Demystifying Deep Learning: A Learning Application for Beginners to Gain Practical Experience
Abstract
Deep learning has revolutionized machine learning, enhancing our ability to solve complex computational problems. From image classification to speech recognition, the technology can be beneficial in a broad range of scenarios. However, the barrier to entry is quite high, especially when programming skills are missing. In this paper, we present the development of a learning application for beginners that is easy to use, yet powerful enough to solve practical deep learning problems.We followed the human-centered design approach and conducted a technical evaluation to identify solvable classification problems. In the future, we plan to conduct a user study to evaluate our learning application online.
- Citation
- BibTeX
Schultze, S., Gruenefeld, U. & Boll, S.,
(2020).
Demystifying Deep Learning: A Learning Application for Beginners to Gain Practical Experience.
In:
Hansen, C., Nürnberger, A. & Preim, B.
(Hrsg.),
Mensch und Computer 2020 - Workshopband.
Bonn:
Gesellschaft für Informatik e.V..
DOI: 10.18420/muc2020-ws111-334
@inproceedings{mci/Schultze2020,
author = {Schultze, Sven AND Gruenefeld, Uwe AND Boll, Susanne},
title = {Demystifying Deep Learning: A Learning Application for Beginners to Gain Practical Experience},
booktitle = {Mensch und Computer 2020 - Workshopband},
year = {2020},
editor = {Hansen, Christian AND Nürnberger, Andreas AND Preim, Bernhard} ,
doi = { 10.18420/muc2020-ws111-334 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Schultze, Sven AND Gruenefeld, Uwe AND Boll, Susanne},
title = {Demystifying Deep Learning: A Learning Application for Beginners to Gain Practical Experience},
booktitle = {Mensch und Computer 2020 - Workshopband},
year = {2020},
editor = {Hansen, Christian AND Nürnberger, Andreas AND Preim, Bernhard} ,
doi = { 10.18420/muc2020-ws111-334 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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xmlui.MetaDataDisplay.field.date: 2020
Language:
(en)

Content Type: Text/Conference Poster