Description: Lecture, three hours; discussion, one hour. Limited to Master of Quantitative Economics students. Exploration of how machine learning can be used to find underpriced real estate opportunities--representative of types of problems frequently faced in industry by analysts, computer scientists, economists, and data scientists. Use of machine learning algorithms and tools to find undervalued assets through applied approach. Exploration, cleaning, wrangling, and analysis of property listings dataset. Use of trees and forests to improve ability to find good deals. Incorporation of additional datasets--demographic and census data--and use of principal component analysis and support vector machines to better identify properties. Use of Python, Pandas, SciKit Learn, Apache Spark, Apache Sedona, and other technologies. Letter grading.

Units: 4.0