700.373 (17S) Lab on Machine Learning and Applications in Intelligent Vehicles

Sommersemester 2017

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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-Anrechungspunkte
3.0
Anmeldungen
12 (20 max.)
Organisationseinheit
Unterrichtssprache
Englisch
LV-Beginn
01.03.2017
Blended Learning
Ja
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

Tag von - bis Raum Details
Di, 07.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 14.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 21.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 28.03.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 04.04.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 25.04.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 02.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 09.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 16.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 23.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 30.05.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 13.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 20.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich
Di, 27.06.2017 12:00 - 14:00 L4.1.02 ICT-Lab wöchentlich

LV-Beschreibung

Prüfungsinformationen

Beurteilungsschema

Note/Grade Benotungsschema

Position im Curriculum

  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Information and Communications Engineering: Supplements (NC, ASR)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Technical Complements (NC, ASR)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics: Advanced (ASR)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Autonomous Systems and Robotics (WI)
      • 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)
  • Masterstudium Information and Communications Engineering (ICE) (SKZ: 488, Version: 15W.1)
    • Fach: Free Electives
      • 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)
  • 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)
  • 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)
  • 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)
  • 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)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

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)
Sommersemester 2014
  • 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)
Sommersemester 2013
  • 700.373 KU Labor: Machine Vision and Smart Sensors for Intelligent Vehicles (2.0h / 3.0ECTS)