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

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.

Détails du produit

• Auteurs: Daniel Graupe, Daniel Graupe, Graupe Daniel
• Edition: Ingram Publishers Services
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 31.07.2019
• EAN: 9789811201226
• ISBN: 978-981-1201-22-6
• Thèmes: Advanced Series in Circuits an; Advanced Series in Circuits an; Advanced Series In Circuits And Systems
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Informatique; COMPUTERS / Data Science / Neural Networks, Neural networks and fuzzy systems, Neural networks & fuzzy systems