Normally when we train a machine learning system we provide our system with thousands of examples of each class that we want to recognise. For example if we're training a system to classify cats and dogs we may provide 10,000 images of each. However, in a number of cases it is not possible to collect all of these examples. Here we use few shot learning techniques to aid us in still being able to classify.