One Shot Learning Using Keras

For a neural network to learn features from images in order to classify them we need data, lots of data. It is difficult for a model to learn from very few samples per class. MNIST dataset has nearly 60000 training images for numbers 0–9 (10 classes). We will implement One shot learning to build a model which will correctly make predictions given only a single example of each new class. As humans, when we are presented with new object, we quickly pickup patterns, shape and other features.