Electronic Resource

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

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Penilaian

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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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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908000653	EB0001229	006.31 Mod	Central Library (OPAC)	Available

Detail Information

Series Title

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Call Number

006.31 Mod

Publisher

Switzerland : Springer Cham., 2021

Collation

x, 515p.:Ill

Language

English

ISBN/ISSN

978-3-030-68291-0

Classification

006.31

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

-

Subject(s)

Machine Learning

Specific Detail Info

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Statement of Responsibility

BRF

Other version/related

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