Isbn: 9783030610807 - computational methods for deep learning: theoretic, practice and applications (texts in computer science) (7 resultados)

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  • Idioma: Inglés

    Editorial: Springer, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

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    Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle

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    Condición: Nuevo

    EUR 53,55

    Envío por EUR 3,47 
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    Cantidad disponible: 1 disponibles

    Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

  • Idioma: Inglés

    Editorial: Springer, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: Nuevo

    EUR 51,05

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    Cantidad disponible: 1 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Springer, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    Condición: Nuevo

    EUR 52,09

    Envío por EUR 9,95 
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    Cantidad disponible: 1 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Springer, Berlin, Springer International Publishing, Springer, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 93,36

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    Cantidad disponible: 1 disponibles

    Buch. 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

    Editorial: Springer International Publishing, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

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    Librería: Buchpark, Trebbin, AlemaniaBuchpark

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    Condición: Usado

    EUR 45,27

    Envío por EUR 105,00 
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    Cantidad disponible: 1 disponibles

    Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

  • Idioma: Inglés

    Editorial: Springer International Publishing, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

    • Tapa dura

    Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer

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    Condición: Usado - Bueno

    EUR 179,00

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    Cantidad disponible: 1 disponibles

    Hardcover. Condición: gut. 2020. Computational Methods for Deep Learning In deutscher Sprache. pages.

  • Idioma: Inglés

    Editorial: Berlin Springer International Publishing Springer Dez 2020, 2020

    3030610802 / 9783030610807

    Serie: Libro 56 de 83 - Texts in Computer Science

    • Tapa blanda
    • Impresión bajo demanda

    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 64,19

    Envío por EUR 23,00 
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    Cantidad disponible: 2 disponibles

    Buch. 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.