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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

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Predictions

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