New Course: CS281 Advanced Machine Learning


Prof. Ryan Adams will be offering a new course this fall in SEAS: CS281 - Advanced Machine Learning. This course is targeted at graduate students and advanced undergraduates. It will focus on probabilistic approaches to machine learning, with particular attention to Bayesian methods. Topics covered will include Markov chain Monte Carlo, variational inference, Bayesian nonparametrics, matrix factorization models, and more. Students taking the class should feel comfortable with basic linear algebra and probability. There will be a significant final project and students should be able to write research code in Matlab, Python or R.

The course website is at