Deep learning is a branch of machine learning where artificial neural networks -- algorithms inspired by the way neurons work in the brain -- find patterns in raw data by combining multiple layers of artificial neurons. As the layers increase, so does the neural network's ability to learn increasingly abstract concepts. For example, neural networks can learn how to recognize human faces. The first layer of neurons takes pixels from example images, the next layers learn the concept of how pixels form an edge, then that layer passes that knowledge to other layers, combining that knowledge of edges to learn the concept of a face. This process of layering knowledge continues until BAM! -- the neural network algorithms recognize specific features, and ultimately specific faces.