Blog: Bayesian optimization

Hyperparameter optimization plays a significant role in the development and refinement of machine learning models, ensuring their optimal performance for specific tasks. The Bayesian optimization algorithm stands out among various methods due to its efficiency and effectiveness. Unlike hyperparameter tuning methods like random search and grid search, which evaluate parameter values independently without considering outcomes from previous iterations, Bayesian optimization leverages results from previous evaluations.