AI-Based Student Performance Prediction System
Python, Flask, Machine Learning, Scikit-learn, Pandas, NumPy, Joblib, HTML, CSS
5 visitors0 file downloads0 screenshots
About this project
AI-Based Student Performance Prediction System is a Machine Learning web application that predicts a student's academic performance using factors such as attendance, study hours, previous marks, assignment score, internal marks, and sleep hours. The system uses a Random Forest Machine Learning model and provides the predicted performance along with prediction confidence.
What this project does
- Student performance prediction using Machine Learning
- Simple web-based user interface
- Attendance-based analysis
- Study-hours analysis
- Previous marks consideration
- Assignment and internal marks analysis
- Sleep-hours consideration
- Good / Needs Improvement prediction
- Prediction confidence percentage
- Random Forest classification model
- Sample dataset included
- Model training script included
- Beginner-friendly Flask application
Requirements
Python 3.9 or above
Flask
Pandas
NumPy
Scikit-learn
Joblib
Web browser
VS Code or any Python IDE
How to run the project
1. Extract the project ZIP file.
2. Open the project folder in VS Code.
3. Open Terminal.
4. Create virtual environment:
python -m venv venv
5. Activate virtual environment:
venv\Scripts\activate
6. Install required packages:
pip install -r requirements.txt
7. Train the Machine Learning model:
python train_model.py
8. Start the Flask application:
python app.py
9. Open the following URL in your browser:
http://127.0.0.1:5000/
Make it your own
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