ChurnPredict Pro is a powerful web application built on top of a Random Forest Classifier model, designed to predict customer churn. It provides businesses with real-time insights into customer retention and helps optimize customer management strategies 💼💰🤖
- Introduction 📝
- Features ✨
- Demo 🚀
- Getting Started 🏁
- App Structure 🧱
- Usage 📊
- Technologies Used 💻🔬
- Contributing 🤝🙌
- License 📜
ChurnPredict Pro uses a state-of-the-art Random Forest Classifier model to predict customer churn. It offers a user-friendly interface for inputting customer data and receiving instant churn predictions.
- Real-time customer churn predictions.
- Interactive user interface.
- Easy-to-use design.
Follow these instructions to get the app up and running on your local machine.
-
Clone the repository:
git clone https://github.com/snyamson/P4-ChurnPredict-Pro.git cd P4-ChurnPredict-Pro
-
Create a virtual environment (optional but recommended):
python -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate`
-
Install the required dependencies:
pip install -r requirements.txt
Run the Gradio app using the following command:
python src/app/app.py
Access the app through your web browser at http://localhost:7860
.
src
: The main application directory.app/
: Directory containing the main application scriptapp.py
.model/
: Directory for storing the pre-trained Random Forest Classifier model and preprocessing tools.notebook/
: Directory containing data preprocessing details and model training.
- Fill in the customer data in the required fields.
- Click the "Submit" button to receive a real-time churn prediction.
- Gradio: Python library for building interactive interfaces.
- Pandas: Data manipulation and analysis library.
- Scikit-Learn: Machine learning library.
Contributions to the ChurnPredict Pro project are welcome. Please follow these guidelines for contributing:
- Fork the repository.
- Create a new branch for your feature or bug fix:
git checkout -b feature-name
- Make your changes and commit them with clear, concise commit messages.
- Push your changes to your fork.
- Create a pull request against the main repository.
This project is licensed under the MIT License.
Solomon Nyamson
Connect with me on LinkedIn: LinkedIn Profile
Feel free to star ⭐ this repository if you find it helpful!