automl-hyperparameter-optimization
From the author
Best practices for AutoML and hyperparameter search with Optuna, Ray Tune, and PyCaret, covering search-space design, validation splits, and leakage prevention. Use when tuning model hyperparameters, setting up a pruned or distributed hyperparameter search, designing a nested validation scheme, or evaluating whether an AutoML leaderboard result is production-ready.
Install
npx skills add Mindrally/skills --skill automl-hyperparameter-optimization -a claude-code
Installs to .claude/skills/automl-hyperparameter-optimization/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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