About
The Hyperparameter Tuner skill empowers Claude to refine machine learning models through automated exploration of hyperparameter spaces. By leveraging grid search, random search, and Bayesian optimization via libraries like scikit-learn and Optuna, it identifies the most effective configurations to maximize performance metrics such as accuracy, precision, and RMSE. This skill is ideal for data scientists and developers looking to transition from manual tuning to an efficient, code-driven optimization workflow that includes data validation, cross-validation, and detailed performance reporting.
