BayesCode/Expresso-Churn-Prediction

Expresso is an African telecommunications company that provides customers with airtime and mobile data bundles. The objective of this challenge is to develop a machine learning model to predict the likelihood of each Expresso customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. This solution will help Expresso to better serve their customers by understanding which customers are at risk of leaving. # Expresso-Churn-Prediction Expresso is an African telecommunications company that provides customers with airtime and mobile data bundles. The objective of this challenge is to develop a machine learning model to predict the likelihood of each Expresso customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. This solution will help Expresso to better serve their customers by understanding which customers are at risk of leaving. ## ABOUT The data describes 500,000 Expresso clients. The objective of this hackathon is to develop a predictive model that determines the likelihood for a customer to churn - to stop purchasing airtime and data from Expresso. ## Evaluation The evaluation metric for this challenge is Log Loss. The values can be between 0 and 1, inclusive. Where 1 indicates the customer churned and 0 indicates the customer stayed with Expresso.