Q$.$No $2$: In the context of the face recognition problem, how does the objective of Linear

Discriminant Analysis $($LDA$)$ differ from Principal Component Analysis $($PCA$)?$

Hint: LDA focuses on class separability and is supervised, whereas PCA is unsupervised

and concentrates on capturing overall data variance.