700.373 (17S) Lab on Machine Learning and Applications in Intelligent Vehicles
Überblick
- Lehrende/r
- LV-Titel englisch Lab on Machine Learning and Applications in Intelligent Vehicles
- LV-Art Kurs (prüfungsimmanente LV )
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 3.0
- Anmeldungen 12 (20 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 07.03.2017
- eLearning zum Moodle-Kurs
-
Anmerkungen
This course will focus on the recent advanced machine learning techniques including: data processing, dimension reduction, deep learning and deep reinforcement learning.
In the field of transportation and autonomous vehicles, deep Learning has become a cutting edge technique. Therefore this course will focus deeply on the IMPLEMENTATION following recent techniques:
1. ConvNets https://www.youtube.com/watch?v=URmxzxYlmtg
2. Long term short term memory network https://www.youtube.com/watch?v=FsVSZpoUdSU
3. Cellular Neural Networks
4. Memory Networks
https://arxiv.org/abs/1605.06065
5. Deep Q network
https://storage.googleapis.com/deepmind-media/dqn/DQNNaturePaper.pdf
In this course we will be using Python with the two most common machine learning tools: sklearn and google tensorflow(https://www.youtube.com/watch?v=mWl45NkFBOc). During this course, students will be ask to do some challenging machine learning task in the frame of self driving cars (check the link https://www.youtube.com/watch?v=Gy69zmKPpD4).
It is mandatory to take the parallel lab course (
700.340 (17S) Machine Learning in Intelligent Transportation
) to master the techniques that will learned during the course
Zeit und Ort
LV-Beschreibung
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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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: 15W.1)
-
Fach: Free Electives
(Freifach)
-
Free Electives (
0.0h XX / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Free Electives (
0.0h XX / 6.0 ECTS)
-
Fach: Free Electives
(Freifach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Technischer Schwerpunkt (Intelligent Transportation Systems)
(Pflichtfach)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
-
Fach: Technischer Schwerpunkt (Intelligent Transportation Systems)
(Pflichtfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Technischer Schwerpunkt (Media Engineering)
(Pflichtfach)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
1.4-1.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
-
Fach: Technischer Schwerpunkt (Media Engineering)
(Pflichtfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Technische Ergänzung II
(Pflichtfach)
-
3.4-3.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
3.4-3.5 Kurs oder Labor (
4.0h KU / 6.0 ECTS)
-
Fach: Technische Ergänzung II
(Pflichtfach)
- Masterstudium Information Technology
(SKZ: 489, Version: 06W.3)
-
Fach: Freie Wahlfächer
(Freifach)
-
Diverse Lehrveranstaltungen (
0.0h VO/VK/VS/KU/PS / 12.0 ECTS)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 ECTS)
-
Diverse Lehrveranstaltungen (
0.0h VO/VK/VS/KU/PS / 12.0 ECTS)
-
Fach: Freie Wahlfächer
(Freifach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Sommersemester 2024
- 700.373 KS Lab: Neurocomputing in Robotics and Intelligent Transportation (2.0h / 3.0ECTS)
-
Sommersemester 2023
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2022
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2021
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2020
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2019
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2018
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2016
- 700.373 KS Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h / 3.0ECTS)
-
Sommersemester 2015
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)
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Sommersemester 2014
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)
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Sommersemester 2013
- 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)