Github Rsalavala Data Science Project Telco Customer Churn

Github Rsalavala Data Science Project Telco Customer Churn Contribute to rsalavala data science project telco customer churn development by creating an account on github. Github is where people build software. more than 100 million people use github to discover, fork, and contribute to over 330 million projects.

Github Dhykac Telco Customer Churn This project focuses on customer churn prediction for a telecommunications company, aiming to identify high risk customers and optimize retention strategies. using machine learning techniques and various resampling methods, the model predicts whether customers will churn based on their subscription history and other features. To identify key patterns and risk factors contributing to customer churn at a telecom company. this solution empowers business stakeholders to take proactive retention actions. Delivered a predictive model that can be integrated into a crm to flag at risk customers. this project focuses on predicting customer churn for a telecommunications company using machine learning and data analytics techniques. 📊 telecom customer churn analysis this project performs exploratory data analysis (eda) on a telecom dataset to uncover customer churn patterns, visualize trends, and provide insights.

Github Dipanshujaiswal Telco Customer Churn Analysis Delivered a predictive model that can be integrated into a crm to flag at risk customers. this project focuses on predicting customer churn for a telecommunications company using machine learning and data analytics techniques. 📊 telecom customer churn analysis this project performs exploratory data analysis (eda) on a telecom dataset to uncover customer churn patterns, visualize trends, and provide insights. Customer churn is a major challenge for telecommunication companies, leading to significant revenue loss and increased customer acquisition costs. predicting and understanding customer churn enables businesses to implement targeted retention strategies and improve customer satisfaction. This repository contains an end to end churn analysis project for a telecom dataset. it combines data science (python) and business intelligence (power bi) to identify factors influencing customer. The purpose of this project is to predict customer churn in a telecommunications company. the analysis focuses on: identifying behavioral patterns of customers who cancel their service. evaluating the most influential variables in churn prediction. training and comparing machine learning models to determine the most effective one. In this project, i designed a predictive model to determine the probability that customers will leave the service (churn) or continue to use the service (retain) at a telco company and achieve a sensitivity score of 80%.