Understanding image datasets – loading, managing, and visualizing the Fashion-MNIST dataset

One of the fields that has grown considerably in DL in the last years has been computer vision (CV). Since the AlexNet revolution in 2012, CV has expanded from lab research to surpassing human performance in real-world datasets (known as “in the wild”).

In this recipe, we will explore the simplest CV task: image classification. Given a set of images, our task is to correctly classify that image among a given set of labels (classes).

One of the most classic image classification datasets is the MNIST (which stands for the Modified National Institute of Standards and Technology) database. Similarly sized, but more suited for current CV analysis, is the Fashion-MNIST dataset. This dataset is a multi-label image classification dataset, with a training set of 60k examples and a test set of 10k examples, with each example belonging to 1 of these 10 categories (starting with...