Here we include 15 machine learning courses and tutorials by leading researchers in the field. Nine of the 15 courses include video lectures. Most of the courses are free and self-paced without the need of registration. The topics covered by these courses include decision trees, Naive Bayes, logistic regression, neural networks and deep learning, estimation, Bayesian learning, support vector machines and kernel methods, clustering, unsupervised learning, boosting, reinforcement learning, and learning theory. If you need to review background for machine learning, professor Geoff Gordon at Carnegie Mellon University has made a great video lecture series Math Background for Machine Learning. For advanced deep learning courses, see 15 deep learning open courses and tutorials for both theoritcal and applications of deep learning.