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ORCID3rd Teaching Machine Learning Workshop 2022: Grenoble, France / Online (hybrid)
- Katherine M. Kinnaird, Peter Steinbach, Oliver Guhr:
The Third Teaching Machine Learning and Artificial Intelligence Workshop, 19-23 September 2022, Grenoble, France and online. Proceedings of Machine Learning Research 207, PMLR 2022 - Ludwig Bothmann, Sven Strickroth
, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl:
Developing Open Source Educational Resources for Machine Learning and Data Science. 1-6 - Donatella Cea, Helene Hoffmann, Marie Piraud:
Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds. 7-11 - Gulustan Dogan:
Teaching Machine Learning with Applied Interdisciplinary Real World Projects. 12-15 - Jan Ebert, Danimir T. Doncevic, Ramona Kloß, Stefan Kesselheim:
Hearts Gym: Learning Reinforcement Learning as a Team Event. 16-21 - Ken Hasselmann, Quentin Lurkin:
Stimulating student engagement with an AI board game tournament. 22-26 - Florian Huber, Erica Dafne van Kuppevelt, Peter Steinbach, Colin Sauze, Yang Liu, Berend Weel:
Will the sun shine? - An accessible dataset for teaching machine learning and deep learning. 27-31 - Lukas Lodes, Alexander Schiendorfer:
A Deep Learning Bootcamp for Engineering & Management Students. 32-36 - Tilman Michaeli, Stefan Seegerer, Lennard Kerber, Ralf Romeike:
Data, Trees, and Forests - Decision Tree Learning in K-12 Education. 37-41 - Gero Szepannek, Laurens Martin Tetzlaff, Alexander Frahm, Karsten Lübke:
Teaching Machine Learning with mlr3 using Shiny. 42-45 - Matias Valdenegro-Toro, Matthia Sabatelli:
Machine Learning Students Overfit to Overfitting. 46-51
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