>> ML requires a solid math background
I've seen many people in ML not quite understanding what they are doing randomly trying different things until it "works".
I've seen many people in ML not quite understanding what they are doing randomly trying different things until it "works".
The problem gets worse in unsupervised ML, e.g. cluster analysis. Whatever variables you choose, clustering will give you some results. But only an experienced person can understand what variables to choose for the clustering, how to do it, and what those clusters really mean. You can't just try different things in clustering until it "works", because it always works.