hyperparameter tuning

Grid and random search ignore past trials. Bayesian optimization fits a surrogate and picks the next point by acquisition. When that sample cost pays off.

Grid search is the wrong answer at scale. The signal is knowing why random beats grid, how Bayesian optimization and early-stopping schemes (Hyperband/ASHA) spend compute smartly, and how to parallelize without stragglers.