Introduction to Machine Learning

What it is about

You receive an introduction to concepts, methods and theoretical foundations of common machine learning algorithms. At the end you know standard procedures for regression, classification, clustering and model selection, you can apply them, validate them, interpret them and assess their limits.

What you will be able to do

• Know standard machine learning algorithms
• Select and apply appropriate algorithms
• Tune, select and validate models
• Interpret results
• Critically assess the strengths and weaknesses of methods

What the module consists of

• LectureConveying the fundamentals and algorithms, partly blackboard, partly with code examples
• Exercises / Problemsevery two weeks, problems on theory and programming for deepening and applying
• Discussion session / Tutorialinteractive forum for questions on problems and deepening individual topics

Teaching method

• Blackboard lectureExplanation of theoretical foundations and derivations
• Code examples and demonstrationsIllustration of the algorithms on simple datasets
• Short group exercises during the lectureactive engagement with concrete questions
• Regular assignments with solutionsmathematical and practical deepening through derivations and application to real data