There are 3 repositories under churn-user-prediction topic.
Predicting user churn for a mobile health app called Diabesties. Capstone project for Galvanize Phoenix Data Science Immersive, October 2017.
Machine-Learning-1
This repository holding a case study on analysis churn in Telecom and building a machine learning model to classify the customer who is likely to churn, which includes EDA, Prediction Model Building, Presentation PDF.
Importance of churn Analysis and some concept upon it
DissertationCA2
Built a logistic regression based predictive model to identify customers at high risk of churn and identify the main indicators of churn.
Predicting Teleco churn dataset from Kaggle. In this repo, I take 3 solution notebooks and combine the analysis into one with some updates.
Tree methods for customer churn prediction. Creating a model to predict whether or not a customer will Churn .
Different methods for churn prediction
Build a model predicting which customers are likely to cancel subscription by analysis of their usage and habbits
R code to predict booking destination of new user
2023년 11월 대한산업공학회(UNIST) : 다중 역할 경험을 고려한 게임 유저 이탈 예측: 롤 게임을 중심으로, 1저자
Predict users churn for a music box app.
Projeto que engloba soluções de Analitycs para empresas do mercado financeiro. Neste projeto envolvemos problemas de Fraud Detection, Churn Detection e Credit Score.
Datathon with a retargeting ad company. Churn date prediction (Normalized RSME 38), clustering (98% Silhouette), automated identification of the gaps between best and average client within a cluster.
Telecom-Churn-Case-Study
Exploring various business cases by using a wide range of statistical methods and machine learning techniques
Build an End-to-End Data Science Project to predict customer churn for the Telecom industry and provide prescriptive countermeasures.
Analyzing factors leading to customers churning; predicting which customers' will churn?
Verwendung von Tidymodel zur Vorhersage der Kundenabwanderung. | Using Tidymodels to predict customer churn.
Binary classification project in PySpark on an AWS-EMR cluster to predict customer churn.
Churn analysis predictor, combining TensorFlow and Supervised Machine Learning
Predicts weather the customer will stay with the current telecom company or leave
Classificação de clientes para redução da Churn Rate
It is prediction strategy used to understand the the factors required to retains customers. Showcased classical machine learning algorithm to analyse and understand the telecom customer dataset using SVMs, Decisions Trees, Random Forests etc.
Focused customer retention programs
The effect of social interaction on individual churn decision in MMORPG Game
A comprehensive project predicting customer churn for a telecommunications company using Logistic Regression, Decision Trees, and Random Forest models. Includes data preprocessing, feature engineering, model evaluation, and result visualization to provide actionable insights for customer retention.
For any company, customer acquisition is important. At the same time, retaining the existing customers is also very important. So for predicting whether the customer will churn or not can be done easily using neural networks.
This repository contains a customer churn prediction model implemented using logistic regression.