I finished Tao’s linear algebra notes (I just had one section left in week 10).

I did the problems in problem set 0 of the Stanford machine learning course. I remember around a year ago when I looked at this problem set, I was quite intimidated because I had forgotten all the linear algebra I had learned at UW. However, the problems turned out to be quite easy (probably because of the time I have recently spent on linear algebra, but also maybe because I didn’t realize how easy the problems were before).

I looked through the “Linear Algebra Review and Reference” notes for the same course. Most of it I knew thanks to studying linear algebra, but there were some things that other resources on linear algebra don’t tend to talk about, like positive semidefinite matrices.