Linguistics | Machine Learning, Empirical and Computational Linguistics
L700 | 3328 | Damir Cavar


Course: L700 - Machine Learning, Empirical and Computational
Linguistics  (Fall 2003)

Section: 3328

Instructor: Damir Cavar 
phone 855-3268
Memorial Hall, room 401
Office hours: TUE+TH 13-14h, or by appointment

Course Information

Machine learning (ML) methods, e.g. statistical and symbolic
algorithms for induction and clustering, are used in modeling and
hypothesis testing of human cognitive abilities, as well as in
empirical linguistic research and applied computational linguistics.
In this course we will discuss a variety of statistical and symbolic
ML algorithms and their application in domains including applied
computational linguistics, psycholinguistics and cognitive
science. Through selected readings, exercises, demonstrations and
programming, this course will a.) survey a range of issues relating ML
algorithms to natural language processing and psycholinguistic and
cognitive modeling, b.) provide practical experience applying
different ML strategies to linguistic data.

(Prior programming experience and/or basic knowledge of statistical
and symbolic ML methods is presupposed.)

More detail will be available at:
http://jones.ling.indiana.edu/cl/