Skip to content

Latest commit

 

History

History
11 lines (8 loc) · 378 Bytes

README.md

File metadata and controls

11 lines (8 loc) · 378 Bytes

Predicting_customer_churn

• Did in depth exploratory data analysis on the churn dataset and got valuable insight for the machine learning model. •

Created a machine learning model using a bunch of algorithms (LR, KNN, SVC, Random Forest, Gradient Boosting) to predict customer churn based on historical data.GB classifier achieved 8% decrease in the overall churn rate