Explores Singular Value Decomposition and Principal Component Analysis for dimensionality reduction, with applications in visualization and efficiency.
Explores natural selection, genetic variation, and evolutionary changes within populations, using examples like sickle cell anemia and flu virus evolution.
Covers Principal Component Analysis for dimensionality reduction, exploring its applications, limitations, and importance of choosing the right components.