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Reliable Machine Learning (Eighth Early Release) PDF

484 Pages·2022·4.8719 MB·other
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About Reliable Machine Learning (Eighth Early Release)

<span><p>Whether you are part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run 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.</p><p>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 guests show you how to run an efficient 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.</p><p>You'll examine:</p><ul><li>What ML <i>is</i>: how it functions and what it relies on</li><li>Conceptual frameworks for understanding how ML "loops" work</li><li>Effective "productionization," and how it can be made easily monitorable, deployable, and operable</li><li>Why ML systems make production troubleshooting more difficult, and how to get around them</li><li>How ML, product, and production teams can communicate effectively</li></ul></span>

Detailed Information

Author:Cathy Chen & Niall Richard Murphy & Kranti Parisa & D. Sculley & Todd Underwood
Publication Year:2022
ISBN:1098106210
Pages:484
Language:other
File Size:4.8719
Format:PDF
Price:FREE
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