#  Machine Learning Tutorials 

 





March 05, 2011

 

 

[Andrew Moore](http://www.cs.cmu.edu/~awm/) has a fairly long list of [tutorials](http://www.autonlab.org/tutorials/) on various topics in Machine Learning and Statistics. Here is the description:

> 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.
> 
> 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.

There is a little modesty in the description here. The slides that I have looked at do a great job motivating the methods using intuition, which is often hugely lacking.

Posted by [Matt Blackwell](http://www.iq.harvard.edu/blog/sss/archives/author/matt-blackwell/) at March 7, 2011 9:50 AM



 

 

 



 

 

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