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Machine Learning (Lecture + Practice)

8.3072

Dozenten

Beschreibung

Prerequisites: None

Being a mainly academic topic about 20 years ago, Machine Learning has become a discipline of major impact on both science and engineering by today. This course introduces the basics of Machine Learning and Data Mining. Major topics are concept learning, decision trees, problems of data in high dimensional representations, clustering algorithms, linear and nonlinear dimension reduction, artificial neural networks (e.g. multilayer perceptrons, RBF networks, self-organizing maps), classification methods, reinforcement learning, modeling uncertainty and temporal probability models.

Weitere Angaben

Ort: 32/102: Mo. 12:00 - 14:00 (11x) Do. 10:00 - 12:00 (13x), 93/E06: Di. 14:00 - 16:00 (14x), 35/E23-E24: Donnerstag, 06.07.2017 10:00 - 12:00
Zeiten: Mo. 12:00 - 14:00 (wöchentlich) - Feedback sessions, Ort: 32/102, Di. 14:00 - 16:00 (wöchentlich), Ort: 93/E06, Do. 10:00 - 12:00 (wöchentlich), Ort: 32/102, Termine am Donnerstag, 06.07.2017 10:00 - 12:00, Ort: 35/E23-E24
Erster Termin: Montag, 03.04.2017 12:00 - 14:00, Ort: 32/102
Veranstaltungsart: Vorlesung und Seminar (Offizielle Lehrveranstaltungen)

Studienbereiche

  • Cognitive Science > Bachelor-Programm
  • Schnupper Uni > Cognitive Science
  • Informatik > Importmodule
  • Human Sciences (e.g. Cognitive Science, Psychology)
  • Cognitive Science