A Deep Learning Tutorial: From Perceptrons to Deep Networks

This setting is incredibly general: your data could be symptoms and your labels illnesses; or your data could be images of handwritten characters and your labels the actual characters they represent. One of the earliest supervised training algorithms is that of the perceptron, a basic neural network building block. Say we have n points in the plane, labeled '0' and '1'. We're given a new point and we want to guess its label (this is akin to the "Dog" and "Not dog" scenario above).