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

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9789355422675
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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 problem
    • Automating the process for continually developing, evaluating, deploying, and updating models
    • Developing a monitoring system to quickly detect and address issues your models might encounter in production
    • Architecting an ML platform that serves across use cases
    • Developing responsible ML systems
    Books
    Author
    Chip Huyen
    Binding
    Paperback
    Condition Type
    New
    Country Origin
    India
    Edition
    First
    Gift Wrap
    N
    Lead time to ship in days (if not in stock)
    ships in 12-15 days
    Leadtime to ship in days (default)
    ships in 1-2 days
    Pages
    388
    Publication Date
    28/05/2022
    Publisher
    Shroff/O'Reilly
    Year
    2022
    Dimensions
    Dimensions (W x H x D)
    7 x 9 x 0.75 inch

    Table of Contents (9789355422675_toc.pdf, 45 Kb) [Download]

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