Olamilekan002/Expresso-Churn-Prediction-Challenge-by-Data-Science-Nigeria

A pre-bootcamp hackaton by DSN # Expresso-Churn-Prediction-Challenge-by-Data-Science-Nigeria Expresso-Customer-Churn-Prediction This repository explains how to predict customer churn. An Hackathon Organized by Data Science Nigeria(DSN-AI) to help Expresso predict customer Churn. This is a solution that could have landed me the 22nd positon , log_loss of 0.247107562 on Zindi where the competition was hosted. 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 My Approach - Handled Missing Values - Preprocessed Catgegorical variables by mapping them - Feature Generation - KFold Validation - Model Blending Improvements that can be made - Feature Selection - Handling missing data more efficiently - Hyper-parameter tuning - Trying other algorithm