Reliable Machine Learning - Applying SRE Principles to ML in Production (Paperback)

Whether you're 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. 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. You'll examine: What ML is: how it functions and what it relies on Conceptual frameworks for understanding how ML "loops" work Effective "productionization," and how it can be made easily monitorable, deployable, and operable Why ML systems make production troubleshooting more difficult, and how to get around them How ML, product, and production teams can communicate effectively

General

Imprint:	O'Reilly Media
Country of origin:	United States
Release date:	September 2022
Authors:	Cathy Chen • Niall Richard Murphy • Kranti Parisa • D Sculley • Todd Underwood
Dimensions:	232 x 178 x 25mm (L x W x T)
Format:	Paperback
Pages:	350
ISBN-13:	978-1-09-810622-5
Categories:	Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	1-09-810622-9
Barcode:	9781098106225

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