## Overview

We give a short introduction to neural networks and the backpropagation algorithm for training neural networks. Our overview is brief because we assume familiarity with partial derivatives, the chain rule, and matrix multiplication.

We also hope this post will be a quick reference for those already familiar with the notation used by Andrew Ng in his course on “Neural Networks and Deep Learning”, the first in the deeplearning.ai series on Coursera. That course provides but doesn’t derive the vectorized form of the backpropagation equations, so we hope to fill in that small gap while using the same notation.