Introduction to Unsupervised Learning

Harvard FAS

An introductory course in unsupervised learning with an emphasis on dimensionality reduction and clustering. Topics include principal component analysis, nonnegative matrix factorization, and spectral clustering. In this course we will study these techniques and others with a focus on high-dimensional geometry and insights provided by linear algebra. Numerous data example will be included throughout the course.