This is a graduate course on statistical natural language processing (NLP). The course has two components: the first is a lecture component to introduce NLP concepts; the second component focuses on understanding state-of-the-art machine learning algorithms for a series of important topics in NLP by discussing reseach papers.
The first few meetings (~6) will be lectures. The rest will
be paper discussions where participants take turns as discussion leaders.
Programming assignments (2) (40%)
Course project (1) (35%)
Paper presentation (1) (15%)
Paper discussions (all) (10%)
[J&M]: Jurafsky and Martin, Speech and Language Processing, 2nd edition (amazon)