Explore hyperparameter tuning of an XGBoost model using Databricks, MLflow, and Optuna in this 37-minute video tutorial. Learn how to leverage these powerful tools in combination to optimize machine learning models. Gain hands-on experience with MLOps practices as you follow along with the step-by-step demonstration. Access the accompanying code on GitHub to further enhance your understanding and apply the techniques to your own projects.
MLOps: Databricks MLFlow and Optuna Hyper-parameter Tuning
The Machine Learning Engineer via YouTube
Overview
Syllabus
MLOps MLFlow: Databricks MLFLow and Optuna Hyper-parameter Tuning
Taught by
The Machine Learning Engineer
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