Here we use MNIST (Modified National Institute of Standards and Technology), which consists of images of handwritten numbers and their labels. Since its release in 1999, this classic dataset is used for benchmarking classification algorithms.
The data files train.csv and test.csv consist of hand-drawn digits, from 0 through 9 in the form of gray-scale images. A digital image is a mathematical function of the form f(x,y)=pixel value. The images are two dimensional.
We can perform any mathematical function on the image. By computing the gradient on the image, we can measure how fast pixel values are changing and the direction in which they are changing. For image recognition, we convert the image into grayscale ...
