Meetup #102

Building a Movie Recommendation System on Tecton with Snowflake

Tecton integrates with Snowflake and enables data teams to process ML features and serve them in production quickly and reliably, without building custom data pipelines. David shows how to build an end-to-end movie recommendation system using a feature platform in three stages: - Batch, daily computed, recommendations - Online recommendations using batch features - Online recommendations using real-time features

Take-aways

After this talk, you will see Tecton, a complete feature platform, in action. You will also learn what are the practical considerations when building a recommendation system.

In this episode

David Hershey

David Hershey

Senior Solutions Architect, Tecton

David Hershey is a Senior Solutions Architect at Tecton, where he helps customers implement feature stores as part of their stack for Operational ML. Prior to Tecton, David was a Solutions Engineer at Determined AI and a Product Manager for Ford’s ML platform. David holds an MS in Computer Science from Stanford University and a BS in Aerospace Engineering from the University of Michigan.

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Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.