Mathematical fundamentals of machine learning

Repository

Repository is empty

Poll

No polls currently selected on this page!

Mathematical fundamentals of machine learning

Code: 268261
ECTS: 5.0
Lecturers in charge: prof. dr. sc. Nikola Sandrić
Take exam: Studomat
Load:

1. komponenta

Lecture typeTotal
Lectures 45
* Load is given in academic hour (1 academic hour = 45 minutes)
Description:
Literature:
  1. Understanding machine learning, S. Ben-David, S. Shalew-Shwartz, Cambridge University Press, Cambridge, 2014.
  2. Statistical learning theory, V. N. Vapnik, John Wiley & Sons, Inc., New York, 1998.
  3. Foundations of Machine Learning, M. Mohri, A. Rostamizadeh, A. Tlwalkar, The MIT Press, Cambridge MA, 2018.
  4. The elements of statistical learning, T. Hastie, R. Tibshirani, J. Friedman, Springe-Verlagr, New York, 2009.
  5. The nature of statistical learning theory, V. N. Vapnik, Springer-Verlag, New York, 2000.
  6. Neural Network Learning: Theoretical Foundations, M. Anthony, P. L. Bartlett, Cambridge University Press, Cambridge, 1999.
1. semester
Izborni predmet 1, 2 - Regular study - Computer Science and Mathematics

2. semester Not active
Izborni predmet 1, 2 - Regular study - Computer Science and Mathematics

3. semester
Izborni predmet 3, 4, 5, 6 - Regular study - Computer Science and Mathematics

4. semester Not active
Izborni predmet 3, 4, 5, 6 - Regular study - Computer Science and Mathematics
Consultations schedule:
  • prof. dr. sc. Nikola Sandrić:

    Wednesdays from 12:00 to 14:00.

    Location: 303