Gwill / Time-series-prediction

A collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter

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Time series prediction

This repo implements the common methods of time series prediction, especially deep learning methods in TensorFlow2. It's highly welcomed to contribute if you have better idea, just create a PR. If any question, feel free to open an issue.

ARIMA

intro

code

GBDT

intro

code

RNN

intro

code

wavenet

intro

code

transformer

intro

code

U-Net

intro

code

n-beats

intro

code

GAN

intro

code

Usage

  1. Install the library
pip install -r requirements.txt
  1. Download the data, if necessary
bash ./data/download_passenger.sh
  1. Train the model, set custom_model_params if you want
cd examples
python run_train.py --use_model seq2seq
  1. Predict new data
python run_test.py

Further reading

https://github.com/awslabs/gluon-ts/

Contributor

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A collection of time series prediction methods: rnn, seq2seq, cnn, wavenet, transformer, unet, n-beats, gan, kalman-filter

License:MIT License


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