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Advanced deep learning for engineers...

Prakash, Kolla Bhanu.

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Advanced deep learning for engineers and scientists = a practical approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advanced deep learning for engineers and scientists/ edited by Kolla Bhanu Prakash ... [et al.].
Reminder of title:	a practical approach /
other author:	Prakash, Kolla Bhanu.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xvii, 285 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Introduction to ANN -- Introduction to Deep Learning -- Deep Soft Computing using Python -- Working with Keras -- Deep learning Applications using Python -- Advanced Deep learning techniques -- Conclusion.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-66519-7
ISBN:	9783030665197

Advanced deep learning for engineers and scientists = a practical approach /
Advanced deep learning for engineers and scientistsa practical approach /[electronic resource] :edited by Kolla Bhanu Prakash ... [et al.]. - Cham :Springer International Publishing :2021. - xvii, 285 p. :ill., digital ;24 cm. - EAI/Springer innovations in communication and computing,2522-8595. - EAI/Springer innovations in communication and computing..

Introduction -- Introduction to ANN -- Introduction to Deep Learning -- Deep Soft Computing using Python -- Working with Keras -- Deep learning Applications using Python -- Advanced Deep learning techniques -- Conclusion.

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them through various projects; Discusses topics such as deep learning in smart grids and renewable energy & sustainable development; Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.

ISBN: 9783030665197

Standard No.: 10.1007/978-3-030-66519-7doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Advanced deep learning for engineers and scientists = a practical approach /
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245 0 0 $a Advanced deep learning for engineers and scientists $h [electronic resource] : $b a practical approach / $c edited by Kolla Bhanu Prakash ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvii, 285 p. : $b ill., digital ; $c 24 cm.
490 1 $a EAI/Springer innovations in communication and computing, $x 2522-8595
505 0 $a Introduction -- Introduction to ANN -- Introduction to Deep Learning -- Deep Soft Computing using Python -- Working with Keras -- Deep learning Applications using Python -- Advanced Deep learning techniques -- Conclusion.
520 $a This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book. Presents practical basics to advanced concepts in deep learning and how to apply them through various projects; Discusses topics such as deep learning in smart grids and renewable energy & sustainable development; Explains how to implement advanced techniques in deep learning using Pytorch, Keras, Python programming.
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650 1 4 $a Communications Engineering, Networks. $3 891094
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650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
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