Student Performance Prediction System

📌 Problem Statement

Predict student academic performance based on demographic, academic, and lifestyle factors using machine learning techniques.
This project aims to identify patterns that influence student outcomes and help institutions provide early academic support.

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📊 Dataset

• Source: Public student performance dataset
• File: students.csv
• Features include:
  • Gender
  • Parental education
  • Study time
  • Test preparation
  • Previous scores
• Target variable:
  • Final student score / performance

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🛠 Tech Stack

• Programming Language: Python
• Libraries:
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Scikit-learn
• Tools:
  • Jupyter Notebook
  • Git & GitHub
  • VS Code

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🔄 Project Workflow

1. Data loading and exploration
2. Data cleaning and preprocessing
3. Exploratory Data Analysis (EDA)
4. Feature selection
5. Model training
6. Model evaluation
7. Performance analysis

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📈 Results

• Built a baseline machine learning model
• Evaluated model using accuracy and error metrics
• Identified key factors affecting student performance

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▶️ How to Run the Project

1. Clone the repository