🎓 Student Placement Predictor

A Flask-based web application that predicts whether a student is likely to get placed based on their academic and soft skill profile. The model is trained using logistic regression and deployed with an interactive frontend.

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🚀 Features

• Built using Flask (Python backend)
• Uses a trained Logistic Regression model (model.pkl)
• Predicts based on:
  • Number of Internships
  • CGPA
  • Workshops/Certifications
  • Aptitude Test Score
  • Soft Skills Rating
• Beautiful, responsive HTML + CSS frontend
• Input form and real-time prediction

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🧠 Technologies Used

• Python 3
• Flask
• Scikit-learn
• Pandas
• HTML + CSS (vanilla)

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📦 Installation

git clone https://github.com/codedbyasim/Student-Placement-Predictor.git
cd Student-Placement-Predictor
pip install -r requirements.txt

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⚙️ Usage

python app.py

Then open your browser and go to:

http://127.0.0.1:5000

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📁 Project Structure

Student-Placement-Predictor/
├── app.py                 # Flask app
├── model.pkl              # Trained Logistic Regression model
├── scaler.pkl             # StandardScaler used for input normalisation
├── requirements.txt       # Dependencies
└── templates/
    └── index.html         # Frontend HTML form

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📊 Model

• Algorithm: Logistic Regression
• Accuracy: ~80%
• Scaled inputs using StandardScaler

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✍️ Author

Asim Hanif GitHub: @codedbyasim