6.862 Applied Machine Learning (New)


Class Info

Introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction; formulation of learning problems; representation, over-fitting, generalization; clustering, classification, probabilistic modeling; and methods such as support vector machines, hidden Markov models, and Bayesian networks. Students taking graduate version complete different assignments.

This class has no prerequisites.

6.862 will not be offered this semester. It will be available in the Spring semester, and will be instructed by R. Barzilay and T. Jaakkola.

This class counts for a total of 12 credits. This is a graduate-level class.

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MIT 6.862 Applied Machine Learning (New) Related Textbooks

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