HYBRID course "Machine Learning A" @ U of Copenhagen in Sep-Oct

[Yevgeny Seldin]

The Department of Computer Science at the University of Copenhagen offers a HYBRID course “Machine Learning A”. It is a 7.5 ECTS master-level course introducing basic theory and algorithms of machine learning. The course will run in Sep-Oct 2024 in a hybrid format and will support fully remote participation. The lectures will be streamed via Zoom and recorded, and the students will have a choice of physical and online exercise classes. The course welcomes students from other universities and people from industry.

The course assumes solid knowledge of linear algebra, calculus, and probability theory, and basic Python programming skills. It also assumes basic knowledge of LaTeX for typing home assignments.

Topics to be covered:

• The meaning of generalization beyond a finite sample under the independent identically distributed (i.i.d.) assumption

• K-Nearest Neighbors algorithm

• Perceptron

• Linear Regression

• Logistic Regression

• Regularization and working in the feature space

• Markov's, Chebyshev's, and Hoeffding's inequalities

• Generalization bounds for finite sets of prediction rules

• Generalization bounds based on training/validation/test sets

• Lower bound for generalization (the impossibility of generalization in the worst case)

• Occam's Razor bound for countable sets of prediction rules and its application to Decision Trees

• Random Forests

• Neural Networks

• Principal Component Analysis (PCA)

• Clustering: k-means & k-means++ algorithms

• Non-linear Dimensionality Reduction via Stochastic Neighbor Embedding

Further information about the course: https://kurser.ku.dk/course/ndak22000u/ and https://sites.google.com/diku.edu/machine-learning-courses/mla. 

Registration links:

• Credit Students (for students enrolled at another Danish educational institute)
• EU Students (for students enrolled at a non-Danish EU educational institute)
  
• Non-EU Students (for students enrolled at an educational institute outside the EU)
• Continuing Education Applicants (for individuals not enrolled at an educational institution, e.g., people from industry)
  

Contact person: Sadegh Talebi <mstale...@gmail.com>