Supervised Learning I : Regressors, Classifiers and Trees

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Supervised learning is the most common type of machine learning, solving prediction and classification problems. These are the most popular algorithms because they can solve the most kinds of problems and are the easiest to interpret. The methods in this unit form the foundation for more complex and layered supervised learning methods later on. You'll learn how and when to implement algorithms such as Linear and Logistic Regression, KNN, and Decision Trees. You'll learn about evaluation metrics such as Precision, Recall, Accuracy, and F1. By the end of this unit, you'll be able to decide when to use each method to solve problems.