Das Modul bietet eine Einführung in grundlegende Methoden des Datamining, der explorativen Datenanalyse und dafür einschlägigen Verfahren maschinellen Lernens und der Visualisierung von Daten.
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.
Nützlich: Neuronale Netze und Lernen, Bildverarbeitung, Vertiefung Mathematik
Querbezüge zu: Information Visualization, Sequenzanalyse, Mustererkennung bzw. Musterklassifikation
Statistics: Numerical Recipes in C (selected chapters including t-test, chi2-test, KS-test, linear correlation, cramer's V, etc.)
Frequency | Weekday | Time | Format / Place | Period | |
---|---|---|---|---|---|
weekly | Mo | - | - | 08.10.2018-01.02.2019 | |
weekly | Mi | 12-14 | CITEC | 08.10.2018-01.02.2019
not on: 11/28/18 / 12/26/18 / 1/2/19 / 1/23/19 / 1/30/19 |
23.01.19 und am 30.01.19 im H1 |
one-time | Mi | 12-14 | H14 | 28.11.2018 | |
weekly | Mi | 12:00-14:00 | H1 | 23.-30.01.2019 | 23.01.19 und am 30.01.19 im H1 |
Module | Course | Requirements | |
---|---|---|---|
39-Inf-DM Grundlagen Datamining | Grundlagen Datamining | Ungraded examination
Graded examination |
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.
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