Math Revisited

Hey everyone, welcome to my personal blog. This will mainly be a public learning blog, with the occasional maker or homelab build post mixed in. Heads up, posts will follow my current interests, so please give me a little room to bounce around, though I'll have some longer-term series running too. Thanks for visiting!

With that out of the way, here's the first series.

Context

I'm kicking off a series called Math Revisited. I studied applied math in college, and since it's been some time, I'd like to revisit the subjects I found most interesting back then. Think of this as public learning. The series will also touch on application areas, particularly computing and social science, which are my favorite places to see math show up.

Structure

I'm working through three books, starting with Applied Linear Algebra and spending the most time there. The other two are threads I'll pick up alongside it as interest pulls me. Each post will focus on a concept or chunk of content from one of the books, leaning qualitative rather than equation-heavy. When equations do show up, I'll explain what they mean and how to read them.

The Books

Applied Linear Algebra is where I'm starting. It's a broad subject with wide-ranging applications, especially in machine learning. I have a decent amount of exposure already, but undergraduate linear algebra tends to be short and computational, which is the least interesting flavor of it. The more conceptual side is where the interesting applied work lives, and that's what I want to spend time on here.

Generative Deep Learning, 2nd Edition is a timely look at generative AI models. I had some exposure to this material in college but only at an overview level, so this is a chance to go deeper.

Scientific Programming and Computer Architecture is the third thread. A numerical analysis professor of mine called this the best book on the subject. I've taken numerical analysis before, but I don't have a strong background in computer architecture, so this one will stretch me when I get to it.

What's next

The first real post will most likely come out of the early chapters of Applied Linear Algebra or Generative Deep Learning, landing in the next couple of weeks. See you then