Introduction
Chapter Highlights
- Understanding Biological Neural Networks
- How is an Artificial Neural Network Constructed
- Finding Good and Bad Uses for Neural Networks
- The History of the Neural Network
- The Future of Neural Networks
Computers can perform many operations considerably faster than a human being. Yet there are many tasks where the computer falls considerably short of its human counterpart. There are numerous examples of this. Given two pictures a preschool child could easily tell the difference between a cat and a dog. Yet this same simple task would confound today’s computers.
This book shows the reader how to construct neural networks with the Java programming language. As with any technology, it is just as important to learn when to use neural networks as it is to learn when not to use neural networks. This chapter begins to answer that question. What programming requirements are conducive to a neural network?
The structure of neural networks will be briefly introduced in this chapter. This discussion begins with an overview of neural network architecture, and how a typical neural network is constructed. Next you will be shown how a neural network is trained. Ultimately the trained neural network’s training must be validated.
This chapter also discusses the history of neural networks. It is important to know where neural networks came from, as well as where they are ultimately headed. Next you will be shown what problems these early networks faced and how current neural networks address these issues.
This chapter gives a broad overview of both the biological and historic context of neural networks. We begin by exploring how real biological neurons store and process information. You will be shown the difference between biological and artificial neurons.
