Customer churn prediction is a crucial task in business analytics that involves identifying customers who are likely to cancel their subscription or stop using a service. This project aims to build a predictive model that can anticipate customer churn and provide actionable insights to retain valuable customers.
The project utilizes:
customer_churn.csv: The dataset used in this project contains information about customer demographics, tenure, usage patterns, and whether they churned or not. The dataset provides the necessary features for training and evaluating the churn prediction model.
The following libraries are required to run the code:
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn
- imblearn
You can install the required libraries using the following command:
pip install pandas numpy matplotlib seaborn scikit-learn imblearn
This project is part of the TechnoHacks Virtual Internship Program August Batch 2023. Special thanks to the program organizers for providing this opportunity to enhance my data science skills.