LIGN 252. Advanced Probabilistic Models of Language (4 units)
Link to catalog page: https://catalog.ucsd.edu/courses/LING.html#lign252
Description
Probabilistic techniques for data analysis and modeling of linguistics cognition. Hierarchical (mixed-effects) regression, graphical models, Bayesian methods, latent-variable models, nonparametric models, probabilistic grammars. Course covers both mathematical foundations and working with datasets using state-of-the-art computational tools. Recommended prerequisite: LIGN 251 or equivalent course with emphasis on probabilistic methods in linguistics. Prerequisites: graduate standing or consent of instructor.
Prerequisite courses
LIGN 252 has no prerequisite courses.
Successor courses
No courses have LIGN 252 as a prerequisite.