This page refers to the Spring 2017 offering of CSE 674 only. The information on this page does not necessarily apply to every offering of CSE 674.
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.
CSE 4/574 or equivalent
M.S.: This course fulfills one Artificial Intelligence Core Area (Depth) requirement.