Tuesday, October 14, 2:30pm - 2:55pm (EDT)
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Speaker: Krishna Chaitanya Chakka
This proposal outlines a presentation on Roku's approach to achieving real-time feature serving at scale and dramatically improving the development velocity for our ML models. We will cover the entire ML development lifecycle, from initial training to production deployment. A key focus will be on how we leveraged open-source projects, such as Chronon, to facilitate incremental aggregations for efficient feature computation.
Speaker: Krishna Chaitanya Chakka
This proposal outlines a presentation on Roku's approach to achieving real-time feature serving at scale and dramatically improving the development velocity for our ML models. We will cover the entire ML development lifecycle, from initial training to production deployment. A key focus will be on how we leveraged open-source projects, such as Chronon, to facilitate incremental aggregations for efficient feature computation.
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Feature Store Summit 2025