representation you learn in the different layers of the network so this is supposed to be this thing right here what you'll do is you'll simply fine-tune that means you on top of this representation you add a classification head that has two outputs cat or dog and you train this entire network on your small data set that we discussed before so you train the entire network all of the parameters this is called fine tuning in contrast to that what you can do is you can simply and this is the easy way you can simply add this