The course is the prerequisite for the more advanced courses in ML option at IEU Departments of Computer Engineering and Software Engineering. The course's goal is to build mathematical and conceptual foundation for students advancing further in that option. The course covers key background topics from machine learning including signals and sampling, digital filters and Fourier transform, numerical optimization, and the fundamentals of the theory of statistical learning comprising the theoretical foundation of machine learning methods.
Matrices and vectors
Numerical optimization at very large scales
Intro to statistical learning theory
Statistical decision theory and function estimation