17.835 Machine Learning and Data Science in Politics
Introduces students to politics by analyzing political science data sets with machine learning methodologies. Covers a variety of data science tools, including supervised and unsupervised learning methods, visualization techniques, text analysis, and network analysis. Emphasizes how the research methodologies can be used for studying political science. Topics include lobbying, international trade, political networks, and estimating ideologies of political leaders.
This class has 6.0001 as a prerequisite.
17.835 will not be offered this semester. It will be available in the Spring semester, and will be instructed by I. S. Kim.
Lecture occurs 9:30 AM to 11:00 AM on Mondays and Wednesdays in 3-133.
This class counts for a total of 12 credits. This class counts as a HASS S.
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