700.395 (19S) Data Mining and Neurocomputing
Überblick
- Lehrende/r
- LV-Titel englisch Data Mining and Neurocomputing
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 23 (25 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 07.05.2019
- eLearning zum Moodle-Kurs
- Seniorstudium Liberale Ja
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
Data Mining and Neurocomputing have different applications in text categorization, e.g., spam filtering, fraud detection, optical character recognition, machine vision, e.g., face detection, licenses plate recognition, advanceddriver assistance systems, natural-language processing, e.g., spoken language understanding, market segmentation, e.g., predict if a customer will get a credit, and bioinformatics, e.g., classify proteins or lipidomes according to their function.
The lecture will (a) explain the basic approaches of Data Mining and Neurocomputing models, (b) guide to transfer the acquired knowledge to solve classification problems for industry and research, and (c) show some use-cases and interesting applications from the state-of-the-art.
Lehrmethodik inkl. Einsatz von eLearning-Tools
Theory + practical examples (Matlab +Python)
Inhalt/e
- Data preprocessing
- Unsupervised Learning and Clustering
- Supervised Learning (SVM, Bayes, Decision Trees, CNN, etc)
- Reinforcement Learning
- Deep Learning
- Time series forecast
- Evaluation Metrics
Prüfungsinformationen
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Fach: Information and Communications Engineering: Supplements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Fach: Technical Complements (NC, ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Autonomous Systems and Robotics: Advanced (ASR)
(Wahlfach)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Fach: Autonomous Systems and Robotics: Advanced (ASR)
(Wahlfach)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Fach: Autonomous Systems and Robotics (WI)
(Wahlfach)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Fach: Autonomous Systems and Robotics (WI)
(Wahlfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Research Track (Methodischer Schwerpunkt)
(Pflichtfach)
-
4.2'-4.3' Theoretisch-Methodische Lehrveranstaltung I/II (
0.0h VO/VK/VS/KU/PS / 6.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
4.2'-4.3' Theoretisch-Methodische Lehrveranstaltung I/II (
0.0h VO/VK/VS/KU/PS / 6.0 ECTS)
-
Fach: Research Track (Methodischer Schwerpunkt)
(Pflichtfach)
- Masterstudium Mathematics
(SKZ: 401, Version: 18W.1)
-
Fach: Information and Communications Engineering
(Wahlfach)
-
9.5 Data Mining and Neurocomputing (
2.0h VC / 4.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
9.5 Data Mining and Neurocomputing (
2.0h VC / 4.0 ECTS)
-
Fach: Information and Communications Engineering
(Wahlfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Wintersemester 2024/25
- 700.395 VC Data Mining, Synthetic Data, and Knowledge Discovery (2.0h / 4.0ECTS)
-
Wintersemester 2023/24
- 700.395 VC Data Mining, Synthetic Data, and Knowledge Discovery (2.0h / 4.0ECTS)
-
Wintersemester 2022/23
- 700.395 VC Data Mining, Synthetic Data and Knowledge Discovery (2.0h / 4.0ECTS)
-
Wintersemester 2021/22
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2020/21
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Sommersemester 2020
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2017/18
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2016/17
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2015/16
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2013/14
- 700.395 VK Data Mining in Intelligent Transportation and Logistics (2.0h / 4.0ECTS)
-
Wintersemester 2012/13
- 700.395 VK Data Mining in Intelligent Transportation and Logistics (2.0h / 4.0ECTS)