"Quickly bring me a beaker of wine, so that I may wet my mind and say something clever."
- Aristophanes, Athenian Playwright
In the earlier chapters, we focused on trying to learn the best algorithm in order to solve an outcome or response, for example, a breast cancer diagnosis or level of Prostate Specific Antigen. In all these cases, we had y, and that y is a function of x, or y = f(x). In our data, we had the actual y values and we could train the x accordingly. This is referred to as supervised learning. However, there are many situations where we try to learn something from our data and either we do not have the y or we actually choose to ...
