The MNIST handwritten digit dataset is one of the most famous image recognition datasets. It consists of square images, 8 x 8 pixels, each containing a single handwritten digit. Thus, the dataset features are an 8 by 8 matrix, containing each pixel's color in grayscale. The target consists of 10 classes, one for each digit from 0 to 9. This is a classification dataset. The following figure is a sample from the handwritten digit dataset: