Implement PCA from scratch: (1) Standardize data, (2) Compute covariance matrix, (3) Find eigenvectors/eigenvalues, (4) Sort by eigenvalue descending, (5) Select top k components, (6) Project data. Apply to Iris dataset, reduce 4D→2D, plot. Show explained variance ratio for each component.
