Determine the right Number of Clusters | WSS | Elbow Method | Silhouette Score | Data Science

In this video, we introduce two powerful methods: Within-Cluster Sum of Squares (WSS) and the Silhouette Score.

🔍 Understand the Theory:
We begin by understanding the concepts behind WSS and Silhouette Score. Learn how WSS measures compactness within clusters and why a lower value is preferred. Then we explore the Silhouette Score, an indicator of cluster separation and cohesion, helping you gauge the quality of your clustering solution.

🧠 Practical Implementation in Python:
Theory alone won't cut it – that's why we provide hands-on coding examples in Python! Witness step-by-step implementations using popular libraries like scikit-learn. You'll see firsthand how to compute WSS and Silhouette Score, allowing you to confidently choose the optimal number of clusters.

📈 Improve Your Clustering Results:
No more trial and error! By the end of this video, you'll possess the knowledge to fine-tune your clusters.

Happy Learning!