Deep Learning Neural Networks: Design and Case Studies

Daniel Graupe

ISBN 10: 9813146443 / ISBN 13: 9789813146440

Verlag: World Scientific Publishing Company, 2016

Beschreibung

pp. 280. Bestandsnummer des Verkäufers 18375040038

Bibliografische Details

Titel: Deep Learning Neural Networks: Design and ...

Verlag: World Scientific Publishing Company

Erscheinungsdatum: 2016

Einband: Hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

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. READERSHIP: RESEARCHERS, ACADEMICS, PROFESSIONALS, GRADUATE AND UNDERGRADUATE STUDENTS IN MACHINE LEARNING, ARTIFICIAL INTELLIGENCE, NEURAL NETWORKS/NETWORKING, SOFTWARE ENGINEERING, AND IN THEIR APPLICATIONS IN MEDICINE, SECURITY ENGINEERING AND FINANCIAL ENGINEERING.

Reseña del editor:

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.