MLOps Coffee Sessions #127 with Niall Murphy & Todd Underwood, Reliable ML co-hosted by David Aponte.
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// Abstract
By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision-making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind. (Book description from O'Reilly)
// Bio
Niall Murphy
Niall has been interested in Internet infrastructure since the mid-1990s. He has worked with all of the major cloud providers from their Dublin, Ireland offices - most recently at Microsoft, where he was the global head of Azure Site Reliability Engineering (SRE). His books have sold approximately a quarter of a million copies worldwide, most notably the award-winning Site Reliability Engineering, and he is probably one of the few people in the world to hold degrees in Computer Science, Mathematics, and Poetry Studies. He lives in Dublin, Ireland, with his wife and two children.
Todd Underwood
Todd is a Director at Google and leads Machine Learning for the Site Reliability Engineering Director. He is also the Site Lead for Google’s Pittsburgh office. ML SRE teams build and scale internal and external ML services and are critical to almost every Product Area at Google.
Before working at Google, Todd held a variety of roles at Renesys. He was in charge of operations, security, and peering for Renesys’s Internet intelligence services, which are now part of Oracle's Cloud service. He also did product work for some early social products that Renesys worked on. Before that, Todd was the Chief Technology Officer of Oso Grande, an independent Internet service provider (AS2901) in New Mexico.
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// Related Links
Reliable Machine Learning book by Cathy Chen, Niall Richard Murphy, Kranti Parisa, D. Sculley, Todd Underwood: https://www.oreilly.com/library/view/reliable-machine-learning/9781098106218/
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Timestamps:
[00:00] Niall and Todd's preferred coffee
[02:27] Takeaways
[06:30] Subscribe to our Video cast and Podcasts channels
[11:36] Tips on running different distributed teams
[14:40] Burnout prevention
[17:14] Process of rewarding people
[22:03] Maturity and growth
[26:35] Help with tooling
[33:44] Magic of different teams' intersections in incident response
[40:12] Systemized framing questions
[45:47] ML problems
[54:21] Preparing the next generation of practitioners
[59:27] Official release of the Reliable Machine Learning book
[1:01:57] Wrap up
