4. Training Classification Models

Overview

In this chapter, you will learn about algorithms such as Support Vector Machines, Random Forests, and k-Nearest Neighbors classifiers. While training and comparing a variety of models, you'll learn about the concept of overfitting with the help of decision boundary charts. By the end of this chapter, you will be able to use scikit-learn to apply these algorithms in order to train models for a real-world classification problem.