- Covers k-means clustering, elbow method, and cluster selection.
- Introduces Principal Component Analysis (PCA) for dimensionality reduction.
- Hands-on exercises with image data and customer segmentation.
- Teaches visualization of high-dimensional datasets.
- Applies unsupervised methods to real-world scenarios.
