K-means clustering is used in all kinds of situations and it's crazy simple. The R code is on the StatQuest GitHub: For a complete index of all the StatQuest videos, check out: If you'd like to support StatQuest, please consider... Patreon: ...or... YouTube Membership: ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... ...or just donating to StatQuest! Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: 0:00 Awesome song and introduction 0:33 The K-means clustering algorithm 4:26 How to pick a value for K (How to use an elbow plot) 6:06 K-means vs Hierarchical Clustering 6:28 K-means clustering and 2-Dimensional data 7:08 K-means clustering and heatmaps Corrections: 5:58 I should have put "Reduction in Variation" instead of "Reduction is Variation" 7:25 Point (7,-8) should be in the lower right-hand quadrant. 8:25 The "nclust =25" in the arguments is actually "nstart=25" #statquest #ML