RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.

This project provides implementations with Keras/Tensorflow of some deep learning algorithms for Multivariate Time Series Forecasting: Transformers, Recurrent neural networks (LSTM and GRU), Convolutional neural networks, Multi-layer perceptron

Monorepo for trading algorithms

Algotrading toolkit using customizable strategies, genetic algorithms, and RNN-based strategies

Pytorch implementation of a sentence sentiment classification model with CNN, RNN, RNF (Recurrent Neural Filter) and BERT

✨Using RNN and LSTM generate poetry by Keras, and translate poetry. (通过Keras实现基于RNN与LSTM的藏头诗自动生成模型, 并将生成的古诗翻译成英文.)

Scripts for M-LARGE training and analysis

RNN 文本生成诗歌

DECtalk song generator using a simple RNN architecture

RNN using LSTM layers in coded in Python using Keras to predict Google open stock prices.

运用 LSTM 网络进行古诗生成，探索人工智能于古典文学创作之应用。

Predictive Modelling of Time Series Data using LSTM RNNs

A web app that visualizes California county vaccination patterns and predicts their future trends with LSTM networks.

This repository is a Pytorch implemented version for CRNN OCR model

AI project on Healthcare emergencies demand immediate and precise intervention. This is quick, accurate and guidance critical in saving lives. This project focuses on AI-powered system specifically designed for healthcare emergencies, enabling efficient, real-time responses through both voice and video calls.

CSCI 59000 BIG DATA ANALYTICS PROJECT

Third Assignment in ׳Deep Learning for Texts and Sequences׳ course by Prof. Yoav Goldberg at Bar-Ilan University

Recurrent neural network for short-term market price prediction using TensorFlow