In this chapter, we will focus on supervised machine learning algorithms, which are one of the most important types of modern algorithms. The distinguishing characteristic of a supervised machine learning algorithm is the use of labeled data to train a model. In this book, supervised machine learning algorithms are divided into two chapters. In this chapter, we will present all the traditional supervised machine learning algorithms, excluding neural networks. The next chapter is all about implementing supervised machine learning algorithms using neural networks. The truth is that with so much ongoing development in this field, neural networks are a comprehensive topic that deserves a separate chapter in this book. 

So, this chapter is the first of two parts about supervised machine learning algorithms. First, we will introduce the fundamental concepts of supervised machine learning. Next, we will present two types of supervised machine models—classifiers and regressors. In order to demonstrate the abilities of classifiers, we will first present a real-world problem as a challenge. Then, we will present six different classification algorithms that are used to solve the problem. Then, we will focus on regression algorithms, first by presenting a similar problem to be solved for the regressors. Next, we will present three regression algorithms and use them to solve the problem. Finally, we will compare the results to help us summarize the concepts presented in this chapter.

The overall objective of this chapter is for you to understand the different types of supervised machine learning techniques and know what the best supervised machine learning techniques are for certain classes of problems. 

The following concepts are discussed in this chapter:

• Understanding supervised machine learning
• Understanding classification algorithms
• The methods for evaluating the performance of classifiers
• Understanding regression algorithms
• The methods for evaluating the performance of regression algorithms

Let's start by looking at the basic concepts behind supervised machine learning.