[tensor]

What usually happens is that people get something working, think they now know ML, but don't even generally know enough to understand the things they did wrong, and never end up getting to the theory.

The best approach is to learn both concurrently. Learn some theory, apply it and understand that applications including pitfalls, then learn a bit more and repeat. Incremental learning with a solid base. It's fun to hate on academia but this is how experts with deep knowledge of a domain get to where they are.

[fxtentacle]

Sadly, you are 100% correct. I see the same problems over and over in newly published AI research papers.

That said, playing for 1-2 weeks might be a good start towards getting motivated for learning the difficult and dry theory needed to excel in this field.