little it about derive versus actually Matic right so I think right so what can we take away from this we know that if you have a small training error that means that the risk itself is just you're really only in leveraging generalization error right so if your training error for example is zero you're just hopefully know somehow that the generalization error is small and sorry and zero training error we know does not imply overfitting even though that's another thing that we do tend to sometimes gets lost in the weeds like