Linear Algebra in Data Science

Peter Zizler is a professor of mathematics at Mount Royal University in Calgary. He holds a Ph.D. in mathematics (linear algebra). He has publications in various journals with research done in diverse areas of linear algebra, Fourier analysis and wavelet analysis. He has also published articles on the Gini index and Lorenz curve, research papers in mathematical education and statistics. He has also previously co-authored a textbook with Springer, Introduction to Modern Analysis (2015), as well as  a chapter Applications of the Gini Index Beyond Economics and Statistics, in the Handbook of the Mathematics of the Arts and Sciences, Springer (2021).  Roberta La Haye is an associate professor of mathematics at Mount Royal University in Calgary.  She holds a Ph.D. in mathematics (group theory).  Her current research interests  include ties between mathematics  and the visual art and ties between mathematics and statistics. She has publications in mathematics journals, visual arts education journals and statistics journals as well as  co-authored book chapters  in Co-Teaching in Higher Education: From Theory to Co-Practice, University of Toronto Press, (2017) and   Applications of the Gini Index Beyond Economics and Statistics, in the Handbook of the Mathematics of the Arts and Sciences, Springer (2021).

"Linear algebra in data science is a remarkable resource that seamlessly connects theoretical principles with practical applications. Zizler and La Haye have created an insightful and engaging guide that caters to a broad audience, from students to seasoned professionals. ... this book empowers readers to apply linear algebra in diverse data science contexts. It is a must-have for anyone seeking to deepen their understanding of the mathematical frameworks driving modern data science." (Pagadala Usha, Computing Reviews, June 4, 2025)