ASU · Team capstone
Make the data something to explore.
An interactive 3D learning environment for machine-learning concepts.
The context
A problem worth solving.
Machine-learning concepts benefit from an environment where learners can inspect and interact with the data.
My contribution
What I brought to the work.
Worked in a team of five on a 3D visualization tool for an ASU professor. The original walkthrough includes data positioning and interactive predictions.
The product
What it makes possible.
Original project / selected screens & walkthrough
The original project imagery and product explanation are retained here. These are historical project materials; current availability may differ.
In the original implementation, data points from the Iris dataset are instantiated in Unity. Each data point is positioned in 3D space based on sepal and petal dimensions. The points are assigned sizes and colors to represent the different species of Iris flowers, enhancing the visualization of machine learning classifications.
The interactive tool generates predictions from user input. It uses a trained model to classify new Iris flower data, allowing for immediate feedback, which helps the user interact with the visualization in an engaging way.
Where it stands
The work keeps moving.
This project remains part of the earlier-work collection. The original materials show the implementation at that point in time; they are not a claim about current operation.