Building an Image Colorization Neural Network -- Part 1: Generative Models and Autoencoders

First of all, let's make sure we have a good understanding of when a model is labeled as generative. Practically, there are two different types of models: the generative and the discriminative. A discriminative model is deemed with the aim of successfully discriminating between different kinds of data samples. The most common discriminative scenario is binary classification, where each data sample has a target value that can belong to one of two distinct classes. Classifying if the image contains a cat or a dog is a basic example.