Grid Search and Random Search

Models have hyperparameters (like max_depth or C) that are not learned from data but set before training. The right values can hugely improve performance, so we search for them systematically.

Trying values by hand is slow and easy to bias. Automated search combined with cross-validation evaluates each candidate fairly and finds the best combination reproducibly.