Lecturer: Emily King
Fields: Mathematics
Content
Linear algebra has ancient roots, appearing even in cuneiform text millennia ago. However, it has proven itself to be resilient and powers many modern techniques in machine learning, natural language processing, cognitive science, and more. Yet, many people use these tools without truly understanding why they work and when they should be used. The purpose of this course is to provide a deep dive into the intuition behind the tools that linear algebra has to offer. It should be of interest both to students who have taken a course in linear algebra and those who have not. We will also touch on the topic of the responsible use of linear algebra and other mathematical techniques.
Literature
- King, E. and Wilson J. “Linear Data” (2023) [open source text to be made available before IK]
Lecturer
Dr. Emily J. King received Ph.D. in mathematics from the University of Maryland in 2009. Since then, she has been an IRTA Postdoctoral Fellow at the National Institutes of Health (USA); a Humboldt Postdoctoral Fellow at Uni Osnabrück, Uni Bonn, and TU Berlin; and a Juniorprofessor at Uni Bremen. She is currently an Associate Professor in the Mathematics Department and member of the data science faculty at Colorado State University. Photo credit: John Eisele/Colorado State University Photography
Affiliation: Colorado State University
Homepage: https://www.math.colostate.edu/~king/