700.340 (18S) Machine Learning in Intelligent Transportation
Overview
- Lecturer
- Course title german Machine Learning in Intelligent Transportation
- Type Lecture - Seminar (continuous assessment course )
- Hours per Week 2.0
- ECTS credits 4.0
- Registrations 13 (20 max.)
- Organisational unit
- Language of instruction English
- Course begins on 09.05.2018
- eLearning Go to Moodle course
- Seniorstudium Liberale Yes
Time and place
Course Information
Intended learning outcomes
After this course student will get the knowledge about the state of the art methods regarding machine learning and particularly deep learning
Students will be able to build and train and validate deep learning models using Tensorflow
Teaching methodology including the use of eLearning tools
After the introduction sessions, we will discuss a cutting edge paper in each lecture, learn how to implement it and evaluate its results.
The paper analysis will be in the morning sessions.
Implementation and presentation of the results will be in the afternoon
Student work during the course will be considered in the final evaluation
Course content
1. Introduction to machine learning
2. Linear and Logistic regression
3. Shallow Neural Networks
4. Deep Neural Networks
5. Backpropagation algorithms
6. Convolutional Neural Networks
7. Autoencoders
8. Recurrent Neural Networks
9. Long Term Short Term Memory Networks
10. Deep Learning in Natural Language Processing (Word2Vec)
11. Differentiable Neural Computing
12. Hierarchical Temporal Memory
Examination information
Examination methodology
Project 50%
Presentation 10%
in Class Work 40%
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Autonomous Systems and Robotics (WI)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Subject: Autonomous Systems and Robotics (WI)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Free Electives
(Optional subject)
-
Free Electives (
0.0h XX / 6.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
Free Electives (
0.0h XX / 6.0 ECTS)
-
Subject: Free Electives
(Optional subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Major Field of Specialization (Intelligent Transportation Systems)
(Compulsory subject)
-
1.1-1.3 Lecture with Exercises or Lecture with Seminar (
6.0h VK/VS / 12.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
1.1-1.3 Lecture with Exercises or Lecture with Seminar (
6.0h VK/VS / 12.0 ECTS)
-
Subject: Major Field of Specialization (Intelligent Transportation Systems)
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Additional Technical Module I
(Compulsory subject)
-
2.1-2.2 Lecture with Exercises or Lecture with Seminar (
4.0h VK/VS / 8.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
2.1-2.2 Lecture with Exercises or Lecture with Seminar (
4.0h VK/VS / 8.0 ECTS)
-
Subject: Additional Technical Module I
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Additional Technical Module II
(Compulsory subject)
-
3.1-3.3 Lecture with Exercises or Lecture with Seminar (
6.0h VK/VS / 12.0 ECTS)
- 700.340 Machine Learning in Intelligent Transportation (2.0h VS / 4.0 ECTS)
-
3.1-3.3 Lecture with Exercises or Lecture with Seminar (
6.0h VK/VS / 12.0 ECTS)
-
Subject: Additional Technical Module II
(Compulsory subject)
Equivalent courses for counting the examination attempts
-
Sommersemester 2024
- 700.340 VS Neurocomputing in Robotics and Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2023
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2022
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2021
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2020
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2019
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2017
- 700.340 VS Machine Learning in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2016
- 700.340 VS Machine Vision in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2015
- 700.340 VS Machine Vision in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2014
- 700.340 VS Machine Vision in Intelligent Transportation (2.0h / 4.0ECTS)
-
Sommersemester 2013
- 700.340 VS Machine Vision in Intelligent Transportation (2.0h / 4.0ECTS)