Get started with these basic examples:
- Time Series Prediction: Learn how to predict future values.
- Time Series Classification: Explore how to classify time series data.
- Time Series Anomaly Detection: Detect anomalies in time series data.
- AutoML for parameters tuning: Try the parameters auto-tune.
Dive deeper with these interactive notebooks:
- single step prediction: A step-by-step guide to single-step time series prediction.
Check out these advanced examples and competition-winning implementations:
Multiple steps prediction
- TFTS-Bert wins the 3rd place in KDD Cup 2022 wind power forecasting
- TFTS-Seq2seq wins the 4th place in Tianchi ENSO prediction 2021
We welcome contributions! If you have an example, notebook, or improvement to share, please follow these steps