It can sometimes be too costly to train a neural network from scratch. In these cases, we can use what has been learnt by models which have been trained for a different task by applying transfer learning. In this session we'll cover both the theory and code behind how to do that to achieve results on a task in a fraction of the time it might take to build something from the ground up.