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Hyperparameter search and cross-validation with Optuna

Hyperparameter search: from grid search to smart exploration

Every ML algorithm has hyperparameters that cannot be learned from the data — they must be tuned. GridSearch tries every combination: with 5 parameters and 5 values each, that is 3125 training runs. RandomSearch samples at random: faster, but without memory. Optuna uses Bayesian optimization: each subsequent trial is smarter than the previous one — the model knows where to look.

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