Description
Optuna is an open-source, automated hyperparameter optimization framework that helps machine learning practitioners fine-tune models efficiently. It supports define-by-run optimization, allowing dynamic search space configuration and enabling efficient Bayesian, grid, and random search strategies. Optuna provides pruning mechanisms to stop unpromising trials early, reducing computational cost. It integrates seamlessly with TensorFlow, PyTorch, Scikit-learn, and other ML libraries. With parallel optimization capabilities, it can scale across multiple CPUs and GPUs. Optuna’s visualization tools help analyze trial results, making hyperparameter tuning more accessible and efficient for both researchers and engineers working in AI and deep learning.
