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. ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚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)