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Instructor Class Description

Time Schedule:

Fei Xia
LING 572
Seattle Campus

Advanced Statistical Methods in Natural Language Processing

Covers several important machine learning algorithms for natural language processing including decision tree, kNN, Naive Bayes, transformation-based learning, support vector machine, maximum entropy and conditional random field. Students implement many of the algorithms and apply these algorithms to some NLP tasks." Prerequisite: LING 570. Offered: W.

Class description

In this course, we will study statistical algorithms that produce state-of-the-art results on NLP tasks. We will compare supervised learning algorithms that require a lot of training data with the unsupervised ones. We will also study a few important discriminative models. Students will gain hands-on experience by applying these algorithms to real NLP tasks.

Student learning goals

General method of instruction

Recommended preparation

Prerequisites: LING 570 and LING 571 Stat 391 (Prob. and Stats for CS) or equivalent Programming: - C/C++ or Java - basic unix/linux commands (e.g., ls, cd, ln, sort, head) - Perl (optional): tutorials on Perl

Class assignments and grading

The information above is intended to be helpful in choosing courses. Because the instructor may further develop his/her plans for this course, its characteristics are subject to change without notice. In most cases, the official course syllabus will be distributed on the first day of class.
Last Update by Fei Xia
Date: 12/11/2005