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Course objectivesThere will be several lectures presented by the lecturers (approximately 6) in which core techniques from the field of AutoML are presented. The other lecture slots are filled with…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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Course objectivesAfter successful completion of this course, students have an understanding, both at the conceptual and the technical level, of natural language processing (NLP) methods for the…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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Course objectivesAt the end of the course, students:Have a clear understanding of information theory (both algorithmic and Shannon's). Have a clear understanding of advanced algorithms for data…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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Course objectivesGetting an overview over and a fundamental understanding of the algorithms that drive Game AI and thus also AI progress, e.g. Monte Carlo Tree Search, Deep (Reinforcement) Learning,…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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Course objectivesAfter completing the reinforcement learning course, the students should be able to:Understand the key features and components of deep reinforcement learning; Knowledge of theoretical…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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Course objectives At the end of the course students are expected to understand the fundamentals of software testing, the basic test types and activities, the principles behind testing coverage…
Faculty and Departments
Science Language
English Creative Commons
All Rights Reserved
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