optuna and optuna-examples
The examples repository serves as supplementary documentation and use-case demonstrations for the main hyperparameter optimization framework, making them complements that are typically used together rather than alternatives.
About optuna
optuna/optuna
A hyperparameter optimization framework
Supports dynamic, conditionally-constructed search spaces through a define-by-run imperative API that allows hyperparameter dependencies. Leverages state-of-the-art sampling algorithms (TPE, GP-based, multi-objective optimization) with built-in early stopping via trial pruning. Integrates with PyTorch, TensorFlow/Keras, LightGBM, XGBoost, and distributed frameworks like Dask for scaling across multiple workers.
About optuna-examples
optuna/optuna-examples
Examples for https://github.com/optuna/optuna
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