The best beginner’s guide on K-Means Clustering.

Everything you need to know about K-means clustering

Picture by Radu Marcusu on Unsplash

The Concept

The Algorithm

1. Initialize K & Centroids

2. Assigning Clusters to datapoints

3. Updating Centroids

4. Stopping Criterion

Evaluating the cluster quality

How many clusters?

Conclusion

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