I found it really hard to get a basic understanding of Support Vector Machines. To learn how SVMs work, I ultimately went through Andrew Ng’s Machine Learning course (available freely from Stanford).  I think the reason SVM tutorials are so challenging is that training an SVM is a complex optimization problem, which requires a lot of math and theory to explain.

This lecture covers:

This lecture covers the Gaussian Discriminant classifier and the Naive Bayes Classifier.

The third lecture covers the following topics (except where noted):

This lecture covers: