Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition): Basic Designs to Deep Learning

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.\n\nThe 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.Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition): Basic Designs to Deep Learning 4th Edition is written by Daniel Graupe and published by World Scientific. ISBNs for Principles Of Artificial Neural Networks: Basic Designs To Deep Learning (4th Edition) are 9789811201240, 9811201242 and the print ISBNs are 9789811201226, 9811201226.