I did not start in machine learning. I started because a friend's phone would not charge properly and I was the person they called.
That is a genuinely useful way into this. You learn that most problems are not as mysterious as they look, that asking one more question beats guessing, and that a fix you do not understand will come back.
Years later that habit is the reason I can take a model that works on a laptop and get it onto a phone. The debugging is the same. You look at the actual data, you find where it stops matching what you expected, and you fix that one thing.
This site is the same idea. Nothing here is theoretical. I write about what I built, what broke, and what I had to change to make it work.