Gbolahan-Aziz/DSN_Expresso_Churn_Hackathon

Data science Nigeria Hackathons # DSN_Expresso_Churn This repository contains the 4th position solution for the Pre-Bootcamp hackathon organised by Data Science Nigeria (DSN) on Zindi, from 8 August—22 August, 2020. (link to hackathon: zindi.africa). ### Aim: To help Expresso to better serve their customers by understanding which customers are at risk of leaving. ### Objective: To develop a predictive model that determines the likelihood for a customer to churn - to stop purchasing airtime and data from Expresso ### Packages Scikit learn Pandas Numpy Matplotlib Catboost Lightgbm Seaborn ### Evaluation: Logloss ### Private LB score: 0.246701956963814 #### Models The solution was built on two models - Catboost and lightgbm, and a weighted average of them, with the averaged model achieving a good performance on the private leaderboard.