Deep Learning Neural Networks: Design And Case Studies (Paperback)

Daniel Graupe

ISBN 10: 9813146451 / ISBN 13: 9789813146457

Published by World Scientific Publishing Co Pte Ltd, Singapore, 2016

About this Item

Paperback. Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance.This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9789813146457

Bibliographic Details

• Title: Deep Learning Neural Networks: Design And Case Studies (Paperback)
• Publisher: World Scientific Publishing Co Pte Ltd, Singapore
• Publication Date: 2016
• Language: English
• ISBN 10: 9813146451
• ISBN 13: 9789813146457
• Binding: Paperback
• Condition: new

About this title

Synopsis

Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, diagnosis, detection and decision problems based on a well-defined computational architecture. It has been successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance. This comprehensive textbook is the first in the new emerging field. Numerous case studies are succinctly demonstrated in the text. It is intended for use as a one-semester graduate-level university text and as a textbook for research and development establishments in industry, medicine and financial research.