I have humble, around-undergraduate level understanding of mathematics. I enjoy abstract algebra and statistics the most. After stumbling upon Michael Izbicki's paper Algebraic classifiers, I decided that I wanted to understand this topic more.
I am looking for resources to study Algebraic Machine Learning. A suitable reference should be self-contained, including the relevant category theory background required for this field. It should also explicitly address the fundamental categorical aspects of algebraic machine learning, such as
- Why do Markov Fields form a monoid and how does it look like?
- Do Bayes Networks form a monoid?
- Do Neural Nets form a monoid?
Can anyone recommend a text or an appropriate media resource?