ML Hyperparameter Tuning Overview Use this skill for designing and running hyperparameter searches. Tuning should improve a valid baseline under a fixed evaluation protocol. Do not tune before data validation, leakage-safe splits, metric selection, reproducible training, and a simple baseline are in place. Search Strategy Selection | Strategy | Use when | Notes | |---|---|---| | Manual informed search | Early debugging or very small budgets | Best when guided by learning curves and domain knowledge | | Grid search | Few categorical/discrete parameters | Wasteful in high dimensions | | Random…