From 369f75e85208c19cd8a9fb72c651cb77fbfec55c Mon Sep 17 00:00:00 2001 From: Vinta Chen Date: Fri, 16 Oct 2026 17:25:24 +0800 Subject: [PATCH] feat: add optuna to Machine Learning > Hyperparameter Optimization Hyperparameter optimization had no use case, and optuna is its obvious choice. Co-Authored-By: Claude --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 40c14308..d2343136 100644 --- a/README.md +++ b/README.md @@ -222,6 +222,8 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git - [statsforecast](https://github.com/Nixtla/statsforecast) - Fast statistical forecasting models such as ARIMA, ETS, and Theta, compiled with numba. - [sktime](https://github.com/sktime/sktime) - A unified scikit-learn-style framework for forecasting and other time-series learning tasks. - [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting, with non-commercial default weights. +- Hyperparameter Optimization + - [optuna](https://github.com/optuna/optuna) - A hyperparameter optimization framework with define-by-run search spaces and pruning of unpromising trials. ### Natural Language Processing