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

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A01=Daniel Graupe
Artificial Intelligence
Author_Daniel Graupe
Category=UYQN
Computer Engineering
Deep Learning
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Image Processing
Machine Learning
Medical Engineering
Neural Networks
Neurosciences
Signal Processing

Product details

  • ISBN 9789811201226
  • Publication Date: 15 Apr 2019
  • Publisher: World Scientific Publishing Co Pte Ltd
  • Publication City/Country: SG
  • Product Form: Hardback
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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.

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