[T-A]

ML runs hundreds of thousands of experiments, each on a slightly different model, and takes the one with the best results.

[ponker]

That's not necessarily p-hacking. It becomes p-hacking when the model is hyperoptimized to the test set and thus fails when applied to new data from outside the test set.