Computing That Serves

CS 479

Course Offerings

Section # Semester Instructor Website Description
1 Fall 2012 Eric Ringger
1 Fall 2011 Eric Ringger
1 Fall 2011 Eric Ringger
1 Fall 2010 Eric Ringger
1 Fall 2009 Eric Ringger

Short Summary: 

Natural Language Processing




Natural Language Processing


CS 479 provides a thorough introduction to Statistical Natural Language Processing (Stat. NLP) for students who are interested in solving problems involving natural (human) language. NLP and language technologies have become an important part of the programmer's toolbox when working with text, speech, and other language data.


Objectives for the course include:

• Enable students to attack problems like web search, speech recognition, machine translation, spam filtering, text classification, question answering, and spell checking

• Help students accomplish the following:
o   Grow in confidence in their mathematical and statistical abilities
o   Understand the models, methods, and algorithms of statistical NLP for common NLP tasks
o   Sharpen their understanding of linguistic phenomena
o   Explore the linguistic features relevant to each task
o   Learn how to design statistical models that can accommodate those features
o   Learn how to estimate parameters for such models
o   Implement these models in code, and run meaningful experiments
o   Apply these statistical approaches to new NLP problems
o   Consider how to apply these techniques to other problems, outside NLP
o   Be familiar with some of the NLP literature, and read and suggest improvements to published work
o   See where the opportunities for research await and be ready to conduct research that will advance the state of the art

Prerequisite: CS 312 & Stat 121; or CS 312 & Stat 201