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Redis? Dynamo? Cassandra? How to choose the right online store for your ML features.

Posted Jan 31
# Feature Stores
# Systems and Architecture
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SPEAKER
Kevin Stumpf
Kevin Stumpf
Kevin Stumpf
Co-Founder and CTO @ Tecton

Kevin co-founded Tecton where he leads a world-class engineering team that is building a next-generation feature store for operational Machine Learning. Kevin and his co-founders built deep expertise in operational ML platforms while at Uber, where they created the Michelangelo platform that enabled Uber to scale from 0 to 1000's of ML-driven applications in just a few years.

Prior to Uber,ÊKevinÊfounded Dispatcher, with the vision to build the Uber for long-haul trucking.ÊKevinÊholds an MBA from Stanford University and a Bachelor's Degree in Computer and Management Sciences from the University of Hagen. Outside of work,ÊKevinÊis a passionate long-distance endurance athlete.

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Kevin co-founded Tecton where he leads a world-class engineering team that is building a next-generation feature store for operational Machine Learning. Kevin and his co-founders built deep expertise in operational ML platforms while at Uber, where they created the Michelangelo platform that enabled Uber to scale from 0 to 1000's of ML-driven applications in just a few years.

Prior to Uber,ÊKevinÊfounded Dispatcher, with the vision to build the Uber for long-haul trucking.ÊKevinÊholds an MBA from Stanford University and a Bachelor's Degree in Computer and Management Sciences from the University of Hagen. Outside of work,ÊKevinÊis a passionate long-distance endurance athlete.

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SUMMARY

Where should you store your ML features to power real-time ML predictions, and why? In this talk, Tecton's Co-Founder and CTO, Kevin Stumpf, will discuss the tradeoffs made and lessons learned while building the Feature Stores at Uber, Tecton and Feast.

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# Data engineering
# Feature Stores
# Open Source