Diagonalization and Linear Transformations - A First Course in Linear Algebra (III) - a complete first course in linear algebraic methods.
In the previous post, we gave theoretical treatments for vector spaces, spans, bases and projections. Here we round up the discussion with matrix diagonalization and linear transformations. Over the span of 1.5 weeks, we released complete notes for an entire first course in linear algebra, that might typically be taught over an entire semester at the undergraduate level. The idea was to get readers comfortable with linear systems, and so that we may reference relevant concepts in discussions further down the road. The total discussion sum to a dense treatment over 79 pages, summarizing the critical results and theorems that are often used computationally.
Moving on, we will discuss portfolio management for the weeks to come. Frankly, the topic is rather large, and therefore I find it rather difficult to engage in a systematic, well defined taxonomy of discussion. Therefore, we will just attack the topic from all directions. As we discuss principle concepts and techniques, the topics will naturally fall into order and we will give a more methodological treatment to the subject. We will write code snippets where relevant, and as key themes are concluded, we hope to then integrate this into the Russian Doll as more extensible code logic. The full range of discussion and implementations will be available for paid readers to access.
Full market notes - 495 pages (paywalled)