Welcome to Central Library, SUST
Amazon cover image
Image from Amazon.com
Image from Google Jackets

Designing machine learning systems : an iterative process for production-ready applications / Chip Huyen.

By: Material type: TextTextPublisher: India : SPD, 2022Edition: First editionDescription: xvi, 367 pages : illustrations ; 24 cmISBN:
  • 9789355422675
Subject(s): DDC classification:
  • 22 006.31 HUD
Contents:
Overview of machine learning systems -- Introduction to machine learning systems design -- Data engineering fundamentals -- Training data -- Feature Engineering -- Model development and offline evaluation -- Model develoypment and prediction service -- Data distribution shifts and monitoring -- Continual learning and test in production -- Infrastructure and tooling for MLOps -- The human side of machine learning
Summary: "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."--Amazon.com.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Copy number Status Date due Barcode
Books Books Central Library, SUST 006.31 HUD (Browse shelf(Opens below)) 1 Available 0078776
Books Books Central Library, SUST 006.31 HUD (Browse shelf(Opens below)) 2 Available 0078777

Includes bibliographical references and index.

Overview of machine learning systems -- Introduction to machine learning systems design -- Data engineering fundamentals -- Training data -- Feature Engineering -- Model development and offline evaluation -- Model develoypment and prediction service -- Data distribution shifts and monitoring -- Continual learning and test in production -- Infrastructure and tooling for MLOps -- The human side of machine learning

"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."--Amazon.com.

There are no comments on this title.

to post a comment.