A Machine Learning Web App to Predict Final Exam Scores (G3)
The Student Performance Predictor uses machine learning to estimate a student's final exam score (G3) based on diverse academic, demographic, and behavioral factors from the UCI Student Performance dataset.
The purpose is early identification of at-risk students, enabling proactive academic support.
🔗 Streamlit Application:
https://studentperformancepredictor-ix2kp5fyavjdeyin7umtnt.streamlit.app/
- Predict final exam grade G3 (0–20)
- 40+ academic & behavioral inputs
- Smart recommendations for improving performance
- Model insights and feature importance visualization
- Clean, mobile-friendly Streamlit UI
- Fully deployed and production-ready
git clone https://github.com/Viole-0/student_performance_predictor.git
cd student_performance_predictor
pip install -r requirements.txt
streamlit run streamlit_app/app.py
- Python
- Streamlit
- Scikit-Learn
- Pandas
- NumPy
- Matplotlib
- Joblib
student_performance_predictor/
├─ models/
│ ├─ random_forest_model.pkl
│ ├─ trained_feature_names.pkl
│ ├─ model_performance_summary.csv
│ └─ feature_importances_rf.csv
│
├─ streamlit_app/
│ └─ app.py
│
├─ notebooks/
│ ├─ 01_data_exploration.ipynb
│ ├─ 02_eda_visualizations.ipynb
│ └─ 03_modeling_and_prediction.ipynb
│
├─ data/
│ └─ student-mat.csv
│
├─ requirements.txt
└─ README.md
#There are some dummy files too to test cases...