The Churn Identifier project is designed to analyze and predict customer churn within a business environment. It provides a set of notebooks for exploratory data analysis (EDA), model training, and deployment using containerization in Kubernetes (K8s). The project aims to help businesses understand customer behavior and proactively identify potential churn risks.
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This project focuses on building a customer churn identification model using machine learning techniques. It aims to deploy the model seamlessly using Continuous Integration and Continuous Deployment (CI/CD) pipelines. The goal is to empower businesses to predict and mitigate customer churn more effectively, thereby enhancing customer retention and revenue.
This project has developed for platform independent using contairization.
Ensure that Python 3.9 is installed on your system. If you are using a Mac refer to the provided blog link for detailed instructions on installing a specific Python version. Please review the information in the blog for guidance. python installation
- Clone the repo
git clone https://github.com/navanith007/churn-identifier.git
- Create python virtual environement
python3.9 -m venv churn_env
source churn_env/bin/activate
- Install the requirements
pip install -r requirements.txt
- Running the churn identifier service locally
sh start_app.sh
To make changes to this service you need follow below steps before going into production
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - merge your changes to preprod and get it QC.
- Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request