Lectures related to Theory of Bagging

Explores Hartree-Fock equations, variational principles, excited states, and quantum physics concepts.

Explores Support Vector Machines theory, parameters, uniqueness, and applications in machine learning.

Explores implicit functions through examples and applications, covering differentiation and functions defined implicitly.

Discusses curved space-time, arguments against scalar gravity, and relativistic effects of motion.

Introduces mechanics, differential and vector calculus, and historical perspectives from Aristotle to Newton.

Emphasizes the importance of theory in academic research and its impact on shaping research outcomes.

Explores examples of categories, morphisms, groupoids, and functors in category theory.