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The QUA³CK Machine Learning Development Process and the Laboratory for Applied Machine Learning Approaches (LAMA)

Becker, Jürgen; Grimm, Daniel; Hotfilter, Tim; Meier, Christopher; Molinar, Gabriela; Stang, Marco; Stock, Simon; Stork, Wilhelm

Abstract (englisch):
According to recent studies, Machine Learning has become a demanded skill in the world of engineering. Therefore, it is possible to find hundreds of online courses offering to teach these abilities. Some companies now call for ‘Machine Learning Engineers’ as a new hiring position. For many engineering students this is a very difficult situation, since taught courses are often focusing on the theoretical backgrounds of machine learning. However, in order to learn the correct use of machine learning methods, students have to apply them to real world problems. Hence, the scientists of the Institute for Information Processing Technologies (ITIV) at the Karlsruhe Institute of Technology (KIT, Germany) created the Laboratory for Applied Machine Learning Approaches (LAMA). We strive for a wide audience of engineering students, independently of their previous machine learning experience. The students go through three phases of learning. First, they get introduced to the theoretical concepts, then they will undertake guided hands-on experiments and lastly there is a creative ‘Into-the-Wild’-part. This approach was very successful and was positively received by the students.
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Zugehörige Institution(en) am KIT Institut für Technik der Informationsverarbeitung (ITIV)
Publikationstyp Vortrag
Publikationsdatum 22.10.2019
Sprache Englisch
Identifikator KITopen-ID: 1000100413
Veranstaltung Symposium Artificial Intelligence for Science, Industry and Society (AISIS 2019), Mexiko-Stadt, Mexiko, 20.10.2019 – 25.12.2019
Externe Relationen Abstract/Volltext
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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