K-Means Clustering Algorithm | Geometric Intuition and Unsupervised Learning

In this video, we are going to learn about the K-means clustering algorithm. k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster.

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⌚Time Stamps⌚

00:00 - Intro
01:10 - Understanding K-Means Clustering through a problem statement
04:34 - Deciding Number of Clusters
04:56 - Initializing Centroids
05:41 - Assigning a Cluster
09:20 - Should we finish the clustering process
14:28 - K-Means Clustering (Elbow Method)