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Machine Learning Design Patterns by Lakshmanan Valliappa (47 results)
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paperback. Condition: Good.
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Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
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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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops (Paperback or Softback)
Language: English
Published by O'Reilly Media 11/3/2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Paperback or Softback. Condition: New. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops. Book.
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Condition: As New. Unread book in perfect condition.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Machine Learning Design Patterns
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. The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.You'll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly.
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Machine Learning Design Patterns (Paperback)
Language: English
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Paperback. Condition: new. Paperback. The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.You'll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Machine Learning Design Patterns : Solutions to Common Challenges in Data Preparation, Model Building, and Mlops
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Machine Learning Design Patterns
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.You'll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly.
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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2020. Paperback. . . . . .
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Machine Learning Design Patterns : Solutions to Common Challenges in Data Preparation, Model Building, and Mlops
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Language: English
Published by O'Reilly Media 2020-10-31, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Paperback. Condition: New.
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Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
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Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops
Language: English
Published by Oreilly & Associates Inc, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Paperback. Condition: Brand New. 400 pages. 9.25x7.00x1.00 inches. In Stock.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Machine Learning Design Patterns
Language: English
Published by O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Seller: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. 390 pp. Englisch.
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Machine Learning Design Patterns
Language: English
Published by O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. 390 pp. Englisch.
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Machine Learning Design Patterns
Language: English
Published by O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Taschenbuch. Condition: Neu. Neuware -The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.
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Paperback. Condition: New. The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation.You'll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure models are treating users fairly.
