This code provides a glimpse on how to analyse Churn, Appetency and Upselling using R

Telecom Churn prediction Using Logistic Regression and Random Forest in R

Machine Learning Project

Predicting Employee Churn with Supervised Machine Learning

Collection of university projects exams

An End-to-End Data Science Project: Churn Prediction for Bank Customers

Churn Prediction using Keras/ANN with Flask Deployment.

Repository to analyse and predict the churn in a telcom company.

EDA on the “Telecom users” dataset to gain insight into how customers’ demographics and behaviors have impact on churn. Three models were built with logistic regressor, random forest classifier, and gradient boosting classifier to predict whether clients would renew the contracts. The best-performed model, logistic regressor, reached an 80% accu…

A vanilla feed forward neural network design to predict a person will churn or not.

Bank Customers Churn Prediction using Artificial Neural Network.

Predicting which customers will churn and assign them an account manager.

Supervised Machine Learning for potential churn customer prediction

Identificación de acciones concretas que ayuden a prevenir la pérdida de clientes (churn).

An AI based technique to determine which employee going to leave or stay in the company.

This repository contains the completion of challenges in the Data Science Batch 1, FGA Kominfo RI x Binar Academy program. It focuses on predicting customer churn in a telecom company using machine learning classification approaches.

Customer Churn Prediction using Artificial Neural Networks

A predictive model for player retention/churn on day-14 after game installation based on features such as in-game metrics, user behavior, and engagement patterns to identify players at risk of churning, accurately predicting 65% of all retention within the top 6% of total population.

A webapp to predict Churn against customers and employees, along with feature for data visualization