GitHub - RiteshopShrivastava/Hierarchical_Clustering: Unsupervised-ML---K-Means-Clustering-Non-Hierarchical-Clustering-Univ. Use Elbow Graph to find optimum number of clusters (K value) from K values range. The K-means algorithm aims to choose centroids that minimise the inertia, or within-cluster sum-of-squares criterion WCSS. Plot K values range vs WCSS to get Elbow graph for choosing K (no. of clusters)

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Unsupervised-ML---K-Means-Clustering-Non-Hierarchical-Clustering-Univ. Use Elbow Graph to find optimum number of clusters (K value) from K values range. The K-means algorithm aims to choose centroids that minimise the inertia, or within-cluster sum-of-squares criterion WCSS. Plot K values range vs WCSS to get Elbow graph for choosing K (no. of c…

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Name		Name	Last commit message	Last commit date
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Assignment_Q1_Clustering.ipynb		Assignment_Q1_Clustering.ipynb
Hierarchical_clustering.ipynb		Hierarchical_clustering.ipynb
Universities_Clustering.csv		Universities_Clustering.csv