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 any better idea, just create a PR. If any question, feel free to open an issue.

Ongoing project, welcome to join

RNN	intro	code
wavenet	intro	code
transformer	intro	code
U-Net	intro	code
n-beats	intro	code
GAN	intro	code

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Usage

1. Install the library

pip install -r requirements.txt

2. Download the data, if necessary

bash ./data/download_passenger.sh

3. Train the model, set custom_model_params if you want, and pay attention to your own feature engineering

cd examples
python run_train.py --use_model seq2seq

4. Predict new data

python run_test.py

Further reading

• https://github.com/awslabs/gluon-ts/
• https://github.com/Azure/DeepLearningForTimeSeriesForecasting

Contributor

• LongxingTan