An interactive machine learning experiment for classifying hand-drawn digits using a neural network trained on the MNIST handwritten digit dataset. Users can draw a digit on a canvas and have the trained model predict which number it represents. Since the classifier always produces one of the ten possible digit classes, even an empty or unclear canvas will still result in a prediction. The project explores the process of bringing a machine learning model into an interactive browser-based application.