images and so the key idea behind these on parametric methods is to learn a metric space that leads to effective comparisons learn a more semantic metric space that leads to effective predictions on the test data points and then we learn how to compare these images to make effective predictions and so the first very simple approach for doing this is to train a Siamese Network to predict whether or not two images are the same so we can train a neural network that takes in two images and is trained to output whether or not they're