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Machine learning and probabilistic graphical models

2017 – 2018, VI semester

Course information

Students will master the theoretical material provided by the course, be able to apply the knowledge gained to solving theoretical and applied problems. The material covered by the course includes: theory of probabilistic graphical models, neural networks, applied problems in data analysis.


Course program


Lecturers

Associate Professor