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In this course, MLOps expert Maria Vechtomova introduces the components and principles that you must understand to successfully deploy machine learning models to production on Databricks. Dive into the step-by-step process of using Feature Engineering in Unity Catalog, tracking model experiments in mlflow, registering a model in Unity Catalog, and deploying your model using Databricks model serving. Explore the use cases where Feature Serving can be used and find out how to deploy a Feature Serving endpoint. Plus, learn how to package your code, deploy your project using Databricks Asset Bundles, and monitor your ML application using inference tables and Lakehouse monitoring.
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