700.373 (16S) Lab on Machine Learning and Applications in Intelligent Vehicles
Overview
- Lecturer
- Course title german Lab on Machine Learning and Applications in Intelligent Vehicles
- Type Course (continuous assessment course )
- Hours per Week 2.0
- ECTS credits 3.0
- Registrations 8 (20 max.)
- Organisational unit
- Language of instruction English
- Course begins on 01.03.2016
Time and place
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Course Information
Course content
Machine Learning, Pattern Recognition, Time Series Analysis With applications on real case studies using Matlab and PythonTopics
- Data preprocessing
- Unsupervised, Supervised, reinforcement, deep and sell taught learning
- Classification (SVM, Bayes, Decision Trees CNN, etc)
- Clustering
- Time series forecast
- Evaluation Metrics
- Python
- Matlab
Teaching objective
Students should be able to deal with real machine learning case studies that include data preprocessing, smart system design and comprehensive evaluationExamination information
Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- 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)
- 700.373 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)
-
Subject: Technical Complements (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)
- 700.373 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)
-
Subject: Technical Complements (NC, ASR)
(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)
- 700.373 Lab on Machine Learning and Applications in Intelligent Vehicles (2.0h KS / 3.0 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)
-
1.4-1.5 Exercises or Lab (
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 Exercises or Lab (
4.0h KU / 6.0 ECTS)
-
Subject: Major Field of Specialization (Intelligent Transportation Systems)
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Major Field of Specialization (Media Engineering)
(Compulsory subject)
-
1.4-1.5 Exercises or Lab (
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 Exercises or Lab (
4.0h KU / 6.0 ECTS)
-
Subject: Major Field of Specialization (Media Engineering)
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Additional Technical Module II
(Compulsory subject)
-
3.4-3.5 Exercises or Lab (
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 Exercises or Lab (
4.0h KU / 6.0 ECTS)
-
Subject: Additional Technical Module II
(Compulsory subject)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Electives
(Optional subject)
-
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)
-
Subject: Electives
(Optional subject)
Equivalent courses for counting the examination attempts
-
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 2017
- 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)