This module offers an introduction into basic methods of data mining, exploratory data analysis and relevant machine learning methods and visualization techniques for high-dimensional data.
The exercises will allow participants to understand selected methods more deeply by implementing them in python (using jupyter notebooks) or applying them to given data sets.
Nützlich: Neuronale Netze und Lernen, Bildverarbeitung, Vertiefung Mathematik
Querbezüge zu: Information Visualization, Sequenzanalyse, Mustererkennung bzw. Musterklassifikation
Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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39-Inf-DM Grundlagen Datamining | Grundlagen Datamining | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.