700.395 (22W) Data Mining, Synthetic Data and Knowledge Discovery
Überblick
Weitere Informationen zum Lehrbetrieb vor Ort finden Sie unter: https://www.aau.at/corona.
- Lehrende/r
- LV-Titel englisch Data Mining, Synthetic Data and Knowledge Discovery
- LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
- LV-Modell Onlinelehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 4.0
- Anmeldungen 27 (30 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 10.12.2022
- eLearning zum Moodle-Kurs
-
Anmerkungen
10.12.22 - 09:00-17:00
17.12.22 - 09:00-17:00
13.01.23 - 09:00-17:00
14.01.23 - 09:00-17:00
- 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 supervised and unsupervised 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
Slides + Exercises (Live Demonstration), Online Quiz
Inhalt/e
- Data preprocessing
- Dimensionality Reduction (Singular Value Decomposition (SVD), Principal Component Analysis (PCA) )
- Unsupervised Learning and Clustering (K-means, Expectation-Maximization)
- Supervised Learning (Support Vector Machine (SVMs), Bayes Classifiers, Decision Trees)
- Regularization Techniques
- Kernel Models
- Recommender Systems (Collaborative Filtering and Association Rule Mining)
- Introduction to Neurocomputing (Activation Functions, Backpropagation, Perceptron and Multi layer perceptron (MLP), A brief Introduction on Recurrent Neural Networks and Convolutional Neural Networks)
- Evaluation Metrics
Literatur
M. Bishop, Pattern Recognition and Machine Learning, Springer
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, Synthetic Data and Knowledge Discovery (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, Synthetic Data and Knowledge Discovery (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, Synthetic Data and Knowledge Discovery (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, Synthetic Data and Knowledge Discovery (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, Synthetic Data and Knowledge Discovery (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, Synthetic Data and Knowledge Discovery (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 and Communications Engineering (ICE)
(SKZ: 488, Version: 22W.1)
-
Fach: Autonomous Systems and Robotics: Advanced
(Wahlfach)
-
2.2 Data Mining and Neurocomputing (
0.0h VC / 4.0 ECTS)
- 700.395 Data Mining, Synthetic Data and Knowledge Discovery (2.0h VC / 4.0 ECTS)
-
2.2 Data Mining and Neurocomputing (
0.0h VC / 4.0 ECTS)
-
Fach: Autonomous Systems and Robotics: Advanced
(Wahlfach)
- 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, Synthetic Data and Knowledge Discovery (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 2023/24
- 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)
-
Sommersemester 2019
- 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)