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Generating Code

published by jeffheaton on Wed, 09/30/2009 - 18:27

The Encog workbench provides two ways that you can make use of your neural network in Java code. First, you can save the neural network and training data to an .EG file. Java applications can then load data from this .EG file. Using .EG files will be covered in much greater detail in Chapter 9, “Encog Persistence”.

Another way to generate code is to use the Encog Workbench. The Encog workbench can generate code in the following languages.

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Encog Activation Functions

published by jeffheaton on Wed, 09/30/2009 - 18:01

The next sections will explain each of the activation functions supported by Encog. There are several factors to consider when choosing an activation function. Firstly, the type of neural network you are using may dictate the activation function you must use. Secondly, you should consider if you would like to train the neural network using propagation. Propagation training requires an activation function that provides a derivative. You must also consider the range of numbers you will be dealing with.

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Chapter 2 of upcoming Encog for Java book now online

published by jeffheaton on Wed, 09/23/2009 - 07:25

The second chapter of the upcoming Encog for Java book is now online.

http://www.heatonresearch.com/online/programming-neural-networks-encog-j...

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Chapter 1: Introduction to Encog

published by jeffheaton on Sun, 09/20/2009 - 13:20

The Encog Framework
What is a Neural Network?
Using a Neural Network
Training a Neural Network

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Choosing the Best C# Array Type for Matrix Multiplication

published by jeffheaton on Mon, 08/24/2009 - 04:35

Implementing 2D arrays in C# involves some decisions as to how to represent the array. C# has two different types of arrays. This is somewhat different than the Java programming language, which supports only a single type of array. In C# you must choose between rectangular and jagged arrays. There are very important considerations for each of these array types. There are also many articles about the differences between array handling in Java and C#. This article focuses on one thing-- performance. Particularly how to implement a matrix with the best performance.

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Encog 2.0 for Java is Released

published by jeffheaton on Mon, 07/06/2009 - 22:27

Encog 2.0 for Java has been released. The beta test period is now over. To download Encog 2.0, visit http://www.encog.org. The forum contains more information on what will be added in Encog 2.1.

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Encog Presentation at Gateway Java Users Group (St. Louis)

published by jeffheaton on Tue, 05/12/2009 - 17:44

On Tuesday, June 2, 2009 I will do a presentation on Encog at the Gateway Java Users Group in St. Louis, MO at 6:00 PM. The information on this presentation can be found here. I will post the material for this presentation online after I complete it.

Implementing a Java Neural Network with the Encog Framework

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Introduction to Groovy

published by jeffheaton on Fri, 05/01/2009 - 06:20

In this article I am going to present a brief introduction to the Groovy programming language. Groovy can be very beneficial to the artificial intelligence programmer. When training a neural network for pattern recognition it is often necessary to pre-process the data considerably before training the neural network. This is particularly true for temporal pattern recognition. Additionally control and training sets must be established, often by statistical analysis. Groovy allows you to very quickly create such code in a scripted way, without all of the ceremony of regular Java.

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Class 3 material for C#/Java has been posted

published by jeffheaton on Thu, 02/05/2009 - 06:41

The class 3 material for Introduction to Neural Networks for C#/Java has been posted, visit the forum area for more information.

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Introduction to Neural Networks for Java, Second Edition Available from Amazon

published by jeffheaton on Fri, 09/26/2008 - 12:52

The Second Edition to our popular Introduction to Neural Networks for Java is now available from Amazon. This sister C# book will be available in about three weeks.

[Amazon: Introduction to Neural Networks for Java, 2nd Edition]

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