Basically, I have been focusing on Probability and Statistics since I need a better grasp on this area of mathematics and its application to Machine Learning, in particular Bayesian Inference. I am familiar with Bayes Theorem, but I am not familiar with Bayesian Belief and Markov Belief Networks, a topic covered in Judea Pearl’s book Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.
I reviewing some other video lectures in Stanford University’s YouTube such as CS106A Program Methodology taught by Professor Mehran Sahami. In addition I have reviewing a couple of MIT OpenCourse courses such as Introduction to Probability and Statistics, and Mathematics for Computer Science.
