Publications (Excerpt)
| [182401] |
| Title: Teaching Machine Learning and Data Literacy to Students of Logistics using Jupyter Notebooks [DELFI Poster Award Winner]. <em>DELFI 2020</em> |
| Written by: Kastner, Marvin and Franzkeit, Janna and Lainé, Anna |
| in: <em>DELFI 2020</em>. (2020). |
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| on pages: 365-366 |
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| Editor: In Zender, Raphael and Ifenthaler, Dirk and Leonhardt, Thiemo and Schumacher, Clara (Eds.) |
| Publisher: Gesellschaft für Informatik e.V.: |
| Series: Lecture Notes in Informatics (LNI) - Proceedings |
| Address: Bonn |
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| ISBN: 978-3-88579-702-9 |
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| URL: https://api.ltb.io/show/BMRWS |
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Note: malitup
Abstract: Teaching machine learning in fields outside of computer sciences can be challenging when the students do not have a solid code knowledge. In this work, the requirements for teaching data literacy and code literacy to students of logistics are explored. Specifically, the use of Jupyter Notebooks in a machine learning course for students in logistics is evaluated, using “Teaching and Learning with Jupyter” written by Barba et al. in 2019 that lists several teaching patterns for Jupyter Notebooks