Mathematical Monk on Machine Learning and Information Theory

There is an excellent series of video tutorials by Mathematical Monk described as "Videos about math, at the graduate level or upper-level undergraduate.". Unlike the usual classroom style videos, the tutorials are recorded as screencasts with the teacher trying to explain concepts by writing down examples and proving theorems while narrating the steps. Quite hands on and effective.

There are about 260 videos on the channel and four main playlists namely information theory advance, probability primer, machine learning and information theory primer. Machine learning is by far the largest area with over 160 videos and 34 hours of very valuable instructions covering topics including but not limited to introduction to machine learning, supervised and unsupervised learning, linear regression, classification trees, Boosting and Bagging, Maximum likelihood estimation, Bayesian inference, Bayesian decision theory, D-Separation, HMM, K-means, graphical models and MCMC.

The Channel can be found here. and individual playlists can be seen here including the machine learning playlist for your learning pleasure.