What are siamese networks?

A siamese network is a special type of neural network and it is one of the simplest and most popularly used one-shot learning algorithms. As we have learned in the previous chapter, one-shot learning is a technique where we learn from only one training example per class. So, a siamese network is predominantly used in applications where we don't have many data points in each class. For instance, let's say we want to build a face recognition model for our organization and about 500 people are working in our organization. If we want to build our face recognition model using a Convolutional Neural Network (CNN) from scratch, then we need many images of all of these 500 people for training the network and attaining good accuracy. But apparently, we will not have many images for all of these 500 people and so it is not feasible to build a model using a CNN or any deep learning algorithm, unless we have sufficient data points. So, in these kinds of scenarios, we can resort...