# Handy maths (and more) on the web

This page lists web-based resources which may be of use to those (most of us) who need a spot of maths from time to time. Please mail with details of any sites for inclusion, or if you find broken links.

Sites are currently listed in the following categories:

Graphical models and Bayesian networks

Documentation for code libraries

### Matrices

A from-the-beginning review of the properties of matrices can be found here and some useful identities here.Loads of matrix stuff can be found at the suitably titled Matrix reference manual. Stuck with the derivative of a matrix expression? This resource includes a set of really handy matrix calculus results.

Another resource full of matrix results is The Matrix Cookbook

Need a definition? Try John Burkardt's glossary of linear algebra terms

### Graphical models and Bayesian networks

A tutorial and links regarding graphical models and Bayesian networks is available courtesy of Kevin Murphy.Jeff Bilmes' graphical model toolkit (GMTK) and associated documentation is found here.

### Kalman filtering

A site dedicated to the Kalman Filter maintained by Greg Welch and Gary Bishop.### Probabilistic modelling

This is the real stuff...Probability theory: the logic of science by E.T. Jaynes.A set of notes from Sam Roweis includes tutorials on various aspects of machine learning and probabilistic modelling.

Learning dynamical systems: a tutorial.

Information on Independent Component Analysis (ICA).

### Entropy

Entropy on the World Wide Web.### Documentation for code libraries

Numerical Recipes home page.The reference manual to the GNU Scientific Library may well be useful for anyone using any of these routines.

### Wavelets

Amara's Wavelet Page.The engineers ultimate guide to wavelet analysis.

### Broad remit

Eric Weisstein's World of Mathematics claims to be the web's most complete mathematical resource.The Math Forum is a "leading center for mathematics and mathematics education on the Internet."

The The Data Analysis Brief Book is a "condensed handbook, or an extended glossary, written in encyclopedic format, covering subjects in statistics, computing, analysis, and related fields. It intends to be both introduction and reference for data analysts, scientists and engineers."