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Statistical machine learning and pattern recognition form a set of tools that are widely applicable for data analysis within a diverse set of problem domains such as data mining, search engines, digital image and signal analysis, natural language modeling, bioinformatics, physics, economics, biology, etc. The purpose of the course is to introduce students to probabilistic data modeling and the most common techniques from statistical machine learning and pattern recognition. This will be done in a case oriented manner (both in lectures and exercises) with a focus on examples of applications from the different problem domains. The students will obtain a working knowledge of probabilistic data modeling and statistical machine learning for pattern recognition. |