Demonstrating SandwichNet—A Playful Tool for Teaching the Basics of Neural Networks
| dc.contributor.author | Sewing, Felix | |
| dc.contributor.author | Flechtner, Rahel | |
| dc.date.accessioned | 2024-08-21T11:08:29Z | |
| dc.date.available | 2024-08-21T11:08:29Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Artificial intelligence (AI) is increasingly crucial for designers, particularly in the field of human–computer interaction. A basic understanding of machine learning (ML) algorithms is essential for design students to effectively engage with this technology both conceptually and practically. However, teaching this complex content in disciplines outside of computer science requires a different approach. To address this, we introduce SandwichNet, an interactive web-based tool to teach the basic principles of neural networks. SandwichNet provides a playful interactive visualization of a neural net whose parameters can be manipulated to recreate and understand the learning behavior of the network. We introduce the tool and outline how it is integrated into our fundamental teaching of AI technologies for designers. | en |
| dc.identifier.doi | 10.18420/muc2024-mci-demo-322 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/44232 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Mensch und Computer 2024 - Workshopband | |
| dc.relation.ispartofseries | Mensch und Computer | |
| dc.rights | http://purl.org/eprint/accessRights/RestrictedAccess | |
| dc.rights.uri | http://purl.org/eprint/accessRights/RestrictedAccess | |
| dc.subject | Machine Learning Education | |
| dc.subject | Artificial Intelligence | |
| dc.title | Demonstrating SandwichNet—A Playful Tool for Teaching the Basics of Neural Networks | en |
| dc.type | Text/Conference Paper | |
| gi.conference.date | 1.-4. September 2024 | |
| gi.conference.location | Karlsruhe | |
| gi.conference.sessiontitle | MCI: Demos: Interactive Systems or Demonstrators |
Dateien
Originalbündel
1 - 1 von 1
Lade...
- Name:
- muc2024-mci-demo-322.pdf
- Größe:
- 1.11 MB
- Format:
- Adobe Portable Document Format