Hyperparameter Tuning with Optuna

One limitation of many hyperparameter libraries and frameworks is that they define the search space before commencing the optimization. In contrast, Optuna is a hyperparameter tuning framework that has a unique "define-by-run" approach and constructs the search space dynamically.In this course, discover how to train a baseline model and use Optuna to perform hyperparameter tuning to identify the model configuration that maximizes the F1 score. Next, learn how to use Optuna Dashboard to visualize the tuning process. Finally, examine the relative strengths, weaknesses, similarities, and differences between Hyperopt, Optuna, and Ray Tune.After completing this video, you will be able to perform hyperparameter tuning with Optuna.