CMPSCI 691BM - S-Bayesian Methods for Text

Institution:

University of Massachusetts Amherst

Subject:

Description:

This course will provide an overview of the key ideas that underlie the Bayesian approach to modeling data, with a particular focus on text. The course will primarily consist of discussing, deriving, and implementing a number of Bayesian models of text (and their associated inference algorithms) in order to understand their fundamental strengths and weaknesses, as well as explore the relationships between them. The aim of the course is to develop the knowledge and skills needed to design, implement, and apply such models to real-world data. Students entering the course should have good programming skills, knowledge of algorithms, knowledge of probability, statistics, or machine learning, and a strong interest in text analysis. To facilitate productive discussion, students with diverse research backgrounds and interests are especially encouraged to participate.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.umass.edu

Phone Number:

(413) 545-0111

Regional Accreditation:

New England Association of Schools and Colleges

Calendar System:

Semester

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