Supervised Machine Learning with Python

Loss functions

First, we'll cover loss functions, and then, prior to diving into hill climbing and descent, we'll take a quick math refresher.

There's going to be some math in this lesson, and while we try to shy away from the purely theoretical concepts, this is something that we simply have to get through in order to understand the guts of most of these algorithms. There will be a brief applied section at the end. Don't panic if you can't remember some of the calculus; just simply try to grasp what is happening behind the black box.

So, as mentioned before, a machine learning algorithm has to measure how close it is to some objective. We define this as a cost function, or a loss function. Sometimes, we hear it referred to as an objective ...