The purpose of this course is to provide a self-contained introduction to the field of machine learning, based on a probabilistic approach. Machine learning is indeed a very active field, which has met with great success in academia and in industry. The first part of the lectures will be dedicated to the analysis of the expectation-maximization (EM) algorithm. The second part will address latent linear models and the last one will focus on the notion of kernels.
Machine learning, Bayesian statistics, Information theory, Classification, Regression