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Introduction to Neural Nets
Basic introduction to Neural Networks including an animated presentation of different Networks learning process. Easy to understand.

AI FAQ/general
Answer to certain questions and topics that come up frequently in the various network discussion groups

Introduction to Neural Networks
This article describes how to implement an artificial neural network
that is capable of being trained to recognize patterns.

Neural Network sample training data from UCI
This is a repository of datasets to be used for neural network training.
Covers more 10 different problem areas.

Introduction to Neural Networks
A well written introduction on artificial neural network and their applications.

Introduction to Neural Networks & Learning Methods
A very good introduction to artificial neural network and their learning methods.

Introduction to Neural Networks from Department of Defense
An excellent introduction to the basic principles of neural networks.

Introduction to Self-Organising Maps
An excellent introduction to the self-organized Maps and Pattern Recognition

Introduction to Support Vector Machine (SVM)
A short introduction to Support Vector Machine

Neural Networks Books
A total of 349 Neural Networks items sorted by poularity. Includes reviews, product descriptions, prices, and buying information.

The society for ANN in Medicine and Biology
A collection of links to people and organisations working with medical applications of artificial neural networks and related techniques.

The Kernel Machines
A Site dedicated to Kernel Machines and related methods. But also Gaussian Process prediction, Mathematical Programming with Kernels, Regularization Networks and Reproducing Kernel Hilbert Spaces.

Neural Network Companies
A Site will reference to companies with products based on Neural Networks.

Information on over 50 NN applications
BrainMaker Neural Network Software: Great list of examples of specific NN applications regarding stocks, business, medicine, and manufacturing.

Neural Networks Tutorial with Java Applets
This site includes a series of exercises and demos. Each exercise consists of a short introduction, a small demonstration program written in Java (Java Applet), and a series of questions which are intended as an invitation to play with the programs and explore the possibilities of different algorithms.

Neural Networks Introduction
NEURAL NETWORK DESIGN provides a clear and detailed survey of fundamental neural network architectures and learning rules. In it, the authors emphasize mathematical analysis of networks, methods for training networks, and application of networks to practical engineering problems in pattern recognition, signal processing, and control systems.

Neural Networks Innovations and Patents
Recent U.S. patents related to Neural Networks

Neural Networks & AI for Gaming
Jay Scott resources site for Machine Learning for Gaming. He describes game programs and their workings; they rely on heuristic search algorithms, neural networks, genetic algorithms, temporal differences, and other methods.

NeuroEvolution of Augmenting Topologies (NEAT)
NEAT is a genetic algorithm for evolving neural networks written by Ken Stanley at University of Texas at Austin and published under the GPL.

SharpNEAT (C# implementation of NEAT)
NEAT is a technique for evolving neural net structure and connection weights, SharpNEAT is one of a number of implementations but happens to be written in C#

NEOXI Neural Network Resources
Content: Professionally selected extensive collection of neural network resources.
Audience: Communities of commerce, industry, academics, engineers, practitioners, and individuals interested in neural networks, machine learning, data mining, artificial intelligence, soft-computing, and numerous other fields directly or indirectly utilizing the neural network technology.
Web Applets for Interactive Tutorials on Artificial Neural Learning.
By Fred Corbett. "This tutorial was developed as part of my undergraduate thesis in Computer Engineering at the University of Manitoba, and was supervised by Dr. H. C. Card. The goal of this project was to demonstrate some elementary aspects of artificial neural networks (ANNs) in an interactive and, hopefully, interesting manner. ... This tutorial is currently divided into three sections [Artificial Neuron, Perceptron Learning, and Multi-Layer Perceptron]. Each section deals with a specific aspect of neural networks and includes a JavaTM applet. The sections include a brief introduction, some theory behind the applet, a set of instructions for using the applet, the source code, and the applet itself."



Related Pages

Helsinki University of Technology
Laboratory of Computer and Information Science
Neural Networks Research Center

Neural Network Projects - Pacific Northwest National Laboratory

Neural networks group - Austrian Research Institute for Artificial Intelligence

Neural Computing Research Group - Aston University -

Computational Intelligence Group - Neural Networks - University of Bristol

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