Machine learning has become widely popular in fields like computer vision, natural language processing, and speech recognition, often performing tasks better than humans. A fundamental building block of many of these algorithms is a neural network known as a multilayer perceptron. In this tutorial we will discuss how to construct these networks and how to train them using back propagation and gradient descent via an interactive demo in Python. The material presented should be accessible to anyone with an understanding of matrix multiplication and chain rule.