apply(recsys) Conference 2022 | Workshop: Choosing Feast or Tecton for Your RecSys Architecture

Posted Dec 12, 2022 | Views 718

# apply(recsys) 2022

# Feature Stores

# Tecton

SPEAKERS

Jake Noble

Software Engineer @ Tecton

Jake is a Software Engineer at Tecton, working on highly scalable data infrastructure for advanced ML use cases like RecSys. Before Tecton, Jake was a Senior Software Engineer and Technical Lead at Youtube, working on very large-scale recommendations ranking models. Jake holds a Bachelor's degree in Computer Science and Mechanical Engineering from Vanderbilt University.

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Danny Chiao

Engineering Lead @ Tecton

Danny Chiao is an engineering lead at Tecton/Feast Inc working on building a next-generation feature store. Previously, Danny was a technical lead at Google working on end to end machine learning problems within Google Workspace, helping build privacy-aware ML platforms / data pipelines and working with research and product teams to deliver large-scale ML powered enterprise functionality. Danny holds a BachelorÕs degree in Computer Science from MIT.

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SUMMARY

Feature stores can be essential components of your infrastructure for recommender systems. They simplify the process of deploying and managing RecSys models. But users often wonder which one is better suited for their use cases - Feast or Tecton? These two products are very different and address different requirements. In this workshop, we’ll give a hands-on, step-by-step example of building RecSys models using both Feast and Tecton. And we’ll provide our recommendations on when to use which product.

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