Added new model: Customer Churn Prediction

[Stuti333]

I've added a new model to predict customer churn in a bank. The notebook, Model.ipynb, includes three different methods: Random Forest Classifier, Logistic Regression, and Gradient Boosting Classifier. The Gradient Boosting Classifier outperformed the others, delivering higher accuracy, precision, and recall values. Therefore, the predictions are based on the Gradient Boosting Classifier.

[yashasvini121]

Hi @Stuti333, thank you for the PR! Unfortunately, we can't accept it as it uses an outdated version of scikit-learn, which is causing some modules to be required that are no longer compatible with the current version.

Please update your code to be compatible with the latest version of scikit-learn or ensure that all the pages in the project work properly regardless of the version. Also, kindly update the requirements.txt file accordingly.

[Stuti333]

Hi @yashasvini121, I have updated my code and created a new pull request. I hope it will not cause any issue this time.
#80