Performed an end-to-end customer churn and retention analysis using Python and machine learning. Cleaned and explored customer data, engineered relevant features, and developed a churn prediction model to identify patterns associated with customer attrition. Presented key findings through an interactive BI dashboard, highlighting customer retention trends, contract types, and internet service metrics.
Excited to share my latest portfolio project: ChurnSense – Customer Churn & Retention Analysis! 📊
In this project, I explored customer data to identify patterns associated with customer churn and retention.
I worked on data cleaning, exploratory analysis, feature engineering, and machine learning to develop a churn prediction model.
Tools used: Python, Pandas, and Scikit-learn.
I also presented key findings through an interactive BI dashboard, exploring contract types, internet services, and customer retention trends.
Turning data into insights, one project at a time! 🚀
0 likes · 3 views · Oct 8, 2026
Analyzed customer churn data using Python and machine learning to identify patterns linked to customer retention. Cleaned and explored the dataset, engineere...
