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Special lecture

Introduction to Machine Learning
Dr. Joschka Bödecker, Dr. Frank Hutter, Dr. Michael Tangermann

  • Dates and Place
    • Tuesday, 12:30 - 14:00, Building 101, Room HS 00 036
    • Thursday, 12:30 - 14:00, Building 101, Room HS 00 036
  • Exercises
    • Exercise dates: 21.4. / 28.4. / 12.5. / 31.5. / 9.6. / 16.6. / 23.6. / 30.6. / 7.7. / 14.7.
  • Teaching Assistants
    • Raghu Rajan
    • Ilir Kola
  • Credits
    • 6 ECTS
    • HISinOne: Lecture 11LE13V-1103, Exercise 11LE13Ü-1103
  • Exam
    • registration via examination office, date and modalitites t.b.a.

Educational objectives

Understanding of the basic concepts of machine learning, ability to think on different levels of abstraction, knowledge of exemplary implementations of learning algorithms, ability to independently identify connections of the concepts presented.

Course Content

Characterization of supervised, unsupervised and reinforcement learning, linear methods for classification and regression, introduction to kernel methods, algorithm independent principles, neural networks, tree-based and committee techniques, statistical learning theory, and subspace decomposition methods.

Slides, Recordings, Exercises, Forum, Wiki

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Ressources