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Customer-Churn-Prediction

  • Developed and deployed a customer churn prediction model using ensemble techniques to forecast account-closures for a bank.
  • Leveraged Python, Flask, and Docker for model creation and AWS for deployment, including services like AWS EC2, ECS, and Code Pipeline.
  • The project involved end-to-end implementation from model training to deployment, with a focus on optimizing and scaling the solution in a cloud environment.

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a customer churn prediction model using ensemble techniques to forecast account - closures for a bank

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