ClusterAlytics: An Interactive Browser-Based Learning Tool for K-means and Hierarchical Clustering

ClusterAlytics is a free, self-contained, browser-based tool for learning unsupervised cluster analysis, authored by Dr Vani Lakshmi R. It teaches the two most widely taught method families, K-means and hierarchical clustering, through animation and direct manipulation rather than static text. The entire tool is a single HTML file that runs in any modern browser with no installation, server, or data upload, so it works offline and on modest hardware and keeps all learner input on the device. Learners explore an animated K-means playground, step-by-step agglomerative and divisive hierarchical clustering with a live dendrogram, an interactive distance laboratory, an elbow and silhouette explorer, a clickable Python and R syntax explorer, a conversational Sneak Peek styled as a student and consultant exchange, and a graded quiz. The interface is colour-blind friendly throughout using the Okabe-Ito palette, with eight colour themes and light and dark display modes. Released under CC BY-NC-ND 4.0.