13. Exercise PCA

In this exercise, we'll use our new skills to build unsupervised learning models, focusing on Principal Component Analysis (PCA). We'll apply PCA to reduce the dimensionality of our data, identifying the most important features while retaining as much variance as possible. This technique will help us simplify complex datasets and improve model performance, especially for exploratory analysis and visualization.