Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 53,28
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 51,78
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Añadir al carritoCondición: New.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 52,25
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Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Springer, Berlin, Springer International Publishing, Springer, 2020
ISBN 10: 3030610802 ISBN 13: 9783030610807
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 70,00
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yanis an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,Visual Cryptography for Image Processing and Security.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030610802 ISBN 13: 9783030610807
Librería: Buchpark, Trebbin, Alemania
EUR 45,27
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030610802 ISBN 13: 9783030610807
Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Alemania
EUR 179,00
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: gut. 2020. Computational Methods for Deep Learning In deutscher Sprache. pages.
Idioma: Inglés
Publicado por Berlin Springer International Publishing Springer Dez 2020, 2020
ISBN 10: 3030610802 ISBN 13: 9783030610807
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 64,19
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yanis an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,Visual Cryptography for Image Processing and Security. 134 pp. Englisch.