Data Brew
Season 2, Episode 3

Infrastructure for ML

Adam Oliner discusses how to design your infrastructure to support ML, from integration tests to glue code, the importance of iteration, and centralized vs decentralized data science teams. He provides valuable advice for companies investing in ML and crucial lessons he’s learned from founding two companies.

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Guest


Adam Oliner

Adam Oliner recently left his role as Head of Machine Learning at Slack to found a company that will help every business get value from their data. Before that, he was Director of Engineering at Splunk, leading a team doing data science and machine learning. Adam was a postdoctoral scholar in the EECS Department at UC Berkeley, working in the AMP Lab, which specializes in cloud computing and Big Data. He earned a PhD in computer science from Stanford University and a MEng in EECS from MIT, where he also earned degrees in computer science and mathematics.

Denny LeePlayPlay hover00:06

Welcome to Data Brew by Databricks with Denny and Brooke. The series allows us to explore various topics in the data and AI community. Whether we’re talking about data engineering or data science, we will interview subject matter experts to dive deeper into these topics. And while we’re at it, we’ll be enjoying our morning brew. My name is Denny Lee, and I’m a developer advocate at Databricks.

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