izam-mohammed / Customer-Churn-MLOps

End-to-End Machine Learning application to predict the customer churn. machine learning is applied to foresee if customers are likely to leave a service. 🤖💼 This involves analyzing customer data, training a model, and predicting churn probabilities. 🚀📊

CustomerChurnPrediction

Arepositoryforpredictthecustomerchurndata

Workflows

1. Update config.yaml
2. Update schema.yaml
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Update the app.py

Contributing

Contributions are welcome! If you'd like to contribute to the project, feel free to submit issues or pull requests. Please ensure your contributions align with the project's coding standards and guidelines.

Repository Code Formatting

This repository follows a consistent code formatting approach to enhance readability and maintainability.

Python Files

Python files in this repository are formatted using Black. Black is a code formatter that automatically formats your Python code to adhere to the PEP 8 style guide.

To ensure that your Python code is formatted correctly, you can install Black and format the code by running the following command in your terminal:

pip install black
black .

HTML Files

HTML files in this repository are formatted using Prettier. Prettier is a code formatter that supports multiple languages, including HTML.

License

This project is licensed under the MIT License.

Acknowledgements

• The project utilizes the Django Framework for web development.
• UI styling is based on Bootstrap for a responsive design.
• Icons are provided by Font Awesome.

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Thanks !