Time series prediction
This repository implements the common methods of time series prediction, especially deep learning methods in TensorFlow2.
It's welcomed to contribute if you have any better idea, just create a PR. If any question, feel free to open an issue.
Ongoing project, I will continue to improve this, so you might want to watch/star this repo to revisit.
RNN |
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wavenet |
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transformer |
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U-Net |
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n-beats |
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GAN |
Usage
- Install the required library
pip install -r requirements.txt
- Download the data, if necessary
bash ./data/download_passenger.sh
- Train the model
setcustom_model_params
if you want (refer to params in./deepts/models/*.py
), and pay attention to feature engineering.
cd examples
python run_train.py --use_model seq2seq
cd ..
tensorboard --logdir=./data/logs
- Predict new data
cd examples
python run_test.py
Further reading
- https://github.com/awslabs/gluon-ts/
- https://github.com/Azure/DeepLearningForTimeSeriesForecasting
- https://github.com/microsoft/forecasting