The "learning theory" part of ML has always been rigorous in their arguments. Same for top tier conferences and journals. ML is really applied math that stands

The "learning theory" part of ML has always been rigorous in their arguments. Same for top tier conferences and journals. ML is really applied math that stands on the shoulders of functional analysis, optimization, probability theory and algorithms. The key way in which the flavor of ML is different from the flavor of statistics is that ML theorems are about guarantees on prediction quality whereas in statistics guarantees are on recovering parameters (which could be infinite dimensional). This is a broad generalization so there will be edge cases. BTW when is the launch. All the best.