| Neural Network Tutorials |
| Artificial Neural Networks Technology [DoD] |
| Very nice and comprehensive introduction to neural networks. The report is intended to help the reader understand what Artificial Neural Networks are, how to use them, and where they are currently being used. |
| Training Neural Networks for Speech Recognition [CSLU] |
| The tutorial describes the method used at CSLU for creating neural-network-based speech recognizers. Included in this tutorial are some general concepts behind training a recognizer, step-by-step instructions on how to train a recognizer, and a description of Tcl scripts that can be used to automate parts of this process. |
| Reinforcement Learning: An Introduction [R. S. Sutton and A. G. Barto] |
| This introductory textbook on reinforcement learning is targeted toward engineers and scientists in artificial intelligence, operations research, neural networks, and control systems. It will also be of interest to psychologists and neuroscientists. |
| Information Theory, Inference, and Learning Algorithms [D. MacKay] |
| The book containing introductory material on Information Theory, Inference, and Learning Algorithms. Downloadable in various formats. |
| Machine Learning, Neural and Statistical Classification [D. Michie, D.J. Spiegelhalter, C.C. Taylor (eds.)] |
| This book is based on the EC (ESPRIT) project StatLog which compare and evaluated a range of classification techniques, with an assessment of their merits, disadvantages and range of application. This integrated volume provides a concise introduction to each method, and reviews comparative trials in large-scale commercial and industrial problems. |
| Introduction to Neural Networks [N. Schraudolph and F. Cummins] |
| The goal is to introduce students to a powerful model class, the Neural Network. In fact, this is a broad term which includes many diverse models and approaches. |
| Artificial Neural Networks Guide [C. Fahey] |
| Nice and illustrative simple introduction to neural networks - from biological backgrounds via simple neuron models to learning by back-propagation. |
| Introduction to Artificial Neural Networks [P. Makhfi] |
| Nice introduction to artificial neural networks. Starting from bio-neurons, you can find simple neuron model, description of neural network types and learning processes + some geometrical interpretations. |
| Neural Networks Tutorial with Java Applets |
| Nice collection 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. The aim of the applets is to illustrate the dynamics of different artificial neural networks. Emphasis has been put on visualization and interactive interfaces. |
| Lecture Notes on Neural Networks [K. Gurney] |
| Notes on neural networks available online have have formed the basis of a book to be published. |
| Neural Networks [StatSoft] |
| Reasonably comprehensive introduction to neural networks, neural network learning and applications. Illustrated with applications of a specific neural network program. |
| Introduction to Artificial Neural Networks [Wolfram Research] |
| Introduction to neural networks and Mathematica's Neural Network package. Neural Networks package in Mathematica is designed to train, visualize, and validate neural network models. |
| Introduction to Neural Networks [C. Stergiou and D. Siganos] |
| The various types of neural networks are explained and demonstrated, applications of neural networks like ANNs in medicine are described, and a detailed historical background is provided. The connection between the artificial and the real thing is also investigated and explained. Finally, the mathematical models involved are presented and demonstrated. |
| Simple Introduction to Artificial Neural Networks [H. Wongsuvan] |
| Contains simple introduction to artificial neural networks (with basic division listing supervised and unsupervised methods) + some 'recommended' reading: books, journals. |
| Neural Networks in Hardware [C. S. Lindsey] |
| Lecture notes: Development of hardware especially designed for NNWs has been slow and with only modest commercial success. This overview looks at some possible reasons for this slow development and some of the areas where hardware NNWs in fact have been very useful and where future growth will occur. |
| Perceptrons: An Associative Learning Network [M. D. Estebon] |
| Simple introduction to perceptron and perceptron-type neural networks. |
| Programming Neural Networks in Java E-Book [J. Heaton] |
| The e-book contains text, diagrams and sample Java code. Topics such as multi-layer networks, genetic algorithms, simulated annealing, backpropagation, and general machine learning are covered. |
| Neural Networks [I. F. Russell] |
| Very simple tutorial. (Printed with permission from the Journal of Undergraduate Mathematics and its Applications, Vol 14, No 1) |
| Kernel Machines Tutorials [www.kernel-machines.org] |
| Collection of tutorials on support vector machines - different people, different tutorials. |
| Support Vector Machines [B. Scholkopf, A. Smola] |
| The web page provides information as well as about a third of the chapters of the book Learning with Kernels. |
| Introduction to Self-organizing Maps [N. M. Allinson] |
| Nice introduction to self-organizing maps. These notes provide an introduction to unsupervised neural networks, in particular Kohonen self-organising maps; together with some fundamental background material on statistical pattern recognition. |
| AI-FAQ - Neural Networks |
| Collection of postings to the Usenet newsgroup comp.ai.neural-nets (as well as comp.answers and news.answers). Its purpose is to provide basic information for individuals who are new to the field of neural networks or who are just beginning to read this group. |
| AI-FAQ - General |
| Collection of postings to the Usenet newsgroup comp.ai. Contains answers to general AI related questions. The collection is divided into the parts. |
