Lecture, four hours; discussion, two hours; outside study, six hours. Requisite: course 145 or M146. Recommended requisite: course 35L. Introduction to wide range of natural language processing, tasks, algorithms for effectively solving these problems, and methods of evaluating their performance. Focus on statistical and neural-network learning algorithms that train on text corpora to automatically acquire knowledge needed to perform task. Discussion of general issues and present abstract algorithms. Assignments on theoretical foundations of linguistic phenomena and implementation of algorithms. Implemented versions of some of algorithms are provided in order to give feel for how discussed systems really work, and allow for extensions and experimentation as part of course projects. Letter grading.

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Course

Instructor
Violet Peng
Previously taught
23W

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