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Machine learning unit is about studying the basic concepts of machine learning and it's relation with different topics based on learning theory, graphical models, dynamic Bayesian Model. It generally includes the study of topics such as Naïve Bayesian Classification, model fitting and EM algorithm, Neural networks and back propagation, support vector machine and kernel methods, latent models, metric learning, Markov random fields, approximation inference and different others.
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