ICME Fundamentals in Data Science
Linear algebra short course. This is a course on linear algebra in the ICME Fundamentals in Data Science (2021) series, taught by Professor Margot Gerritsen and myself. The Github is available here. I wrote the notes, homework, and all of the interactive coding modules, so I hope you enjoy!
In this course, we look at several important concepts at the intersection of statistics, linear algebra, and data science, such as principal component analysis (PCA), linear regression, ordinary least squares (OLS), eigenvectors and eigenvalues, the SVD, and the spectral decomposition. This class is meant to be an introductory, casual, and hands-on exploration of these topics. Some example applications we consider are (1) characterizing breast tumors with PCA based on this data set from the University of Wisconsin, and (2) heart health in adolescent women.