The issue with abstractions is that ML isn't just a few variables or dissimilar systems to choose from, the whole problem domain that could be helped with ML ha

The issue with abstractions is that ML isn't just a few variables or dissimilar systems to choose from, the whole problem domain that could be helped with ML has so many dimensions. Natural language, speech processing, pattern recognition etc. are all completely different. The only thing they have in common is that you might use computers for them. I think that is why people find ML so hard. It isn't a single sausage machine to create insight from, it is a set of entire stacks from philosophy all the way down to the electronics.