Designing machine learning systems : an iterative process for production-ready applications /
"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 holisti...
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| Format: | Book |
| Language: | English |
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Navi Mumbai : Sebastopol, CA :
Shroff Publishers and Distributors ; O'Reilly Media,
c2022 [reprinted 2025].
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| Classic Catalogue: | View this record in Classic Catalogue |
| 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. |
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| Item Description: | First edition : May 2022 |
| Physical Description: | xvi, 367 pages : illustrations ; 24 cm |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9789355422675 (paperback) 1098107969 (paperback) 9781098107963 (paperback) |