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feat: add statsforecast to Machine Learning > Time Series Forecasting

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The use case had no fast classical statistical forecasting library (ARIMA, ETS, Theta).

Co-Authored-By: Claude <noreply@anthropic.com>
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Vinta Chen
2026-10-02 11:37:54 +08:00
co-authored by Claude
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@@ -210,6 +210,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git
- [catboost](https://github.com/catboost/catboost) - A fast, scalable, high performance gradient boosting on decision trees library.
- Time Series Forecasting
- [prophet](https://github.com/facebook/prophet) - A tool for producing forecasts for time series with multiple seasonality and trend changes.
- [statsforecast](https://github.com/Nixtla/statsforecast) - Fast statistical forecasting models such as ARIMA, ETS, and Theta, compiled with numba.
- [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting, with non-commercial default weights.
### Natural Language Processing