1. KMEANS CLUSTERING

2. KMeans Clustering

3. KMeans Clustering
RANDOM INITITALIZE TRAP

4. KMeans Clustering

5. KMeans Clustering
STEP BY STEP
STEP 1
K = 3 | Number of Clusters

6. KMeans Clustering
STEP 2
K = 3 | Assign the Centroids

7. KMeans Clustering
STEP 3
K = 3 | Assign each data the Closest centroid

8. KMeans Clustering STEP 4
K = 3 | Compute and Place the new Centroid of each cluster

9. KMeans Clustering STEP 5
K = 3 | Reassign each datapoint to closest centroid. If any reassignment took place, GO TO Step 4, else FIN

10. KMeans Clustering WITHIN CLUSTER SUM of SQUARES

11. KMeans Clustering
CLUSTER FORMATIONS

12. KMeans Clustering
ELBOW CURVE