CS 4740 - Natural Language Processing

(crosslisted) COGST 4740 , LING 4474
(SMR-AS)

Fall. 4 credits. Student option grading (no audit).

Strong programming skills are important. Three semesters of programming classes are strongly recommended (e.g., completion of CS3110). CS2110 may suffice if you individually could have successfully and easily completed the assignments by yourself.
Python experience.
Pytorch experience (as through CS4780) not required but some students report it being very helpful.
Comfort with elementary probability.
Clear understanding of matrix and vector operations.
Familiarity with differentiation.

Co-meets with CS 5740.

L. Lee.

This course constitutes an introduction to natural language processing (NLP), the goal of which is to enable computers to use human languages as input, output, or both. NLP is at the heart of many of today’s most exciting technological achievements, including machine translation, automatic conversational assistants and Internet search. The course will introduce core problems and methodologies in NLP, including machine learning, problem design, and evaluation methods.

This class satisfies the practicum/project requirement for CS majors. As a consequence, expect each of the roughly four connected programming assignments to take tens of hours, although this time is distributed over multiple weeks; to require writing code to massage raw-ish data into different formats and other accessory functions as well as to implement core algorithms; and to necessitate much independent examination of documentation.