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Reliable machine learning : applying SRE principles to ML in production /

Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Chen, Cathy
Other Authors: Murphy, Niall Richard, Parisa, Kranti, Sculley, D., Underwood, Todd, Charrington, Sam
Format: Electronic eBook
Language:Inglés
Published: Sebastopol, CA : O'Reilly Media, Inc, USA, 2022.
Subjects:
Online Access:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. 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. 
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