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September 27-30, 2021
Seattle, Washington, USA + Virtual
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Tuesday, September 28 • 5:00pm - 5:50pm
Self-serve Feature Engineering Platform Using Flyte and Feast - Ketan Umare, Union.ai & Felix Wang, Tecton

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Feature Engineering off-late has become one of the most prominent topics in Machine Learning. Feast (LF AI & data Incubating project) is an open source store to organize and serve these features for online inferencing. Flyte (LF AI & Data Incubating project) provides a standardized, user-friendly way to integrate different data sources and tools onto a single platform. Flyte provides a way to train models and perform feature engineering as a single pipeline. But, it provides no way to serve these features to production, when the model matures and is ready to be served in production. This is where the integration between Flyte and Feast can help the users to take their models and features from prototyping all the way to production in a cost-effective and efficient manner. This talk will provide an overview of the problems faced by users when training models and engineering new features. It will walk through a demonstration that shows how users can start with prototyping and deliver the features to an online served model. This will help the audience to understand how the various components of the LF AI & Data stack can be used to create a production ready, self-served (for their users) Feature engineering platform.

Speakers
avatar for Felix Wang

Felix Wang

Software Engineer, Tecton
Felix is a software engineer at Tecton, working on Feast, the open-source feature store.
avatar for Ketan Umare

Ketan Umare

Chief Software Architect, Union.ai
Ketan Umare is the TSC Chair for Flyte (incubating under LF AI & Data). He is also currently the Chief Software Architect at Union.ai. Previously he had multiple Senior Lead roles at Lyft, Oracle and Amazon ranging from Cloud, Distributed storage, mapping and machine learning systems... Read More →


Tuesday September 28, 2021 5:00pm - 5:50pm PDT
MeetingPlay Platform + Virtual Learning Lab
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