Student Performance Predictor

Overview

This project aims to predict student academic performance using machine learning techniques.
It uses data analytics to identify key factors that influence student success.

Features

• Data preprocessing and cleaning
• Exploratory Data Analysis (EDA)
• Linear Regression model
• Performance prediction

Technologies Used

• Python
• Pandas
• NumPy
• Scikit-learn
• Matplotlib

Dataset

The dataset contains information about:

• Study hours
• Attendance
• Previous scores
• Other academic factors

Installation

git clone https://github.com/yourusername/student-performance-predictor.git
cd student-performance-predictor
pip install -r requirements.txt

Usage

Run the model:

python src/model.py

Example Output

The model predicts student scores based on input features.

Project Purpose

This project was created as part of my learning journey in:

• Data Analytics
• Artificial Intelligence
• Machine Learning

License

This project is open-source and free to use.

Authors

Muhammad Fauzil Adhim GitHub: https://github.com/fauzildev