K-Means Clustering Algorithm | Geometric Intuition | Clustering | 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:   / campusx-official   CampusX on Instagram for daily tips:   / campusx.official   My LinkedIn:   / nitish-singh-03412789   Discord:   / discord   E-mail us at [email protected] ⌚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)

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