A machine learning infrastructure tool that handles offline and online feature transformations. Think of them as the interface between your models and data.
Feature stores are used to:
– Serve as the central source for feature transformations
– Allow for the same feature transformations to be used in both offline training and online serving
– Enable team members to share their transformations for experimentation
– Provide a strong versioning for feature transformation code
