A machine learning-based web application that predicts the likelihood of diabetes using key health metrics — helping users make proactive health decisions.
📽️ Watch the project in action:
👉 Click to View Video
| Role | Name | Profile Link |
|---|---|---|
| 👨💻 Team Leader | Utkarsh Gupta |
- 🧠 Predicts diabetes risk based on user-inputted health data
- 📊 Displays prediction result with clear visuals and messages
- 🔒 No data is stored — fully privacy-respecting
- ⚡ Lightweight and fast web interface using Streamlit
- Language: Python
- Libraries: Pandas, NumPy, Scikit-learn
- Interface: Streamlit
- Model: Logistic Regression / Random Forest (based on implementation)
- User enters key health indicators (e.g., glucose level, BMI, age).
- Model processes the data and predicts diabetes risk.
- Results are instantly shown on the web interface.
Feel free to reach out to the team for collaboration or improvements!
🧬 Built with purpose and precision by Team 2AMcoder 💡