Grundlagen der Mathematik und Statistik

Every model ultimately reduces to operations on vectors and matrices, and every act of “learning” is ultimately the reduction of a loss along a gradient. This domain does not aim for a mathematician’s completeness; it selects only what is needed to understand AI: linear algebra gives data and weights their shape, probability gives uncertainty its measure, and calculus gives improvement its direction.