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Reliable ML // Niall Murphy & Todd Underwood // Coffee Sessions #127

Reliable ML // Niall Murphy & Todd Underwood // Coffee Sessions #127

FromMLOps.community


Reliable ML // Niall Murphy & Todd Underwood // Coffee Sessions #127

FromMLOps.community

ratings:
Length:
62 minutes
Released:
Oct 7, 2022
Format:
Podcast episode

Description

MLOps Coffee Sessions #127 with Niall Murphy & Todd Underwood, Reliable ML co-hosted by David Aponte.

// 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)

MLOps Coffee Sessions #127 with Niall Murphy & Todd Underwood, Reliable ML co-hosted by David Aponte.   // 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)  It was great that they wrote this book in the first place in a space that's new and lots of people are entering it with a lot of questions and this book clarifies those questions. It was also great to have all of their experiences documented in this one book and there's a lot of value in putting them all in one place so that people can benefit from it.

// 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 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.

// MLOps Jobs board  
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// 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/

--------------- ✌️Connect With Us ✌️ -------------
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Connect with Niall on LinkedIn: https://www.linkedin.com/in/niallm/
Connect with Todd on LinkedIn: https://www.linkedin.com/in/toddunder/
Released:
Oct 7, 2022
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.