AI-Powered Multimodal Mental Health Detection and Wellness Recommendation System

An AI-powered multimodal system that detects mental health conditions and recommends wellness actions.

An AI-powered multimodal system that detects mental health conditions and recommends wellness actions. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want hands-on experience of the whole machine learning workflow: data collection and cleaning, feature engineering, model training and tuning, evaluation and presenting results.

The main parts are personalised recommendations ranked by relevance, fusion of more than one type of input, data preparation and exploration, model training and comparison of algorithms, and evaluation with standard metrics. The reference build uses Python, scikit-learn, Pandas, and Flask, with a clear project structure, setup instructions and sample data so that it can be run and extended.