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Reliable Machine Learning

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Description: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.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML loops workHow effective productionization can make your ML systems easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to compensate accordinglyHow ML, product, and production teams can communicate effectivelyWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Reliable Machine Learning. To get started finding Reliable Machine Learning, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 410

Format: PDF, EPUB & Kindle Edition

Publisher: O'Reilly Media

Release: 2021

ISBN: 1098106199

Description: 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.You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML loops workHow effective productionization can make your ML systems easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to compensate accordinglyHow ML, product, and production teams can communicate effectivelyWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Reliable Machine Learning. To get started finding Reliable Machine Learning, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Reliable Machine Learning

Reliable Machine Learning

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