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Neural Smithing: Supervised - Hardcover, by Reed Russell D.; - Very Good

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Last updated on 03 Aug, 2025 10:00:32 AESTView all revisionsView all revisions

Item specifics

Condition
Very good: A book that does not look new and has been read but is in excellent condition. No obvious ...
Book Title
Neural Smithing: Supervised Learning in Feedforward Artificial Ne
ISBN
9780262181907

About this product

Product Identifiers

Publisher
MIT Press
ISBN-10
0262181908
ISBN-13
9780262181907
eBay Product ID (ePID)
757749

Product Key Features

Number of Pages
360 Pages
Language
English
Publication Name
Neural Smithing : Supervised Learning in Feedforward Artificial Neural Networks
Publication Year
1999
Subject
Computer Science, Neural Networks
Type
Textbook
Subject Area
Computers
Author
Russell D. Reed, Robert J. Marks II
Format
Hardcover

Dimensions

Item Height
1.1 in
Item Weight
29.1 Oz
Item Length
9 in
Item Width
7.2 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
98-013416
Dewey Edition
21
Grade From
College Graduate Student
Illustrated
Yes
Dewey Decimal
006.3/2
Synopsis
Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition). This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.
LC Classification Number
QA76.87.R44 1998

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