Ask HN: Does it matter which deep learning framework I use?
On one hand I fully understand there are differences in language and specific features available depending on framework out there.
On the other hand, if a framework "correctly" implements the underlying statistical theory/principals of deep learning, shouldn't I get the same results regardless of whichever framework I use?
If not, how would I know which framework produces "more correct" interpretations of the underlying data?
On the other hand, if a framework "correctly" implements the underlying statistical theory/principals of deep learning, shouldn't I get the same results regardless of whichever framework I use?
If not, how would I know which framework produces "more correct" interpretations of the underlying data?