Find patterns in data by manually grouping similar points, then compare with K-means!
This game demonstrates the power of both human intuition and machine learning in pattern recognition. Humans excel at visual pattern recognition and can often identify meaningful clusters quickly. The K-means algorithm systematically groups data by minimizing the distance between points and cluster centers. By comparing your manual clustering with K-means, you can see how human insight and algorithmic precision complement each other in data analysis!