Tuesday, October 15, 12:40pm - 1:00pm (EDT)
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24h
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Speakers: Prachi Poddar, Tianne Cui
Feature data freshness is essential to many Machine Learning use cases and impacts model performance. Etsy’s journey of building Rivulet, our Real-Time Feature Store began several years ago. Since then, we have gone through multiple iterations to facilitate creating and exploring real-time computation and accessing ML features in production. In this talk we will cover end to end Rivulet architecture powered by GCP and how it interacts with other parts of the Etsy Feature System to provide a cohesive feature engineering workflow for real-time features.
Feature data freshness is essential to many Machine Learning use cases and impacts model performance. Etsy’s journey of building Rivulet, our Real-Time Feature Store began several years ago. Since then, we have gone through multiple iterations to facilitate creating and exploring real-time computation and accessing ML features in production. In this talk we will cover end to end Rivulet architecture powered by GCP and how it interacts with other parts of the Etsy Feature System to provide a cohesive feature engineering workflow for real-time features.
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Feature Store Summit 2024