K-means clustering is used in all kinds of situations and it's crazy simple. The R code is on the StatQuest GitHub: https://github.com/StatQuest/k_means_clustering_demo/blob/master/k_means_clustering_demo.R For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: null ...a cool StatQuest t-shirt or sweatshirt: null ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 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