K-means clustering, originating from signal processing, is a technique in vector quantization. Its objective is to divide a set of n observations into k clusters, with each observation assigned to the cluster whose mean (cluster center or centroid) is closest, thereby acting as a representative of that cluster. I love working on recommendation engines. Whenever … Continue reading The Ultimate Guide to K-Means Clustering: Definition, Methods and Applications