The PHOTON Wizard -- Towards Educational Machine Learning Code Generators
February 13, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Ramona Leenings, Nils Ralf Winter, Kelvin Sarink, Jan Ernsting, Xiaoyi Jiang, Udo Dannlowski, Tim Hahn
arXiv ID
2002.05432
Category
cs.SE: Software Engineering
Cross-listed
cs.LG
Citations
1
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Despite the tremendous efforts to democratize machine learning, especially in applied-science, the application is still often hampered by the lack of coding skills. As we consider programmatic understanding key to building effective and efficient machine learning solutions, we argue for a novel educational approach that builds upon the accessibility and acceptance of graphical user interfaces to convey programming skills to an applied-science target group. We outline a proof-of-concept, open-source web application, the PHOTON Wizard, which dynamically translates GUI interactions into valid source code for the Python machine learning framework PHOTON. Thereby, users possessing theoretical machine learning knowledge gain key insights into the model development workflow as well as an intuitive understanding of custom implementations. Specifically, the PHOTON Wizard integrates the concept of Educational Machine Learning Code Generators to teach users how to write code for designing, training, optimizing and evaluating custom machine learning pipelines.
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