Imperial College London (CO-493) The course is co-taught by Duncan Gillies and Marc Deisenroth.
Syllabus Bayes’ Theorem and Bayesian Inference Bayesian Decision Trees -Evidence and message passing Inference in singly connected networks Building networks from data Cause and Independence Model Accuracy Approximate Inference Exact Inference Probability propagation in Join Trees Probability distributions and parameter estimation Graphical models Gaussian mixture models, EM, model selection Dimensionality reduction with PCA Linear discriminant analysis Sampling Variational inference by Hugh Salimbeni