Welcome to the K-Means
In this beginner-friendly session, we’ll explore the fundamentals of K-Means Clustering with an easy and practical approach. You’ll learn:
What is K-Means and how it works
Real-life examples of clustering
How to choose the number of clusters (K)
The concept of centroids and distance
Step-by-step implementation using Python and Scikit-learn
