UB - University at Buffalo, The State University of New York

Artificial Intelligence/Machine Learning

Machine Learning techniques are a systematic approach to designing information processing systems, such as those for classification and regression, wherein significant uncertainty exists in the data. In the machine learning approach, input-output relationships are learnt from representative samples. This course will build upon basic techniques covered in the pre-requisite courses and cover advanced topics to include: graphical models (including Bayesian networks), mixture models and expectation maximization, approximate inference, sampling methods, continuous latent variables, sequential data, and combining models.

http://www.cedar.buffalo.edu/~srihari/CSE574

CSE 4/574 or equivalent