Idioma: Inglés
Publicado por Springer (edition 1st ed. 2023), 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 51,75
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Añadir al carritoHardcover. Condición: Very Good. 1st ed. 2023. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Idioma: Inglés
Publicado por Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 69,77
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Añadir al carritoHardcover. Condición: new. Hardcover. 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.
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EUR 70,49
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Añadir al carritoCondición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Añadir al carritoCondición: New. In English.
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Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: Revaluation Books, Exeter, Reino Unido
EUR 116,41
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Añadir al carritoHardcover. Condición: Brand New. 350 pages. 9.25x6.10x0.98 inches. In Stock.
Idioma: Inglés
Publicado por Springer, Springer Nature Singapore, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 79,75
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Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 116,07
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Añadir al carritoHardcover. Condición: new. Hardcover. 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.
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 71,81
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Añadir al carritoCondición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: Revaluation Books, Exeter, Reino Unido
EUR 72,65
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: Brand New. 350 pages. 9.25x6.10x0.98 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Springer Nature Singapore Mrz 2023, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 74,89
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: 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. 352 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Berlin|Springer Nature Singapore|Publishing House of Electronics Industry|Springer, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: moluna, Greven, Alemania
EUR 64,33
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Añadir al carritoGebunden. Condición: 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.
Idioma: Inglés
Publicado por Springer, Springer Mär 2023, 2023
ISBN 10: 9811975833 ISBN 13: 9789811975837
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 74,89
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.