Supervised Learning: Regression and Classification

Supervised learning is a type of machine learning algorithm that uses a labeled dataset to train the model. The machine learning model in this type of learning will work with both input features and the target label as direct examples for the model to learn from and generalize to any unseen data. The method is helpful in many situations where we already have data that represents the problem we want to solve, and we want to automate the decision-making process. There are two most common techniques within supervised learning: regression and classification. In this chapter, we will learn to understand, implement, and evaluate both methods.

In many real-world data science applications, supervised learning is one of the most commonly used methods. Examples include predicting insurance claims amounts by insurer (regression) or classifying spam emails (classification). As a data professional, it has become essential to master supervised...