This project implements a Convolutional Neural Network (CNN) for recognizing handwritten digits from the MNIST dataset, built entirely using pure CSS. The model has 1,996 parameters and an accuracy of 91.73% (though it often feels like 20%). The input canvas for drawing digits is also created solely with CSS.
