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Machine Learning 1
Course - Master- The student can explain, motivate and distinguish the main areas of machine learning in general and on examples
- The student can explain the major statistical learning frameworks/principles together with their advantages and shortcomings
- The student knows the major linear and non-linear statistical models together with their advantages and disadvantages, can explain them and the made model assumptions, can reason about and inside them, and can manipulate them
- The student can set up learning objectives with the taught models, can train and evaluate them and can assess the quality of fit
- The student can implement all the above in Python and apply the learned principles and models to real world problems and data sets
Master’s Artificial Intelligence
Master’s Brain and Cognitive Sciences
Master’s Computational Science (joint degree)
Master’s Forensic Science
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