CE395 Special Topics in Machine Learning

Instructor:Assoc.Prof.Dr. Yuriy Mishchenko
Link to the courses's webpage at IEU:CE395 webpage at IEU

Course objectives

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.

Course program

  1. Signals
  2. Filters
  3. Fourier Transform
  4. Matrices and vectors
  5. Numerical optimization
  6. Numerical optimization at very large scales
  7. Probability
  8. Intro to statistical learning theory
  9. Statistical decision theory and function estimation
  10. Model assesment and selection
  11. Cross-validation and related topics

Lecture notes

  1. Lecture 1 - Intro and Signals
  2. Lecture 2 - Filters and Filtering
  3. Lecture 3 - Fourier Transform
  4. Lecture 4 - Matrices and Vectors
  5. Lecture 5 - Optimization I

Click here to go to homepage.