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Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they’re data dependent, with data varying wildly from one use case to the next. In this book, you’ll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements.
Author Chip Huyen, co-founder of Claypot AI, considers each design decision–such as how to process and create training data, which features to use, how often to retrain models, and what to monitor–in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references.
This book will help you tackle scenarios such as:
Engineering data and choosing the right metrics to solve a business problemAutomating the process for continually developing, evaluating, deploying, and updating modelsDeveloping a monitoring system to quickly detect and address issues your models might encounter in productionArchitecting an ML platform that serves across use casesDeveloping responsible ML systems
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Publisher : O’Reilly Media; 1st edition (June 21, 2022)
Language : English
Paperback : 386 pages
ISBN-10 : 1098107969
ISBN-13 : 978-1098107963
Item Weight : 1.36 pounds
Dimensions : 7 x 0.8 x 9.19 inches
Customers say
Customers find the book provides great content to understand the practical and operational aspects of machine learning. They say it expands their thinking and improves their work. Readers also describe the book as a good entry-level read with easy-to-follow code snippets and examples.
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