - 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) (👨‍💻 74 · 🔀 780 · 📥 900 · 📦 140 · 📋 960 - 1% open · ⏱️ 04.12.2021): @@ -5779,7 +5779,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge snorkel ```
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csvkit (🥈27 · ⭐ 4.8K) - A suite of utilities for converting to and working with CSV, the king of.. MIT +
csvkit (🥈27 · ⭐ 4.8K) - 一套实用工具，可转换为CSV并操作。MIT - [GitHub](https://github.com/wireservice/csvkit) (👨‍💻 100 · 🔀 540 · 📦 970 · 📋 830 - 7% open · ⏱️ 08.10.2021): @@ -5795,7 +5795,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge csvkit ```
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PDFMiner (🥈26 · ⭐ 4.7K · 💀) - Python PDF Parser (Not actively maintained). Check out pdfminer.six. MIT +
PDFMiner (🥈26 · ⭐ 4.7K · 💀) - Python PDF解析器。MIT - [GitHub](https://github.com/euske/pdfminer) (👨‍💻 28 · 🔀 960 · 📦 2.7K · 📋 230 - 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 · ⭐ 2.3K) - Utils for streaming large files (S3, HDFS, gzip, bz2...). MIT +
smart-open (🥈26 · ⭐ 2.3K) - 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) (👨‍💻 89 · 🔀 290 · 📋 330 - 18% open · ⏱️ 02.12.2021): @@ -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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python-magic (🥉25 · ⭐ 2K) - A python wrapper for libmagic. ❗Unlicensed +
python-magic (🥉25 · ⭐ 2K) - 用于libmagic的python包装器。❗Unlicensed - [GitHub](https://github.com/ahupp/python-magic) (👨‍💻 53 · 🔀 220 · 📦 21K · 📋 160 - 14% open · ⏱️ 23.10.2021): @@ -5839,7 +5839,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge python-magic ```
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textract (🥉24 · ⭐ 3.2K) - extract text from any document. no muss. no fuss. MIT +
textract (🥉24 · ⭐ 3.2K) - 从任何文档中提取文本。MIT - [GitHub](https://github.com/deanmalmgren/textract) (👨‍💻 39 · 🔀 440 · 📋 200 - 37% open · ⏱️ 21.08.2021): @@ -5855,7 +5855,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge textract ```
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Intake (🥉24 · ⭐ 660) - Intake is a lightweight package for finding, investigating, loading and.. BSD-2 +
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 - [GitHub](https://github.com/intake/intake) (👨‍💻 67 · 🔀 110 · 📦 320 · 📋 280 - 25% open · ⏱️ 01.12.2021): @@ -5871,7 +5871,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge intake ```
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SDV (🥉23 · ⭐ 600) - Synthetic Data Generation for tabular, relational and time series data. MIT +
SDV (🥉23 · ⭐ 600) - 用于表格，关系和时间序列数据的综合数据生成。MIT - [GitHub](https://github.com/sdv-dev/SDV) (👨‍💻 39 · 🔀 100 · 📦 41 · 📋 410 - 33% open · ⏱️ 15.12.2021): @@ -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 · ⭐ 220 · 💤) - Python library for reading and writing tabular data via streams. MIT +
tabulator-py (🥉22 · ⭐ 220 · 💤) - 用于读取和写入图像数据的Python库。MIT - [GitHub](https://github.com/frictionlessdata/tabulator-py) (👨‍💻 27 · 🔀 42 · 📦 670 · ⏱️ 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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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 · 📦 220 · 📋 85 - 35% open · ⏱️ 13.11.2019): @@ -5911,7 +5911,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install messytables ```
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pandas-datareader (🥉20 · ⭐ 2.2K) - Extract data from a wide range of Internet sources.. ❗Unlicensed +
pandas-datareader (🥉20 · ⭐ 2.2K) - 从各种各样的网络来源中提取数据。❗Unlicensed - [GitHub](https://github.com/pydata/pandas-datareader) (👨‍💻 83 · 🔀 550 · 📋 480 - 19% open · ⏱️ 07.08.2021): @@ -5927,7 +5927,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge pandas-datareader ```
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pyexcel-xlsx (🥉20 · ⭐ 95 · 💀) - A wrapper library to read, manipulate and write data in.. ❗Unlicensed +
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 - [GitHub](https://github.com/pyexcel/pyexcel-xlsx) (👨‍💻 4 · 🔀 17 · 📥 51 · 📦 1.4K · 📋 33 - 39% open · ⏱️ 28.11.2020): @@ -5943,7 +5943,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s conda install -c conda-forge pyexcel-xlsx ```
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Camelot (🥉19 · ⭐ 3.1K · 💀) - Camelot: PDF Table Extraction for Humans. ❗Unlicensed +
Camelot (🥉19 · ⭐ 3.1K · 💀) - Camelot：简单的PDF表提取。❗Unlicensed - [GitHub](https://github.com/atlanhq/camelot) (👨‍💻 23 · 🔀 330 · 📋 350 - 21% open · ⏱️ 15.10.2019): @@ -5955,7 +5955,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install camelot-py ```
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datatest (🥉19 · ⭐ 250) - Tools for test driven data-wrangling and data validation. ❗Unlicensed +
datatest (🥉19 · ⭐ 250) - 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 · 🔀 12 · 📦 59 · 📋 52 - 19% open · ⏱️ 05.12.2021): @@ -5967,7 +5967,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install datatest ```
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Singer (🥉18 · ⭐ 910 · 💤) - Standard for moving data between databases, web APIs, files,.. ❗️AGPL-3.0 +
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 - [GitHub](https://github.com/singer-io/getting-started) (👨‍💻 26 · 🔀 120 · 📋 37 - 51% open · ⏱️ 29.04.2021): @@ -5979,7 +5979,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install singer-python ```
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rows (🥉18 · ⭐ 780) - A common, beautiful interface to tabular data, no matter the format. ❗️LGPL-3.0 +
rows (🥉18 · ⭐ 780) - 通用美观的表格数据界面。❗️LGPL-3.0 - [GitHub](https://github.com/turicas/rows) (👨‍💻 30 · 🔀 130 · 📥 37 · 📦 130 · 📋 290 - 48% open · ⏱️ 13.12.2021): @@ -5991,7 +5991,7 @@ _Libraries for loading, collecting, and extracting data from a variety of data s pip install rows ```
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openpyxl (🥉15 · ⭐ 31) - A Python library to read/write Excel 2010 xlsx/xlsm files. MIT +
openpyxl (🥉15 · ⭐ 31) - 一个用于读取/写入Excel 2010 xlsx/xlsm文件的Python库。MIT - [PyPi](https://pypi.org/project/openpyxl) (📥 20M / 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 ( ⭐ 1.4K) - 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 (🥇37 · ⭐ 18K) - Asynchronous task queue/job queue based on distributed message.. ❗Unlicensed +
Celery (🥇37 · ⭐ 18K) - 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 · 🔀 4K · 📦 62K · 📋 4.6K - 9% open · ⏱️ 16.12.2021): @@ -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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joblib (🥇34 · ⭐ 2.6K) - Computing with Python functions. BSD-3 +
joblib (🥇34 · ⭐ 2.6K) - 使用Python函数进行计算。BSD-3 - [GitHub](https://github.com/joblib/joblib) (👨‍💻 110 · 🔀 300 · 📦 150K · 📋 660 - 43% open · ⏱️ 08.11.2021): @@ -6061,7 +6061,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge joblib ```
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Dagster (🥇31 · ⭐ 4.1K) - A data orchestrator for machine learning, analytics, and ETL. Apache-2 +
Dagster (🥇31 · ⭐ 4.1K) - 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) (👨‍💻 180 · 🔀 480 · 📦 270 · 📋 3.5K - 22% open · ⏱️ 16.12.2021): @@ -6077,7 +6077,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge dagster ```
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Airflow (🥇29 · ⭐ 24K) - Platform to programmatically author, schedule, and monitor workflows. Apache-2 +
Airflow (🥇29 · ⭐ 24K) - 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) (👨‍💻 2.2K · 🔀 9.4K · 📥 220K · 📋 4.6K - 17% open · ⏱️ 16.12.2021): @@ -6097,7 +6097,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched docker pull apache/airflow ```
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Prefect (🥇29 · ⭐ 7.9K) - The easiest way to automate your data. Apache-2 +
Prefect (🥇29 · ⭐ 7.9K) - 自动化数据的最简单方法。Apache-2 - [GitHub](https://github.com/PrefectHQ/prefect) (👨‍💻 280 · 🔀 730 · 📦 530 · 📋 2K - 18% open · ⏱️ 15.12.2021): @@ -6113,7 +6113,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge prefect ```
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Beam (🥇29 · ⭐ 5.1K) - Unified programming model to define and execute data processing.. ❗Unlicensed +
Beam (🥇29 · ⭐ 5.1K) - 统一的编程模型，用于定义和执行数据处理。❗Unlicensed - [GitHub](https://github.com/apache/beam) (👨‍💻 1.2K · 🔀 3.2K · ⏱️ 16.12.2021): @@ -6125,7 +6125,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install apache-beam ```
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luigi (🥈28 · ⭐ 15K) - Luigi is a Python module that helps you build complex pipelines of batch.. Apache-2 +
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 - [GitHub](https://github.com/spotify/luigi) (👨‍💻 570 · 🔀 2.2K · 📦 1.6K · 📋 920 - 7% open · ⏱️ 27.11.2021): @@ -6141,7 +6141,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c anaconda luigi ```
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rq (🥈28 · ⭐ 8.1K) - Simple job queues for Python. ❗Unlicensed +
rq (🥈28 · ⭐ 8.1K) - 适用于Python的简单作业队列。❗Unlicensed - [GitHub](https://github.com/rq/rq) (👨‍💻 250 · 🔀 1.2K · 📦 9.2K · 📋 930 - 16% open · ⏱️ 11.12.2021): @@ -6157,7 +6157,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge rq ```
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dbt (🥈28 · ⭐ 3.9K) - dbt (data build tool) enables data analysts and engineers to transform.. Apache-2 +
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): @@ -6173,7 +6173,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge dbt ```
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mrjob (🥈27 · ⭐ 2.6K · 💀) - Run MapReduce jobs on Hadoop or Amazon Web Services. Apache-2 +
mrjob (🥈27 · ⭐ 2.6K · 💀) - 在Hadoop或Amazon Web Services上运行MapReduce作业。Apache-2 - [GitHub](https://github.com/Yelp/mrjob) (👨‍💻 140 · 🔀 570 · 📦 900 · 📋 1.3K - 15% open · ⏱️ 16.11.2020): @@ -6189,7 +6189,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge mrjob ```
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petl (🥈27 · ⭐ 950) - Python Extract Transform and Load Tables of Data. MIT +
petl (🥈27 · ⭐ 950) - Python提取转换并加载数据表。MIT - [GitHub](https://github.com/petl-developers/petl) (👨‍💻 51 · 🔀 160 · 📦 580 · 📋 420 - 17% open · ⏱️ 16.12.2021): @@ -6205,7 +6205,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched conda install -c conda-forge petl ```
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faust (🥈26 · ⭐ 5.9K · 💀) - Python Stream Processing. ❗Unlicensed +
faust (🥈26 · ⭐ 5.9K · 💀) - Python流处理。❗Unlicensed - [GitHub](https://github.com/robinhood/faust) (👨‍💻 93 · 🔀 490 · 📦 900 · 📋 460 - 48% open · ⏱️ 09.10.2020): @@ -6217,7 +6217,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install faust ```
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Kedro (🥈26 · ⭐ 4.8K) - A Python framework for creating reproducible, maintainable and modular.. Apache-2 +
Kedro (🥈26 · ⭐ 4.8K) - 用于创建可重现，可维护和模块化的Python框架。Apache-2 - [GitHub](https://github.com/quantumblacklabs/kedro) (👨‍💻 130 · 🔀 530 · 📦 640 · 📋 590 - 7% open · ⏱️ 16.12.2021): @@ -6229,7 +6229,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install kedro ```
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Hub (🥈26 · ⭐ 4K) - Fastest unstructured dataset management for TensorFlow/PyTorch... MPL-2.0 +
Hub (🥈26 · ⭐ 4K) - TensorFlow/PyTorch最快的非结构化数据集管理。MPL-2.0 - [GitHub](https://github.com/activeloopai/Hub) (👨‍💻 88 · 🔀 320 · 📦 140 · 📋 310 - 14% open · ⏱️ 16.12.2021): @@ -6241,7 +6241,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install hub ```
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Great Expectations (🥈24 · ⭐ 5.8K) - Always know what to expect from your data. Apache-2 +
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 - [GitHub](https://github.com/great-expectations/great_expectations) (👨‍💻 250 · 🔀 780 · 📋 1.1K - 11% open · ⏱️ 16.12.2021): @@ -6253,7 +6253,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install great_expectations ```
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TaskTiger (🥉22 · ⭐ 1.1K) - Python task queue using Redis. MIT +
TaskTiger (🥉22 · ⭐ 1.1K) - 使用Redis的Python任务队列。MIT - [GitHub](https://github.com/closeio/tasktiger) (👨‍💻 24 · 🔀 59 · 📦 21 · 📋 57 - 38% open · ⏱️ 02.12.2021): @@ -6265,7 +6265,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install tasktiger ```
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PyFunctional (🥉21 · ⭐ 1.9K) - Python library for creating data pipelines with chain functional.. MIT +
PyFunctional (🥉21 · ⭐ 1.9K) - 用于创建具有链功能的数据管道的Python库。MIT - [GitHub](https://github.com/EntilZha/PyFunctional) (👨‍💻 25 · 🔀 100 · 📦 370 · 📋 120 - 4% open · ⏱️ 05.11.2021): @@ -6277,7 +6277,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pyfunctional ```
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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 · 🔀 120 · 📦 130 · 📋 180 - 38% open · ⏱️ 10.03.2021): @@ -6289,7 +6289,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install bonobo ```
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streamparse (🥉21 · ⭐ 1.4K · 💤) - Run Python in Apache Storm topologies. Pythonic API,.. ❗Unlicensed +
streamparse (🥉21 · ⭐ 1.4K · 💤) - 在Apache Storm拓扑中运行Python。 Pythonic API，CLI 等。❗Unlicensed - [GitHub](https://github.com/Parsely/streamparse) (👨‍💻 41 · 🔀 210 · 📦 52 · 📋 320 - 19% open · ⏱️ 18.12.2020): @@ -6301,7 +6301,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install streamparse ```
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pysparkling (🥉21 · ⭐ 240 · 💤) - A pure Python implementation of Apache Spark's RDD and.. ❗Unlicensed +
pysparkling (🥉21 · ⭐ 240 · 💤) - Apache Spark的RDD和DStream的纯Python实现。❗Unlicensed - [GitHub](https://github.com/svenkreiss/pysparkling) (👨‍💻 10 · 🔀 41 · 📦 81 · 📋 27 - 22% open · ⏱️ 22.02.2021): @@ -6313,7 +6313,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pysparkling ```
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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 · 📦 4 · ⏱️ 25.12.2020): @@ -6325,7 +6325,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install dpark ```
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TFX (🥉20 · ⭐ 1.7K) - TFX is an end-to-end platform for deploying production ML pipelines. Apache-2 +
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 - [GitHub](https://github.com/tensorflow/tfx) (👨‍💻 120 · 🔀 510 · 📋 710 - 32% open · ⏱️ 16.12.2021): @@ -6337,7 +6337,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install tfx ```
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mrq (🥉20 · ⭐ 860 · 💤) - Mr. Queue - A distributed worker task queue in Python using Redis & gevent. MIT +
mrq (🥉20 · ⭐ 860 · 💤) - 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) (👨‍💻 37 · 🔀 110 · 📦 27 · 📋 170 - 30% open · ⏱️ 13.12.2020): @@ -6349,7 +6349,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install mrq ```
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ploomber (🥉20 · ⭐ 790) - Lean Data Science workflows: develop and test locally. Deploy to.. Apache-2 +
ploomber (🥉20 · ⭐ 790) - 精益数据科学工作流程。Apache-2 - [GitHub](https://github.com/ploomber/ploomber) (👨‍💻 23 · 🔀 64 · 📦 22 · 📋 400 - 19% open · ⏱️ 13.12.2021): @@ -6361,7 +6361,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install ploomber ```
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zenml (🥉18 · ⭐ 1.5K) - ZenML : MLOps framework to create reproducible ML pipelines for.. Apache-2 +
zenml (🥉18 · ⭐ 1.5K) - ZenML：MLOps框架。Apache-2 - [GitHub](https://github.com/zenml-io/zenml) (👨‍💻 21 · 🔀 83 · 📋 49 - 8% open · ⏱️ 16.12.2021): @@ -6373,7 +6373,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install zenml ```
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Optimus (🥉18 · ⭐ 1.1K) - Agile Data Preparation Workflows madeeasy with pandas, dask,.. Apache-2 +
Optimus (🥉18 · ⭐ 1.1K) - 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 · 🔀 200 · 📋 220 - 13% open · ⏱️ 09.12.2021): @@ -6385,7 +6385,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install optimuspyspark ```
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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) (👨‍💻 16 · 🔀 460 · 📦 19 · 📋 100 - 73% open · ⏱️ 19.08.2021): @@ -6393,7 +6393,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched git clone https://github.com/databricks/spark-deep-learning ```
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BatchFlow (🥉17 · ⭐ 170) - BatchFlow helps you conveniently work with random or sequential.. Apache-2 +
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 - [GitHub](https://github.com/analysiscenter/batchflow) (👨‍💻 30 · 🔀 37 · 📋 100 - 33% open · ⏱️ 14.12.2021): @@ -6405,7 +6405,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install batchflow ```
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Mara Pipelines (🥉16 · ⭐ 1.8K) - A lightweight opinionated ETL framework, halfway between plain.. MIT +
Mara Pipelines (🥉16 · ⭐ 1.8K) - 一个轻量级的ETL框架。MIT - [GitHub](https://github.com/mara/mara-pipelines) (👨‍💻 16 · 🔀 85 · 📦 8 · 📋 18 - 33% open · ⏱️ 18.09.2021): @@ -6417,7 +6417,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install mara-pipelines ```
-
riko (🥉16 · ⭐ 1.6K · 💀) - A Python stream processing engine modeled after Yahoo! Pipes. MIT +
riko (🥉16 · ⭐ 1.6K · 💀) - 一个模仿Yahoo!的Python流处理引擎。MIT - [GitHub](https://github.com/nerevu/riko) (👨‍💻 18 · 🔀 67 · 📋 29 - 72% open · ⏱️ 14.08.2020): @@ -6429,7 +6429,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install riko ```
-
pdpipe (🥉16 · ⭐ 630) - Easy pipelines for pandas DataFrames. ❗Unlicensed +
pdpipe (🥉16 · ⭐ 630) - pandas DataFrames的简单管道。❗Unlicensed - [GitHub](https://github.com/pdpipe/pdpipe) (👨‍💻 9 · 🔀 29 · 📦 38 · 📋 38 - 39% open · ⏱️ 14.12.2021): @@ -6441,7 +6441,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pdpipe ```
-
Pypeline (🥉15 · ⭐ 1.3K · 💤) - Concurrent data pipelines in Python . MIT +
Pypeline (🥉15 · ⭐ 1.3K · 💤) - Python中的并发数据管道。MIT - [GitHub](https://github.com/cgarciae/pypeln) (👨‍💻 10 · 🔀 73 · 📋 52 - 26% open · ⏱️ 13.04.2021): @@ -6453,7 +6453,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install pypeln ```
-
Databolt Flow (🥉15 · ⭐ 940) - Python library for building highly effective data science workflows. 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 · 🔀 68 · 📦 17 · 📋 22 - 40% open · ⏱️ 28.09.2021): @@ -6465,7 +6465,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install d6tflow ```
-
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 · ⏱️ 05.11.2021): @@ -6477,7 +6477,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install flupy ```
-
bodywork-core (🥉12 · ⭐ 310) - MLOps tool for deploying machine learning projects to.. ❗️AGPL-3.0 +
bodywork-core (🥉12 · ⭐ 310) - 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 · 🔀 14 · 📦 9 · 📋 55 - 21% open · ⏱️ 05.07.2021): @@ -6489,7 +6489,7 @@ _Libraries for data batch- and stream-processing, workflow automation, job sched pip install bodywork-core ```
-
Botflow (🥉11 · ⭐ 1.2K · 💀) - Python Fast Dataflow programming framework for Data pipeline.. ❗Unlicensed +
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 - [GitHub](https://github.com/kkyon/botflow) (👨‍💻 11 · 🔀 100 · 📦 1 · 📋 4 - 50% 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。_ -
dask (🥇32 · ⭐ 9.3K) - Parallel computing with task scheduling. BSD-3 +
dask (🥇32 · ⭐ 9.3K) - 具有任务调度的并行计算。BSD-3 - [GitHub](https://github.com/dask/dask) (👨‍💻 490 · 🔀 1.4K · 📦 32K · 📋 4K - 16% open · ⏱️ 15.12.2021): @@ -6525,7 +6525,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge dask ```
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Ray (🥇28 · ⭐ 19K) - An open source framework that provides a simple, universal API for.. Apache-2 +
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 - [GitHub](https://github.com/ray-project/ray) (👨‍💻 600 · 🔀 3K · 📦 3.5K · 📋 8.6K - 21% open · ⏱️ 16.12.2021): @@ -6537,7 +6537,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install ray ```
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dask.distributed (🥇28 · ⭐ 1.3K) - A distributed task scheduler for Dask. ❗Unlicensed +
dask.distributed (🥇28 · ⭐ 1.3K) - Dask的分布式任务调度规划程序。❗Unlicensed - [GitHub](https://github.com/dask/distributed) (👨‍💻 260 · 🔀 560 · 📦 21K · 📋 2.4K - 29% open · ⏱️ 14.12.2021): @@ -6553,7 +6553,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge distributed ```
-
DEAP (🥈27 · ⭐ 4.5K) - Distributed Evolutionary Algorithms in Python. ❗️LGPL-3.0 +
DEAP (🥈27 · ⭐ 4.5K) - Python中的分布式进化算法。❗️LGPL-3.0 - [GitHub](https://github.com/DEAP/deap) (👨‍💻 76 · 🔀 920 · 📦 2.3K · 📋 430 - 42% open · ⏱️ 21.11.2021): @@ -6569,7 +6569,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge deap ```
-
Mesh (🥈27 · ⭐ 1.2K) - Mesh TensorFlow: Model Parallelism Made Easier. Apache-2 +
Mesh (🥈27 · ⭐ 1.2K) - Mesh TensorFlow：简化模型并行化。Apache-2 - [GitHub](https://github.com/tensorflow/mesh) (👨‍💻 44 · 🔀 200 · 📦 610 · 📋 75 - 81% open · ⏱️ 18.10.2021): @@ -6581,7 +6581,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install mesh-tensorflow ```
-
BigDL (🥈26 · ⭐ 3.8K) - BigDL: Distributed Deep Learning Framework for Apache Spark. Apache-2 +
BigDL (🥈26 · ⭐ 3.8K) - 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) (👨‍💻 130 · 🔀 890 · 📦 31 · 📋 1K - 25% open · ⏱️ 16.12.2021): @@ -6601,7 +6601,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn ```
-
analytics-zoo (🥈25 · ⭐ 2.4K) - Distributed Tensorflow, Keras and PyTorch on Apache.. Apache-2 +
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): @@ -6613,7 +6613,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install analytics-zoo ```
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horovod (🥈24 · ⭐ 12K) - Distributed training framework for TensorFlow, Keras, PyTorch,.. ❗Unlicensed +
horovod (🥈24 · ⭐ 12K) - 基于TensorFlow，Keras，PyTorch，MXNet等的分布式训练框架。❗Unlicensed - [GitHub](https://github.com/horovod/horovod) (👨‍💻 140 · 🔀 1.9K · 📦 480 · 📋 1.9K - 13% open · ⏱️ 16.12.2021): @@ -6625,7 +6625,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install horovod ```
-
DeepSpeed (🥈24 · ⭐ 6K) - DeepSpeed is a deep learning optimization library that makes.. MIT +
DeepSpeed (🥈24 · ⭐ 6K) - DeepSpeed是一个深度学习优化库。MIT - [GitHub](https://github.com/microsoft/DeepSpeed) (👨‍💻 86 · 🔀 640 · 📦 130 · 📋 720 - 47% open · ⏱️ 15.12.2021): @@ -6641,7 +6641,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull deepspeed/deepspeed ```
-
MMLSpark (🥈23 · ⭐ 2.9K) - Microsoft Machine Learning for Apache Spark. MIT +
MMLSpark (🥈23 · ⭐ 2.9K) - 适用于Apache Spark的Microsoft机器学习。MIT - [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 78 · 🔀 590 · 📋 480 - 40% open · ⏱️ 15.12.2021): @@ -6653,7 +6653,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install mmlspark ```
-
dask-ml (🥈23 · ⭐ 770) - Scalable Machine Learning with Dask. BSD-3 +
dask-ml (🥈23 · ⭐ 770) - 使用Dask进行可扩展的机器学习。BSD-3 - [GitHub](https://github.com/dask/dask-ml) (👨‍💻 69 · 🔀 210 · 📦 530 · 📋 420 - 44% open · ⏱️ 30.11.2021): @@ -6669,7 +6669,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge dask-ml ```
-
Elephas (🥉22 · ⭐ 1.5K) - Distributed Deep learning with Keras & Spark. MIT keras +
Elephas (🥉22 · ⭐ 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 · 📦 51 · 📋 150 - 10% open · ⏱️ 17.08.2021): @@ -6681,7 +6681,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install elephas ```
-
petastorm (🥉22 · ⭐ 1.3K) - Petastorm library enables single machine or distributed training.. Apache-2 +
petastorm (🥉22 · ⭐ 1.3K) - Petastorm库单机或分布式训练。Apache-2 - [GitHub](https://github.com/uber/petastorm) (👨‍💻 43 · 🔀 220 · 📥 310 · 📦 53 · 📋 260 - 49% open · ⏱️ 27.10.2021): @@ -6693,7 +6693,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install petastorm ```
-
ipyparallel (🥉21 · ⭐ 2.1K) - Interactive Parallel Computing in Python. ❗Unlicensed +
ipyparallel (🥉21 · ⭐ 2.1K) - Python中的交互式并行计算。❗Unlicensed - [GitHub](https://github.com/ipython/ipyparallel) (👨‍💻 100 · 🔀 810 · 📦 1.8K · 📋 310 - 15% open · ⏱️ 08.12.2021): @@ -6709,7 +6709,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge ipyparallel ```
-
mpi4py (🥉21 · ⭐ 480) - Python bindings for MPI. BSD-2 +
mpi4py (🥉21 · ⭐ 480) - MPI的Python接口。BSD-2 - [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 20 · 🔀 74 · 📥 2.7K · 📋 54 - 24% open · ⏱️ 25.11.2021): @@ -6725,7 +6725,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge mpi4py ```
-
Apache Singa (🥉19 · ⭐ 2.4K) - a distributed deep learning platform. Apache-2 +
Apache Singa (🥉19 · ⭐ 2.4K) - 分布式深度学习平台。Apache-2 - [GitHub](https://github.com/apache/singa) (👨‍💻 76 · 🔀 720 · 📦 1 · 📋 67 - 26% open · ⏱️ 10.08.2021): @@ -6741,7 +6741,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull apache/singa ```
-
FairScale (🥉19 · ⭐ 1.5K) - PyTorch extensions for high performance and large scale training. BSD-3 +
FairScale (🥉19 · ⭐ 1.5K) - PyTorch扩展用于高性能和大规模训练。BSD-3 - [GitHub](https://github.com/facebookresearch/fairscale) (👨‍💻 51 · 🔀 140 · 📦 120 · 📋 250 - 21% open · ⏱️ 16.12.2021): @@ -6753,7 +6753,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install fairscale ```
-
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 · 📋 91 - 52% open · ⏱️ 15.11.2019): @@ -6765,7 +6765,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install tensorframes ```
-
somoclu (🥉19 · ⭐ 230) - Massively parallel self-organizing maps: accelerate training on.. MIT +
somoclu (🥉19 · ⭐ 230) - 大规模并行的自组织图：加速训练。MIT - [GitHub](https://github.com/peterwittek/somoclu) (👨‍💻 19 · 🔀 61 · 📥 1.5K · 📋 130 - 18% open · ⏱️ 31.10.2021): @@ -6781,7 +6781,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge somoclu ```
-
TensorFlowOnSpark (🥉18 · ⭐ 3.7K) - TensorFlowOnSpark brings TensorFlow programs to.. Apache-2 +
TensorFlowOnSpark (🥉18 · ⭐ 3.7K) - TensorFlowOnSpark将TensorFlow程序引入Spark。Apache-2 - [GitHub](https://github.com/yahoo/TensorFlowOnSpark) (👨‍💻 33 · 🔀 920 · 📋 360 - 1% open · ⏱️ 15.10.2021): @@ -6793,7 +6793,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install tensorflowonspark ```
-
Hivemind (🥉17 · ⭐ 880) - Decentralized deep learning in PyTorch. Built to train models on.. MIT +
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): @@ -6805,7 +6805,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install hivemind ```
-
BytePS (🥉16 · ⭐ 3K) - A high performance and generic framework for distributed DNN training. Apache-2 +
BytePS (🥉16 · ⭐ 3K) - 分布式DNN训练的高性能通用框架。Apache-2 - [GitHub](https://github.com/bytedance/byteps) (👨‍💻 19 · 🔀 420 · 📋 250 - 37% open · ⏱️ 12.10.2021): @@ -6821,7 +6821,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn docker pull bytepsimage/tensorflow ```
-
Fiber (🥉16 · ⭐ 950 · 💤) - Distributed Computing for AI Made Simple. Apache-2 +
Fiber (🥉16 · ⭐ 950 · 💤) - 简化了AI的分布式计算。Apache-2 - [GitHub](https://github.com/uber/fiber) (👨‍💻 5 · 🔀 100 · 📦 30 · 📋 24 - 66% open · ⏱️ 15.03.2021): @@ -6833,7 +6833,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install fiber ```
-
Submit it (🥉15 · ⭐ 510) - Python 3.6+ toolbox for submitting jobs to Slurm. MIT +
Submit it (🥉15 · ⭐ 510) - 用于将作业提交到Slurm的Python工具箱。MIT - [GitHub](https://github.com/facebookincubator/submitit) (👨‍💻 17 · 🔀 48 · 📋 53 - 41% open · ⏱️ 09.12.2021): @@ -6849,7 +6849,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn conda install -c conda-forge submitit ```
-
sk-dist (🥉12 · ⭐ 270) - Distributed scikit-learn meta-estimators in PySpark. Apache-2 +
sk-dist (🥉12 · ⭐ 270) - PySpark中的分布式scikit学习元估计器。Apache-2 - [GitHub](https://github.com/Ibotta/sk-dist) (👨‍💻 7 · 🔀 46 · 📦 8 · 📋 17 - 41% open · ⏱️ 07.07.2021): @@ -6861,7 +6861,7 @@ _Libraries that provide capabilities to distribute and parallelize machine learn pip install sk-dist ```
-
LazyCluster (🥉10 · ⭐ 43) - Distributed machine learning made simple. Apache-2 +
LazyCluster (🥉10 · ⭐ 43) - 分布式机器学习框架。Apache-2 - [GitHub](https://github.com/ml-tooling/lazycluster) (👨‍💻 2 · 🔀 8 · 📦 7 · ⏱️ 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 (🥇33 · ⭐ 5.7K) - A hyperparameter optimization framework. MIT +
Optuna (🥇33 · ⭐ 5.7K) - 超参数优化框架。MIT - [GitHub](https://github.com/optuna/optuna) (👨‍💻 170 · 🔀 620 · 📦 2.3K · 📋 1K - 11% open · ⏱️ 16.12.2021): @@ -6897,7 +6897,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge optuna ```
-
scikit-optimize (🥇31 · ⭐ 2.3K) - Sequential model-based optimization with a `scipy.optimize`.. BSD-3 +
scikit-optimize (🥇31 · ⭐ 2.3K) - SMBO模型优化实现。BSD-3 - [GitHub](https://github.com/scikit-optimize/scikit-optimize) (👨‍💻 75 · 🔀 410 · 📦 2.2K · 📋 580 - 34% open · ⏱️ 12.10.2021): @@ -6913,7 +6913,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge scikit-optimize ```
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Keras Tuner (🥇30 · ⭐ 2.4K · 📈) - Hyperparameter tuning for humans. Apache-2 +
Keras Tuner (🥇30 · ⭐ 2.4K · 📈) - 简单易用的超参数调整。Apache-2 - [GitHub](https://github.com/keras-team/keras-tuner) (👨‍💻 41 · 🔀 310 · 📦 1K · 📋 360 - 45% open · ⏱️ 10.12.2021): @@ -6925,7 +6925,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install keras-tuner ```
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Bayesian Optimization (🥇29 · ⭐ 5.6K · 💤) - A Python implementation of global optimization with.. MIT +
Bayesian Optimization (🥇29 · ⭐ 5.6K · 💤) - 全局优化的Python实现。MIT - [GitHub](https://github.com/fmfn/BayesianOptimization) (👨‍💻 27 · 🔀 1.2K · 📥 70 · 📦 990 · 📋 220 - 20% open · ⏱️ 19.12.2020): @@ -6937,7 +6937,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install bayesian-optimization ```
-
Hyperopt (🥇28 · ⭐ 6K) - Distributed Asynchronous Hyperparameter Optimization in Python. ❗Unlicensed +
Hyperopt (🥇28 · ⭐ 6K) - Python中的分布式异步超参数优化。❗Unlicensed - [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 93 · 🔀 810 · 📦 5.4K · 📋 590 - 60% open · ⏱️ 29.11.2021): @@ -6953,7 +6953,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge hyperopt ```
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featuretools (🥇28 · ⭐ 5.9K) - An open source python library for automated feature engineering. BSD-3 +
featuretools (🥇28 · ⭐ 5.9K) - 一个用于自动化特征工程的开源python库。BSD-3 - [GitHub](https://github.com/alteryx/featuretools) (👨‍💻 57 · 🔀 750 · 📦 890 · 📋 700 - 21% open · ⏱️ 12.12.2021): @@ -6969,7 +6969,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge featuretools ```
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TPOT (🥈27 · ⭐ 8.4K · 💤) - A Python Automated Machine Learning tool that optimizes.. ❗️LGPL-3.0 +
TPOT (🥈27 · ⭐ 8.4K · 💤) - Python自动化机器学习工具。❗️LGPL-3.0 - [GitHub](https://github.com/EpistasisLab/tpot) (👨‍💻 110 · 🔀 1.4K · 📦 1.2K · 📋 830 - 27% open · ⏱️ 06.01.2021): @@ -6985,7 +6985,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge tpot ```
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AutoKeras (🥈26 · ⭐ 8.3K) - AutoML library for deep learning. Apache-2 +
AutoKeras (🥈26 · ⭐ 8.3K) - 用于深度学习的AutoML库。Apache-2 - [GitHub](https://github.com/keras-team/autokeras) (👨‍💻 130 · 🔀 1.3K · 📥 1.7K · 📦 260 · 📋 790 - 7% open · ⏱️ 04.12.2021): @@ -6997,7 +6997,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autokeras ```
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AutoGluon (🥈26 · ⭐ 3.9K) - AutoGluon: AutoML for Text, Image, and Tabular Data. Apache-2 +
AutoGluon (🥈26 · ⭐ 3.9K) - AutoGluon：用于文本，图像和表格数据的AutoML。Apache-2 - [GitHub](https://github.com/awslabs/autogluon) (👨‍💻 62 · 🔀 500 · 📦 86 · 📋 560 - 22% open · ⏱️ 16.12.2021): @@ -7009,7 +7009,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autogluon ```
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BoTorch (🥈26 · ⭐ 2.1K) - Bayesian optimization in PyTorch. MIT +
BoTorch (🥈26 · ⭐ 2.1K) - PyTorch中的贝叶斯优化。MIT - [GitHub](https://github.com/pytorch/botorch) (👨‍💻 64 · 🔀 230 · 📦 190 · 📋 230 - 21% open · ⏱️ 14.12.2021): @@ -7021,7 +7021,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install botorch ```
-
Ax (🥈26 · ⭐ 1.7K) - Adaptive Experimentation Platform. MIT +
Ax (🥈26 · ⭐ 1.7K) - 自适应实验平台。MIT - [GitHub](https://github.com/facebook/Ax) (👨‍💻 110 · 🔀 170 · 📦 220 · 📋 320 - 6% open · ⏱️ 16.12.2021): @@ -7033,7 +7033,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install ax-platform ```
-
NNI (🥈25 · ⭐ 11K) - An open source AutoML toolkit for automate machine learning lifecycle,.. MIT +
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): @@ -7045,7 +7045,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install nni ```
-
auto-sklearn (🥈24 · ⭐ 5.9K) - Automated Machine Learning with scikit-learn. BSD-3 +
auto-sklearn (🥈24 · ⭐ 5.9K) - 使用scikit-learn的自动化机器学习。BSD-3 - [GitHub](https://github.com/automl/auto-sklearn) (👨‍💻 77 · 🔀 1.1K · 📦 240 · 📋 810 - 11% open · ⏱️ 09.11.2021): @@ -7057,7 +7057,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install auto-sklearn ```
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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 · 📦 220 · 📋 250 - 36% open · ⏱️ 19.11.2021): @@ -7069,7 +7069,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install hyperas ```
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nevergrad (🥈23 · ⭐ 3.2K) - A Python toolbox for performing gradient-free optimization. MIT +
nevergrad (🥈23 · ⭐ 3.2K) - 用于执行无梯度优化(gradient-free optimization)的Python工具箱。MIT - [GitHub](https://github.com/facebookresearch/nevergrad) (👨‍💻 46 · 🔀 300 · 📦 270 · 📋 210 - 27% open · ⏱️ 15.12.2021): @@ -7085,7 +7085,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc conda install -c conda-forge nevergrad ```
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GPyOpt (🥈23 · ⭐ 780 · 💀) - Gaussian Process Optimization using GPy. BSD-3 +
GPyOpt (🥈23 · ⭐ 780 · 💀) - 使用GPy进行高斯过程优化。BSD-3 - [GitHub](https://github.com/SheffieldML/GPyOpt) (👨‍💻 49 · 🔀 240 · 📦 230 · 📋 280 - 34% open · ⏱️ 05.11.2020): @@ -7097,7 +7097,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install gpyopt ```
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SMAC3 (🥈21 · ⭐ 640) - Sequential Model-based Algorithm Configuration. ❗Unlicensed +
SMAC3 (🥈21 · ⭐ 640) - Sequential Model-based算法的配置。❗Unlicensed - [GitHub](https://github.com/automl/SMAC3) (👨‍💻 38 · 🔀 160 · 📋 350 - 18% open · ⏱️ 05.11.2021): @@ -7109,7 +7109,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install smac ```
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mljar-supervised (🥈20 · ⭐ 1.7K) - Automated Machine Learning Pipeline with Feature Engineering.. MIT +
mljar-supervised (🥈20 · ⭐ 1.7K) - 使用scikit-learn的自动化机器学习。MIT - [GitHub](https://github.com/mljar/mljar-supervised) (👨‍💻 14 · 🔀 240 · 📦 33 · 📋 450 - 16% open · ⏱️ 06.12.2021): @@ -7133,7 +7133,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install auto_ml ```
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Talos (🥈20 · ⭐ 1.5K · 💤) - Hyperparameter Optimization for TensorFlow, Keras and PyTorch. MIT +
Talos (🥈20 · ⭐ 1.5K · 💤) - TensorFlow，Keras和PyTorch的超参数优化。MIT - [GitHub](https://github.com/autonomio/talos) (👨‍💻 19 · 🔀 250 · 📦 130 · 📋 390 - 8% open · ⏱️ 27.05.2021): @@ -7145,7 +7145,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install talos ```
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MLBox (🥈20 · ⭐ 1.3K · 💀) - MLBox is a powerful Automated Machine Learning python library. ❗Unlicensed +
MLBox (🥈20 · ⭐ 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 · 🔀 260 · 📦 28 · 📋 90 - 17% open · ⏱️ 25.08.2020): @@ -7157,7 +7157,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install mlbox ```
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lazypredict (🥈20 · ⭐ 270) - Lazy Predict help build a lot of basic models without much code.. MIT +
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 - [GitHub](https://github.com/shankarpandala/lazypredict) (👨‍💻 16 · 🔀 36 · 📦 210 · 📋 59 - 49% open · ⏱️ 18.10.2021): @@ -7169,7 +7169,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install lazypredict ```
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AdaNet (🥉19 · ⭐ 3.3K) - Fast and flexible AutoML with learning guarantees. Apache-2 +
AdaNet (🥉19 · ⭐ 3.3K) - 具有学习保证的快速灵活的AutoML。Apache-2 - [GitHub](https://github.com/tensorflow/adanet) (👨‍💻 27 · 🔀 520 · 📦 41 · 📋 110 - 58% open · ⏱️ 30.08.2021): @@ -7181,7 +7181,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install adanet ```
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sklearn-deap (🥉19 · ⭐ 670) - Use evolutionary algorithms instead of gridsearch in.. MIT +
sklearn-deap (🥉19 · ⭐ 670) - 使用进化算法而非gridsearch的超参数优化。MIT - [GitHub](https://github.com/rsteca/sklearn-deap) (👨‍💻 22 · 🔀 110 · 📦 30 · 📋 50 - 32% open · ⏱️ 30.07.2021): @@ -7193,7 +7193,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install sklearn-deap ```
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HpBandSter (🥉19 · ⭐ 500 · 💀) - a distributed Hyperband implementation on Steroids. BSD-3 +
HpBandSter (🥉19 · ⭐ 500 · 💀) - 分布式自动化机器学习库。BSD-3 - [GitHub](https://github.com/automl/HpBandSter) (👨‍💻 11 · 🔀 110 · 📦 190 · 📋 86 - 59% open · ⏱️ 26.03.2019): @@ -7205,7 +7205,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install hpbandster ```
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Neuraxle (🥉19 · ⭐ 490) - A Sklearn-like Framework for Hyperparameter Tuning and AutoML in.. Apache-2 +
Neuraxle (🥉19 · ⭐ 490) - 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 · 📦 24 · 📋 310 - 41% open · ⏱️ 01.11.2021): @@ -7217,7 +7217,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install neuraxle ```
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Test Tube (🥉18 · ⭐ 700 · 💀) - Python library to easily log experiments and parallelize.. MIT +
Test Tube (🥉18 · ⭐ 700 · 💀) - 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 · 🔀 64 · 📥 10 · 📋 44 - 52% open · ⏱️ 17.03.2020): @@ -7229,7 +7229,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install test_tube ```
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AlphaPy (🥉18 · ⭐ 680) - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras,.. Apache-2 +
AlphaPy (🥉18 · ⭐ 680) - 使用scikit-learn的自动化机器学习。Apache-2 - [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (👨‍💻 3 · 🔀 140 · 📦 3 · 📋 40 - 27% open · ⏱️ 23.10.2021): @@ -7241,7 +7241,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install alphapy ```
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Dragonfly (🥉17 · ⭐ 610 · 💀) - An open source python library for scalable Bayesian optimisation. MIT +
Dragonfly (🥉17 · ⭐ 610 · 💀) - 一个用于自动化特征工程的开源python库。MIT - [GitHub](https://github.com/dragonfly/dragonfly) (👨‍💻 12 · 🔀 200 · 📋 49 - 63% open · ⏱️ 03.07.2020): @@ -7253,7 +7253,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install dragonfly-opt ```
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optunity (🥉17 · ⭐ 380 · 💀) - optimization routines for hyperparameter tuning. BSD-3 +
optunity (🥉17 · ⭐ 380 · 💀) - 超参数优化的优化例程。BSD-3 - [GitHub](https://github.com/claesenm/optunity) (👨‍💻 9 · 🔀 73 · 📥 67 · 📦 68 · 📋 95 - 49% open · ⏱️ 11.05.2020): @@ -7265,7 +7265,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install optunity ```
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Auto ViML (🥉17 · ⭐ 310) - Automatically Build Multiple ML Models with a Single Line of Code... Apache-2 +
Auto ViML (🥉17 · ⭐ 310) - 用单行代码自动构建多个ML模型。Apache-2 - [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 6 · 🔀 69 · 📦 15 · 📋 18 - 22% open · ⏱️ 06.12.2021): @@ -7277,7 +7277,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install autoviml ```
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Sherpa (🥉17 · ⭐ 310 · 💀) - Hyperparameter optimization that enables researchers to.. ❗Unlicensed +
Sherpa (🥉17 · ⭐ 310 · 💀) - 超参数优化库。❗Unlicensed - [GitHub](https://github.com/sherpa-ai/sherpa) (👨‍💻 43 · 🔀 48 · 📦 17 · 📋 56 - 26% open · ⏱️ 18.10.2020): @@ -7289,7 +7289,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install parameter-sherpa ```
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Orion (🥉17 · ⭐ 210) - Asynchronous Distributed Hyperparameter Optimization. ❗Unlicensed +
Orion (🥉17 · ⭐ 210) - 异步分布式超参数优化。❗Unlicensed - [GitHub](https://github.com/Epistimio/orion) (👨‍💻 24 · 🔀 41 · 📦 47 · 📋 200 - 29% open · ⏱️ 01.12.2021): @@ -7301,7 +7301,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install orion ```
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Auto Tune Models (🥉16 · ⭐ 510 · 💀) - Auto Tune Models - A multi-tenant, multi-data system for.. MIT +
Auto Tune Models (🥉16 · ⭐ 510 · 💀) - 自动调整模型。MIT - [GitHub](https://github.com/HDI-Project/ATM) (👨‍💻 16 · 🔀 130 · 📦 8 · 📋 88 - 19% open · ⏱️ 21.02.2020): @@ -7313,7 +7313,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install atm ```
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featurewiz (🥉16 · ⭐ 99) - Use advanced feature engineering strategies and select the.. Apache-2 +
featurewiz (🥉16 · ⭐ 99) - 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) (👨‍💻 3 · 🔀 27 · 📦 3 · 📋 7 - 71% open · ⏱️ 10.12.2021): @@ -7325,7 +7325,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install featurewiz ```
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automl-gs (🥉15 · ⭐ 1.8K · 💀) - Provide an input CSV and a target field to predict, generate a.. MIT +
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 - [GitHub](https://github.com/minimaxir/automl-gs) (👨‍💻 7 · 🔀 160 · 📥 27 · 📋 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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Advisor (🥉15 · ⭐ 1.4K · 💀) - Open-source implementation of Google Vizier for hyper parameters.. Apache-2 +
Advisor (🥉15 · ⭐ 1.4K · 💀) - 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): @@ -7353,7 +7353,7 @@ _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): @@ -7365,7 +7365,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install xcessiv ```
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Parfit (🥉15 · ⭐ 200 · 💀) - A package for parallelizing the fit and flexibly scoring of.. MIT +
Parfit (🥉15 · ⭐ 200 · 💀) - 并行化拟合与评估工具库。MIT - [GitHub](https://github.com/jmcarpenter2/parfit) (👨‍💻 2 · 🔀 25 · 📦 9 · 📋 11 - 54% open · ⏱️ 04.04.2020): @@ -7377,7 +7377,7 @@ _Libraries for hyperparameter optimization, automl and neural architecture searc pip install parfit ```
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HyperparameterHunter (🥉14 · ⭐ 680 · 💤) - Easy hyperparameter optimization and automatic result.. MIT +
HyperparameterHunter (🥉14 · ⭐ 680 · 💤) - 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 · 🔀 87 · 📥 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 · ⭐ 2.5K · 💀) - PyTorch implementation of Efficient Neural Architecture Search via.. Apache-2 +
ENAS (🥉13 · ⭐ 2.5K · 💀) - Efficient Neural Architecture Search的Pytorch实现。Apache-2 - [GitHub](https://github.com/carpedm20/ENAS-pytorch) (👨‍💻 6 · 🔀 460 · 📋 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 · ⭐ 180 · 💤) - An automatic ML model optimization tool. ❗️GPL-3.0 +
Auptimizer (🥉13 · ⭐ 180 · 💤) - 自动ML模型优化工具。❗️GPL-3.0 - [GitHub](https://github.com/LGE-ARC-AdvancedAI/auptimizer) (👨‍💻 11 · 🔀 21 · ⏱️ 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 · ⭐ 97 · 💀) - Better, faster hyper-parameter optimization. BSD-3 +
Hypermax (🥉12 · ⭐ 97 · 💀) - 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 (🥉11 · ⭐ 120 · 💀) - A toolset for black-box hyperparameter optimisation. Apache-2 +
Hypertunity (🥉11 · ⭐ 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 · ⭐ 26K) - A toolkit for developing and comparing reinforcement learning.. MIT +
OpenAI Gym (🥇36 · ⭐ 26K) - 开发和比较强化学习的工具包。MIT - [GitHub](https://github.com/openai/gym) (👨‍💻 330 · 🔀 7K · 📦 25K · 📋 1.4K - 6% open · ⏱️ 16.12.2021): @@ -7461,7 +7461,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install gym ```
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ViZDoom (🥇23 · ⭐ 1.3K) - Doom-based AI Research Platform for Reinforcement Learning from.. ❗Unlicensed +
ViZDoom (🥇23 · ⭐ 1.3K) - 人工智能强化学习工具库。❗Unlicensed - [GitHub](https://github.com/mwydmuch/ViZDoom) (👨‍💻 45 · 🔀 300 · 📥 11K · 📦 120 · 📋 420 - 19% open · ⏱️ 13.12.2021): @@ -7473,7 +7473,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install vizdoom ```
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baselines (🥈22 · ⭐ 12K · 💀) - OpenAI Baselines: high-quality implementations of reinforcement.. MIT +
baselines (🥈22 · ⭐ 12K · 💀) - OpenAI基线：强化学习的高质量实现。MIT - [GitHub](https://github.com/openai/baselines) (👨‍💻 110 · 🔀 3.3K · 📦 360 · 📋 820 - 47% open · ⏱️ 31.01.2020): @@ -7485,7 +7485,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install baselines ```
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keras-rl (🥈22 · ⭐ 5.2K · 💀) - Deep Reinforcement Learning for Keras. MIT +
keras-rl (🥈22 · ⭐ 5.2K · 💀) - Keras的深度强化学习。MIT - [GitHub](https://github.com/keras-rl/keras-rl) (👨‍💻 40 · 🔀 1.3K · 📦 540 · 📋 230 - 4% open · ⏱️ 11.11.2019): @@ -7497,7 +7497,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install keras-rl ```
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Acme (🥈22 · ⭐ 2.4K) - A library of reinforcement learning components and agents. Apache-2 +
Acme (🥈22 · ⭐ 2.4K) - 强化学习组件和代理库。Apache-2 - [GitHub](https://github.com/deepmind/acme) (👨‍💻 53 · 🔀 290 · 📦 47 · 📋 140 - 27% open · ⏱️ 13.12.2021): @@ -7509,7 +7509,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install dm-acme ```
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TF-Agents (🥈21 · ⭐ 2.1K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. Apache-2 +
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 - [GitHub](https://github.com/tensorflow/agents) (👨‍💻 110 · 🔀 560 · 📦 650 · 📋 510 - 19% open · ⏱️ 10.12.2021): @@ -7521,7 +7521,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tf-agents ```
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PFRL (🥈21 · ⭐ 750) - PFRL: a PyTorch-based deep reinforcement learning library. MIT +
PFRL (🥈21 · ⭐ 750) - PFRL：基于PyTorch的深度强化学习库。MIT - [GitHub](https://github.com/pfnet/pfrl) (👨‍💻 15 · 🔀 98 · 📦 27 · 📋 56 - 41% open · ⏱️ 06.12.2021): @@ -7533,7 +7533,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install pfrl ```
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TensorForce (🥈20 · ⭐ 3.1K) - Tensorforce: a TensorFlow library for applied.. Apache-2 +
TensorForce (🥈20 · ⭐ 3.1K) - Tensorforce：一个基于TensorFlow的强化学习库。Apache-2 - [GitHub](https://github.com/tensorforce/tensorforce) (👨‍💻 81 · 🔀 490 · 📋 620 - 0% open · ⏱️ 10.11.2021): @@ -7545,7 +7545,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tensorforce ```
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garage (🥈20 · ⭐ 1.4K) - A toolkit for reproducible reinforcement learning research. MIT +
garage (🥈20 · ⭐ 1.4K) - 用于可重复的强化学习研究的工具包。MIT - [GitHub](https://github.com/rlworkgroup/garage) (👨‍💻 78 · 🔀 240 · 📦 23 · 📋 990 - 19% open · ⏱️ 20.10.2021): @@ -7557,7 +7557,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install garage ```
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ChainerRL (🥈20 · ⭐ 1K · 💤) - ChainerRL is a deep reinforcement learning library built on top of.. MIT +
ChainerRL (🥈20 · ⭐ 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 · 🔀 210 · 📦 110 · 📋 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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Dopamine (🥉18 · ⭐ 9.7K) - Dopamine is a research framework for fast prototyping of.. Apache-2 +
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 - [GitHub](https://github.com/google/dopamine) (👨‍💻 14 · 🔀 1.3K · 📋 140 - 42% open · ⏱️ 14.12.2021): @@ -7581,7 +7581,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install dopamine-rl ```
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TensorLayer (🥉18 · ⭐ 6.8K) - Deep Learning and Reinforcement Learning Library for.. ❗Unlicensed +
TensorLayer (🥉18 · ⭐ 6.8K) - 深度学习和强化学习库。❗Unlicensed - [GitHub](https://github.com/tensorlayer/TensorLayer) (👨‍💻 130 · 🔀 1.5K · 📥 1.3K · 📋 460 - 3% open · ⏱️ 29.10.2021): @@ -7593,7 +7593,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install tensorlayer ```
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PARL (🥉18 · ⭐ 2.3K) - A high-performance distributed training framework for Reinforcement.. Apache-2 +
PARL (🥉18 · ⭐ 2.3K) - 强化学习高性能分布式训练框架。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PARL) (👨‍💻 28 · 🔀 590 · 📦 84 · 📋 280 - 21% open · ⏱️ 15.12.2021): @@ -7605,7 +7605,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install parl ```
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Stable Baselines (🥉17 · ⭐ 3.4K) - A fork of OpenAI Baselines, implementations of reinforcement.. MIT +
Stable Baselines (🥉17 · ⭐ 3.4K) - OpenAI Baselines的一个分支，强化学习的实现。MIT - [GitHub](https://github.com/hill-a/stable-baselines) (👨‍💻 110 · 🔀 650 · 📋 900 - 11% open · ⏱️ 25.08.2021): @@ -7617,7 +7617,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install stable-baselines ```
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ReAgent (🥉17 · ⭐ 3.1K) - A platform for Reasoning systems (Reinforcement Learning,.. BSD-3 +
ReAgent (🥉17 · ⭐ 3.1K) - 推理系统平台。BSD-3 - [GitHub](https://github.com/facebookresearch/ReAgent) (👨‍💻 120 · 🔀 420 · 📋 97 - 22% open · ⏱️ 08.12.2021): @@ -7625,7 +7625,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst git clone https://github.com/facebookresearch/ReAgent ```
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Coach (🥉17 · ⭐ 2.1K) - Reinforcement Learning Coach by Intel AI Lab enables easy.. Apache-2 +
Coach (🥉17 · ⭐ 2.1K) - 英特尔AI实验室的强化学习训练器。Apache-2 - [GitHub](https://github.com/IntelLabs/coach) (👨‍💻 35 · 🔀 410 · 📋 260 - 29% open · ⏱️ 28.06.2021): @@ -7637,7 +7637,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install rl_coach ```
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RLax (🥉17 · ⭐ 720) - A library of reinforcement learning building blocks in JAX. Apache-2 jax +
RLax (🥉17 · ⭐ 720) - 强化学习组件和代理库。Apache-2 jax - [GitHub](https://github.com/deepmind/rlax) (👨‍💻 16 · 🔀 56 · 📦 32 · 📋 12 - 25% open · ⏱️ 02.12.2021): @@ -7649,7 +7649,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst pip install rlax ```
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DeepMind Lab (🥉16 · ⭐ 6.6K) - A customisable 3D platform for agent-based AI research. ❗️GPL-2.0 +
DeepMind Lab (🥉16 · ⭐ 6.6K) - 可定制的3D平台，用于agent-based AI研究。❗️GPL-2.0 - [GitHub](https://github.com/deepmind/lab) (👨‍💻 7 · 🔀 1.3K · 📋 210 - 23% open · ⏱️ 21.07.2021): @@ -7657,7 +7657,7 @@ _Libraries for building and evaluating reinforcement learning & agent-based syst git clone https://github.com/deepmind/lab ```
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TRFL (🥉16 · ⭐ 3.1K) - TensorFlow Reinforcement Learning. Apache-2 +
TRFL (🥉16 · ⭐ 3.1K) - TensorFlow强化学习。Apache-2 - [GitHub](https://github.com/deepmind/trfl) (👨‍💻 13 · 🔀 370 · 📦 68 · 📋 20 - 20% open · ⏱️ 16.08.2021): @@ -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。_ -
TF Recommenders (🥇25 · ⭐ 1.1K) - TensorFlow Recommenders is a library for building.. Apache-2 +
TF Recommenders (🥇25 · ⭐ 1.1K) - 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) (👨‍💻 29 · 🔀 150 · 📦 61 · 📋 200 - 53% open · ⏱️ 09.12.2021): @@ -7689,7 +7689,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorflow-recommenders ```
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lightfm (🥇24 · ⭐ 3.9K · 💤) - A Python implementation of LightFM, a hybrid recommendation.. Apache-2 +
lightfm (🥇24 · ⭐ 3.9K · 💤) - 全局优化的Python实现。Apache-2 - [GitHub](https://github.com/lyst/lightfm) (👨‍💻 44 · 🔀 610 · 📦 610 · 📋 430 - 20% open · ⏱️ 07.02.2021): @@ -7705,7 +7705,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge lightfm ```
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implicit (🥇24 · ⭐ 2.6K) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. MIT +
implicit (🥇24 · ⭐ 2.6K) - 隐式反馈数据集的快速Python协同过滤。MIT - [GitHub](https://github.com/benfred/implicit) (👨‍💻 30 · 🔀 500 · 📦 520 · 📋 370 - 22% open · ⏱️ 02.10.2021): @@ -7721,7 +7721,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge implicit ```
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Cornac (🥇24 · ⭐ 490) - A Comparative Framework for Multimodal Recommender Systems. Apache-2 +
Cornac (🥇24 · ⭐ 490) - 多模态推荐系统的比较框架。Apache-2 - [GitHub](https://github.com/PreferredAI/cornac) (👨‍💻 13 · 🔀 81 · 📦 68 · 📋 74 - 1% open · ⏱️ 30.09.2021): @@ -7737,7 +7737,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge cornac ```
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scikit-surprise (🥈22 · ⭐ 5.1K · 💀) - A Python scikit for building and analyzing recommender.. BSD-3 +
scikit-surprise (🥈22 · ⭐ 5.1K · 💀) - 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) (👨‍💻 38 · 🔀 890 · 📋 330 - 12% open · ⏱️ 05.08.2020): @@ -7753,7 +7753,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c conda-forge scikit-surprise ```
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RecBole (🥉21 · ⭐ 1.5K) - A unified, comprehensive and efficient recommendation library. MIT +
RecBole (🥉21 · ⭐ 1.5K) - 统一，全面，高效的推荐库。MIT - [GitHub](https://github.com/RUCAIBox/RecBole) (👨‍💻 41 · 🔀 250 · 📋 260 - 16% open · ⏱️ 09.12.2021): @@ -7769,7 +7769,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c aibox recbole ```
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Recommenders (🥉19 · ⭐ 12K) - Best Practices on Recommendation Systems. MIT +
Recommenders (🥉19 · ⭐ 12K) - 推荐系统最佳实践。MIT - [GitHub](https://github.com/microsoft/recommenders) (👨‍💻 100 · 🔀 2K · 📥 85 · 📦 5 · 📋 630 - 23% open · ⏱️ 23.09.2021): @@ -7777,7 +7777,7 @@ _Libraries for building and evaluating recommendation systems._ git clone https://github.com/microsoft/recommenders ```
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TF Ranking (🥉19 · ⭐ 2.4K) - Learning to Rank in TensorFlow. Apache-2 +
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): @@ -7789,7 +7789,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorflow_ranking ```
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Case Recommender (🥉19 · ⭐ 370) - Case Recommender: A Flexible and Extensible Python.. MIT +
Case Recommender (🥉19 · ⭐ 370) - 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 · 🔀 77 · 📦 9 · 📋 24 - 16% open · ⏱️ 25.11.2021): @@ -7801,7 +7801,7 @@ _Libraries for building and evaluating recommendation systems._ pip install caserecommender ```
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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 · 📦 26 · 📋 120 - 28% open · ⏱️ 04.02.2020): @@ -7813,7 +7813,7 @@ _Libraries for building and evaluating recommendation systems._ pip install tensorrec ```
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recmetrics (🥉18 · ⭐ 330) - A library of metrics for evaluating recommender systems. MIT +
recmetrics (🥉18 · ⭐ 330) - 用于评估推荐系统的度量标准库。MIT - [GitHub](https://github.com/statisticianinstilettos/recmetrics) (👨‍💻 13 · 🔀 74 · 📦 20 · 📋 16 - 37% open · ⏱️ 27.10.2021): @@ -7825,7 +7825,7 @@ _Libraries for building and evaluating recommendation systems._ pip install recmetrics ```
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Spotlight (🥉17 · ⭐ 2.6K · 💀) - Deep recommender models using PyTorch. MIT +
Spotlight (🥉17 · ⭐ 2.6K · 💀) - 使用PyTorch的深度推荐系统模型实现。MIT - [GitHub](https://github.com/maciejkula/spotlight) (👨‍💻 11 · 🔀 390 · 📋 110 - 55% open · ⏱️ 09.02.2020): @@ -7837,7 +7837,7 @@ _Libraries for building and evaluating recommendation systems._ conda install -c maciejkula spotlight ```
-
fastFM (🥉17 · ⭐ 960 · 💤) - fastFM: A Library for Factorization Machines. ❗Unlicensed +
fastFM (🥉17 · ⭐ 960 · 💤) - fastFM：用于分解机的工具库。❗Unlicensed - [GitHub](https://github.com/ibayer/fastFM) (👨‍💻 20 · 🔀 190 · 📥 420 · 📦 91 · 📋 110 - 43% open · ⏱️ 24.03.2021): @@ -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 · ⭐ 7.8K) - A library for answering questions using data you cannot see. Apache-2 +
PySyft (🥇26 · ⭐ 7.8K) - 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) (👨‍💻 430 · 🔀 1.7K · 📋 3K - 9% open · ⏱️ 10.12.2021): @@ -7869,7 +7869,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install syft ```
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TensorFlow Privacy (🥈23 · ⭐ 1.5K) - Library for training machine learning models with.. Apache-2 +
TensorFlow Privacy (🥈23 · ⭐ 1.5K) - 用于训练机器学习模型的库。Apache-2 - [GitHub](https://github.com/tensorflow/privacy) (👨‍💻 43 · 🔀 330 · 📥 59 · 📋 140 - 39% open · ⏱️ 14.12.2021): @@ -7881,7 +7881,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install tensorflow-privacy ```
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FATE (🥈22 · ⭐ 3.8K) - An Industrial Grade Federated Learning Framework. Apache-2 +
FATE (🥈22 · ⭐ 3.8K) - 工业级联邦学习框架。Apache-2 - [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 68 · 🔀 1.1K · 📋 1K - 33% open · ⏱️ 14.12.2021): @@ -7889,7 +7889,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l git clone https://github.com/FederatedAI/FATE ```
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Opacus (🥈22 · ⭐ 1K) - Training PyTorch models with differential privacy. Apache-2 +
Opacus (🥈22 · ⭐ 1K) - 使用不同的隐私训练PyTorch模型。Apache-2 - [GitHub](https://github.com/pytorch/opacus) (👨‍💻 40 · 🔀 160 · 📥 40 · 📦 69 · 📋 110 - 15% open · ⏱️ 14.12.2021): @@ -7901,7 +7901,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install opacus ```
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TFEncrypted (🥉19 · ⭐ 960 · 💀) - A Framework for Encrypted Machine Learning in TensorFlow. Apache-2 +
TFEncrypted (🥉19 · ⭐ 960 · 💀) - TensorFlow中的加密机器学习框架。Apache-2 - [GitHub](https://github.com/tf-encrypted/tf-encrypted) (👨‍💻 28 · 🔀 170 · 📦 58 · 📋 410 - 42% open · ⏱️ 19.08.2020): @@ -7913,7 +7913,7 @@ _Libraries for encrypted and privacy-preserving machine learning using methods l pip install tf-encrypted ```
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CrypTen (🥉17 · ⭐ 970) - A framework for Privacy Preserving Machine Learning. MIT +
CrypTen (🥉17 · ⭐ 970) - 隐私保护的机器学习框架。MIT - [GitHub](https://github.com/facebookresearch/CrypTen) (👨‍💻 25 · 🔀 160 · 📦 12 · 📋 110 - 16% open · ⏱️ 15.12.2021): @@ -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 · ⭐ 5.7K) - TensorFlow's Visualization Toolkit. Apache-2 +
Tensorboard (🥇37 · ⭐ 5.7K) - TensorFlow的可视化工具包。Apache-2 - [GitHub](https://github.com/tensorflow/tensorboard) (👨‍💻 270 · 🔀 1.4K · 📦 88K · 📋 1.6K - 32% open · ⏱️ 16.12.2021): @@ -7949,7 +7949,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge tensorboard ```
-
SageMaker SDK (🥇32 · ⭐ 1.5K) - A library for training and deploying machine learning.. Apache-2 +
SageMaker SDK (🥇32 · ⭐ 1.5K) - 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) (👨‍💻 240 · 🔀 700 · 📦 980 · 📋 930 - 31% open · ⏱️ 15.12.2021): @@ -7961,7 +7961,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install sagemaker ```
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tensorboardX (🥇30 · ⭐ 7.2K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). MIT +
tensorboardX (🥇30 · ⭐ 7.2K) - pytorch（和链接器，mxnet，numpy，...）的张量板。MIT - [GitHub](https://github.com/lanpa/tensorboardX) (👨‍💻 67 · 🔀 830 · 📥 340 · 📦 16K · 📋 420 - 14% open · ⏱️ 12.09.2021): @@ -7977,7 +7977,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge tensorboardx ```
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mlflow (🥇27 · ⭐ 11K) - Open source platform for the machine learning lifecycle. Apache-2 +
mlflow (🥇27 · ⭐ 11K) - 机器学习生命周期的开源平台。Apache-2 - [GitHub](https://github.com/mlflow/mlflow) (👨‍💻 340 · 🔀 2.3K · 📋 2K - 40% open · ⏱️ 16.12.2021): @@ -7993,7 +7993,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge mlflow ```
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Catalyst (🥇27 · ⭐ 2.8K) - Accelerated deep learning R&D. Apache-2 +
Catalyst (🥇27 · ⭐ 2.8K) - 加快深度学习研发。Apache-2 - [GitHub](https://github.com/catalyst-team/catalyst) (👨‍💻 100 · 🔀 350 · 📦 450 · 📋 320 - 1% open · ⏱️ 16.12.2021): @@ -8005,7 +8005,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install catalyst ```
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Metaflow (🥈26 · ⭐ 5.1K) - Build and manage real-life data science projects with ease. Apache-2 +
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 - [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 42 · 🔀 420 · 📦 230 · 📋 350 - 45% open · ⏱️ 16.12.2021): @@ -8021,7 +8021,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge metaflow ```
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PyCaret (🥈26 · ⭐ 4.6K) - An open-source, low-code machine learning library in Python. MIT +
PyCaret (🥈26 · ⭐ 4.6K) - Python中的开源代码，低代码机器学习库。MIT - [GitHub](https://github.com/pycaret/pycaret) (👨‍💻 68 · 🔀 1K · 📥 500 · 📦 1.6K · 📋 1.2K - 15% open · ⏱️ 15.12.2021): @@ -8033,7 +8033,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install pycaret ```
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wandb client (🥈26 · ⭐ 3.6K) - A tool for visualizing and tracking your machine learning.. MIT +
wandb client (🥈26 · ⭐ 3.6K) - 用于可视化和跟踪机器学习的工具。MIT - [GitHub](https://github.com/wandb/client) (👨‍💻 97 · 🔀 280 · 📋 1.4K - 17% open · ⏱️ 16.12.2021): @@ -8045,7 +8045,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install wandb ```
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snakemake (🥈26 · ⭐ 1.2K) - This is the development home of the workflow management system.. MIT +
snakemake (🥈26 · ⭐ 1.2K) - 工作流管理系统snakemake。MIT - [GitHub](https://github.com/snakemake/snakemake) (👨‍💻 230 · 🔀 270 · 📦 990 · 📋 790 - 62% open · ⏱️ 09.12.2021): @@ -8061,7 +8061,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c bioconda snakemake ```
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VisualDL (🥈25 · ⭐ 4.3K) - Deep Learning Visualization Toolkit. Apache-2 +
VisualDL (🥈25 · ⭐ 4.3K) - 深度学习可视化工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/VisualDL) (👨‍💻 31 · 🔀 570 · 📥 160 · 📦 840 · 📋 390 - 14% open · ⏱️ 26.11.2021): @@ -8073,7 +8073,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install visualdl ```
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ClearML (🥈25 · ⭐ 2.9K) - ClearML - Auto-Magical Suite of tools to streamline your ML.. Apache-2 +
ClearML (🥈25 · ⭐ 2.9K) - ClearML-自动精简工具套件。Apache-2 - [GitHub](https://github.com/allegroai/clearml) (👨‍💻 42 · 🔀 380 · 📥 380 · 📦 170 · 📋 420 - 32% open · ⏱️ 14.12.2021): @@ -8089,7 +8089,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ docker pull allegroai/trains ```
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AzureML SDK (🥈25 · ⭐ 2.8K) - Python notebooks with ML and deep learning examples with Azure.. MIT +
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 - [GitHub](https://github.com/Azure/MachineLearningNotebooks) (👨‍💻 57 · 🔀 1.9K · 📥 430 · 📋 1.2K - 16% open · ⏱️ 13.12.2021): @@ -8101,7 +8101,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install azureml-sdk ```
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DVC (🥈24 · ⭐ 9K) - Data Version Control | Git for Data & Models. Apache-2 +
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 - [GitHub](https://github.com/iterative/dvc) (👨‍💻 250 · 🔀 850 · 📥 48K · 📋 3.4K - 16% open · ⏱️ 16.12.2021): @@ -8117,7 +8117,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge dvc ```
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sacred (🥈24 · ⭐ 3.7K) - Sacred is a tool to help you configure, organize, log and reproduce.. MIT +
sacred (🥈24 · ⭐ 3.7K) - 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) (👨‍💻 95 · 🔀 340 · 📦 1.1K · 📋 520 - 17% open · ⏱️ 05.11.2021): @@ -8129,7 +8129,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install sacred ```
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livelossplot (🥉23 · ⭐ 1.1K) - Live training loss plot in Jupyter Notebook for Keras,.. MIT +
livelossplot (🥉23 · ⭐ 1.1K) - Jupyter Notebook for Keras的实时训练loss图。MIT - [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 690 · 📋 73 - 4% open · ⏱️ 12.10.2021): @@ -8141,7 +8141,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install livelossplot ```
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knockknock (🥉20 · ⭐ 2.3K · 💀) - Knock Knock: Get notified when your training ends with only two.. MIT +
knockknock (🥉20 · ⭐ 2.3K · 💀) - 当您的训练结束后通知您。MIT - [GitHub](https://github.com/huggingface/knockknock) (👨‍💻 18 · 🔀 190 · 📦 230 · 📋 37 - 37% open · ⏱️ 16.03.2020): @@ -8157,7 +8157,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge knockknock ```
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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 · 🔀 220 · 📦 88 · 📋 80 - 57% open · ⏱️ 24.04.2020): @@ -8169,7 +8169,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install hiddenlayer ```
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lore (🥉20 · ⭐ 1.5K · 💀) - Lore makes machine learning approachable for Software Engineers and.. MIT +
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): @@ -8181,7 +8181,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install lore ```
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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) (👨‍💻 35 · 🔀 190 · 📋 58 - 39% open · ⏱️ 05.01.2021): @@ -8193,7 +8193,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install torchnet ```
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ml-metadata (🥉20 · ⭐ 410) - For recording and retrieving metadata associated with ML.. Apache-2 +
ml-metadata (🥉20 · ⭐ 410) - 用于记录和检索与ML相关的元数据。Apache-2 - [GitHub](https://github.com/google/ml-metadata) (👨‍💻 13 · 🔀 75 · 📥 1.7K · 📦 170 · 📋 74 - 24% open · ⏱️ 16.12.2021): @@ -8205,7 +8205,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install ml-metadata ```
-
kaggle (🥉19 · ⭐ 4.5K · 💤) - Official Kaggle API. Apache-2 +
kaggle (🥉19 · ⭐ 4.5K · 💤) - 官方Kaggle API。Apache-2 - [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 36 · 🔀 870 · 📋 320 - 54% open · ⏱️ 15.03.2021): @@ -8221,7 +8221,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ conda install -c conda-forge kaggle ```
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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 · 📦 65 · 📋 65 - 76% open · ⏱️ 15.01.2021): @@ -8233,7 +8233,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install tensorwatch ```
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Guild AI (🥉19 · ⭐ 640) - Experiment tracking, ML developer tools. Apache-2 +
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): @@ -8245,7 +8245,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install guildai ```
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MXBoard (🥉19 · ⭐ 330 · 💀) - Logging MXNet data for visualization in TensorBoard. Apache-2 +
MXBoard (🥉19 · ⭐ 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 · 🔀 47 · 📦 130 · 📋 31 - 51% open · ⏱️ 24.01.2020): @@ -8257,7 +8257,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install mxboard ```
-
Labml (🥉18 · ⭐ 890) - Monitor deep learning model training and hardware usage from your mobile.. MIT +
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 - [GitHub](https://github.com/labmlai/labml) (👨‍💻 6 · 🔀 58 · 📦 39 · 📋 25 - 60% open · ⏱️ 06.09.2021): @@ -8269,7 +8269,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install labml ```
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Studio.ml (🥉17 · ⭐ 370) - Studio: Simplify and expedite model building process. Apache-2 +
Studio.ml (🥉17 · ⭐ 370) - 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): @@ -8281,7 +8281,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install studioml ```
-
gokart (🥉17 · ⭐ 230) - A wrapper of the data pipeline library luigi. MIT +
gokart (🥉17 · ⭐ 230) - 数据管道库luigi的包装。MIT - [GitHub](https://github.com/m3dev/gokart) (👨‍💻 29 · 🔀 38 · 📋 62 - 17% open · ⏱️ 16.11.2021): @@ -8293,7 +8293,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install gokart ```
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aim (🥉16 · ⭐ 1.9K) - Aim a super-easy way to record, search and compare 1000s of ML training.. Apache-2 +
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 - [GitHub](https://github.com/aimhubio/aim) (👨‍💻 22 · 🔀 110 · 📦 44 · 📋 260 - 33% open · ⏱️ 16.12.2021): @@ -8305,7 +8305,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install aim ```
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quinn (🥉16 · ⭐ 300 · 💤) - pyspark methods to enhance developer productivity. ❗Unlicensed +
quinn (🥉16 · ⭐ 300 · 💤) - pyspark方法可提高开发人员的工作效率。❗Unlicensed - [GitHub](https://github.com/MrPowers/quinn) (👨‍💻 6 · 🔀 40 · 📋 23 - 60% open · ⏱️ 09.02.2021): @@ -8317,7 +8317,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install quinn ```
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SKLL (🥉15 · ⭐ 530) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. ❗Unlicensed +
SKLL (🥉15 · ⭐ 530) - SciKit学习实验室（SKLL）使机器学习易于操作。❗Unlicensed - [GitHub](https://github.com/EducationalTestingService/skll) (👨‍💻 36 · 🔀 63 · 📥 11 · 📦 34 · 📋 390 - 8% open · ⏱️ 09.12.2021): @@ -8329,7 +8329,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install skll ```
-
steppy (🥉14 · ⭐ 130 · 💀) - Lightweight, Python library for fast and reproducible experimentation. MIT +
steppy (🥉14 · ⭐ 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 · 📦 42 · 📋 63 - 20% open · ⏱️ 23.11.2018): @@ -8341,7 +8341,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install steppy ```
-
datmo (🥉13 · ⭐ 340 · 💀) - Open source production model management tool for data scientists. MIT +
datmo (🥉13 · ⭐ 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): @@ -8353,7 +8353,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install datmo ```
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ModelChimp (🥉13 · ⭐ 120) - Experiment tracking for machine and deep learning projects. BSD-2 +
ModelChimp (🥉13 · ⭐ 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): @@ -8369,7 +8369,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ docker pull modelchimp/modelchimp-server ```
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TensorBoard Logger (🥉12 · ⭐ 620 · 💀) - Log TensorBoard events without touching TensorFlow. MIT +
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): @@ -8381,7 +8381,7 @@ _Libraries to organize, track, and visualize machine learning experiments._ pip install tensorboard_logger ```
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traintool (🥉7 · ⭐ 9 · 💤) - Train off-the-shelf machine learning models in one.. Apache-2 +
traintool (🥉7 · ⭐ 9 · 💤) - 一站式训练现成的机器学习模型。Apache-2 - [GitHub](https://github.com/jrieke/traintool) (🔀 1 · ⏱️ 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 (🥇35 · ⭐ 12K) - Open standard for machine learning interoperability. Apache-2 +
onnx (🥇35 · ⭐ 12K) - 机器学习互操作性的开放标准。Apache-2 - [GitHub](https://github.com/onnx/onnx) (👨‍💻 220 · 🔀 2.2K · 📥 17K · 📦 5K · 📋 1.7K - 23% open · ⏱️ 15.12.2021): @@ -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 · ⭐ 2.5K) - Core ML tools contain supporting tools for Core ML model.. BSD-3 +
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 - [GitHub](https://github.com/apple/coremltools) (👨‍💻 120 · 🔀 370 · 📥 3.8K · 📦 700 · 📋 830 - 38% open · ⏱️ 14.12.2021): @@ -8429,7 +8429,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install coremltools ```
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TorchServe (🥈24 · ⭐ 2.3K) - Model Serving on PyTorch. Apache-2 +
TorchServe (🥈24 · ⭐ 2.3K) - 在PyTorch上进行模型服务。Apache-2 - [GitHub](https://github.com/pytorch/serve) (👨‍💻 94 · 🔀 420 · 📥 720 · 📋 740 - 14% open · ⏱️ 15.12.2021): @@ -8449,7 +8449,7 @@ _Libraries to serialize models to files, convert between a variety of model form docker pull pytorch/torchserve ```
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cortex (🥈23 · ⭐ 7.6K) - Cost-effective serverless computing at scale. Apache-2 +
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): @@ -8461,7 +8461,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install cortex ```
-
mmdnn (🥈23 · ⭐ 5.5K · 💀) - MMdnn is a set of tools to help users inter-operate among different deep.. MIT +
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 - [GitHub](https://github.com/microsoft/MMdnn) (👨‍💻 85 · 🔀 950 · 📥 3.5K · 📦 66 · 📋 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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Hummingbird (🥉22 · ⭐ 2.7K) - Hummingbird compiles trained ML models into tensor computation for.. MIT +
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 - [GitHub](https://github.com/microsoft/hummingbird) (👨‍💻 27 · 🔀 200 · 📥 150 · 📦 20 · 📋 230 - 21% open · ⏱️ 16.12.2021): @@ -8485,7 +8485,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install hummingbird-ml ```
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m2cgen (🥉22 · ⭐ 2K) - Transform ML models into a native code (Java, C, Python, Go, JavaScript,.. MIT +
m2cgen (🥉22 · ⭐ 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) (👨‍💻 12 · 🔀 160 · 📦 7 · 📋 82 - 41% open · ⏱️ 25.11.2021): @@ -8497,7 +8497,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install m2cgen ```
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sklearn-porter (🥉18 · ⭐ 1.1K · 💀) - Transpile trained scikit-learn estimators to C, Java,.. MIT +
sklearn-porter (🥉18 · ⭐ 1.1K · 💀) - 将经过训练的scikit-learn估计器转换为C，Java等。MIT - [GitHub](https://github.com/nok/sklearn-porter) (👨‍💻 11 · 🔀 140 · 📋 67 - 56% open · ⏱️ 18.12.2019): @@ -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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Larq Compute Engine (🥉17 · ⭐ 180) - Highly optimized inference engine for Binarized.. Apache-2 +
Larq Compute Engine (🥉17 · ⭐ 180) - 高度优化的二值化推理引擎。Apache-2 - [GitHub](https://github.com/larq/compute-engine) (👨‍💻 18 · 🔀 28 · 📥 330 · 📦 4 · 📋 130 - 9% open · ⏱️ 15.12.2021): @@ -8521,7 +8521,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install larq-compute-engine ```
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pytorch2keras (🥉16 · ⭐ 760) - PyTorch to Keras model convertor. MIT +
pytorch2keras (🥉16 · ⭐ 760) - PyTorch到Keras模型转换器。MIT - [GitHub](https://github.com/gmalivenko/pytorch2keras) (👨‍💻 13 · 🔀 130 · 📦 26 · 📋 120 - 42% open · ⏱️ 06.08.2021): @@ -8533,7 +8533,7 @@ _Libraries to serialize models to files, convert between a variety of model form pip install pytorch2keras ```
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tfdeploy (🥉14 · ⭐ 340 · 💤) - Deploy tensorflow graphs for fast evaluation and export to.. BSD-3 +
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 - [GitHub](https://github.com/riga/tfdeploy) (👨‍💻 4 · 🔀 37 · 📋 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 · ⭐ 15K) - A game theoretic approach to explain the output of any machine learning model. MIT +
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 - [GitHub](https://github.com/slundberg/shap) (👨‍💻 160 · 🔀 2.2K · 📦 4K · 📋 1.8K - 68% open · ⏱️ 04.12.2021): @@ -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 · ⭐ 9.4K) - Lime: Explaining the predictions of any machine learning classifier. BSD-2 +
Lime (🥇30 · ⭐ 9.4K) - Lime：解释任何机器学习分类器的预测。BSD-2 - [GitHub](https://github.com/marcotcr/lime) (👨‍💻 61 · 🔀 1.5K · 📦 1.8K · 📋 550 - 3% 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 · 🔀 320 · 📦 2.9K · 📋 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 (🥇27 · ⭐ 4.4K) - Fit interpretable models. Explain blackbox machine learning. MIT +
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 - [GitHub](https://github.com/interpretml/interpret) (👨‍💻 28 · 🔀 540 · 📦 140 · 📋 260 - 31% open · ⏱️ 11.12.2021): @@ -8613,7 +8613,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install interpret ```
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Captum (🥇27 · ⭐ 2.8K) - Model interpretability and understanding for PyTorch. BSD-3 +
Captum (🥇27 · ⭐ 2.8K) - PyTorch的模型可解释性和理解。BSD-3 - [GitHub](https://github.com/pytorch/captum) (👨‍💻 77 · 🔀 290 · 📦 340 · 📋 300 - 21% open · ⏱️ 14.12.2021): @@ -8625,7 +8625,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install captum ```
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Model Analysis (🥈26 · ⭐ 1.1K) - Model analysis tools for TensorFlow. Apache-2 +
Model Analysis (🥈26 · ⭐ 1.1K) - TensorFlow的模型分析工具。Apache-2 - [GitHub](https://github.com/tensorflow/model-analysis) (👨‍💻 36 · 🔀 220 · 📋 61 - 22% open · ⏱️ 16.12.2021): @@ -8637,7 +8637,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tensorflow-model-analysis ```
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arviz (🥈26 · ⭐ 1.1K) - Exploratory analysis of Bayesian models with Python. Apache-2 +
arviz (🥈26 · ⭐ 1.1K) - 使用Python探索性分析贝叶斯模型。Apache-2 - [GitHub](https://github.com/arviz-devs/arviz) (👨‍💻 110 · 🔀 250 · 📥 110 · 📦 1.7K · 📋 690 - 19% open · ⏱️ 15.12.2021): @@ -8653,7 +8653,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge arviz ```
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scikit-plot (🥈25 · ⭐ 2.2K · 💀) - An intuitive library to add plotting functionality to.. MIT +
scikit-plot (🥈25 · ⭐ 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 · 📦 1.5K · 📋 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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Alibi (🥈25 · ⭐ 1.4K) - Algorithms for monitoring and explaining machine learning models. Apache-2 +
Alibi (🥈25 · ⭐ 1.4K) - 监视和解释机器学习模型的算法。Apache-2 - [GitHub](https://github.com/SeldonIO/alibi) (👨‍💻 18 · 🔀 160 · 📦 120 · 📋 240 - 39% open · ⏱️ 13.12.2021): @@ -8681,7 +8681,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install alibi ```
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Fairness 360 (🥈24 · ⭐ 1.6K) - A comprehensive set of fairness metrics for datasets and.. Apache-2 +
Fairness 360 (🥈24 · ⭐ 1.6K) - 一整套用于数据集的公平度量标准。Apache-2 - [GitHub](https://github.com/Trusted-AI/AIF360) (👨‍💻 46 · 🔀 500 · 📦 130 · 📋 110 - 47% open · ⏱️ 18.11.2021): @@ -8693,7 +8693,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aif360 ```
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Lucid (🥈23 · ⭐ 4.3K · 💤) - A collection of infrastructure and tools for research in.. Apache-2 +
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 - [GitHub](https://github.com/tensorflow/lucid) (👨‍💻 40 · 🔀 580 · 📦 590 · 📋 170 - 41% open · ⏱️ 19.03.2021): @@ -8705,7 +8705,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lucid ```
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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 · 🔀 610 · 📦 1.5K · 📋 210 - 53% open · ⏱️ 20.04.2020): @@ -8717,7 +8717,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install keras-vis ```
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CausalNex (🥈23 · ⭐ 1.4K) - A Python library that helps data scientists to infer.. Apache-2 +
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 - [GitHub](https://github.com/quantumblacklabs/causalnex) (👨‍💻 22 · 🔀 150 · 📦 33 · 📋 100 - 13% open · ⏱️ 11.11.2021): @@ -8729,7 +8729,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install causalnex ```
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DoWhy (🥈22 · ⭐ 3.5K) - DoWhy is a Python library for causal inference that supports explicit.. MIT +
DoWhy (🥈22 · ⭐ 3.5K) - DoWhy是用于因果推断的Python库。MIT - [GitHub](https://github.com/microsoft/dowhy) (👨‍💻 45 · 🔀 520 · 📥 24 · 📦 78 · 📋 160 - 29% open · ⏱️ 05.12.2021): @@ -8745,7 +8745,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge dowhy ```
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eli5 (🥈22 · ⭐ 2.5K · 💀) - A library for debugging/inspecting machine learning classifiers and.. MIT +
eli5 (🥈22 · ⭐ 2.5K · 💀) - 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): @@ -8761,7 +8761,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge eli5 ```
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dtreeviz (🥈22 · ⭐ 1.9K) - A python library for decision tree visualization and model interpretation. MIT +
dtreeviz (🥈22 · ⭐ 1.9K) - 用于决策树可视化和模型解释的python库。MIT - [GitHub](https://github.com/parrt/dtreeviz) (👨‍💻 17 · 🔀 240 · 📦 270 · 📋 110 - 16% open · ⏱️ 03.12.2021): @@ -8773,7 +8773,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dtreeviz ```
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Explainability 360 (🥈22 · ⭐ 1K) - Interpretability and explainability of data and machine.. Apache-2 +
Explainability 360 (🥈22 · ⭐ 1K) - 数据和机器学习的可解释性。Apache-2 - [GitHub](https://github.com/Trusted-AI/AIX360) (👨‍💻 29 · 🔀 210 · 📦 36 · 📋 56 - 55% open · ⏱️ 12.10.2021): @@ -8785,7 +8785,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aix360 ```
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tf-explain (🥈22 · ⭐ 890) - Interpretability Methods for tf.keras models with Tensorflow 2.x. MIT +
tf-explain (🥈22 · ⭐ 890) - 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) (👨‍💻 16 · 🔀 89 · 📦 92 · 📋 86 - 43% open · ⏱️ 30.11.2021): @@ -8797,7 +8797,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tf-explain ```
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checklist (🥈21 · ⭐ 1.5K) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. MIT +
checklist (🥈21 · ⭐ 1.5K) - 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) (👨‍💻 12 · 🔀 150 · 📦 58 · 📋 80 - 1% open · ⏱️ 28.09.2021): @@ -8809,7 +8809,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install checklist ```
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keract (🥈21 · ⭐ 940) - Layers Outputs and Gradients in Keras. Made easy. MIT +
keract (🥈21 · ⭐ 940) - 在Keras中分层输出和渐变。MIT - [GitHub](https://github.com/philipperemy/keract) (👨‍💻 16 · 🔀 180 · 📦 110 · 📋 83 - 2% open · ⏱️ 28.07.2021): @@ -8821,7 +8821,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install keract ```
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imodels (🥈21 · ⭐ 400) - Interpretable ML package for concise, transparent, and accurate predictive.. MIT +
imodels (🥈21 · ⭐ 400) - 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) (👨‍💻 7 · 🔀 40 · 📦 10 · 📋 17 - 17% open · ⏱️ 16.12.2021): @@ -8833,7 +8833,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install imodels ```
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yellowbrick (🥉20 · ⭐ 3.4K) - Visual analysis and diagnostic tools to facilitate machine.. Apache-2 +
yellowbrick (🥉20 · ⭐ 3.4K) - 可视化分析和诊断工具，方便机器使用。Apache-2 - [GitHub](https://github.com/DistrictDataLabs/yellowbrick) (👨‍💻 100 · 🔀 490 · 📋 630 - 13% open · ⏱️ 10.11.2021): @@ -8845,7 +8845,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install yellowbrick ```
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Skater (🥉20 · ⭐ 1K · 💀) - Python Library for Model Interpretation/Explanations. ❗️UPL-1.0 +
Skater (🥉20 · ⭐ 1K · 💀) - 用于模型解释/说明的Python库。❗️UPL-1.0 - [GitHub](https://github.com/oracle/Skater) (👨‍💻 34 · 🔀 160 · 📋 160 - 40% open · ⏱️ 29.06.2020): @@ -8861,7 +8861,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge skater ```
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DALEX (🥉20 · ⭐ 970) - moDel Agnostic Language for Exploration and eXplanation. ❗️GPL-3.0 +
DALEX (🥉20 · ⭐ 970) - 用于模型探索和扩展的模块。❗️GPL-3.0 - [GitHub](https://github.com/ModelOriented/DALEX) (👨‍💻 20 · 🔀 120 · 📦 26 · 📋 330 - 4% open · ⏱️ 08.11.2021): @@ -8873,7 +8873,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dalex ```
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explainerdashboard (🥉20 · ⭐ 770) - Quickly build Explainable AI dashboards that show the inner.. MIT +
explainerdashboard (🥉20 · ⭐ 770) - 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) (👨‍💻 12 · 🔀 91 · 📦 46 · 📋 130 - 15% open · ⏱️ 08.12.2021): @@ -8885,7 +8885,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install explainerdashboard ```
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fairlearn (🥉19 · ⭐ 1.1K) - A Python package to assess and improve fairness of machine.. MIT +
fairlearn (🥉19 · ⭐ 1.1K) - 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) (👨‍💻 61 · 🔀 270 · 📋 320 - 37% open · ⏱️ 15.12.2021): @@ -8901,7 +8901,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin conda install -c conda-forge fairlearn ```
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TreeInterpreter (🥉19 · ⭐ 690 · 💤) - Package for interpreting scikit-learn's decision tree.. BSD-3 +
TreeInterpreter (🥉19 · ⭐ 690 · 💤) - 解释scikit-learn决策树的程序包。BSD-3 - [GitHub](https://github.com/andosa/treeinterpreter) (👨‍💻 11 · 🔀 130 · 📦 180 · 📋 23 - 82% open · ⏱️ 28.02.2021): @@ -8913,7 +8913,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install treeinterpreter ```
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What-If Tool (🥉19 · ⭐ 610) - Source code/webpage/demos for the What-If Tool. Apache-2 +
What-If Tool (🥉19 · ⭐ 610) - What-If工具的源代码/网页/演示。Apache-2 - [GitHub](https://github.com/PAIR-code/what-if-tool) (👨‍💻 20 · 🔀 120 · 📋 94 - 51% open · ⏱️ 01.11.2021): @@ -8929,7 +8929,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin npm install wit-widget ```
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deeplift (🥉19 · ⭐ 600) - Public facing deeplift repo. MIT +
deeplift (🥉19 · ⭐ 600) - Public facing deeplift repo。MIT - [GitHub](https://github.com/kundajelab/deeplift) (👨‍💻 11 · 🔀 130 · 📦 52 · 📋 81 - 40% open · ⏱️ 11.11.2021): @@ -8941,7 +8941,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install deeplift ```
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sklearn-evaluation (🥉19 · ⭐ 320) - Machine learning model evaluation made easy: plots,.. MIT +
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): @@ -8953,7 +8953,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install sklearn-evaluation ```
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aequitas (🥉18 · ⭐ 440 · 💤) - Bias and Fairness Audit Toolkit. MIT +
aequitas (🥉18 · ⭐ 440 · 💤) - 偏差和公平审计工具包。MIT - [GitHub](https://github.com/dssg/aequitas) (👨‍💻 16 · 🔀 84 · 📦 87 · 📋 58 - 63% open · ⏱️ 27.05.2021): @@ -8965,7 +8965,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install aequitas ```
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random-forest-importances (🥉17 · ⭐ 490 · 💤) - Code to compute permutation and drop-column.. MIT +
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): @@ -8977,7 +8977,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install rfpimp ```
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model-card-toolkit (🥉17 · ⭐ 240) - a tool that leverages rich metadata and lineage.. Apache-2 +
model-card-toolkit (🥉17 · ⭐ 240) - 模型解释与分析卡片工具库。Apache-2 - [GitHub](https://github.com/tensorflow/model-card-toolkit) (👨‍💻 11 · 🔀 41 · 📦 5 · 📋 6 - 66% open · ⏱️ 10.12.2021): @@ -8989,7 +8989,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install model-card-toolkit ```
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fairness-indicators (🥉17 · ⭐ 240) - Tensorflow's Fairness Evaluation and Visualization.. Apache-2 +
fairness-indicators (🥉17 · ⭐ 240) - Tensorflow的公平性评估和可视化。Apache-2 - [GitHub](https://github.com/tensorflow/fairness-indicators) (👨‍💻 25 · 🔀 66 · 📋 10 - 20% open · ⏱️ 03.12.2021): @@ -9001,7 +9001,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install fairness-indicators ```
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LIT (🥉16 · ⭐ 2.7K) - The Language Interpretability Tool: Interactively analyze NLP models for.. Apache-2 +
LIT (🥉16 · ⭐ 2.7K) - 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) (👨‍💻 17 · 🔀 270 · 📦 7 · 📋 86 - 29% open · ⏱️ 14.11.2021): @@ -9013,7 +9013,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lit-nlp ```
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XAI (🥉16 · ⭐ 740) - XAI - An eXplainability toolbox for machine learning. MIT +
XAI (🥉16 · ⭐ 740) - XAI-用于机器学习的可解释性工具箱。MIT - [GitHub](https://github.com/EthicalML/xai) (👨‍💻 3 · 🔀 110 · 📦 11 · 📋 8 - 12% open · ⏱️ 30.10.2021): @@ -9025,7 +9025,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install xai ```
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DiCE (🥉16 · ⭐ 730) - Generate Diverse Counterfactual Explanations for any machine.. MIT +
DiCE (🥉16 · ⭐ 730) - 生成任何机器学习的各种反事实说明。MIT - [GitHub](https://github.com/interpretml/DiCE) (👨‍💻 12 · 🔀 96 · 📋 90 - 44% open · ⏱️ 11.12.2021): @@ -9037,7 +9037,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install dice-ml ```
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tcav (🥉16 · ⭐ 500) - Code for the TCAV ML interpretability project. Apache-2 +
tcav (🥉16 · ⭐ 500) - TCAV ML可解释性项目的代码。Apache-2 - [GitHub](https://github.com/tensorflow/tcav) (👨‍💻 19 · 🔀 120 · 📦 11 · 📋 55 - 5% open · ⏱️ 16.09.2021): @@ -9049,7 +9049,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install tcav ```
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iNNvestigate (🥉15 · ⭐ 920) - A toolbox to iNNvestigate neural networks' predictions!. BSD-2 +
iNNvestigate (🥉15 · ⭐ 920) - 神经网络预估分析工具箱。BSD-2 - [GitHub](https://github.com/albermax/innvestigate) (👨‍💻 19 · 🔀 200 · 📋 230 - 28% open · ⏱️ 03.08.2021): @@ -9061,7 +9061,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install innvestigate ```
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Anchor (🥉15 · ⭐ 680) - Code for High-Precision Model-Agnostic Explanations paper. BSD-2 +
Anchor (🥉15 · ⭐ 680) - High-Precision Model-Agnostic Explanations论文代码。BSD-2 - [GitHub](https://github.com/marcotcr/anchor) (👨‍💻 10 · 🔀 93 · 📋 67 - 23% open · ⏱️ 17.11.2021): @@ -9073,7 +9073,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install anchor_exp ```
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LOFO (🥉15 · ⭐ 420) - Leave One Feature Out Importance. MIT +
LOFO (🥉15 · ⭐ 420) - Leave One Feature Out特征重要度。MIT - [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 3 · 🔀 50 · 📦 6 · 📋 17 - 23% open · ⏱️ 04.10.2021): @@ -9085,7 +9085,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install lofo-importance ```
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ExplainX.ai (🥉15 · ⭐ 250 · 💤) - Explainable AI framework for data scientists. Explain & debug any.. MIT +
ExplainX.ai (🥉15 · ⭐ 250 · 💤) - 适用于数据科学家的可解释AI框架。MIT - [GitHub](https://github.com/explainX/explainx) (👨‍💻 4 · 🔀 36 · 📥 2 · 📋 24 - 29% open · ⏱️ 02.02.2021): @@ -9097,7 +9097,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install explainx ```
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FlashTorch (🥉13 · ⭐ 640 · 💤) - Visualization toolkit for neural networks in PyTorch! Demo --. MIT +
FlashTorch (🥉13 · ⭐ 640 · 💤) - PyTorch中用于神经网络的可视化工具包。MIT - [GitHub](https://github.com/MisaOgura/flashtorch) (👨‍💻 2 · 🔀 77 · 📦 8 · 📋 29 - 24% open · ⏱️ 27.04.2021): @@ -9109,7 +9109,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install flashtorch ```
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Attribution Priors (🥉12 · ⭐ 90 · 💤) - Tools for training explainable models using.. MIT +
Attribution Priors (🥉12 · ⭐ 90 · 💤) - 训练可解释模型的工具。MIT - [GitHub](https://github.com/suinleelab/attributionpriors) (👨‍💻 6 · 🔀 10 · 📦 3 · 📋 4 - 25% open · ⏱️ 19.03.2021): @@ -9121,7 +9121,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install attributionpriors ```
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contextual-ai (🥉12 · ⭐ 74) - Contextual AI adds explainability to different stages of.. Apache-2 +
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): @@ -9133,7 +9133,7 @@ _Libraries to visualize, explain, debug, evaluate, and interpret machine learnin pip install contextual-ai ```
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bias-detector (🥉12 · ⭐ 36) - Bias Detector is a python package for detecting bias in machine.. MIT +
bias-detector (🥉12 · ⭐ 36) - 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 · 🔀 9 · ⏱️ 27.10.2021): @@ -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 ( ⭐ 2.7K) - Benchmarks of approximate nearest neighbor libraries in Python. -
Milvus (🥇27 · ⭐ 9K) - An open source embedding vector similarity search engine powered by.. Apache-2 +
Milvus (🥇27 · ⭐ 9K) - 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) (👨‍💻 180 · 🔀 1.3K · 📥 6.1K · 📋 4.1K - 4% open · ⏱️ 16.12.2021): @@ -9171,7 +9171,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit docker pull milvusdb/milvus ```
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Faiss (🥇26 · ⭐ 16K) - A library for efficient similarity search and clustering of dense vectors. MIT +
Faiss (🥇26 · ⭐ 16K) - 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) (👨‍💻 90 · 🔀 2.4K · 📦 520 · 📋 1.7K - 12% open · ⏱️ 11.12.2021): @@ -9187,7 +9187,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge faiss ```
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NMSLIB (🥇26 · ⭐ 2.7K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. Apache-2 +
NMSLIB (🥇26 · ⭐ 2.7K) - 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) (👨‍💻 45 · 🔀 370 · 📦 520 · 📋 380 - 14% open · ⏱️ 19.09.2021): @@ -9203,7 +9203,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge nmslib ```
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PyNNDescent (🥈25 · ⭐ 530) - A Python nearest neighbor descent for approximate nearest neighbors. BSD-2 +
PyNNDescent (🥈25 · ⭐ 530) - 适用于近似最近邻查找的Python库。BSD-2 - [GitHub](https://github.com/lmcinnes/pynndescent) (👨‍💻 18 · 🔀 68 · 📦 1K · 📋 88 - 44% open · ⏱️ 08.12.2021): @@ -9219,7 +9219,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit conda install -c conda-forge pynndescent ```
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Annoy (🥈24 · ⭐ 9.3K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. Apache-2 +
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 - [GitHub](https://github.com/spotify/annoy) (👨‍💻 75 · 🔀 950 · 📦 1.9K · 📋 340 - 11% open · ⏱️ 18.10.2021): @@ -9231,7 +9231,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install annoy ```
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hnswlib (🥉22 · ⭐ 1.8K) - Header-only C++/python library for fast approximate nearest neighbors. Apache-2 +
hnswlib (🥉22 · ⭐ 1.8K) - 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) (👨‍💻 52 · 🔀 340 · 📦 180 · 📋 220 - 46% open · ⏱️ 09.12.2021): @@ -9243,7 +9243,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install hnswlib ```
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Magnitude (🥉19 · ⭐ 1.5K · 💀) - A fast, efficient universal vector embedding utility package. MIT +
Magnitude (🥉19 · ⭐ 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 · 🔀 100 · 📦 210 · 📋 80 - 36% 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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NearPy (🥉16 · ⭐ 690 · 💀) - Python framework for fast (approximated) nearest neighbour search in.. MIT +
NearPy (🥉16 · ⭐ 690 · 💀) - 用于快速（近似）最近邻搜索的Python框架。MIT - [GitHub](https://github.com/pixelogik/NearPy) (👨‍💻 18 · 🔀 140 · 📦 63 · 📋 62 - 38% open · ⏱️ 21.10.2018): @@ -9267,7 +9267,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install NearPy ```
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N2 (🥉16 · ⭐ 500 · 💤) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. Apache-2 +
N2 (🥉16 · ⭐ 500 · 💤) - 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 · 🔀 61 · 📦 22 · 📋 30 - 33% open · ⏱️ 20.05.2021): @@ -9279,7 +9279,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install n2 ```
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NGT (🥉14 · ⭐ 830) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. Apache-2 +
NGT (🥉14 · ⭐ 830) - 最近邻搜索算法实现包。Apache-2 - [GitHub](https://github.com/yahoojapan/NGT) (👨‍💻 12 · 🔀 82 · 📋 83 - 9% open · ⏱️ 25.10.2021): @@ -9291,7 +9291,7 @@ _Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarit pip install ngt ```
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PySparNN (🥉11 · ⭐ 890 · 💀) - Approximate Nearest Neighbor Search for Sparse Data in Python!. BSD-3 +
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 - [GitHub](https://github.com/facebookresearch/pysparnn) (👨‍💻 5 · 🔀 150 · 📋 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。_ -
hmmlearn (🥇29 · ⭐ 2.4K) - Hidden Markov Models in Python, with scikit-learn like API. BSD-3 +
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 - [GitHub](https://github.com/hmmlearn/hmmlearn) (👨‍💻 38 · 🔀 650 · 📦 1.1K · 📋 360 - 14% open · ⏱️ 12.12.2021): @@ -9323,7 +9323,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge hmmlearn ```
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filterpy (🥇28 · ⭐ 2K · 💤) - Python Kalman filtering and optimal estimation library. Implements.. MIT +
filterpy (🥇28 · ⭐ 2K · 💤) - Python卡尔曼过滤和最佳估计库。MIT - [GitHub](https://github.com/rlabbe/filterpy) (👨‍💻 36 · 🔀 470 · 📦 1.1K · 📋 190 - 20% open · ⏱️ 04.05.2021): @@ -9339,7 +9339,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge filterpy ```
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GPflow (🥇26 · ⭐ 1.5K) - Gaussian processes in TensorFlow. Apache-2 +
GPflow (🥇26 · ⭐ 1.5K) - TensorFlow中的高斯过程。Apache-2 - [GitHub](https://github.com/GPflow/GPflow) (👨‍💻 72 · 🔀 400 · 📦 310 · 📋 720 - 13% open · ⏱️ 14.12.2021): @@ -9355,7 +9355,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge gpflow ```
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pomegranate (🥈25 · ⭐ 2.8K) - Fast, flexible and easy to use probabilistic modelling in Python. MIT +
pomegranate (🥈25 · ⭐ 2.8K) - 在Python中快速，灵活且易于使用的概率建模。MIT - [GitHub](https://github.com/jmschrei/pomegranate) (👨‍💻 65 · 🔀 510 · 📦 590 · 📋 640 - 5% open · ⏱️ 20.11.2021): @@ -9371,7 +9371,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pomegranate ```
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patsy (🥈25 · ⭐ 810) - Describing statistical models in Python using symbolic formulas. ❗Unlicensed +
patsy (🥈25 · ⭐ 810) - 使用符号公式描述Python中的统计模型。❗Unlicensed - [GitHub](https://github.com/pydata/patsy) (👨‍💻 16 · 🔀 85 · 📦 45K · 📋 130 - 46% open · ⏱️ 26.09.2021): @@ -9387,7 +9387,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge patsy ```
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Pyro (🥈24 · ⭐ 7.2K) - Deep universal probabilistic programming with Python and PyTorch. Apache-2 +
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): @@ -9399,7 +9399,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pyro-ppl ```
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PyMC3 (🥈24 · ⭐ 6.2K) - Probabilistic Programming in Python: Bayesian Modeling and.. ❗Unlicensed +
PyMC3 (🥈24 · ⭐ 6.2K) - Python中的概率编程。❗Unlicensed - [GitHub](https://github.com/pymc-devs/pymc) (👨‍💻 350 · 🔀 1.4K · 📥 1.2K · 📦 570 · 📋 2.5K - 8% open · ⏱️ 16.12.2021): @@ -9415,7 +9415,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pymc3 ```
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tensorflow-probability (🥈24 · ⭐ 3.6K) - Probabilistic reasoning and statistical analysis in.. Apache-2 +
tensorflow-probability (🥈24 · ⭐ 3.6K) - 概率推理与统计分析。Apache-2 - [GitHub](https://github.com/tensorflow/probability) (👨‍💻 430 · 🔀 910 · 📋 1.1K - 42% open · ⏱️ 14.12.2021): @@ -9431,7 +9431,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge tensorflow-probability ```
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GPyTorch (🥈24 · ⭐ 2.6K) - A highly efficient and modular implementation of Gaussian Processes.. MIT +
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): @@ -9443,7 +9443,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install gpytorch ```
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pingouin (🥈24 · ⭐ 870) - Statistical package in Python based on Pandas. ❗️GPL-3.0 +
pingouin (🥈24 · ⭐ 870) - 基于Pandas的Python统计软件包。❗️GPL-3.0 - [GitHub](https://github.com/raphaelvallat/pingouin) (👨‍💻 23 · 🔀 76 · 📦 410 · 📋 180 - 13% open · ⏱️ 08.12.2021): @@ -9459,7 +9459,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pingouin ```
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pgmpy (🥉21 · ⭐ 1.9K) - Python Library for learning (Structure and Parameter) and inference.. MIT +
pgmpy (🥉21 · ⭐ 1.9K) - 用于学习（结构和参数）和推理的Python库。MIT - [GitHub](https://github.com/pgmpy/pgmpy) (👨‍💻 100 · 🔀 610 · 📥 120 · 📦 300 · 📋 730 - 25% open · ⏱️ 04.12.2021): @@ -9471,7 +9471,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pgmpy ```
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SALib (🥉21 · ⭐ 550) - Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris,.. MIT +
SALib (🥉21 · ⭐ 550) - Python（Numpy）中的灵敏度分析库。MIT - [GitHub](https://github.com/SALib/SALib) (👨‍💻 34 · 🔀 160 · 📋 260 - 15% open · ⏱️ 25.11.2021): @@ -9487,7 +9487,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge salib ```
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Edward (🥉20 · ⭐ 4.7K · 💀) - A probabilistic programming language in TensorFlow. Deep.. ❗Unlicensed +
Edward (🥉20 · ⭐ 4.7K · 💀) - TensorFlow中的一种概率编程语言。❗Unlicensed - [GitHub](https://github.com/blei-lab/edward) (👨‍💻 87 · 🔀 750 · 📥 15 · 📦 250 · 📋 510 - 36% open · ⏱️ 25.07.2018): @@ -9499,7 +9499,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install edward ```
-
scikit-posthocs (🥉19 · ⭐ 220) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. MIT +
scikit-posthocs (🥉19 · ⭐ 220) - Python中的多个成对比较（Post Hoc）测试。MIT - [GitHub](https://github.com/maximtrp/scikit-posthocs) (👨‍💻 8 · 🔀 23 · 📥 23 · 📋 43 - 9% open · ⏱️ 26.11.2021): @@ -9511,7 +9511,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install scikit-posthocs ```
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Orbit (🥉18 · ⭐ 840) - A Python package for Bayesian forecasting with object-oriented.. ❗Unlicensed +
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 - [GitHub](https://github.com/uber/orbit) (👨‍💻 14 · 🔀 61 · 📦 5 · 📋 300 - 12% open · ⏱️ 15.12.2021): @@ -9523,7 +9523,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install orbit-ml ```
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Baal (🥉18 · ⭐ 490) - Using approximate bayesian posteriors in deep nets for active learning. Apache-2 +
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 - [GitHub](https://github.com/ElementAI/baal) (👨‍💻 11 · 🔀 48 · 📋 62 - 29% open · ⏱️ 14.12.2021): @@ -9535,7 +9535,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install baal ```
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bambi (🥉17 · ⭐ 700) - BAyesian Model-Building Interface (Bambi) in Python. MIT +
bambi (🥉17 · ⭐ 700) - Python中的贝叶斯模型构建接口（Bambi）。MIT - [GitHub](https://github.com/bambinos/bambi) (👨‍💻 21 · 🔀 67 · 📦 18 · 📋 210 - 14% open · ⏱️ 01.12.2021): @@ -9547,7 +9547,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install bambi ```
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Funsor (🥉17 · ⭐ 180) - Functional tensors for probabilistic programming. Apache-2 +
Funsor (🥉17 · ⭐ 180) - 用于概率编程的函数张量。Apache-2 - [GitHub](https://github.com/pyro-ppl/funsor) (👨‍💻 9 · 🔀 14 · 📦 20 · 📋 140 - 47% open · ⏱️ 13.12.2021): @@ -9559,7 +9559,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install funsor ```
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pyhsmm (🥉16 · ⭐ 500 · 💀) - Bayesian inference in HSMMs and HMMs. MIT +
pyhsmm (🥉16 · ⭐ 500 · 💀) - HSMM和HMM中的贝叶斯推断。MIT - [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 13 · 🔀 160 · 📦 23 · 📋 95 - 36% open · ⏱️ 24.08.2020): @@ -9571,7 +9571,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes pip install pyhsmm ```
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PyStan (🥉15 · ⭐ 140) - PyStan, a Python interface to Stan, a platform for statistical modeling... ISC +
PyStan (🥉15 · ⭐ 140) - PyStan是Stan的Python接口。ISC - [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 10 · 🔀 34 · 📋 160 - 3% open · ⏱️ 21.10.2021): @@ -9587,7 +9587,7 @@ _Libraries providing capabilities for probabilistic programming/reasoning, bayes conda install -c conda-forge pystan ```
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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。_ -
CleverHans (🥇25 · ⭐ 5.4K) - An adversarial example library for constructing attacks,.. MIT +
CleverHans (🥇25 · ⭐ 5.4K) - 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 · 📦 280 · 📋 440 - 4% open · ⏱️ 23.09.2021): @@ -9615,7 +9615,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install cleverhans ```
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Foolbox (🥈23 · ⭐ 2.1K) - A Python toolbox to create adversarial examples that fool neural networks.. MIT +
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 - [GitHub](https://github.com/bethgelab/foolbox) (👨‍💻 32 · 🔀 360 · 📦 260 · 📋 330 - 18% open · ⏱️ 05.06.2021): @@ -9627,7 +9627,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install foolbox ```
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TextAttack (🥈23 · ⭐ 1.8K) - TextAttack is a Python framework for adversarial attacks, data.. MIT +
TextAttack (🥈23 · ⭐ 1.8K) - TextAttack是用于对抗攻击，数据的Python框架。MIT - [GitHub](https://github.com/QData/TextAttack) (👨‍💻 46 · 🔀 210 · 📦 48 · 📋 170 - 13% open · ⏱️ 16.12.2021): @@ -9639,7 +9639,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install textattack ```
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ART (🥉20 · ⭐ 2.6K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. MIT +
ART (🥉20 · ⭐ 2.6K) - 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) (👨‍💻 87 · 🔀 730 · 📦 170 · 📋 610 - 11% open · ⏱️ 13.12.2021): @@ -9651,7 +9651,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install adversarial-robustness-toolbox ```
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robustness (🥉18 · ⭐ 640) - A library for experimenting with, training and evaluating neural.. MIT +
robustness (🥉18 · ⭐ 640) - 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 · 🔀 120 · 📦 67 · 📋 67 - 19% open · ⏱️ 30.11.2021): @@ -9663,7 +9663,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install robustness ```
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advertorch (🥉16 · ⭐ 980) - A Toolbox for Adversarial Robustness Research. ❗️GPL-3.0 +
advertorch (🥉16 · ⭐ 980) - 对抗性鲁棒性研究的工具箱。❗️GPL-3.0 - [GitHub](https://github.com/BorealisAI/advertorch) (👨‍💻 18 · 🔀 160 · 📦 57 · 📋 48 - 31% open · ⏱️ 30.07.2021): @@ -9675,7 +9675,7 @@ _Libraries for testing the robustness of machine learning models against attacks pip install advertorch ```
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AdvBox (🥉14 · ⭐ 1.2K · 💤) - Advbox is a toolbox to generate adversarial examples that fool.. Apache-2 +
AdvBox (🥉14 · ⭐ 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 · 📋 35 - 17% open · ⏱️ 03.05.2021): @@ -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 · ⭐ 5.6K) - A NumPy-compatible array library accelerated by CUDA. MIT +
CuPy (🥇32 · ⭐ 5.6K) - CUDA加速了与NumPy兼容的数组库。MIT - [GitHub](https://github.com/cupy/cupy) (👨‍💻 290 · 🔀 510 · 📥 23K · 📦 890 · 📋 1.6K - 19% open · ⏱️ 16.12.2021): @@ -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 (🥇27 · ⭐ 2.7K) - A simple command-line utility for querying and monitoring GPU status. MIT +
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 - [GitHub](https://github.com/wookayin/gpustat) (👨‍💻 12 · 🔀 210 · 📦 1.5K · 📋 75 - 25% open · ⏱️ 13.08.2021): @@ -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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Apex (🥈23 · ⭐ 6K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. BSD-3 +
Apex (🥈23 · ⭐ 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) (👨‍💻 88 · 🔀 850 · 📦 830 · 📋 900 - 56% open · ⏱️ 16.12.2021): @@ -9743,7 +9743,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c conda-forge nvidia-apex ```
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GPUtil (🥈23 · ⭐ 800 · 💀) - A Python module for getting the GPU status from NVIDA GPUs using.. MIT +
GPUtil (🥈23 · ⭐ 800 · 💀) - 一个Python模块，用于从NVIDA GPU获取GPU状态。MIT - [GitHub](https://github.com/anderskm/gputil) (👨‍💻 13 · 🔀 85 · 📦 1.6K · 📋 25 - 44% 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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py3nvml (🥈20 · ⭐ 200) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. BSD-3 +
py3nvml (🥈20 · ⭐ 200) - NVML库的Python3接口。在内部获取NVIDIA GPU状态。BSD-3 - [GitHub](https://github.com/fbcotter/py3nvml) (👨‍💻 8 · 🔀 28 · 📦 360 · 📋 12 - 16% open · ⏱️ 06.09.2021): @@ -9771,7 +9771,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c conda-forge py3nvml ```
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cuDF (🥈19 · ⭐ 4.4K) - cuDF - GPU DataFrame Library. Apache-2 +
cuDF (🥈19 · ⭐ 4.4K) - cuDF-GPU DataFrame库。Apache-2 - [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 230 · 🔀 570 · 📋 4.2K - 14% open · ⏱️ 16.12.2021): @@ -9783,7 +9783,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cudf ```
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ArrayFire (🥈19 · ⭐ 3.7K) - ArrayFire: a general purpose GPU library. ❗Unlicensed +
ArrayFire (🥈19 · ⭐ 3.7K) - ArrayFire：通用GPU库。❗Unlicensed - [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 81 · 🔀 480 · 📥 1.7K · 📋 1.5K - 15% open · ⏱️ 15.10.2021): @@ -9795,7 +9795,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install arrayfire ```
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cuML (🥉18 · ⭐ 2.5K) - cuML - RAPIDS Machine Learning Library. Apache-2 +
cuML (🥉18 · ⭐ 2.5K) - cuML-RAPIDS机器学习库。Apache-2 - [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 140 · 🔀 370 · 📋 1.9K - 32% open · ⏱️ 16.12.2021): @@ -9807,7 +9807,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cuml ```
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DALI (🥉17 · ⭐ 3.6K) - A GPU-accelerated library containing highly optimized building blocks.. Apache-2 +
DALI (🥉17 · ⭐ 3.6K) - 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) (👨‍💻 67 · 🔀 450 · 📋 1.1K - 13% open · ⏱️ 16.12.2021): @@ -9815,7 +9815,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize git clone https://github.com/NVIDIA/DALI ```
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BlazingSQL (🥉17 · ⭐ 1.6K) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. Apache-2 +
BlazingSQL (🥉17 · ⭐ 1.6K) - 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) (👨‍💻 47 · 🔀 160 · 📋 710 - 17% open · ⏱️ 30.09.2021): @@ -9827,7 +9827,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize conda install -c blazingsql blazingsql-protocol ```
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PyCUDA (🥉17 · ⭐ 1.2K) - CUDA integration for Python, plus shiny features. ❗Unlicensed +
PyCUDA (🥉17 · ⭐ 1.2K) - 适用于Python的CUDA集成，有着出色的功能。❗Unlicensed - [GitHub](https://github.com/inducer/pycuda) (👨‍💻 74 · 🔀 240 · 📦 1.1K · 📋 210 - 26% open · ⏱️ 07.12.2021): @@ -9839,7 +9839,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install pycuda ```
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cuGraph (🥉17 · ⭐ 870) - cuGraph - RAPIDS Graph Analytics Library. Apache-2 +
cuGraph (🥉17 · ⭐ 870) - cuGraph-RAPIDS图形分析库。Apache-2 - [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 70 · 🔀 170 · 📋 730 - 8% open · ⏱️ 15.12.2021): @@ -9851,7 +9851,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install cugraph ```
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scikit-cuda (🥉17 · ⭐ 870) - Python interface to GPU-powered libraries. ❗Unlicensed +
scikit-cuda (🥉17 · ⭐ 870) - GPU工具库的python接口。❗Unlicensed - [GitHub](https://github.com/lebedov/scikit-cuda) (👨‍💻 45 · 🔀 170 · 📦 150 · 📋 220 - 23% open · ⏱️ 13.07.2021): @@ -9863,7 +9863,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install scikit-cuda ```
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Vulkan Kompute (🥉17 · ⭐ 620) - General purpose GPU compute framework for cross vendor.. Apache-2 +
Vulkan Kompute (🥉17 · ⭐ 620) - 适用于跨供应商的通用GPU计算框架。Apache-2 - [GitHub](https://github.com/KomputeProject/kompute) (👨‍💻 16 · 🔀 49 · 📥 100 · 📦 2 · 📋 160 - 32% open · ⏱️ 15.12.2021): @@ -9875,7 +9875,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install kp ```
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cuSignal (🥉14 · ⭐ 550) - GPU accelerated signal processing. Apache-2 +
cuSignal (🥉14 · ⭐ 550) - GPU加速信号处理。Apache-2 - [GitHub](https://github.com/rapidsai/cusignal) (👨‍💻 36 · 🔀 80 · 📋 120 - 9% open · ⏱️ 08.12.2021): @@ -9883,7 +9883,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize git clone https://github.com/rapidsai/cusignal ```
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SpeedTorch (🥉13 · ⭐ 640 · 💀) - Library for faster pinned CPU - GPU transfer in Pytorch. MIT +
SpeedTorch (🥉13 · ⭐ 640 · 💀) - 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 · 📦 3 · 📋 6 - 66% open · ⏱️ 21.02.2020): @@ -9895,7 +9895,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install SpeedTorch ```
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nvidia-ml-py3 (🥉11 · ⭐ 71 · 💀) - Python 3 Bindings for the NVIDIA Management Library. ❗Unlicensed +
nvidia-ml-py3 (🥉11 · ⭐ 71 · 💀) - NVIDIA Management Library的Python3接口。❗Unlicensed - [GitHub](https://github.com/nicolargo/nvidia-ml-py3) (👨‍💻 2 · 🔀 15 · 📦 4.6K · ⏱️ 06.03.2019): @@ -9907,7 +9907,7 @@ _Libraries that require and make use of CUDA/GPU system capabilities to optimize pip install nvidia-ml-py3 ```
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ipyexperiments (🥉10 · ⭐ 140) - jupyter/ipython experiment containers for GPU and.. ❗Unlicensed +
ipyexperiments (🥉10 · ⭐ 140) - jupyter/ipython实验容器。❗Unlicensed - [GitHub](https://github.com/stas00/ipyexperiments) (👨‍💻 3 · 🔀 10 · 📦 5 · ⏱️ 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。_ -
tensorflow-hub (🥇28 · ⭐ 3K) - A library for transfer learning by reusing parts of.. Apache-2 +
tensorflow-hub (🥇28 · ⭐ 3K) - 通过重用部分库来进行迁移学习的库。Apache-2 - [GitHub](https://github.com/tensorflow/hub) (👨‍💻 83 · 🔀 1.6K · 📦 9.5K · 📋 630 - 2% open · ⏱️ 13.12.2021): @@ -9943,7 +9943,7 @@ _Libraries that extend TensorFlow with additional capabilities._ conda install -c conda-forge tensorflow-hub ```
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tensor2tensor (🥇27 · ⭐ 12K) - Library of deep learning models and datasets designed to.. Apache-2 +
tensor2tensor (🥇27 · ⭐ 12K) - 设计深度学习模型和数据集的库。Apache-2 - [GitHub](https://github.com/tensorflow/tensor2tensor) (👨‍💻 240 · 🔀 2.9K · 📦 1.1K · 📋 1.2K - 45% open · ⏱️ 02.12.2021): @@ -9955,7 +9955,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensor2tensor ```
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TF Addons (🥇27 · ⭐ 1.4K · 📉) - Useful extra functionality for TensorFlow 2.x maintained.. Apache-2 +
TF Addons (🥇27 · ⭐ 1.4K · 📉) - 由TensorFlow 2.x维护的有用额外功能。Apache-2 - [GitHub](https://github.com/tensorflow/addons) (👨‍💻 180 · 🔀 480 · 📦 4.9K · 📋 860 - 19% open · ⏱️ 15.12.2021): @@ -9967,7 +9967,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-addons ```
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TF Model Optimization (🥈24 · ⭐ 1.2K) - A toolkit to optimize ML models for deployment for.. Apache-2 +
TF Model Optimization (🥈24 · ⭐ 1.2K) - 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) (👨‍💻 64 · 🔀 250 · 📦 1.4K · 📋 260 - 45% open · ⏱️ 16.12.2021): @@ -9979,7 +9979,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-model-optimization ```
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efficientnet (🥈22 · ⭐ 1.9K) - Implementation of EfficientNet model. Keras and.. Apache-2 +
efficientnet (🥈22 · ⭐ 1.9K) - EfficientNet模型的实现。Apache-2 - [GitHub](https://github.com/qubvel/efficientnet) (👨‍💻 10 · 🔀 430 · 📥 200K · 📦 830 · 📋 110 - 48% open · ⏱️ 16.07.2021): @@ -9991,7 +9991,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install efficientnet ```
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TensorFlow Transform (🥈22 · ⭐ 900 · 📉) - Input pipeline framework. Apache-2 +
TensorFlow Transform (🥈22 · ⭐ 900 · 📉) - 输入管道框架。Apache-2 - [GitHub](https://github.com/tensorflow/transform) (👨‍💻 27 · 🔀 180 · 📦 640 · 📋 170 - 11% open · ⏱️ 16.12.2021): @@ -10003,7 +10003,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-transform ```
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Neural Structured Learning (🥉20 · ⭐ 890) - Training neural models with structured signals. Apache-2 +
Neural Structured Learning (🥉20 · ⭐ 890) - 用结构化信号训练神经模型。Apache-2 - [GitHub](https://github.com/tensorflow/neural-structured-learning) (👨‍💻 30 · 🔀 160 · 📦 150 · 📋 59 - 3% open · ⏱️ 06.12.2021): @@ -10027,7 +10027,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-io ```
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TensorFlow Cloud (🥉19 · ⭐ 320) - The TensorFlow Cloud repository provides APIs that.. Apache-2 +
TensorFlow Cloud (🥉19 · ⭐ 320) - TensorFlow Cloud存储库提供的API。Apache-2 - [GitHub](https://github.com/tensorflow/cloud) (👨‍💻 25 · 🔀 64 · 📦 120 · 📋 80 - 67% open · ⏱️ 07.09.2021): @@ -10039,7 +10039,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-cloud ```
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TensorNets (🥉17 · ⭐ 1K · 💤) - High level network definitions with pre-trained weights in.. MIT +
TensorNets (🥉17 · ⭐ 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 · 🔀 190 · 📦 42 · 📋 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 (🥉15 · ⭐ 550) - Data compression in TensorFlow. Apache-2 +
TF Compression (🥉15 · ⭐ 550) - TensorFlow中的数据压缩。Apache-2 - [GitHub](https://github.com/tensorflow/compression) (👨‍💻 10 · 🔀 200 · 📋 76 - 3% open · ⏱️ 26.10.2021): @@ -10063,7 +10063,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tensorflow-compression ```
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tffm (🥉14 · ⭐ 770 · 💀) - TensorFlow implementation of an arbitrary order Factorization Machine. MIT +
tffm (🥉14 · ⭐ 770 · 💀) - 任意阶乘分解机的TensorFlow实现。MIT - [GitHub](https://github.com/geffy/tffm) (👨‍💻 10 · 🔀 180 · 📦 11 · 📋 39 - 43% open · ⏱️ 22.05.2020): @@ -10075,7 +10075,7 @@ _Libraries that extend TensorFlow with additional capabilities._ pip install tffm ```
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Saliency (🥉14 · ⭐ 750) - Framework-agnostic implementation for state-of-the-art saliency.. Apache-2 +
Saliency (🥉14 · ⭐ 750) - 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) (👨‍💻 14 · 🔀 160 · 📦 19 · ⏱️ 28.07.2021): @@ -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 (🥇31 · ⭐ 5.6K) - A Python Package to Tackle the Curse of Imbalanced.. MIT +
imbalanced-learn (🥇31 · ⭐ 5.6K) - 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) (👨‍💻 61 · 🔀 1.1K · 📦 8.4K · 📋 480 - 8% open · ⏱️ 07.12.2021): @@ -10127,7 +10127,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge category_encoders ```
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MLxtend (🥈27 · ⭐ 3.7K) - A library of extension and helper modules for Python's data.. ❗Unlicensed +
MLxtend (🥈27 · ⭐ 3.7K) - 用于Python数据的扩展和帮助程序模块库。❗Unlicensed - [GitHub](https://github.com/rasbt/mlxtend) (👨‍💻 85 · 🔀 720 · 📦 4.8K · 📋 390 - 23% open · ⏱️ 29.11.2021): @@ -10143,7 +10143,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge mlxtend ```
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sklearn-contrib-lightning (🥈21 · ⭐ 1.5K) - Large-scale linear classification, regression and.. ❗Unlicensed +
sklearn-contrib-lightning (🥈21 · ⭐ 1.5K) - 大规模线性分类，回归分析等。❗Unlicensed - [GitHub](https://github.com/scikit-learn-contrib/lightning) (👨‍💻 17 · 🔀 170 · 📥 100 · 📦 96 · 📋 85 - 52% open · ⏱️ 15.06.2021): @@ -10159,7 +10159,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge sklearn-contrib-lightning ```
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fancyimpute (🥈21 · ⭐ 1K) - Multivariate imputation and matrix completion algorithms.. Apache-2 +
fancyimpute (🥈21 · ⭐ 1K) - 多元插补和矩阵补全算法。Apache-2 - [GitHub](https://github.com/iskandr/fancyimpute) (👨‍💻 12 · 🔀 160 · 📦 1.1K · 📋 110 - 0% open · ⏱️ 21.10.2021): @@ -10171,7 +10171,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install fancyimpute ```
-
scikit-opt (🥈20 · ⭐ 2.8K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. MIT +
scikit-opt (🥈20 · ⭐ 2.8K) - 遗传算法，粒子群优化等实现。MIT - [GitHub](https://github.com/guofei9987/scikit-opt) (👨‍💻 13 · 🔀 660 · 📦 55 · 📋 130 - 22% open · ⏱️ 04.12.2021): @@ -10183,7 +10183,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-opt ```
-
scikit-lego (🥈19 · ⭐ 670) - Extra blocks for scikit-learn pipelines. MIT +
scikit-lego (🥈19 · ⭐ 670) - scikit学习管道的额外块。MIT - [GitHub](https://github.com/koaning/scikit-lego) (👨‍💻 48 · 🔀 75 · 📦 39 · 📋 230 - 13% open · ⏱️ 09.12.2021): @@ -10199,7 +10199,7 @@ _Libraries that extend scikit-learn with additional capabilities._ conda install -c conda-forge scikit-lego ```
-
scikit-multilearn (🥉18 · ⭐ 710 · 💀) - A scikit-learn based module for multi-label et. al... BSD-2 +
scikit-multilearn (🥉18 · ⭐ 710 · 💀) - 基于scikit-learn的多标签等模块。BSD-2 - [GitHub](https://github.com/scikit-multilearn/scikit-multilearn) (👨‍💻 15 · 🔀 130 · 📦 610 · 📋 170 - 43% open · ⏱️ 21.05.2019): @@ -10211,7 +10211,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-multilearn ```
-
iterative-stratification (🥉18 · ⭐ 610) - scikit-learn cross validators for iterative.. BSD-3 +
iterative-stratification (🥉18 · ⭐ 610) - scikit-learn交叉验证器。BSD-3 - [GitHub](https://github.com/trent-b/iterative-stratification) (👨‍💻 6 · 🔀 56 · 📦 180 · 📋 19 - 21% open · ⏱️ 11.11.2021): @@ -10223,7 +10223,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install iterative-stratification ```
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combo (🥉17 · ⭐ 560) - (AAAI' 20) A Python Toolbox for Machine Learning Model.. BSD-2 xgboost +
combo (🥉17 · ⭐ 560) - （AAAI'20）用于机器学习模型的Python工具箱。BSD-2 xgboost - [GitHub](https://github.com/yzhao062/combo) (🔀 93 · 📦 440 · 📋 12 - 75% open · ⏱️ 02.10.2021): @@ -10235,7 +10235,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install combo ```
-
sklearn-crfsuite (🥉16 · ⭐ 380 · 💀) - scikit-learn inspired API for CRFsuite. ❗Unlicensed +
sklearn-crfsuite (🥉16 · ⭐ 380 · 💀) - 用于CRFsuite的scikit-learn启发式API。❗Unlicensed - [GitHub](https://github.com/TeamHG-Memex/sklearn-crfsuite) (👨‍💻 6 · 🔀 180 · 📦 3.3K · 📋 53 - 56% open · ⏱️ 05.12.2019): @@ -10247,7 +10247,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install sklearn-crfsuite ```
-
skggm (🥉16 · ⭐ 190 · 💤) - Scikit-learn compatible estimation of general graphical models. MIT +
skggm (🥉16 · ⭐ 190 · 💤) - 通用图形模型的Scikit学习兼容估计。MIT - [GitHub](https://github.com/skggm/skggm) (👨‍💻 5 · 🔀 34 · 📦 8 · 📋 75 - 37% open · ⏱️ 24.12.2020): @@ -10259,7 +10259,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install skggm ```
-
DESlib (🥉15 · ⭐ 370) - A Python library for dynamic classifier and ensemble selection. BSD-3 +
DESlib (🥉15 · ⭐ 370) - 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) (👨‍💻 13 · 🔀 56 · 📦 22 · 📋 140 - 8% open · ⏱️ 10.10.2021): @@ -10271,7 +10271,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install deslib ```
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scikit-tda (🥉15 · ⭐ 320) - Topological Data Analysis for Python. ❗Unlicensed +
scikit-tda (🥉15 · ⭐ 320) - Python的拓扑数据分析。❗Unlicensed - [GitHub](https://github.com/scikit-tda/scikit-tda) (👨‍💻 3 · 🔀 38 · 📦 24 · 📋 16 - 75% open · ⏱️ 03.08.2021): @@ -10283,7 +10283,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install scikit-tda ```
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skope-rules (🥉14 · ⭐ 420 · 💀) - machine learning with logical rules in Python. ❗Unlicensed +
skope-rules (🥉14 · ⭐ 420 · 💀) - 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 · 🔀 69 · 📦 58 · 📋 27 - 81% open · ⏱️ 23.10.2020): @@ -10295,7 +10295,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install skope-rules ```
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celer (🥉14 · ⭐ 130) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. BSD-3 +
celer (🥉14 · ⭐ 130) - 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) (👨‍💻 9 · 🔀 23 · 📦 10 · 📋 69 - 20% open · ⏱️ 10.12.2021): @@ -10307,7 +10307,7 @@ _Libraries that extend scikit-learn with additional capabilities._ pip install celer ```
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dabl (🥉12 · ⭐ 110) - Data Analysis Baseline Library. BSD-3 +
dabl (🥉12 · ⭐ 110) - 数据分析基准库。BSD-3 - [GitHub](https://github.com/amueller/dabl) (👨‍💻 21 · 🔀 9 · ⏱️ 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 (🥇27 · ⭐ 3.9K) - The easiest way to use deep metric learning in your application. Modular,.. MIT +
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 - [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (👨‍💻 21 · 🔀 480 · 📦 180 · 📋 310 - 12% open · ⏱️ 08.12.2021): @@ -10343,7 +10343,7 @@ _Libraries that extend Pytorch with additional capabilities._ conda install -c metric-learning pytorch-metric-learning ```
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pytorch-summary (🥇24 · ⭐ 3.3K · 💤) - Model summary in PyTorch similar to `model.summary()`.. MIT +
pytorch-summary (🥇24 · ⭐ 3.3K · 💤) - PyTorch中的模型摘要类似于`model.summary（）`。MIT - [GitHub](https://github.com/sksq96/pytorch-summary) (👨‍💻 11 · 🔀 370 · 📦 3.9K · 📋 130 - 70% open · ⏱️ 10.05.2021): @@ -10355,7 +10355,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchsummary ```
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pytorch-optimizer (🥇23 · ⭐ 2.2K) - torch-optimizer -- collection of optimizers for.. Apache-2 +
pytorch-optimizer (🥇23 · ⭐ 2.2K) - torch-optimizer - pytorch的优化器集合。Apache-2 - [GitHub](https://github.com/jettify/pytorch-optimizer) (👨‍💻 25 · 🔀 210 · 📦 410 · 📋 43 - 34% open · ⏱️ 11.11.2021): @@ -10367,7 +10367,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch_optimizer ```
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pretrainedmodels (🥈22 · ⭐ 8.3K · 💀) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. BSD-3 +
pretrainedmodels (🥈22 · ⭐ 8.3K · 💀) - pytorch预训练的ConvNets：NASNet，ResNeXt等BSD-3 - [GitHub](https://github.com/Cadene/pretrained-models.pytorch) (👨‍💻 22 · 🔀 1.7K · 📦 1.3K · 📋 170 - 46% open · ⏱️ 16.04.2020): @@ -10379,7 +10379,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pretrainedmodels ```
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EfficientNet-PyTorch (🥈22 · ⭐ 6.7K · 💤) - A PyTorch implementation of EfficientNet and.. Apache-2 +
EfficientNet-PyTorch (🥈22 · ⭐ 6.7K · 💤) - EfficientNet等模型的PyTorch实现Apache-2 - [GitHub](https://github.com/lukemelas/EfficientNet-PyTorch) (👨‍💻 24 · 🔀 1.3K · 📥 1M · 📋 260 - 49% open · ⏱️ 15.04.2021): @@ -10391,7 +10391,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install efficientnet-pytorch ```
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SRU (🥈22 · ⭐ 2K · 💤) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). MIT +
SRU (🥈22 · ⭐ 2K · 💤) - 与CNN一样快地训练RNN（https://arxiv.org/abs/1709.02755）。MIT - [GitHub](https://github.com/asappresearch/sru) (👨‍💻 21 · 🔀 290 · 📦 17 · 📋 120 - 44% open · ⏱️ 19.05.2021): @@ -10403,7 +10403,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install sru ```
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reformer-pytorch (🥈22 · ⭐ 1.6K) - Reformer, the efficient Transformer, in Pytorch. MIT +
reformer-pytorch (🥈22 · ⭐ 1.6K) - Reformer，Pytorch中高效的transformer实现。MIT - [GitHub](https://github.com/lucidrains/reformer-pytorch) (👨‍💻 10 · 🔀 220 · 📋 120 - 10% open · ⏱️ 06.11.2021): @@ -10415,7 +10415,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install reformer-pytorch ```
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torchdiffeq (🥈21 · ⭐ 3.8K) - Differentiable ODE solvers with full GPU support and.. MIT +
torchdiffeq (🥈21 · ⭐ 3.8K) - 具有完整GPU支持的可微分ODE求解器。MIT - [GitHub](https://github.com/rtqichen/torchdiffeq) (👨‍💻 20 · 🔀 660 · 📦 180 · 📋 160 - 17% open · ⏱️ 22.09.2021): @@ -10427,7 +10427,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchdiffeq ```
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Torchmeta (🥈21 · ⭐ 1.5K) - A collection of extensions and data-loaders for few-shot learning.. MIT +
Torchmeta (🥈21 · ⭐ 1.5K) - 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 · 🔀 180 · 📦 78 · 📋 120 - 26% open · ⏱️ 20.09.2021): @@ -10439,7 +10439,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torchmeta ```
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TabNet (🥈21 · ⭐ 1.5K) - PyTorch implementation of TabNet paper :.. MIT +
TabNet (🥈21 · ⭐ 1.5K) - Efficient Neural Architecture Search的Pytorch实现。MIT - [GitHub](https://github.com/dreamquark-ai/tabnet) (👨‍💻 18 · 🔀 290 · 📋 180 - 8% open · ⏱️ 12.11.2021): @@ -10451,7 +10451,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pytorch-tabnet ```
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Pytorch Toolbelt (🥈21 · ⭐ 1.2K) - PyTorch extensions for fast R&D prototyping and Kaggle.. MIT +
Pytorch Toolbelt (🥈21 · ⭐ 1.2K) - PyTorch扩展用于快速研发原型和Kaggle实验。MIT - [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (👨‍💻 6 · 🔀 85 · 📋 22 - 18% open · ⏱️ 06.12.2021): @@ -10463,7 +10463,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install pytorch_toolbelt ```
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torch-scatter (🥉20 · ⭐ 840) - PyTorch Extension Library of Optimized Scatter Operations. MIT +
torch-scatter (🥉20 · ⭐ 840) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_scatter) (👨‍💻 18 · 🔀 86 · 📋 230 - 8% open · ⏱️ 13.11.2021): @@ -10475,7 +10475,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch-scatter ```
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PyTorch Sparse (🥉20 · ⭐ 540) - PyTorch Extension Library of Optimized Autograd Sparse.. MIT +
PyTorch Sparse (🥉20 · ⭐ 540) - 优化图聚类的PyTorch扩展库MIT - [GitHub](https://github.com/rusty1s/pytorch_sparse) (👨‍💻 17 · 🔀 68 · 📋 150 - 16% open · ⏱️ 13.11.2021): @@ -10487,7 +10487,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install torch-sparse ```
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Poutyne (🥉20 · ⭐ 510) - A simplified framework and utilities for PyTorch. ❗️LGPL-3.0 +
Poutyne (🥉20 · ⭐ 510) - PyTorch的简化框架和实用程序。❗️LGPL-3.0 - [GitHub](https://github.com/GRAAL-Research/poutyne) (👨‍💻 16 · 🔀 56 · 📦 73 · 📋 44 - 13% open · ⏱️ 09.11.2021): @@ -10499,7 +10499,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install poutyne ```
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Antialiased CNNs (🥉19 · ⭐ 1.5K) - pip install antialiased-cnns to improve stability and.. ❗️CC BY-NC-SA 4.0 +
Antialiased CNNs (🥉19 · ⭐ 1.5K) - 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 · 🔀 180 · 📦 12 · 📋 41 - 24% open · ⏱️ 29.09.2021): @@ -10511,7 +10511,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install antialiased-cnns ```
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EfficientNets (🥉19 · ⭐ 1.4K) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. Apache-2 +
EfficientNets (🥉19 · ⭐ 1.4K) - 预训练的EfficientNet，EfficientNet-Lite，MixNet等Apache-2 - [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (👨‍💻 5 · 🔀 190 · 📦 87 · 📋 51 - 3% open · ⏱️ 08.07.2021): @@ -10523,7 +10523,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install geffnet ```
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Higher (🥉19 · ⭐ 1.3K) - higher is a pytorch library allowing users to obtain higher.. Apache-2 +
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 - [GitHub](https://github.com/facebookresearch/higher) (👨‍💻 9 · 🔀 95 · 📦 100 · 📋 95 - 47% open · ⏱️ 26.10.2021): @@ -10535,7 +10535,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install higher ```
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Performer Pytorch (🥉19 · ⭐ 760) - An implementation of Performer, a linear attention-.. MIT +
Performer Pytorch (🥉19 · ⭐ 760) - Performer的实现。MIT - [GitHub](https://github.com/lucidrains/performer-pytorch) (👨‍💻 6 · 🔀 99 · 📦 34 · 📋 68 - 39% open · ⏱️ 07.11.2021): @@ -10547,7 +10547,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install performer-pytorch ```
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Tez (🥉18 · ⭐ 730) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. Apache-2 +
Tez (🥉18 · ⭐ 730) - Tez是用于PyTorch的超级简单且轻巧的Trainer。Apache-2 - [GitHub](https://github.com/abhishekkrthakur/tez) (🔀 110 · 📦 17 · 📋 26 - 61% open · ⏱️ 27.09.2021): @@ -10559,7 +10559,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install tez ```
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Pywick (🥉18 · ⭐ 360) - High-level batteries-included neural network training library.. ❗Unlicensed +
Pywick (🥉18 · ⭐ 360) - 更高层次的pytorch神经网络训练库。❗Unlicensed - [GitHub](https://github.com/achaiah/pywick) (👨‍💻 4 · 🔀 38 · 📦 5 · 📋 13 - 7% open · ⏱️ 22.10.2021): @@ -10579,7 +10579,7 @@ _Libraries that extend Pytorch with additional capabilities._ git clone https://github.com/geohot/tinygrad ```
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AdaBound (🥉16 · ⭐ 2.9K · 💀) - An optimizer that trains as fast as Adam and as good as SGD. Apache-2 +
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 - [GitHub](https://github.com/Luolc/AdaBound) (👨‍💻 2 · 🔀 320 · 📦 120 · 📋 24 - 70% open · ⏱️ 06.03.2019): @@ -10591,7 +10591,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install adabound ```
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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 · 🔀 150 · 📦 3 · 📋 27 - 44% open · ⏱️ 18.11.2020): @@ -10603,7 +10603,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install lambda-networks ```
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Tensor Sensor (🥉16 · ⭐ 620) - The goal of this library is to generate more helpful.. MIT +
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 - [GitHub](https://github.com/parrt/tensor-sensor) (👨‍💻 3 · 🔀 31 · 📦 7 · 📋 23 - 34% open · ⏱️ 13.12.2021): @@ -10615,7 +10615,7 @@ _Libraries that extend Pytorch with additional capabilities._ pip install tensor-sensor ```
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torchsde (🥉15 · ⭐ 880) - Differentiable SDE solvers with GPU support and efficient.. Apache-2 +
torchsde (🥉15 · ⭐ 880) - 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 · 🔀 96 · 📦 9 · 📋 41 - 17% 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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Torch-Struct (🥉14 · ⭐ 1K) - Fast, general, and tested differentiable structured prediction.. MIT +
Torch-Struct (🥉14 · ⭐ 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) (👨‍💻 13 · 🔀 76 · 📋 49 - 42% open · ⏱️ 04.11.2021): @@ -10631,7 +10631,7 @@ _Libraries that extend Pytorch with additional capabilities._ git clone https://github.com/harvardnlp/pytorch-struct ```
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micrograd (🥉12 · ⭐ 1.8K · 💀) - A tiny scalar-valued autograd engine and a neural net library.. MIT +
micrograd (🥉12 · ⭐ 1.8K · 💀) - 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 · 🔀 140 · 📦 4 · 📋 5 - 40% open · ⏱️ 18.04.2020): @@ -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 ( ⭐ 2) - Collection of database clients for python.
-## Chinese NLP +## 中文自然语言处理 -Back to top +Back to top
jieba (🥇31 · ⭐ 28K · 💀) - 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 (🥇39 · ⭐ 8.9K) - Ecosystem of open-source software for mathematics, science, and engineering. BSD-3 +
scipy (🥇39 · ⭐ 8.9K) - 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) (👨‍💻 1.2K · 🔀 3.9K · 📥 330K · 📦 440K · 📋 7.8K - 18% open · ⏱️ 16.12.2021): @@ -10709,7 +10709,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge scipy ```
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SymPy (🥇33 · ⭐ 8.7K) - A computer algebra system written in pure Python. ❗Unlicensed +
SymPy (🥇33 · ⭐ 8.7K) - 用纯Python编写的计算机代数系统。❗Unlicensed - [GitHub](https://github.com/sympy/sympy) (👨‍💻 1.1K · 🔀 3.5K · 📥 440K · 📦 38K · 📋 11K - 32% open · ⏱️ 15.12.2021): @@ -10725,7 +10725,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge sympy ```
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PyOD (🥇31 · ⭐ 5.1K) - (JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly.. BSD-2 +
PyOD (🥇31 · ⭐ 5.1K) - （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) (👨‍💻 31 · 🔀 990 · 📦 1K · 📋 220 - 48% open · ⏱️ 01.11.2021): @@ -10737,7 +10737,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install pyod ```
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DeepChem (🥇27 · ⭐ 3.3K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. MIT +
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 - [GitHub](https://github.com/deepchem/deepchem) (👨‍💻 180 · 🔀 1.2K · 📦 65 · 📋 1.4K - 27% open · ⏱️ 15.12.2021): @@ -10749,7 +10749,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install deepchem ```
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hdbscan (🥇27 · ⭐ 2K) - A high performance implementation of HDBSCAN clustering. BSD-3 +
hdbscan (🥇27 · ⭐ 2K) - HDBSCAN群集的高性能实现。BSD-3 - [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (👨‍💻 74 · 🔀 360 · 📦 1.1K · 📋 400 - 62% open · ⏱️ 24.11.2021): @@ -10765,7 +10765,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge hdbscan ```
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Cython BLIS (🥇27 · ⭐ 180) - Fast matrix-multiplication as a self-contained Python.. ❗Unlicensed +
Cython BLIS (🥇27 · ⭐ 180) - 快速矩阵乘法库。❗Unlicensed - [GitHub](https://github.com/explosion/cython-blis) (👨‍💻 10 · 🔀 29 · 📦 15K · 📋 27 - 18% open · ⏱️ 17.11.2021): @@ -10781,7 +10781,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge cython-blis ```
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Pythran (🥈26 · ⭐ 1.7K) - Ahead of Time compiler for numeric kernels. BSD-3 +
Pythran (🥈26 · ⭐ 1.7K) - 用于数字内核的时间编译器。BSD-3 - [GitHub](https://github.com/serge-sans-paille/pythran) (👨‍💻 64 · 🔀 160 · 📦 89 · 📋 730 - 13% open · ⏱️ 14.12.2021): @@ -10797,7 +10797,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pythran ```
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agate (🥈26 · ⭐ 1.1K) - A Python data analysis library that is optimized for humans instead of.. MIT +
agate (🥈26 · ⭐ 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 · 🔀 130 · 📦 690 · 📋 640 - 0% open · ⏱️ 15.07.2021): @@ -10813,7 +10813,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge agate ```
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PaddleHub (🥈25 · ⭐ 7.3K) - Awesome pre-trained models toolkit based on.. Apache-2 +
PaddleHub (🥈25 · ⭐ 7.3K) - 基于PaddlePaddle的出色的预训练模型工具包。Apache-2 - [GitHub](https://github.com/PaddlePaddle/PaddleHub) (👨‍💻 48 · 🔀 1.4K · 📥 560 · 📦 600 · 📋 970 - 36% open · ⏱️ 16.12.2021): @@ -10825,7 +10825,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install paddlehub ```
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Autograd (🥈25 · ⭐ 5.6K · 💤) - Efficiently computes derivatives of numpy code. MIT +
Autograd (🥈25 · ⭐ 5.6K · 💤) - 高效地计算导数的numpy代码。MIT - [GitHub](https://github.com/HIPS/autograd) (👨‍💻 51 · 🔀 770 · 📦 2.8K · 📋 360 - 39% open · ⏱️ 03.03.2021): @@ -10841,7 +10841,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge autograd ```
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pyclustering (🥈25 · ⭐ 900 · 💤) - pyclustring is a Python, C++ data mining library. BSD-3 +
pyclustering (🥈25 · ⭐ 900 · 💤) - pyclustring是Python，C++数据挖掘库。BSD-3 - [GitHub](https://github.com/annoviko/pyclustering) (👨‍💻 26 · 🔀 210 · 📥 380 · 📦 260 · 📋 640 - 8% open · ⏱️ 12.02.2021): @@ -10857,7 +10857,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyclustering ```
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pyjanitor (🥈25 · ⭐ 780) - Clean APIs for data cleaning. Python implementation of R package Janitor. MIT +
pyjanitor (🥈25 · ⭐ 780) - 用于数据清理的API。MIT - [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (👨‍💻 95 · 🔀 130 · 📦 130 · 📋 420 - 20% open · ⏱️ 22.11.2021): @@ -10873,7 +10873,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyjanitor ```
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carla (🥈24 · ⭐ 7K) - Open-source simulator for autonomous driving research. MIT +
carla (🥈24 · ⭐ 7K) - 用于自动驾驶研究的开源模拟器。MIT - [GitHub](https://github.com/carla-simulator/carla) (👨‍💻 140 · 🔀 2K · 📦 110 · 📋 3.6K - 12% open · ⏱️ 19.11.2021): @@ -10885,7 +10885,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install carla ```
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Datasette (🥈24 · ⭐ 5.6K) - An open source multi-tool for exploring and publishing data. Apache-2 +
Datasette (🥈24 · ⭐ 5.6K) - 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) (👨‍💻 60 · 🔀 360 · 📥 34 · 📦 560 · 📋 1.2K - 26% open · ⏱️ 15.12.2021): @@ -10897,7 +10897,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install datasette ```
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Gradio (🥈24 · ⭐ 4.3K) - Wrap UIs around any model, share with anyone. Apache-2 +
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): @@ -10909,7 +10909,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install gradio ```
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causalml (🥉23 · ⭐ 2.5K) - Uplift modeling and causal inference with machine learning.. ❗Unlicensed +
causalml (🥉23 · ⭐ 2.5K) - 利用机器学习提升建模和因果推理。❗Unlicensed - [GitHub](https://github.com/uber/causalml) (👨‍💻 31 · 🔀 380 · 📦 33 · 📋 230 - 16% open · ⏱️ 14.12.2021): @@ -10921,7 +10921,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install causalml ```
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PySwarms (🥉23 · ⭐ 870) - A research toolkit for particle swarm optimization in Python. MIT +
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): @@ -10933,7 +10933,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install pyswarms ```
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Streamlit (🥉22 · ⭐ 17K) - Streamlit The fastest way to build data apps in Python. Apache-2 +
Streamlit (🥉22 · ⭐ 17K) - Streamlit用Python构建数据应用程序的最快方法。Apache-2 - [GitHub](https://github.com/streamlit/streamlit) (👨‍💻 130 · 🔀 1.5K · 📦 190 · 📋 2.1K - 23% open · ⏱️ 15.12.2021): @@ -10945,7 +10945,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install streamlit ```
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Trax (🥉22 · ⭐ 6.7K) - Trax Deep Learning with Clear Code and Speed. Apache-2 +
Trax (🥉22 · ⭐ 6.7K) - 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) (👨‍💻 74 · 🔀 660 · 📦 40 · 📋 200 - 41% open · ⏱️ 03.12.2021): @@ -10957,7 +10957,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install trax ```
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TabPy (🥉22 · ⭐ 1.2K) - Execute Python code on the fly and display results in Tableau visualizations:. MIT +
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 - [GitHub](https://github.com/tableau/TabPy) (👨‍💻 43 · 🔀 440 · 📦 79 · 📋 280 - 5% open · ⏱️ 11.10.2021): @@ -10969,7 +10969,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install tabpy ```
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metric-learn (🥉21 · ⭐ 1.2K) - Metric learning algorithms in Python. MIT +
metric-learn (🥉21 · ⭐ 1.2K) - Python中的度量学习算法。MIT - [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (👨‍💻 21 · 🔀 210 · 📦 180 · 📋 160 - 27% open · ⏱️ 17.11.2021): @@ -10981,7 +10981,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install metric-learn ```
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StreamAlert (🥉20 · ⭐ 2.6K) - StreamAlert is a serverless, realtime data analysis framework.. Apache-2 +
StreamAlert (🥉20 · ⭐ 2.6K) - StreamAlert是无服务器的实时数据分析框架。Apache-2 - [GitHub](https://github.com/airbnb/streamalert) (👨‍💻 33 · 🔀 310 · 📋 340 - 24% open · ⏱️ 04.11.2021): @@ -10989,7 +10989,7 @@ _Libraries for connecting to, operating, and querying databases._ git clone https://github.com/airbnb/streamalert ```
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cleanlab (🥉20 · ⭐ 2.5K) - The standard package for machine learning with noisy labels and.. ❗️AGPL-3.0 +
cleanlab (🥉20 · ⭐ 2.5K) - 机器学习的标准软件包。❗️AGPL-3.0 - [GitHub](https://github.com/cleanlab/cleanlab) (👨‍💻 6 · 🔀 240 · 📦 24 · 📋 81 - 41% open · ⏱️ 08.11.2021): @@ -11001,7 +11001,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install cleanlab ```
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gplearn (🥉20 · ⭐ 1K) - Genetic Programming in Python, with a scikit-learn inspired API. BSD-3 +
gplearn (🥉20 · ⭐ 1K) - 使用scikit-learn启发式API进行Python遗传编程。BSD-3 - [GitHub](https://github.com/trevorstephens/gplearn) (👨‍💻 10 · 🔀 180 · 📦 210 · 📋 170 - 26% open · ⏱️ 18.10.2021): @@ -11013,7 +11013,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install gplearn ```
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pyopencl (🥉20 · ⭐ 860) - OpenCL integration for Python, plus shiny features. ❗Unlicensed +
pyopencl (🥉20 · ⭐ 860) - 适用于Python的OpenCL集成。❗Unlicensed - [GitHub](https://github.com/inducer/pyopencl) (👨‍💻 90 · 🔀 210 · 📦 590 · 📋 290 - 20% open · ⏱️ 13.12.2021): @@ -11029,7 +11029,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge pyopencl ```
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Prince (🥉20 · ⭐ 740) - Python factor analysis library (PCA, CA, MCA, MFA, FAMD). MIT +
Prince (🥉20 · ⭐ 740) - Python因子分析库（PCA，CA，MCA，MFA，FAMD）。MIT - [GitHub](https://github.com/MaxHalford/prince) (👨‍💻 10 · 🔀 130 · 📦 170 · 📋 100 - 33% open · ⏱️ 11.12.2021): @@ -11041,7 +11041,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install prince ```
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findspark (🥉20 · ⭐ 420) - Find pyspark to make it importable. BSD-3 +
findspark (🥉20 · ⭐ 420) - 查找pyspark并导入的工具库。BSD-3 - [GitHub](https://github.com/minrk/findspark) (👨‍💻 14 · 🔀 66 · 📦 2.1K · 📋 21 - 52% open · ⏱️ 14.06.2021): @@ -11057,7 +11057,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge findspark ```
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River (🥉19 · ⭐ 3K) - Online machine learning in Python. BSD-3 +
River (🥉19 · ⭐ 3K) - Python中的在线机器学习。BSD-3 - [GitHub](https://github.com/online-ml/river) (👨‍💻 70 · 🔀 320 · 📦 56 · 📋 330 - 1% open · ⏱️ 16.12.2021): @@ -11065,7 +11065,7 @@ _Libraries for connecting to, operating, and querying databases._ git clone https://github.com/online-ml/river ```
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impyute (🥉19 · ⭐ 300) - Data imputations library to preprocess datasets with missing data. MIT +
impyute (🥉19 · ⭐ 300) - 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 · 🔀 43 · 📦 120 · 📋 64 - 42% open · ⏱️ 06.11.2021): @@ -11077,7 +11077,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install impyute ```
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AstroML (🥉16 · ⭐ 790 · 💤) - Machine learning, statistics, and data mining for astronomy and.. BSD-2 +
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 - [GitHub](https://github.com/astroML/astroML) (👨‍💻 30 · 🔀 260 · 📋 140 - 37% open · ⏱️ 07.04.2021): @@ -11093,7 +11093,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge astroml ```
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BioPandas (🥉16 · ⭐ 400) - Working with molecular structures in pandas DataFrames. BSD-3 +
BioPandas (🥉16 · ⭐ 400) - 在pandas DataFrames中处理分子结构。BSD-3 - [GitHub](https://github.com/rasbt/biopandas) (👨‍💻 8 · 🔀 89 · 📋 39 - 38% open · ⏱️ 24.09.2021): @@ -11109,7 +11109,7 @@ _Libraries for connecting to, operating, and querying databases._ conda install -c conda-forge biopandas ```
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SUOD (🥉16 · ⭐ 300) - (MLSys' 21) An Acceleration System for Large-scare Unsupervised.. BSD-2 +
SUOD (🥉16 · ⭐ 300) - （MLSys' 21）大型无人驾驶加速系统。BSD-2 - [GitHub](https://github.com/yzhao062/SUOD) (🔀 36 · 📦 400 · 📋 6 - 66% open · ⏱️ 02.10.2021): @@ -11121,7 +11121,7 @@ _Libraries for connecting to, operating, and querying databases._ pip install suod ```
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Feature Engine (🥉12 · ⭐ 9) - Feature engineering package with sklearn like functionality. BSD-3 +
Feature Engine (🥉12 · ⭐ 9) - 具有sklearn类功能的功能工程包。BSD-3 - [GitHub](https://github.com/solegalli/feature_engine) (👨‍💻 24 · 🔀 6 · ⏱️ 06.08.2021):