First steps with the MNIST dataset

MNIST is the dataset that is always discussed first when making first steps in the world of neural networks and image classification. MNIST is a database of grayscale images of handwritten digits. It has a training set of 60,000 examples, and a test set of 10,000 examples. 

In the following activities, we will be predicting the value written on an image by building our first neural network.

Getting the data

In order to get to the process of building the neural networks quickly, we will be using the MNIST dataset, which is available in the MLDatasets.jl package. The package provides easy and user-friendly access to some of the datasets publicly available out there on the internet. If you don't have the MLDatasets package installed, you can do so by running the Pkg.add command:

Pkg.add("MLDatasets")

The moment the MLDatasets package is loaded, the MNIST dataset can be easily downloaded and made available with the traindata and testdata functions from the MNIST...