it which either can be like linear you can put a linear classifier on top of the H or you can fine-tune the entire architecture to solve some other task the idea is if you have a large data set you may use this dataset to train these good representations of these images and then you can transfer learn transfer this to a task where you might be not have as much data and because you don't have as much data it's not enough to completely train an architecture like this but it is enough to take an architecture that's been trained with