Maximum Likelihood Estimation
Tutorial Slides by Andrew Moore
MLE is a solid tool for learning parameters of a data mining model. It is a methodlogy which tries to do two things. First, it is a reasonably well-principled way to work out what computation you should be doing when you want to learn some kinds of model from data. Second, it is often fairly computationally tractable. In any case, the important thing is that in order to understand things like polynomial regression, neural nets, mixture models, hidden Markov models and many other things it's going to really help if you're happy with MLE.
Powerpoint Format: The Powerpoint originals of these slides are freely available to anyone who wishes to use them for their own work, or who wishes to teach using them in an academic institution. Please email Andrew Moore at firstname.lastname@example.org if you would like him to send them to you. The only restriction is that they are not freely available for use as teaching materials in classes or tutorials outside degree-granting academic institutions.
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