Last few months I was playing with Artificial Neural Network (ANN) and how to implement it in to the GPdotNET. ANN is one of the most popular methods in Machine Learning, specially Back Propagation algorithm. First of all, the Artificial Neural Network is more complex than Genetic Algorithm, and you need to dive deeper in to math and other related fields in order to understand some of the core concept of the ANN. But likely there are tons of fantastic learning sources about ANN. Here is my recommendation of ANN learning sources:
First of all there are several MSDN Magazine articles about ANN and how to implement it in C#.
2. Classification and Prediction Using Neural Networks
3. Neural Network Back-Propagation for Programmers
If you want to know what’s behind the scene of ANN, read this fantastic online book with great animations of how neuron and neural networks work.
1. Neural Networks and Deep Learning, by Michael Nielsen.
There is a series you tube video about ANN.
1. Neural Networks Demystified [Part 1: Data and Architecture]
Open source libraries about ANN in C#:
1. AForge.NET. – Computer Vision, Artificial Intelligence, Robotics.
2. numl – Common Machine Learning Algorithms by Seth Juarez
The first GPdotNET v4.0 beta will be out very soon.