April 2017
Beginner to intermediate
420 pages
9h 58m
English
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 ...
Read now
Unlock full access