aliduabubakari/Expresso-Telco-Churn-Classification

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,” # Expresso-Telco-Churn-Classification ## Project Overview 🚀 The Expresso-Telco-Churn-Classification challenge focuses on developing a machine learning model for an African telecommunications company. The objective is to predict customer churn, which refers to customers becoming inactive and not making any transactions for 90 days. By identifying potential churners, the company can take proactive measures to retain customers and improve satisfaction. This solution will help this telecom company to better serve their customers by understanding which customers are at risk of leaving. ## Table of Contents - Project Overview - Getting Started - Data - Modeling - Evaluation - Deployment - Contact ## Objectives 🎯 : - 📌 Objective 1: Data Exploration :mag_right: - 📌 Objective 2: Data Preprocessing :gear: - 📌 Objective 3: Model Selection and Training :computer: - 📌 Objective 4: Model Evaluation and Optimization :chart_with_upwards_trend: - 📌 Objective 5: Interpretation and Insights :bulb: - 📌 Objective 6: Deployment and Future Improvements :rocket: ## Summary | Code | Name | Published Article | Deployed App | Streamlit App | |------|-----------------------------------------------------|------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------| | Capstone | Churn Prediction Classification with FastAPI and Streamlit | Medium Article | FastAPI App | Streamlit App …