Chapter 1, Getting Started with Neural Networks, introduces neural networks concepts and shows the very basic neuron structures (Single Layer Perceptrons, Adaline), activation functions, weights, and learning algorithms. Besides, this chapter shows the process of creating basic neural networks in Java from start to finish.

Chapter 2, Getting Neural Networks to Learn, presents the details of the neural network learning process. Useful concepts, such as training, test, and validation are introduced. We show how to implement training and validation algorithms. This chapter also shows methods for error evaluation.

Chapter 3, Perceptrons and Supervised Learning, gets you acquainted with perceptrons and the supervised learning features. We present training algorithms for these types of Neural Network. The reader will learn how to implement these features in Java.

Chapter 4, Self-Organizing Maps, introduces unsupervised learning with self-organizing maps, namely the Kohonen neural network, and their applications, especially with classification and clustering problems.

Chapter 5, Forecasting Weather, covers one practical problem using neural networks, which is forecasting weather. You will be presented with a time series dataset of historical weather records from different regions, and learn how to apply preprocessing before presenting them to neural networks.

Chapter 6, Classifying Disease Diagnosis, introduces a classification problem, which is also encompassed in supervised learning. Using patient records data, a neural network is built to act as an expert system, being capable of giving a diagnosis based on patients, symptoms.

Chapter 7, Clustering Customer Profies, will teach you about clustering using neural networks, as well as applying unsupervised learning algorithms to achieve that goal.

Chapter 8, Text Recognition, presents another common task involving neural networks, optical character recognition (OCR), which is a very useful and impressive task that really shows the powerful learning skill neural networks have.

Chapter 9, Optimizing and Adapting Neural Networks, demonstrates techniques that help optimizing neural networks, such as input selection, better dataset separation into training, validation and test, as well as data filtering and the choice of number of the hidden neurons.

Chapter 10, Current Trends in Neural Networks, will make you aware of the current state of the art in the field of neural networks, enabling you to understand and design new strategies to apply to more complex problems.

Appendix A, Setting up Netbeans Environment, This appendix shows a step-by-step procedure for the reader to set up the development environment for the Netbeans IDE.

Appendix B, Setting up Eclipse Environment, This appendix shows a step-by-step procedure for the reader to set up your development environment if you want to use Eclipse IDE.

These Appendices are not present in the book but are available for download at the following link: https://www.packtpub.com/sites/default/files/downloads/Neural_Network_Programming_with_Java_SecondEdition_Appendices.pdf

You'll need Netbeans (www.netbeans.org) or Eclipse (www.eclipse.org). Both are free and available for download from their websites.

This book is for Java developers who want to know how to develop smarter applications using the power of neural networks. Those who deal with a lot of complex data and want to use it efficiently in their day-to-day apps will find this book quite useful. Some basic experience with statistical computations is expected.

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "Layers are initialized and calculated as well as the neurons; they also implement the init() and calc() methods."

A block of code is set as follows:

public abstract class NeuralLayer {
  protected int numberOfNeuronsInLayer;
  private ArrayList<Neuron> neuron;
  protected IActivationFunction activationFnc;
  protected NeuralLayer previousLayer;
  protected NeuralLayer nextLayer;
  protected ArrayList<Double> input;
  protected ArrayList<Double> output;
  protected int numberOfInputs;
}

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "After selecting the parameters, the training begins by clicking the Start Training button."

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