The Math Behind Decision Trees: An Exploration of Decision Trees

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Decision trees are an effective supervised learning technique for predicting the class or value of a target variable. Unlike other supervised learning methods, they're well-suited to classification and regression tasks. Use this course to learn how to work with decision trees and classification, distinguishing between rule-based and ML-based approaches. As you progress through the course, investigate how to work with entropy, Gini impurity, and information gain. Practice implementing both rule-based and ML-based decision trees and leveraging powerful Python visualization libraries to construct intuitive graphical representations of decision trees. Upon completion, you'll be able to create, use, and share rule-based and ML-based decision trees.