A full-stack web application that combines habit tracking with predictive analytics to help users improve their daily routines through data-driven insights and AI-powered recommendations.
- 📊 Habit Tracking: Log daily sleep hours, water intake, and mood (1-5 scale)
- 🤖 AI Predictions: Machine learning model predicts future mood based on habit patterns
- 📈 Real-time Visualizations: Interactive charts showing trends and progress over time
- 🎯 Personalized Feedback: AI-generated insights and recommendations for improvement
- 📱 Responsive Dashboard: Clean, intuitive interface accessible on any device
| Layer | Technology |
|---|---|
| Backend | FastAPI, Python |
| Database | SQLite, SQLAlchemy ORM |
| Machine Learning | scikit-learn, pandas, numpy |
| Data Visualization | Matplotlib, Seaborn |
| Frontend | HTML, CSS, JavaScript |
| Server | Uvicorn ASGI server |
- Data Collection: Users input daily sleep, water, and mood data through an intuitive web interface
- Trend Analysis: System calculates 3-day rolling averages and trend slopes using linear regression
- AI Prediction: Random Forest Regressor model forecasts future mood based on historical patterns
- Feedback Generation: Personalized insights and recommendations generated from analysis results
- Visualization: Interactive charts dynamically display progress and predictive trendlines