The difference between statistical modelling and machine learning is that the first aims to make models that have a "right" accuracy on a given data-model compl

The difference between statistical modelling and machine learning is that the first aims to make models that have a "right" accuracy on a given data-model complexity balance while the second those that work well on "unseen data". Thus if you use AIC to find best subset of variables for a linear model its statistical modelling, but if you use cross-validation for the same purpose it is machine learning (while, to be honest, both ideas are wrong).