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Demystifying Deep Learning: A Learning Application for Beginners to Gain Practical Experience

Author:
Schultze, Sven [DBLP] ;
Gruenefeld, Uwe [DBLP] ;
Boll, Susanne [DBLP]
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}
}
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More Info

DOI: 10.18420/muc2020-ws111-334
xmlui.MetaDataDisplay.field.date: 2020
Language: en (en)
Content Type: Text/Conference Poster

Keywords

  • deep learning
  • machine learning
  • explainable
  • education
Collections
  • Workshopband MuC 2020 [67]

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Diese Digital Library basiert auf DSpace.

 

 


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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.