Machine Learning: Menschen Lernen Maschinelles Lernen
- This paper describes the concept and some results of the project "Menschen Lernen Maschinelles Lernen" (Humans Learn Machine Learning, ML2) of the University of Applied Sciences Offenburg. It brings together students of different courses of study and practitioners from companies on the subject of Machine Learning. A mixture of blended learning and practical projects ensures a tight coupling ofThis paper describes the concept and some results of the project "Menschen Lernen Maschinelles Lernen" (Humans Learn Machine Learning, ML2) of the University of Applied Sciences Offenburg. It brings together students of different courses of study and practitioners from companies on the subject of Machine Learning. A mixture of blended learning and practical projects ensures a tight coupling of machine learning theory and application. The paper details the phases of ML2 and mentions two successful example projects.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/3950 | Bibliografische Angaben |
Title (English): | Machine Learning: Menschen Lernen Maschinelles Lernen |
Conference: | The Upper-Rhine Artificial Intelligence Symposium (UR-AI 2019), Offenburg, March 13, 2019 |
Author: | Ralph IsenmannGND, Jürgen PrinzbachGND, Stephan TrahaschStaff MemberORCiDGND, Volker SängerStaff MemberGND, Tobias LauerStaff MemberGND, Tobias HagenStaff MemberORCiDGND, Klaus DorerStaff MemberORCiDGND |
Year of Publication: | 2019 |
Creating Corporation: | Hochschule Karlsruhe |
Contributing Corporation: | Hochschule Offenburg |
Page Number: | 5 |
First Page: | 37 |
Last Page: | 41 |
Parent Title (English): | Artificial Intelligence. From Research To Application |
Editor: | Andreas Christ, Franz Quint |
ISBN: | 978-3-9820756-0-0 (Print) |
ISBN: | 978-3-9820756-1-7 (eBook) |
Language: | English | Inhaltliche Informationen |
Institutes: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
Forschung / IMLA - Institute for Machine Learning and Analytics | |
Fakultät Wirtschaft (W) | |
Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) | |
Institutes: | Bibliografie |
Projekte / Magma Offenburg | Formale Angaben |
Open Access: | Open Access |
Licence (German): | Urheberrechtlich geschützt |
ArXiv Id: | http://arxiv.org/abs/1903.08495 |