This course focuses on building statistical models of natural language. We do this with two aims. First, these models have tremendous value in the practical/computational domain and are widely used in human language technology applications. Second, these models have significant appeal as theoretical models of how language is processed, or how grammars are organized. This is a highly interdisciplinary course, bringing together elements of both linguistics and computer science. Natural Language Processing (NLP) has a large applied component, and as such this course will have a considerable focus on project-based assignments rather than written ones.
Time and Place
Tuesday/Thursday 2:00 - 3:15 in Communication, Room 113
Instructor: Mihai Surdeanu
msurdeanu AT email DOT arizona DOT edu
Office: Gould-Simpson 746
Office Hours: Tue 12:30 - 2
TA: Gus Hahn-Powell
hahnpowell AT email DOT arizona DOT edu
Office: Gould-Simpson 903
Office Hours: Wed 2 - 3
TA: Patricia Lee
pllee AT email DOT arizona DOT edu
Office Hours: TBA
This term we will be using Piazza for class discussion. The system is highly catered to getting you help fast and efficiently from classmates, the TA, and myself. Rather than emailing questions to the teaching staff, I encourage you to post your questions on Piazza. If you have any problems or feedback for the developers, email email@example.com.
Find our class page at: https://piazza.com/arizona/fall2017/ling439539/home (log in, then go the Q & A section)