In this 24-hour hackathon, we tackled the challenge of clustering a dataset containing tuples and their features. Our objective was to implement a solution that accurately identifies the ideal number of clusters for the data. We employed various clustering algorithms, primarily focusing on K-Means, to segment the data effectively. The final output was formatted as required: id 1300 class 1, id 1301 class 1, so on.