Artificial neural networks are programming techniques that attempt to emulate the human brain's biological neural networks. Artificial neural networks (ANNs) are just one branch of artificial intelligence (AI). This book focuses primarily on artificial neural networks, frequently called simply neural networks, and the use of the Encog Artificial Intelligence Framework, usually just referred to as Encog. Encog is an open source project that provides neural network and HTTP bot functionality.
This book explains how to use neural networks with Encog and the Java programming language. The emphasis is on how to use the neural networks, rather than how to actually create the software necessary to implement a neural network. Encog provides all of the low-level code necessary to construct many different kinds of neural networks. If you are interested in learning to actually program the internals of a neural network, using Java, you may be interested in the book “Introduction to Neural Networks with Java” (ISBN: 978-1604390087).
Encog provides the tools to create many different neural network types. Encog supports feedforward, recurrent, self organizing maps, radial basis function and Hopfield neural networks. The low-level types provided by Encog can be recombined and extended to support additional neural network architectures as well. The Encog Framework can be obtained from the following URL:
Encog is released under the Lessor GNU Public License (LGPL). All of the source code for Encog is provided in a Subversion (SVN) source code repository provided by the Google Code project. Encog is also available for the Microsoft .Net platform.
Encog neural networks, and related data, can be stored in .EG files. These files can be edited by a GUI editor provided with Encog. The Encog Workbench allows you to edit, train and visualize neural networks. The Encog Workbench can also generate code in Java, Visual Basic or C#. The Encog Workbench can be downloaded from the above URL.