Product Description

Introduction to Neural Networks with Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures, such as the feedforward, Hopfield, and self-organizing map architectures are discussed. Training techniques, such as backpropagation, genetic algorithms and simulated annealing are also introduced. Practical examples are given for each neural network. Examples include the traveling salesman problem, handwriting recognition, financial prediction, game strategy, mathematical functions, and Internet bots. All Java source code is available online for easy downloading.

Product Details

• Amazon Sales Rank: #79825 in Books
• Published on: 2008-10-01
• Original language: English
• Number of items: 1
• Binding: Paperback
• 440 pages

About the Author
Jeff Heaton is an author, college instructor, and consultant. Jeff lives in Chesterfield (St. Louis), Missouri. The author of seven books and over two dozen journal and magazine articles, Jeff specializes in Internet, socket-level/spidering and Artificial Intelligence programming. Jeff has worked with companies such as MasterCard, Anheuser-Busch and Boeing. A Sun Certified Java Programmer and a Senior Member of the IEEE. Jeff holds a Masters Degree in Information Management from Washington University in St. Louis.

Customer Reviews

Simple yet effective
I happened to start reading the first edition of the book and realized quite fast that it was outdated, however after browsing Amazon for a while I decided to go with the same author, and I wasn't left disappointed.

This is a very good book for anyone starting learning Neural Networks. It might not give you everything in detail, but as far as giving a hands on approach to learning NN this is the book to read. If you, like me, happened to get the first edition I would recommend you to upgrade as well. This edition of the book is much more mature.

I would caution anyone that don't know object oriented programming that this book is based that. I bought the C# version of the book as well, and it doesn't seem any different than syntax wise.