The MNIST dataset is a set of 28x28 drawn images of numbers between 0-9. A common exercise is to use convolutional neural networks (CNNs) to create a model capable of identifying the numbers pictured.
Using a model trained for 20 epochs on 60000 training images, I created a model that can identify numbers drawn with >99.7% accuracy.