Three types of learning algorithms
The scenarios we have seen in the previous section were not selected at random. They match the standard categorization of ML algorithms that provides for three fundamental types: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. When we want to apply the ML way, we need to select one of these three routes: our choice will depend on the nature of the problem we need to solve. Let's now go through each group to understand what they are made of and what types of tasks they fulfill.
Supervised learning
In supervised learning, your objective is to predict something "unknown" by learning from some "known" pieces of information. The easiest way to make sense of the supervised learning approach is to think about how it differs from traditional programming. In Figure 4.2, you will find on the left a very familiar setup. In plain computer programming, we need some input data, a program, and a computer to...