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Modern approaches in machine learnin...

Gunjan, Vinit Kumar.

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Modern approaches in machine learning and cognitive science = a walkthrough : latest trends in AI.. Volume 2 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Modern approaches in machine learning and cognitive science/ edited by Vinit Kumar Gunjan, Jacek M. Zurada.
Reminder of title:	a walkthrough : latest trends in AI.
other author:	Gunjan, Vinit Kumar.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	x, 515 p. :ill., digital ;24 cm.
[NT 15003449]:	Using CNN to predict regressive STD drug efficacy score -- Emotion Recognition in Hindi Speech using CNN-LSTM Model -- Refinery Profit Planning via Evolutionary Many-Objective Optimization -- A Deep Learning Technique for Image inpainting with GANs -- A Comparative Study on Distributed File Systems.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-68291-0
ISBN:	9783030682910

Modern approaches in machine learning and cognitive science = a walkthrough : latest trends in AI.. Volume 2 /
Modern approaches in machine learning and cognitive sciencea walkthrough : latest trends in AI.Volume 2 /[electronic resource] :edited by Vinit Kumar Gunjan, Jacek M. Zurada. - Cham :Springer International Publishing :2021. - x, 515 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9561860-949X ;. - Studies in computational intelligence ;v.956..

Using CNN to predict regressive STD drug efficacy score -- Emotion Recognition in Hindi Speech using CNN-LSTM Model -- Refinery Profit Planning via Evolutionary Many-Objective Optimization -- A Deep Learning Technique for Image inpainting with GANs -- A Comparative Study on Distributed File Systems.

This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems - theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.

ISBN: 9783030682910

Standard No.: 10.1007/978-3-030-68291-0doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .M634 2021

Dewey Class. No.: 006.31

Modern approaches in machine learning and cognitive science = a walkthrough : latest trends in AI.. Volume 2 /
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245 0 0 $a Modern approaches in machine learning and cognitive science $h [electronic resource] : $b a walkthrough : latest trends in AI. $n Volume 2 / $c edited by Vinit Kumar Gunjan, Jacek M. Zurada.
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505 0 $a Using CNN to predict regressive STD drug efficacy score -- Emotion Recognition in Hindi Speech using CNN-LSTM Model -- Refinery Profit Planning via Evolutionary Many-Objective Optimization -- A Deep Learning Technique for Image inpainting with GANs -- A Comparative Study on Distributed File Systems.
520 $a This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems - theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
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