• Course code:63566
  • Credits:6
  • Semester: summer
  • Contents

Linear models. Linear regression. Linear discriminant analysis. Logistic regression. Gradient descent. Stochastic gradient descent.

The machine learning approach. Cost functions. Empirical risk minimization. Maximum likelihood estimation. Model evaluation. Cross-validation.

Feature selection. Search-based feature selection. Regularization.

Tree-based models. Decision trees. Random forest. Bagging. Gradient tree boosting.

Clustering. k-means. Expectation Maximization.

Non-linear regression. Basis functions. Splines. Support vector machines. Kernel trick.

Neural networks. Perceptron. Activation functions. Backpropagation.
  • Study programmes
  • Distribution of hours per semester
45
hours
lectures
30
hours
laboratory work
  • Professor
Instructor
Room:R3.20 - Laboratorij LB
Instructor
Room:R3.17 - Kabinet
Teaching Assistant
Room:R3.22 - Laboratorij LB