💘 Crush Predictor Webapp

A fun, lightweight machine learning web app that predicts the likelihood that your crush likes you back based on 10 behavioral inputs. This project is built using Streamlit, making it super easy to run and deploy.

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Model Information

• Algorithm: Random Forest Regressor
• Accuracy: ~77%
• Inputs: 10 behavioral features (0–10 scale)
• Output: Percentage likelihood (0–100)
• Reaction Images: Changes based on the score bracket

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Demo

To view the full demo, check the link above.
Try the app

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🚀 How to Clone & Run Locally

1. Clone the repository

git clone https://github.com/prashant-g0/ml-model-crush-predictor-streamlit-app.git
cd ml-model-crush-predictor-streamlit-app

2. Install dependencies

pip install -r requirements.txt

3. Run the app

streamlit run app.py
or
python -m streamlit run app.py

The app will start at:

http://localhost:8501

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🤝 Contribution Guidelines

Contributions are welcome! If you want to improve the UI, model, or add new features:

1. Fork the repository
2. Create a new branch
3. Make your changes
4. Submit a pull request

Feel free to open an issue if you have suggestions or bugs to report.

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👨‍💻 Author

Developed by Prashant Gupta, a CSE undergrad exploring machine learning, data science, and fun experimental ideas.

If you liked the project, feel free to star the repo or reach out!