Most ML textbooks start you off with a simple model like a Perceptron. But if you have made it this far in the book, you are a rock star and deserve to be introduced to the big guns. Since they usually provide better results, you will run into these modes far more frequently than perceptrons anyway.

We will start with Random Forest models. Besides having a cool sounding name, they are flexible and tend to generalize well. They also have value in explaining the usefulness of input features using a method called variable importance.