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paperback. Condition: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority!
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback or Softback)
Published by O'Reilly Media 6/21/2022, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
Paperback or Softback. Condition: New. Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications 1.36. Book.
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Designing Machine Learning Systems
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Paperback. Condition: New. 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.
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Designing Machine Learning Systems (Paperback)
Published by O'Reilly Media, Sebastopol, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
Paperback. Condition: new. Paperback. 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
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Designing Machine Learning Systems : An Iterative Process for Production-ready Applications
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
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Designing Machine Learning Systems
Published by American Orthopsychiatric Association, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Designing Machine Learning Systems
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Add to basketPaperback. Condition: New. 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.
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Designing Machine Learning Systems : An Iterative Process for Production-ready Applications
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
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Designing Machine Learning Systems
Published by American Orthopsychiatric Association, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
Condition: New. pp. 360.
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Designing Machine Learning Systems: An Iterative Process for Production-ready Applications
Published by Oreilly & Associates Inc, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Add to basketPaperback. Condition: Brand New. 350 pages. 9.19x7.00x0.80 inches. In Stock.
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Designing Machine Learning Systems
Published by American Orthopsychiatric Association, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Designing Machine Learning Systems (Paperback)
Published by O'Reilly Media, Sebastopol, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Add to basketPaperback. Condition: new. Paperback. 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 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Designing Machine Learning Systems
Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware 367 pp. Englisch.
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Designing Machine Learning Systems
Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Add to basketTaschenbuch. Condition: Neu. Neuware 367 pp. Englisch.
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Designing Machine Learning Systems
Published by O'reilly Media Jul 2022, 2022
ISBN 10: 1098107969 ISBN 13: 9781098107963
Language: English
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Add to basketPaperback. Condition: New. 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.
