The Art of Learning
Neural Networks and Education
1st Edition
Published on 13. September 2018
96 pages
978-1-351-11633-6 (ISBN)
Description
This book presents the idea that innovative ways of teaching and learning are very essential to retention and growth. Presented in 15 sections, the book starts with the common sense training on education and moves on to neural network operation. Throughout the book, the art of learning, associative, cognitive, and creative learning are stated and defined. Learning simplicity, information content as related to neural network learning are discussed. The author also discusses neural plasticity and adaptability in smarter neural networks.
If we know our human brain's basic abilities and limitation then a better educational methods can be implemented.
Presents the idea that innovative ways of teaching and learning are very essential to retention and growth
Discusses major differences and constraints between neural network and computer
Presents the significances of learning simplicity and information content as related to neural network learning are included
Stresses the neural network learning capabilities and limitations and their role in developing more efficient learning techniques
If we know our human brain's basic abilities and limitation then a better educational methods can be implemented.
Presents the idea that innovative ways of teaching and learning are very essential to retention and growth
Discusses major differences and constraints between neural network and computer
Presents the significances of learning simplicity and information content as related to neural network learning are included
Stresses the neural network learning capabilities and limitations and their role in developing more efficient learning techniques
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
File size
6,03 MB
ISBN-13
978-1-351-11633-6 (9781351116336)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
10/2023
1st Edition
CRC Press
€47.22
Shipment within 10-20 days
Book
08/2018
1st Edition
CRC Press
€82.70
Shipment within 15-20 days
Persons
Francis T. S. Yu received his B.S.E.E. degree from Mapua Institute of
Technology Manila, Philippines, and his M.S. and Ph.D. degrees in
Electrical Engineering from the University of Michigan. He has been a
consultant to several industrial and governmental laboratories. He is an
active researcher in the fields of optical signal processing, holography,
information optics, optical computing, neural networks, photorefractive
optics, fiber sensors, and photonic devices. He has published over five
hundred papers, in which over three hundred are referred. He is a
recipient of the 1983 Faculty Scholar Medal for Outstanding Achievement
in Physical Sciences and Engineering, a recipient of the 1984
Outstanding Researcher in the College of Engineering, was named Evan
Pugh Professor of Electrical Engineering in 1985 at Penn State, a
recipient of the 1993 Premier Research Award from the Penn State
Engineering Society, was named Honorary Professor in Nankai University
in 1995, is the corecipient of the 1998 IEEE Donald G. Fink
Prize Paper Award, was named Honorary Professor of the National
Chiao-Tung University in Taiwan, and is the recipient of the SPIE 2004
Dennis Garbor Award. He has served as an associate editor editorial
board member, and a guest editor for various international journals. He
is the author and coauthor of nine books. Dr. Yu is a life fellow of IEEE
and a fellow of OSA, SPIE, and PSC.
Edward H. Yu is a teacher, writer, and the author of The Art of
Slowing Down: A Sense-Able Approach to Running Faster(Panenthea
Press) and The Mass Psychology of Fittism: Fitness, Evolution & the
First Two Laws of Thermodynamics (Undocumented Worker Press).
Ann G. Yu lives and works in Los Angeles.
Technology Manila, Philippines, and his M.S. and Ph.D. degrees in
Electrical Engineering from the University of Michigan. He has been a
consultant to several industrial and governmental laboratories. He is an
active researcher in the fields of optical signal processing, holography,
information optics, optical computing, neural networks, photorefractive
optics, fiber sensors, and photonic devices. He has published over five
hundred papers, in which over three hundred are referred. He is a
recipient of the 1983 Faculty Scholar Medal for Outstanding Achievement
in Physical Sciences and Engineering, a recipient of the 1984
Outstanding Researcher in the College of Engineering, was named Evan
Pugh Professor of Electrical Engineering in 1985 at Penn State, a
recipient of the 1993 Premier Research Award from the Penn State
Engineering Society, was named Honorary Professor in Nankai University
in 1995, is the corecipient of the 1998 IEEE Donald G. Fink
Prize Paper Award, was named Honorary Professor of the National
Chiao-Tung University in Taiwan, and is the recipient of the SPIE 2004
Dennis Garbor Award. He has served as an associate editor editorial
board member, and a guest editor for various international journals. He
is the author and coauthor of nine books. Dr. Yu is a life fellow of IEEE
and a fellow of OSA, SPIE, and PSC.
Edward H. Yu is a teacher, writer, and the author of The Art of
Slowing Down: A Sense-Able Approach to Running Faster(Panenthea
Press) and The Mass Psychology of Fittism: Fitness, Evolution & the
First Two Laws of Thermodynamics (Undocumented Worker Press).
Ann G. Yu lives and works in Los Angeles.
Content
Preface. Motivation. Common Sense on Training (or Education). Neural Networks. Major Differences between Neural Networks & Computers. Memory-Based Neural Networks. Artificial Neuron Operation. Associative Memory Neural Network. Supervised and Unsupervised Learning Neural Networks. Cognitive Learning (The Art of Understanding). Learning Simplicity (The Basics). Information Content and Neural Network Learning. Brain (Neural Network) Plasticity and Adaptively. Innovative Education (i.e., Training). Search for Innovative Education. A Few Thoughts to Share. Leadership in Education.
