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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
From the brand
Machine Learning, AI & more
Machine Learning
Artificial Intelligence
Deep Learning
Language Processing (NLP, LLM)
Sharing the knowledge of experts
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ASIN : B0B1LGL2SR
Publisher : O’Reilly Media
Accessibility : Learn more
Publication date : May 17, 2022
Edition : 1st
Language : English
File size : 8.7 MB
Simultaneous device usage : Unlimited
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 619 pages
ISBN-13 : 978-1098107925
Page Flip : Enabled