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BANK CUSTOMER CHURN

This project consist of supervised machine learning. It makes use of classification algorithms to predict the likelihood of a customer to churn.

Problem Statement

To address the challenges with addressing churn reactively, I developed a model that can predict the likelihood of user churn in the near future and empowered the sales team with insights from this model to prevent at risk accounts from churning.

Business Understanding

Components

Installation

pip install

  npm install my-project
  cd my-project

Documentation

Documentation

Environment Variables

To run this project, you will need to add the following environment variables to your .env file

API_KEY

ANOTHER_API_KEY

FAQ

Question 1

Answer 1

Question 2

Answer 2

Deployment

To deploy this project run

  npm run deploy

Demo

Insert gif or link to demo

Contributing

Contributions are always welcome!

See contributing.md for ways to get started.

Please adhere to this project's code of conduct.

Optimizations

What optimizations did you make in your code? E.g. refactors, performance improvements, accessibility

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