Churn-Prediction

Churn Prediction Web Application

• This web application is deployed on streamlit
• I have used the dataset from IBM community datasets which was a dataset from a fictional Telco Organization
• The Dataset has features representing the demographic data for each customer, the services used or not used by the customer and the churn labels for each customer as well
• The jupyter notebook file Churn.ipynb has the extensive EDA and all the preprocessing steps (handling missing values, null values, categorical data and balancing of the dataset)
• The model is saved in the model.SAV file
• the data directory has the raw dataset as well as the preprocessed training features dataset, and the target dataset
• the churn.py file is the main file to run to view the streamlit web app

Predictions