|Meeting Time:||G: MWF 2:00-2:50|
|Exam Group:||07: 05/12/17 at 2:00 PM|
|Offered this year?||Yes|
|When Offered?||Every year|
Introduction to computational linguistics (also known as natural-language processing) including the related mathematics and several programming projects. Particular topics include: language modeling (as used in e.g., speech recognition, machine translation), machine translation, part-of-speech labeling, syntactic parsing, and topic modeling. Mathematical techniques include basic probability, noisy channel models, the EM (Expectation-Maximization) algorithm, hidden Markov models, probabilistic context-free grammars, and the forward-backward algorithm.
Prerequisites are CSCI1410 or permission of instructor. Permission will be given to all students with a solid background in programming (which programming language is secondary) and either basic probability, or enough mathematical background to quickly absorb the latter.