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customer-churn-analysis

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Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.

  • Updated Dec 29, 2021
  • Jupyter Notebook

In this project, we embark on an exciting journey to explore and analyze customer churn within the Telecom network service using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework.

  • Updated Aug 20, 2023
  • Python

The core purpose of this study is to find the impact of Sentiment Analysis in predicting customer churn for the e-commerce industry by employing different predictive models. Furthermore, the study is also focused on observing which model is best in a more accurate prediction for determining the churn rate of customers.

  • Updated Jul 24, 2024
  • Jupyter Notebook

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