What is Hyperparameter Tuning?

Hyperparameter tuning, also known as hyperparameter optimization, is the process of finding the optimal set of hyperparameters for a machine learning algorithm. Hyperparameters are parameters whose values are set prior to the commencement of the learning process. Common methods include grid search, random search, and Bayesian optimization. It is used to improve model performance and generalization.