Isbn: 9783031820120 - a guide to implementing mlops: from data to operations (synthesis lectures on engineering, science, and technology) (8 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2026

    3031820126 / 9783031820120

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    EUR 71,95

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    Condición: New.

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031820126 / 9783031820120

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 54,15

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    Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Over the past decade, machine learning has come a long way, with organisations of all sizes exploring its potential to extract valuable insights from data. However, despite the promise of machine learning, many organisations need help deploying and managing machine learning models in production. This is where MLOps comes in. MLOps, or machine learning operations, is an emerging field that focuses on the deployment, management, and monitoring of machine learning models in production environments. MLOps combines the principles of DevOps with the unique requirements of machine learning, enabling organisations to build and deploy models at scale while maintaining high levels of reliability and accuracy. This book is a comprehensive guide to MLOps, providing readers with a deep understanding of the principles, best practices, and emerging trends in the field. From training models to deploying them in production, the book covers all aspects of the MLOps process, providing readers with the knowledge and tools they need to implement MLOps in their organisations. The book is aimed at data scientists, machine learning engineers, and IT professionals who are interested in deploying machine learning models at scale. It assumes a basic understanding of machine learning concepts and programming, but no prior knowledge of MLOps is required. Whether you're just getting started with MLOps or looking to enhance your existing knowledge, this book is an essential resource for anyone interested in scaling machine learning in production.…

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031820126 / 9783031820120

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    EUR 45,95

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    Taschenbuch. Condición: Neu. A Guide to Implementing MLOps | From Data to Operations | Prafful Mishra | Taschenbuch | Synthesis Lectures on Engineering, Science, and Technology | xiv | Englisch | 2026 | Springer | EAN 9783031820120 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Idioma: Inglés

    Editorial: Springer, Springer Feb 2026, 2026

    3031820126 / 9783031820120

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 48,14

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Over the past decade, machine learning has come a long way, with organisations of all sizes exploring its potential to extract valuable insights from data. However, despite the promise of machine learning, many organisations need help deploying and managing machine learning models in production. This is where MLOps comes in. MLOps, or machine learning operations, is an emerging field that focuses on the deployment, management, and monitoring of machine learning models in production environments. MLOps combines the principles of DevOps with the unique requirements of machine learning, enabling organisations to build and deploy models at scale while maintaining high levels of reliability and accuracy. This book is a comprehensive guide to MLOps, providing readers with a deep understanding of the principles, best practices, and emerging trends in the field. From training models to deploying them in production, the book covers all aspects of the MLOps process, providing readers with the knowledge and tools they need to implement MLOps in their organisations. The book is aimed at data scientists, machine learning engineers, and IT professionals who are interested in deploying machine learning models at scale. It assumes a basic understanding of machine learning concepts and programming, but no prior knowledge of MLOps is required. Whether you're just getting started with MLOps or looking to enhance your existing knowledge, this book is an essential resource for anyone interested in scaling machine learning in production. 148 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031820126 / 9783031820120

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: Nuevo

    EUR 70,96

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    Cantidad disponible: 4 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Springer, 2026

    3031820126 / 9783031820120

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    Condición: Nuevo

    EUR 71,59

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    Cantidad disponible: 4 disponibles

    Condición: New. PRINT ON DEMAND.

  • Idioma: Inglés

    Editorial: Springer Verlag GmbH, 2026

    3031820126 / 9783031820120

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 42,96

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    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

  • Idioma: Inglés

    Editorial: Springer, Springer International Publishing Feb 2026, 2026

    3031820126 / 9783031820120

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 48,14

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    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Over the past decade, machine learning has come a long way, with organisations of all sizes exploring its potential to extract valuable insights from data. However, despite the promise of machine learning, many organisations need help deploying and managing machine learning models in production. This is where MLOps comes in. MLOps, or machine learning operations, is an emerging field that focuses on the deployment, management, and monitoring of machine learning models in production environments. MLOps combines the principles of DevOps with the unique requirements of machine learning, enabling organisations to build and deploy models at scale while maintaining high levels of reliability and accuracy. This book is a comprehensive guide to MLOps, providing readers with a deep understanding of the principles, best practices, and emerging trends in the field. From training models to deploying them in production, the book covers all aspects of the MLOps process, providing readers with the knowledge and tools they need to implement MLOps in their organisations. The book is aimed at data scientists, machine learning engineers, and IT professionals who are interested in deploying machine learning models at scale. It assumes a basic understanding of machine learning concepts and programming, but no prior knowledge of MLOps is required. Whether you're just getting started with MLOps or looking to enhance your existing knowledge, this book is an essential resource for anyone interested in scaling machine learning in production.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch. …