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Añadir al carritoCondición: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Librería: WorldofBooks, Goring-By-Sea, WS, Reino Unido
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Añadir al carritoPaperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Librería: Studibuch, Stuttgart, Alemania
EUR 26,66
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Añadir al carritopaperback. Condición: Gut. 390 Seiten; 9781098115784.3 Gewicht in Gramm: 1.
EUR 42,87
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 47,31
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Publicado por O'Reilly Media 11/3/2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 42,21
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Añadir al carritoPaperback or Softback. Condición: New. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and Mlops 1.43. Book.
EUR 50,08
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Añadir al carritoPaperback. Condición: 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.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 51,77
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Añadir al carritoPaperback. Condición: 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.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 48,40
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Añadir al carritoCondición: New. 2020. Paperback. . . . . .
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 39,88
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days. 526.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 41,83
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 42,86
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Añadir al carritoCondición: New.
EUR 61,35
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Añadir al carritoPaperback. Condición: 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.
Publicado por O'Reilly Media, Inc, USA 2020-10-27, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
EUR 46,53
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Añadir al carritoPaperback. Condición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 48,77
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 66,06
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Añadir al carritoCondición: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 57,56
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Añadir al carritoCondición: New.
EUR 66,56
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Añadir al carritoPaperback. Condición: 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.
Librería: moluna, Greven, Alemania
EUR 52,67
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Añadir al carritoCondición: New. 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 ex.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 67,66
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Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
Publicado por Oreilly & Associates Inc, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 66,06
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Añadir al carritoPaperback. Condición: Brand New. 400 pages. 9.25x7.00x1.00 inches. In Stock.
Librería: Goodwill Books, Hillsboro, OR, Estados Unidos de America
EUR 12,40
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Añadir al carritoCondición: Acceptable. Fairly worn, but readable and intact. If applicable: Dust jacket, disc or access code may not be included.
Publicado por O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Alemania
EUR 66,50
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Añadir al carritoTaschenbuch. Condición: 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.
Publicado por O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 66,50
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Añadir al carritoTaschenbuch. Condición: 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.
Publicado por O'Reilly Media (edition 1), 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 13,88
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Añadir al carritoPaperback. Condición: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Publicado por O'Reilly Media (edition 1), 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 14,05
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Añadir al carritoPaperback. Condición: As New. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Publicado por O'reilly Media Okt 2020, 2020
ISBN 10: 1098115783 ISBN 13: 9781098115784
Idioma: Inglés
Librería: Wegmann1855, Zwiesel, Alemania
EUR 66,50
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Añadir al carritoTaschenbuch. Condición: 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.