VII, 163 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband besto�en, daher M�ngelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Cognitive Computation Trends, Volume 2. Sprache: Englisch. N� de r�f. du vendeur 34891AB

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Deep Learning: Fundamentals, Theory and Applications (Cognitive Computation Trends, Band 2)

Kaizhu Huang

Edit� par Springer International Publishing, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Gebundene Ausgabe. Etat : Gut. Gebraucht - Gut GU - Besch�digungen, Verschmutzungen, ungelesenes M�ngelexemplar, gestempelt, Versand B�chersendung - The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications. N� de r�f. du vendeur INF1000495922

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Deep Learning: Fundamentals, Theory and Applications

Kaizhu Huang

Edit� par Springer International Publishing Mrz 2019, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

Neuf Couverture rigide

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications. 172 pp. Englisch. N� de r�f. du vendeur 9783030060725

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Deep Learning: Fundamentals, Theory and Applications

Huang, Kaizhu|Hussain, Amir|Wang, Qiu-Feng|Zhang, Rui

Edit� par Springer International Publishing, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

Neuf Couverture rigide

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Vendeur : moluna, Greven, Allemagne

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides thorough&nbspbackground of deep learningIntroduces &nbspwidely-used learning architectures and algorithmsIncludes new theory and applications of deep learning. N� de r�f. du vendeur 256091318

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Deep Learning: Fundamentals, Theory and Applications

Kaizhu Huang

Edit� par Springer International Publishing, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications. N� de r�f. du vendeur 9783030060725

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Deep Learning: Fundamentals, Theory and Applications (Cognitive Computation Trends, 2)

Edit� par Springer, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

Neuf Couverture rigide

Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis

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Etat : New. N� de r�f. du vendeur ABLING22Oct2018170258202

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Deep Learning: Fundamentals, Theory and Applications (Hardcover)

Kaizhu Huang

Edit� par Springer Nature Switzerland AG, Cham, 2019

ISBN 10 : 3030060721 ISBN 13 : 9783030060725

Neuf Couverture rigide Edition originale

Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis

�valuation du vendeur 5 sur 5 �toiles

Hardcover. Etat : new. Hardcover. The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how many deep learning methodologies have brought great breakthroughs in various applications of text, image, video, speech and audio processing. Deep learning (DL) has been widely considered as the next generation of machine learning methodology. DL attracts much attention and also achieves great success in pattern recognition, computer vision, data mining, and knowledge discovery due to its great capability in learning high-level abstract features from vast amount of data. This new book will not only attempt to provide a general roadmap or guidance to the current deep learning methodologies, but also present the challenges and envision new perspectives which may lead to further breakthroughs in this field. This book will serve as a useful reference for senior (undergraduate or graduate) students in computer science, statistics, electrical engineering, as well as others interested in studying or exploring the potential of exploiting deep learning algorithms. It will also be of special interest to researchers in the area of AI, pattern recognition, machine learning and related areas, alongside engineers interested in applying deep learning models in existing or new practical applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9783030060725

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