Arogo-AI
A machine-learning workflow for predicting mental-health treatment needs, from data processing to model serving.
Overview · Implementation · Evidence
01THE MOTIVATION
The problem
End-to-end ML experiments need data preparation, evaluation, and a usable prediction surface—not only a trained model. This project combines those pieces as a research prototype.
STATUS / Research prototype
02UNDER THE HOOD
The implementation
THE BUILDImplemented dataset preparation, imbalance handling, classical ML experiments, DVC/MLflow tracking and prediction surfaces through Flask and Streamlit. A research prototype, not a medical diagnostic service.
03ACTUAL ARTIFACTS
Inside the build
Screens from the application, with the workflow and context for each view.
04THE EVIDENCE
Read the source
Explore the code, run the application where available, or watch the original demonstration.