Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

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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

O’Reilly’s mission is to change the world by sharing the knowledge of innovators. For over 40 years, we’ve inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

Publisher ‏ : ‎ O’Reilly Media
Publication date ‏ : ‎ June 21, 2022
Edition ‏ : ‎ 1st
Language ‏ : ‎ English
Print length ‏ : ‎ 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’s content practical and useful, particularly for beginners in data science, with one customer noting how complex concepts are made accessible through practical examples. Moreover, the writing is clear and easy to read. However, the graphics quality receives mixed feedback, with several customers expressing dissatisfaction with the style.

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