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The Post Modern Stack

Posted Jun 21, 2022 | Views 613
# Post-modern Stack
# Snowflake
# Real-world Recommendation Pipeline
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Jacopo Tagliabue
Director of AI @ Coveo

Educated in several acronyms across the globe (UNISR, SFI, MIT), Jacopo Tagliabue was co-founder and CTO of Tooso, an A.I. company in San Francisco acquired by Coveo in 2019. Jacopo is currently the Director of AI at Coveo, shipping models to hundreds of customers and millions of users. When not busy building products, he is exploring topics at the intersection of language, reasoning, and learning: his research and industry work is often featured in the general press and premier A.I. venues. In previous lives, he managed to get a Ph.D., do sciency things for a pro basketball team, and simulate a pre-Columbian civilization.

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SUMMARY

In this workshop, we discuss our “Post-Modern Data Stack”, that is, a deconstruction of the MLOps stack we previously shared with the community. In particular, we join the “modern data stack” (Snowflake + dbt) with “modern MLOps” practices, using Metaflow to bridge the gap between data, training, and inference in a pure serverless fashion.

As usual, we refuse to work in a toy stack, and with toy data: leveraging our huge data release from last year, we walk through a real-world recommendation pipeline, going from raw data to a live endpoint serving predictions.

You can download: Joining the modern data stack with the modern ML stack: https://github.com/jacopotagliabue/post-modern-stack

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