Ibrahim-I-Babana/Customer-Churn-Prediction-Project-for-Azubian

This challenge is for 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 customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. ## **Customer-Churn-Prediction-Project-for-Azubian** ## ## Introduction This challenge is organized by Azubi Africa as a Capstone Project and made available on Zindi. Details of the project can be found here ### What is Customer Churn? It is the process of using data analysis and predictive modeling techniques to identify customers who are likely to stop using a product or service. Churn, in this context, refers to customer attrition or the loss of customers from this African Telecommunications Company. ### Project Description This challenge is for an African telecommunications company that provides customers with airtime and mobile data bundles. The solution will help this telecom company to better serve its customers by understanding which customers are at risk of leaving. ### Project Objective The objective of this challenge is to develop a machine learning model to predict the likelihood of each customer “churning,” i.e. becoming inactive and not making any transactions for 90 days. ### Project Outline * Define Business Questions * Define Hypothesis * Perform Exploratory Data Analysis * Perform Feature Processing & Engineering * Machine Learning Modelling and Hyperparameter Tuning * Develop Application with Gradio * Deploy Application in Hugging Face ### Evaluation The evaluation metric for this challenge is Area Under the Curve (AUC). The values representing Churn are 0 and 1. Where 1 indicates the customer churned and 0 indicates the customer stayed with the telecom company. ### Dataset Kindly find the dataset for this challenge here