As we discussed, the more traditional predictive models such as linear regression don't scale well, because they always need to calculate the whole solution using all the available points or data. These types of techniques or models have no ability to remember, learn, and improve, and they are generally classified as supervised models. This has led to the evolution of more advanced learning models known as reinforcement learning (RL) techniques for solving ML problems. In fact, deep learning and deep reinforcement learning techniques now outclass statistical methods in performance and accuracy by several orders of magnitude. However, that wasn't always the case, and statistical methods are also improving just as dramatically everyday. It really is an exciting time to be getting into Machine Learning.
The following diagram demonstrates the reinforcement learning process:
Reinforcement learning process
In the diagram, you can see that there is an Agent (assume computer) and the...