Hyperparameter Tuning with Ray Tune on Databricks

Ray Tune is another great choice for hyperparameter tuning technology that integrates with Databricks and MLflow. The special appeal of Ray Tune is its strength in distributed hyperparameter tuning.In this course, explore the key features of Ray Tune, where it fits into the Ray framework, and how Ray Tune simplifies distributed hyperparameter tuning and integrates with Databricks and MLflow. Next, discover how to perform hyperparameter tuning with Ray Tune using Ray Tasks to manage large computational processes and MLflow to track experiments and results efficiently. Finally, learn how to execute parallel model training and logging using Ray. After completing this video, you will be able to perform hyperparameter tuning with Ray Tune on Databricks.