Learning Program: Machine Learning (ML) Course

Topics covered include Algorithmic models of learning. Learning classifiers, functions, relations, grammars, probabilistic models, value functions, behaviors and programs from experience. Bayesian, maximum posteriori, and minimum description length frameworks. Parameter estimation, sufficient statistics, decision trees, neural networks, support vector machines. You would find this course helpful for every programming jobs.Live Projects.Interview preparation.100% placement ratio.