[D] Ideas for interesting (eye-opening for beginner) mathematics in machine learning?
So I’m an IB high school student and the IB curriculum requires us to write an extended essay, which is a 4000-word mini-research paper answering a research question. As I’m interested in machine learning, but CS is not available at school, I chose to write about mathematics. I explored some basic stuffs such as gradient descent and back propagation; but they are too fixed and I can’t seem to formulate a question around them. Can you guys suggest some interesting mathematics in machine learning to investigate on?
Also, an adult friend of mine suggest me to try “beta distribution”, but after an hour of research I can’t find the relationship between it and machine learning. Some insight will be hugely appreciated. Thanks.