Unsupervised learning with clustering algorithms to discover natural groupings in data. Comparison of K-Means, MiniBatch K-Means, and Gaussian Mixture Models.
- K-Means - Centroid-based clustering with iterative refinement
- MiniBatchKMeans - Scalable variant using mini-batches
- Gaussian Mixture Model (GMM) - Probabilistic clustering with soft assignments
- Silhouette Score - Measure of cluster separation quality
- Inertia - Within-cluster sum of squares
- Visual Analysis - Cluster plots and centroids
- Python 3.x
- scikit-learn - Clustering algorithms
- pandas - Data manipulation
- numpy - Numerical operations
- matplotlib - Visualization