Student Performance Prediction

Predicting student performance using factors like study time and previous scores

📌 Project Overview

This project uses linear regression to predict student performance based on:

• Previous Scores
• Hours Studied

Achieved an R² score of 0.99, showing strong predictive accuracy.

📊 Results

• Mean Absolute Error (MAE): 1.83
• Mean Squared Error (MSE): 5.24
• R-Squared Score: 0.99

📂 Files Included

• student_performance.ipynb → Full Python Notebook with code & analysis.
• requirements.txt → List of dependencies (pip install -r requirements.txt to install).