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Chapter 10: Unsupervised Learning

Learning Objectives

•Differentiate between supervised and unsupervised learning techniques.

•Examine the basic principles of cluster analysis.

•Apply the k-means clustering algorithm to a dataset.

•Assess the quality and reliability of the generated clusters.

Google Drive For Chapter 10 Review Questions

Google Drive For Chapter 10 "Try It Yourself" Python Notebooks

Google Drive For Chapter 10 Data Sets

Section 10.1: What Is Unsupervised Learning?

Try It Yourself: Detect Anomalies

Try It Yourself: Recognize Unsupervised Learning

Section 10.2: Getting to Know Cluster Analysis

Try It Yourself: Calculate Similarity Using Distance

Section 10.3: Introduction to k-Means Clustering

Try It Yourself: Choose Variables for Clustering

Section 10.4: Introduction to Hierarchical Clustering

Try It Yourself: Compare Cluster Analysis Results

Section 10.5: Assessing the Quality of Clusters

Try It Yourself: Examine the Elbow of a Cluster Analysis

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