Churn-Model A company X required a churn model to mitigate the monetary losses from discounts provided to customers. Documentation All the analysis is shown in an html file, the source code is on the jupyter notebook (.ipynb). data was not uploaded for privacy matters EDA Categorical Variable Analysis Numerical Variable Analysis Histograms Results 1. Logistic Regression 2. XGB Boost 3. Random Forest 4. KNN