Isbn: 9789811975868 - Introduction to Transfer Learning: Algorithms and Practice (machine Learning: Foundations, Methodologies, and Applications) (18 results)

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  • Language: English

    Published by Springer, 2024

    9811975868 / 9789811975868

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  • Language: English

    Published by Springer Verlag, Singapore, Singapore, 2024

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    Paperback. Condition: new. Paperback. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a students perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Language: English

    Published by Springer 10/19/2024, 2024

    9811975868 / 9789811975868

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    Paperback or Softback. Condition: New. Introduction to Transfer Learning: Algorithms and Practice. Book.

  • Language: English

    Published by Springer, 2024

    9811975868 / 9789811975868

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  • Language: English

    Published by Springer Verlag, Singapore, SG, 2024

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    Paperback. Condition: New. 2023 ed. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

  • Language: English

    Published by Springer Verlag, Singapore, SG, 2024

    9811975868 / 9789811975868

    • Softcover

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    Paperback. Condition: New. 2023 ed. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

  • Language: English

    Published by Springer, 2024

    9811975868 / 9789811975868

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2024

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  • Language: English

    Published by Springer, 2024

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  • Language: English

    Published by Springer Nature, 2024

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    • Softcover

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    Paperback. Condition: Brand New. 350 pages. 9.25x6.10x9.21 inches. In Stock.

  • Language: English

    Published by Springer Verlag, Singapore, SG, 2024

    9811975868 / 9789811975868

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    Paperback. Condition: New. 2023 ed. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

  • Language: English

    Published by Springer, 2024

    9811975868 / 9789811975868

    • Softcover

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a 'student's' perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

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    Language: English

    Published by Springer, 2024

    9811975868 / 9789811975868

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    Taschenbuch. Condition: Neu. Introduction to Transfer Learning | Algorithms and Practice | Jindong Wang (u. a.) | Taschenbuch | Machine Learning: Foundations, Methodologies, and Applications | xxi | Englisch | 2024 | Springer | EAN 9789811975868 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by Springer Verlag, Singapore, Singapore, 2024

    9811975868 / 9789811975868

    • Softcover

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    Paperback. Condition: new. Paperback. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a students perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Language: English

    Published by Springer Verlag, Singapore, SG, 2024

    9811975868 / 9789811975868

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    Paperback. Condition: New. 2023 ed. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

  • Language: English

    Published by Springer Apr 2024, 2024

    9811975868 / 9789811975868

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a 'student's' perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice. 329 pp. Englisch.

  • Language: English

    Published by Springer, Berlin|Springer Nature Singapore|Publishing House of Electronics Industry|Springer, 2024

    9811975868 / 9789811975868

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attra.

  • Language: English

    Published by Springer, Springer Okt 2024, 2024

    9811975868 / 9789811975868

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning.This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a 'student's' perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 352 pp. Englisch.