UMD CMSC 742 Entire Class

University of Maryland CMSC 742 Algorithms in Machine Learning: Guarantees and Analyses Entire Class

 

Machine learning studies automatic methods for learning to make accurate predictions, understand patterns in observed features and make useful decisions based on past observations. This course introduces theoretical machine learning, including mathematical models of machine learning, and the design and rigorous analysis of learning algorithms. Topics include (1) Learning theory (traditional and modern), PAC learning basics, Boosting theory, and PAC learning in neural nets. (2) Latent variable graphical models, including spectral methods for learning latent variable models. (3) Reinforcement learning theory, including algorithms, sample complexity, and analyses.

Note: This entire class includes discussions, assignments, course projects, and exams.


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