model-selection

Hyperparameter tuning with GridSearchCV and randomized search

Hyperparameter search should be targeted, not theatrical. I usually combine a strong baseline, a compact search space, and a metric aligned with business cost. GridSearchCV is good for interpretable sweeps; randomized search is better when the space g

Train test split and stratified cross validation done properly

Evaluation goes wrong when data splitting is treated like boilerplate. I stratify imbalanced targets, guard time order when necessary, and make sure preprocessing lives inside cross-validation. This is the difference between a model that looks good in