fyf-393's Stars
wubin5/STTN
paper : <Spatial-Temporal Transformer Networks for Traffic Flow Forecasting>
zhouhaoyi/Informer2020
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
philipperemy/n-beats
Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.
locuslab/TCN
Sequence modeling benchmarks and temporal convolutional networks
philipperemy/keras-tcn
Keras Temporal Convolutional Network.
morielcoh/Stocks-prediction-pytorch
Stocks prediction using LSTM and GRU
jsyoon0823/Time-series-prediction
Basic RNN, LSTM, GRU, and Attention for time-series prediction
FraPochetti/StocksProject
Predict Stocks Market Machine Learning
jbamford/stock_surface
Machine Learning Algorithm To Predict Stock Direction
UWFlex/stock-prediction
Machine learning pipeline for training TensorFlow models to forecast stock prices. Written in Python.
lilianweng/stock-rnn
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
jaungiers/LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
Jake0303/StockPricePrediction
Attemp to predict stock prices with previous historical data using machine learning specifically regression.
borisbanushev/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
yjustc2019/StockPricePrediction
Stock Price Prediction using Machine Learning Techniques