Introducing the Notes

Linear algebra is a foundational branch of mathematics that primarily investigates in linear equations, vectors, and their relations. The application of linear algebra is so immense that numerous fields require foundational understanding of linear algebra. For instance, it would not be possible to gain profound understandings in machine learning and data science without the basics of linear algebra. This collection of notes discuss the essence of linear algebra in perspective of teaching.

One of the most effective way to learn, at least for me, is to teach. During the summer of 2026, I was enrolled in the course XM511 from Stanford Pre-Collegiate University-Level Online Math, instructed by Dr. Margarita Kanarsky [MATH02-1]. During the lectures, I thought it would be a great idea to write notes on linear algebra just as I wrote the notes for machine learning. Writing the teaching-style notes for machine learning allowed me to differentiate what I truly know.

That being said, my notes do not represent the course. I have included my understandings the supporting textbook [MATH02-2] from numerous external sources and restructured the notes itself to adhere to the Permission to Use Materials. Therefore, any errors in these notes are my responsibility.