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.
- Install the required library
$ pip install -r requirements.txt
- Download the data, if necessary
$ sh ./data/download_passenger.sh
- Train the model
setcustom_model_params
if you want (refer to params in./tfts/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