Marie Dvorzak
Coding, Design & Research
–> Selected Work –> Information–> E-mail

Marie Dvorzak
Coding, Design & Research
–> Selected Work
–> About
∆ Objects & Exhibitions:
–> Decline All
–> 200.000.000 x Second
–> The After Monument
–> Internationals in the city
–> A matter of Accessiblity
–> Attention Lab  

∆ Digital Projects:
–> Accessible Deep Learning
–> Wild Wireframekit
–> Liquid Font
–> Three.js Visualizations
–> Attention Lab

∆ Workshops & Lectures:
–> Relearning the Internet 

∆ Editorial Design:
–> Death Design Data

Accessible Deep Learning


T-SNE, or t-distributed stochastic neighbor embedding, is a dimensionality reduction algorithm that is especially useful for the analysis of genomic data, cancer research, and finding similarities in images. It was developed by Sam Roweis, Geoffrey Hinton, and Laurens van der Maaten in 2008. My implementation of the algorithm as a Three.js powered Vue.js plugin aimed to make the implementation of this data visualization easier and faster. The interface allows users to specify the visual outcomes of the algorithm, adjust the properties, and add HTML text labels to their images if needed. The project was developed as part of my Bachelor's thesis '3D-Programmierung im Web mit Vue.js Komponenten am Beispiel einer Implementierung des t-SNE Algorithmus' at the University of Applied Sciences Upper Austria in 2019.
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