SandwichNet

Interactive web-based tool for teaching the basic principles of neural networks

Teaching neural nets and machine learning to students of non-technical disciplines often gets tricky when we look at what goes on within the training process of a model. While a parametric model with thousands to billions of parameters configured to output correct approximate predictions is already pretty complex, understanding the overarching principle that makes modern machine learning algorithms possible is key. And that’s where the tool "SandwichNet" comes in.

Inspired by a particularly simple and memorable example from the textbook: “You Look like a Thing and I Love You” from Janelle Shane (Wildfire, 2020), we created an interactive web application that lets students copy the actions of a training algorithm.

We’re using the tool in our foundational machine learning courses to help students understand the possibilities and limitations of the technology better down the road. We really believe that teaching these highly technical concepts in a hands-on way will benefit the students when they start working on technologically complex problems and projects in the future.

SandwichNet was presented at the MuC 2024 conference in Karlsruhe. Feel free to give it a try on the links below. You can use it in your own classes and adapt it to suit your needs. The code is provided via a GitHub repository.

Ressources

Shane, Janelle. You Look like a Thing and I Love You. Wildfire, 2020.
SandwichNet Conference Paper MuC 2024
SandwichNet - Level 1
SandwichNet - Level 2
SandwichNet - Level 3
GitHub repository of SandwichNet