Andrew speaking at CMU in April 2014 Andrew W. Moore

The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms.

Here are all the tutorials in .ppt (powerpoint) form. Feel free to use and adapt them any way you like, but please include a pointer back to this web page. Thanks!

These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. They include regression algorithms such as multivariate polynomial regression, MARS, Locally Weighted Regression, GMDH and neural nets. And they include other data mining operations such as clustering (mixture models, k-means and hierarchical), Bayesian networks and Reinforcement Learning.

I hope they're useful (and please let me know if they are, or if you have suggestions or error-corrections). Click here for a short list of topics.