**MISSION 40**

# K-means Clustering

Learn how to use K-means clustering to group together similar NBA players.

#### Objectives

#### Mission Outline

1. Clustering NBA Players

2. Point Guards

3. Points Per Game

4. Assist Turnover Ratio

5. Visualizing the Point Guards

6. Clustering players

7. The Algorithm

8. Visualize Centroids

9. Setup (continued)

10. Step 1 (Euclidean Distance)

11. Step 1 (Continued)

12. Visualizing Clusters

13. Step 2

14. Repeat Step 1

15. Repeat Step 2 and Step 1

16. Challenges of K-Means

17. Conclusion

18. Takeaways