I recently came across this concept of hyperparameter tuning and yielding out the optimal set of hyperparameters for a given model, and RandomizedSearchCV was one of the types. I get that how it works, it takes out samples from a population and then trains the model with those hyperparameters, and then evaluates its performance. And I get the difference between this and GridSearchCV. My teacher just taught me in class regarding its types but didn’t provide any code snippet to work with, can any one of you please let me know about its types and how do they work using code snippets?