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Designing Machine Learning Systems by Chip Huyen (44 results)
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Published by O'Reilly Media
paperback. Condition: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
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International EditionPaperback. Condition: USED BOOKS. Used Books ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Designing Machine Learning Systems
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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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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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, cofounder 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; and developing responsible ML systems. 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 (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
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 48.37
US$ 19.74 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 55.00
US$ 15.77 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Designing Machine Learning Systems
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
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: 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. Book.
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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
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2022. Paperback. . . . . .
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Designing Machine Learning Systems : An Iterative Process for Production-ready Applications
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 56.68
US$ 19.74 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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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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Condition: New. 2022. Paperback. . . . . . Books ship from the US and Ireland.
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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
Paperback. Condition: Brand New. 350 pages. 9.19x7.00x0.80 inches. In Stock.
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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 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
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -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. 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
Seller: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -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. 367 pp. Englisch.
