Interactive Linear Algebra

Interactive Linear Algebra with R and Python

This modern linear algebra book considers practical engineering and science problems and uses real world data. Its treatment of rectangular space-time data matrix and is space-time decomposistion using singular value decomposition are novel in linear algebra instructions. The book's plain-language and visual descriptions of deep mathematical theorems gave me joy while reading the book. Its Python and R codes are very helpful for students to solve real life problems, which can help students find jobs in the summer or upon graduation.
- Professor John S. Meyer

This linear algebra book is a timely contribution to the mathematical textbooks for the digital economy. The book introduces many linear algebra methods for data science and machine learning. If you want your students to use linear algebra skills for data science and AI applications, this book is an ideal text for you to use. This is not only a textbook, but also a convenient tool book for engineers and scientists, who deal with data in their career. I highly recommend this book to anyone who would like to analyze and visualize space-time data.
- Professor Otto Brewtynski

The book has many unique ways to treat the tradtional linear topics. It asks student the meaning of "eigen" i the term "eigenvector" because non-German speakers do not understand that "eigen" means "my own" or "my." This question makes the concept of matrix A's eigenvector u very easy: A times u does not change vector u's direction, and hence make u a special vector of A's own. Since Au is in the same direction as u, thus there is a scaler λ such that A u = λ u. Its treatment of rectangular matrices is another innovation in teaching linear algebra and makes this subject much more useful than the traditional texts built on square matrices. Thus, this book is not only an excellent modern text for students, but also experienced linear algebra professors can learn some exciting ways to treat matrices.
- Nancy Bernstein

About the author: Samuel S. P. Shen is Distinguished Professor of Mathematics and Statistics at San Diego State University, and Visiting Research Mathematician at Scripps Institution of Oceanography, University of California, San Diego. Formerly, he was McCalla Professor of Mathematical and Statistical Sciences at the University of Alberta, Canada, and President of the Canadian Applied and Industrial Mathematics Society. He has held visiting positions at the NASA Goddard Space Flight Center, the NOAA Climate Prediction Center, and the University of Tokyo. Shen holds a B.Sc. degree in Engineering Mechanics , and M.A. and Ph.D. degrees in Applied Mathematics.

Citation: Shen, S.S.P., 2025: Interactive Linear Algebra with R and Python, Version 2.0, San Diego State University lecture notes, 251pp.