This course aims to give a thorough introduction to several machine learning (ML) techniques. The first part of the course will cover supervised ML (i.e., regression and classification) techniques such as lasso, ridge regression, support vector machines, neural networks etc. The second part will cover unsupervised ML techniques including clustering (K-nearest neighbors), topic modeling, and word embeddings. The course will also include applications of some of these techniques in the fields of development economics, environmental economics, labor economics, and political economy.
Prerequisite: ECO 5401 (Econometrics I)