This project is a machine learning-based placement prediction system that predicts whether a student will be placed based on their IQ level and CGPA. It is designed to help students and institutions understand the relationship between academic performance and placement success.
- Predicts placement status (
PlacedorNot Placed) using IQ and CGPA - Trained on a clean dataset with supervised learning models
- Supports model evaluation with accuracy, confusion matrix, etc.
- Easy to understand, extend, and deploy
- Input Features: IQ, CGPA
- Target Output: Placement Status
- Algorithm Used: Logistic Regression (can be extended to other models)
- Python
- Pandas
- NumPy
- scikit-learn
- Matplotlib / Seaborn (for visualization)
- Clone the repository:
git clone https://github.com/Vivek-ML001/Palcement_prediction.git cd Palcement_prediction
python -m venv placement_env placement_env\Scripts\activate # For Windows
pip install -r requirements.txt
python placement_predictor.py
Palcement_prediction/ ├── data/ │ └── student_data.csv ├── placement_predictor.py ├── model.pkl ├── README.md └── requirements.txt
Let me know if you want this as a Jupyter Notebook project, want to add graphs, or include a Streamlit web app version – I’ll tailor the README further! Created with ❤️ by Vivek Kumar