Since this project was model‑focused, usage happens entirely through scripts and notebooks. DASS questionnaire responses are preprocessed into numerical features and passed into the trained ML models. Each model outputs predicted categories for depression, anxiety, and stress based on learned patterns from the dataset.

The setup is ideal for experimentation, benchmarking algorithms, and studying how different ML techniques perform on the same psychological dataset. The project is intended strictly for academic and learning purposes, showcasing the predictive capabilities of machine learning rather than serving as any form of diagnostic tool.