Algorithms for supervised and unsupervised learning from data. Content may include maximum likelihood, log-linear models including logistic regression and conditional random fields, nearest neighbor methods, kernel methods, decision trees, ensemble methods, optimization algorithms, topic models, neural networks and backpropagation. CSE 103 or similar course recommended.
graduate standing in CSE or consent of instructor.
Formerly CSE 250B - Artificial Intelligence: Learning