Machine Learning for Social Science

Graduate credit

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. See attached for additional description information.