Placement Prediction using Machine Learning

A web application to identify patterns and trends in campus placement data using machine learning. Predict placement outcomes for MBA students based on academic and personal details.

---

🚀 Features

• Interactive web form for inputting student details
• Machine learning model for placement prediction
• Deployed using IBM Watson Studio & IBM Watson Machine Learning
• Clean and modern UI (see templates/index.html)
• Jupyter notebook for data analysis and model training

📊 Data

Dataset from Kaggle: Factors Affecting Campus Placement

🛠️ Requirements

• Python 3.7+
• Flask
• pandas
• scikit-learn
• numpy

Install dependencies:

pip install flask pandas scikit-learn numpy

🏗️ Setup & Usage

1. Clone this repository:

   git clone https://github.com/NikhilKartha5/Placement-prediction-ml.git
   cd Placement-prediction-ml

2. Ensure the model file (Model_placement_full_data_class.pkl) is present in the project directory.
3. Start the Flask app:

   flask run

4. Open your browser and go to http://localhost:5000 to use the app.

📁 Project Structure

• app.py - Flask backend for prediction
• templates/index.html - Web UI
• Identify Trends and Patterns in Campus Placement-Copy1.ipynb - Data analysis & model training
• badges/ - Certificates and badges

🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License.