Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough
Author :
Publisher : Springer Nature
Total Pages : 515
Release :
ISBN-10 : 9783030682910
ISBN-13 : 3030682919
Rating : 4/5 (919 Downloads)

Book Synopsis Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough by : Vinit Kumar Gunjan

Download or read book Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2021-04-26 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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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