Machine Learning with Application to Text as Data
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Course Description
Machine Learning methods are increasingly useful for the social sciences. This course introduces a framework for using machine learning methods to make social science inferences, with a particular focus on text as data. The course will explain how machine learning methods can be used to facilitate discovery, measure quantities of interest, and to make causal inferences and predictions. We will introduce a variety of methods for representing texts as quantitative data and then we will introduce a wide array of commonly used methods. Prerequisites are POLISCI 450A, 450B, and 450C.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
5
Course Repeatable for Degree Credit?
No
Course Component
Seminar
Enrollment Optional?
No
Programs
POLISCI452
is a
completion requirement
for: