Feature Sharing and Discovery Using the Databricks Feature Store

Machine learning teams often struggle to share, govern, and reuse features across projects, leading to duplicated work, inconsistent data between training and serving, and a lack of visibility into how features are created and used.
Machine learning teams often struggle to share, govern, and reuse features across projects, leading to duplicated work, inconsistent data between training and serving, and a lack of visibility into how features are created and used.
In this course, Feature Sharing and Discovery Using the Databricks Feature Store, you'll gain the ability to build, manage, and serve reusable machine learning features using Unity Catalog and the Databricks Feature Store.
First, you'll explore how to create, organize, and discover feature tables with governance and lineage.
Next, you'll discover how to build training datasets using feature lookups while ensuring point-in-time correctness and reproducibility.
Finally, you'll learn how to publish features to online stores and enable automatic feature lookup for low-latency model serving.
When you're finished with this course, you'll have the skills and knowledge needed to build scalable, governed feature engineering workflows that support consistent training and real-time inference.
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