PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS: BASIC DESIGNS TO DEEP LEARNING (4TH EDITION)*

Daniel Graupe

ISBN 10: 0000988995 / ISBN 13: 9780000988997

Published by World Scientific, 2020

About this Item

Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Seller Inventory # ABNR-301878

Bibliographic Details

• Title: PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS: BASIC DESIGNS TO DEEP LEARNING (4TH EDITION)*
• Publisher: World Scientific
• Publication Date: 2020
• Language: English
• ISBN 10: 0000988995
• ISBN 13: 9780000988997
• Binding: Soft cover
• Edition: International Edition
• Condition: New

About this title

Synopsis

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning. This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained. The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.