In this article I will discuss some of the primary issues with GPU programming. This article will focus on how we implemented the first version of GPU support in the Encog Machine Learning Framework. This article focuses mainly on using OpenCL from Java or C#, however it is general enough to apply to any language that can commu icate with OpenCL.

In this tutorial I will show you how to download, install, and execute the examples for “Introduction to Neural Networks for Java, 2nd Edition”. This example shows how to use the NetBeans IDE. If you would like to use Eclipse, this is covered in a separate tutorial.

The first step is to download the book’s examples. These can be found at the following URL:

http://www.heatonresearch.com/download

The file you should download is named.

In this tutorial I will show you how to download, install, and execute the examples for
"Introduction to Neural Networks for Java, 2nd Edition". This example shows how to use the Eclipse IDE. If you would like to use NetBeans, this is covered in a separate tutorial.
The first step is to download the book’s examples. These can be found at the following URL:

http://www.heatonresearch.com/download

The file you should download is named.

Encog 2.4.2 has been released. This is only a service release, however it fixes some important bugs.

Work is still progressing on Encog 2.5.0, which will add several new features.

Encog 2.4.2 addresses the following issues:

2.4.2: Added stress test
2.4.2: Fixed OpenCL threading issue.
2.4.2: Prune incremental to support elman/jordan
2.4.2: Pool items now pass on errors
2.4.2: Added shutdown method
2.4.2: Fixed pattern typos
2.4.2: Fixed many bugs in BufferedNeuralDataSet
2.4.2: Fixed bug where csv2binary had the number of columns hard-coded

Here is an announcement from both the Encog and Neuroph teams.

http://netbeans.dzone.com/encog-neuroph-collaboration

Encog and Neuroph are both AI frameworks that provide neural network functions. Neuroph allows neural networks to be modeled at the neuron level and is particularly adept at allowing the programmer to create entirely new neural network architectures. Encog is more focused on performance, multi-core and GPU usage of known neural network architectures. We are going to make the platforms more compatible and offer the best of both worlds.

Today we released Encog 2.4 for both Java and .Net. This is a very major upgrade to Encog. It contains the following enhancements. Encog is an advanced machine learning framework for Java.

The goal of this article is to help you understand what a neural network is, and how it is used. Most people, even non-programmers, have heard of neural networks. There are many science fiction overtones associated with them. And like many things, sci-fi writers have created a vast, but somewhat inaccurate, public idea of what a neural network is.