MNIST is a classic image classification exercise - a dataset of 60,000 training images and 10,000 testing images where each image is a handwritten numeral as a 28x28 pixel grayscale image.
The challenge is to build a computer vision model that can tell which numeral each handwritten digit represents.
The challenge is to build a computer vision model that can tell which numeral each handwritten digit represents.
https://en.wikipedia.org/wiki/MNIST_database
78% accuracy on a solution is pretty bad, but achieving it just using GZIP is a very neat hack.