This program visualizes the learning process of a perceptron. For simplicity, we consider the perceptron to learn the identity function. We give a 2 dimensional input <x, y> and classify each point as being below the line or above the line (binary classification). We update the weights of the perceptron whenever misclassification occurs. Over several examples, the perceptron learns the identity mapping.
The code is publicly available on github.