EUR 30,74
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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.
EUR 30,35
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Añadir al carritohardcover. Condición: Sehr gut. 520 Seiten; 9783319944623.2 Gewicht in Gramm: 2.
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 37,47
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Añadir al carritohardcover. Condición: Very Good. Cover and edges may have some wear.
EUR 43,04
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Añadir al carritoCondición: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
EUR 43,04
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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: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 51,45
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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.
Publicado por Springer Nature Switzerland Ag, 2018
ISBN 10: 3030068560 ISBN 13: 9783030068561
Idioma: Inglés
Librería: Anybook.com, Lincoln, Reino Unido
EUR 41,54
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Añadir al carritoCondición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1150grams, ISBN:9783030068561.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 53,02
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Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 54,20
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Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 51,61
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Añadir al carritoCondición: New.
EUR 53,45
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Añadir al carritoPaperback. Condición: Brand New. 2nd edition. 553 pages. 10.00x7.00x10.00 inches. In Stock.
Librería: Tefka, Albuquerque, NM, Estados Unidos de America
Original o primera edición
EUR 26,25
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Añadir al carritoHardcover. Condición: Very Good. No Jacket. 1st Edition. Very good+ hardcover with clean & bright boards w/minor bumps/dents to boards; interior pages are white & crisp, no marks, looks barely used if at all. No dust jacket as issued. See photos.
Publicado por Springer International Publishing, 2024
ISBN 10: 3031296443 ISBN 13: 9783031296444
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work When do they work better than off-the-shelf machine-learning models When is depth useful Why is training neural networks so hard What are the pitfalls The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories:The basics of neural networks:The backpropagation algorithm is discussed in Chapter 2.Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks.Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines.Advanced topics in neural networks: Chapters 8, 9, and 10 discussrecurrent neural networks, convolutional neural networks, and graph neural networks.Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12.The textbook is written for graduate students and upper under graduate level students. Researchers and practitioners working within this related field will want to purchase this as well.Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition.Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 50,84
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Añadir al carritoCondición: New.
Librería: Romtrade Corp., STERLING HEIGHTS, MI, Estados Unidos de America
EUR 69,25
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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.
Librería: Marlton Books, Bridgeton, NJ, Estados Unidos de America
EUR 34,46
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Añadir al carritoCondición: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2023.
EUR 55,52
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Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 55,93
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 71,50
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Añadir al carritoCondición: New. In.
EUR 67,69
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Añadir al carritoCondición: New.
EUR 69,91
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Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 63,65
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Añadir al carritoCondición: New.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 74,36
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Añadir al carritoCondición: New.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 71,36
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Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 66,94
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Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 68,26
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Toscana Books, AUSTIN, TX, Estados Unidos de America
EUR 61,17
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Añadir al carritoHardcover. Condición: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Publicado por Springer (edition 1st ed. 2018), 2018
ISBN 10: 3319944622 ISBN 13: 9783319944623
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 21,86
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Añadir al carritoHardcover. Condición: Very Good. 1st ed. 2018. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Publicado por Springer (edition 1st ed. 2018), 2018
ISBN 10: 3319944622 ISBN 13: 9783319944623
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 21,86
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Añadir al carritoHardcover. Condición: Good. 1st ed. 2018. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
Publicado por Springer International Publishing Jun 2023, 2023
ISBN 10: 3031296419 ISBN 13: 9783031296413
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 74,89
Convertir monedaCantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work When do they work better than off-the-shelf machine-learning models When is depth useful Why is training neural networks so hard What are the pitfalls The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories:The basics of neural networks:The backpropagation algorithm is discussed in Chapter 2.Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks.Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines.Advanced topics in neural networks: Chapters 8, 9, and 10 discussrecurrent neural networks, convolutional neural networks, and graph neural networks.Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12.The textbook is written for graduate students and upper under graduate level students. Researchers and practitioners working within this related field will want to purchase this as well.Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition.Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.