AI Student Performance Predictor & Feedback Generator
An intelligent system to predict student performance and generate customized feedback using machine learning models. Designed to assist educators and institutions in evaluating student progress and guiding improvement.
Project Highlights
- Predict student performance based on scores, attendance, and other inputs.
- Generates smart feedback reports personalized for each student.
- Supports multiple ML models (KNN, Random Forest, XGBoost, Logistic Regression).
- Comparative analysis of model accuracies.
- Includes an interactive Gradio GUI dashboard.
Tech Stack
| Area | Tools |
|---|---|
| Language | Python |
| Data Handling | Pandas, NumPy |
| ML Models | Random Forest, XGBoost, KNN, Logistic Regression |
| GUI | Gradio |
| Visualization | Matplotlib, Seaborn |
| IDE | Google Colab |
| Deployment | GitHub (future-ready for Streamlit / Hugging Face) |
Features
- Real-time performance prediction
- Graph-based feedback
- Accurate model selection
- Excel/CSV support for bulk input
- Clean, interactive dashboard