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feat: add optuna to Machine Learning > Hyperparameter Optimization
Hyperparameter optimization had no use case, and optuna is its obvious choice. Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -222,6 +222,8 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git
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- [statsforecast](https://github.com/Nixtla/statsforecast) - Fast statistical forecasting models such as ARIMA, ETS, and Theta, compiled with numba.
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- [sktime](https://github.com/sktime/sktime) - A unified scikit-learn-style framework for forecasting and other time-series learning tasks.
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- [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting, with non-commercial default weights.
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- Hyperparameter Optimization
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- [optuna](https://github.com/optuna/optuna) - A hyperparameter optimization framework with define-by-run search spaces and pruning of unpromising trials.
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### Natural Language Processing
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