RAI Crash Course: Clustering, K-Means, Hierarchical & DBSCAN | Module 2, Ch 2

Unsupervised learning: finding groups without labels. Why distance is everything (Euclidean vs Manhattan), K-means animated step by step and how to choose K (elbow and silhouette), hierarchical clustering, linkage and the dendrogram, DBSCAN for clusters of any shape plus outliers, and how to tell the three apart. ⏱ Chapters 00:00 Clustering: finding groups without labels 00:43 What is clustering for? 02:01 Animation: K-means clustering 03:21 Choosing k: the elbow 04:21 K-means: strengths and limits 05:04 Animation: Hierarchical clustering 06:08 Animation: DBSCAN 08:01 Example: DBSCAN on a number line 08:50 Which clustering method? 10:21 Recap 📚 Full course: see the "RAI Crash Course" playlist on this channel ▶ Next: Linear & Logistic Regression Explained | Module 2, Ch 3 ⚠ Unofficial: this is an independent study guide. It is not affiliated with, endorsed by or sponsored by GARP. "RAI" refers to the Risk and AI certificate only to describe what the material helps you study. All explanations, examples and questions are original and written in our own words; always study from the official curriculum. 🤖 AI disclosure: the narration is an AI-generated (synthetic) voice, and the visuals are generated programmatically. Scripts are human-reviewed. No real exam questions are used or disclosed. #RAI #RiskAndAI #MachineLearning #AIExplained