Introduces perspective definitions and image construction methods in descriptive geometry, emphasizing radial projection principles and image construction on planes.
Covers PCA and LDA for dimensionality reduction, explaining variance maximization, eigenvector problems, and the benefits of Kernel PCA for nonlinear data.