GitHub topics: churn-prediction | Ecosyste.ms: Repos

halacoded/Churn-Prediction-Model-Based-on-Huawei-SmartCare

Developed as part of the Huawei Internship Program in collaboration with Kuwait University. It replicates a simplified version of Huawei SmartCare’s churn analysis capabilities using public telecom data.

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Eswarpuli/bank-customer-churn-prediction

Machine learning app to predict bank customer churn using Streamlit and Random Forest

Language: Python - Size: 0 Bytes - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 0 - Forks: 0

fjk1533/smurphcast

SmurphCast – percentage‑first time‑series forecasting (churn, CTR, conversion, retention) with additive + GBM + ES‑RNN stacking and automatic model selection. 100 % Python, CPU‑friendly, explainable.

Language: Python - Size: 69.3 KB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 1 - Forks: 0

Arrehman507/ANN-Customer-Churn-Prediction

Predict customer churn using an Artificial Neural Network (ANN) with the Churn_Modelling dataset. Explore data preprocessing, model training, and evaluation. 🐙🌟

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faradayio/faraday-js

Typescript library to access Faraday's API infrastructure for B2C predictions

Language: TypeScript - Size: 1.66 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 24 - Forks: 1

vinit714/Player-Retention-Analysis

A complete Streamlit + Machine Learning + SHAP + NLP project to analyze, predict, and improve player retention in games. This project simulates a game environment, models churn behavior, and provides insights using SHAP, NLP word clouds, and strategy simulators.

Language: Python - Size: 207 KB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0

vleonel-junior/customer-churn-ft_transformer

Ce dépôt propose des modèles FT-Transformer interprétables (ftt, ftt_plus, ftt_plus_plus, ftt_random) pour prédire et expliquer le churn client dans la banque et les télécoms, une première dans la littérature.

Language: Python - Size: 485 KB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0

gattsu001/Telecom-Churn-Predictor

Predicts which telecom customers are likely to churn with 95% accuracy using engineered features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

Language: Python - Size: 191 KB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 1 - Forks: 0

nguyenbinhminh85/Telco-Customer-Churn-Prediction-ML-Streamlit

This repository contains a complete churn prediction pipeline using logistic regression and Streamlit, aimed at helping telecom companies retain customers. Explore the dataset and model to understand customer behavior and reduce churn risk effectively. 🐙💻

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RozaAbolghasemi/Churn_Prediction

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Hippaho/Sparkify

A music streaming company, Sparkify, has decided that it is time to introduce more automation and monitoring to their data warehouse ETL pipelines and come to the conclusion that the best tool to achieve this is Apache Airflow.

Language: Python - Size: 17.6 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0

nirmal2i43a5/Employee-Churn-Prediction

An interactive HR-analytics app predicting employee churn via scikit-learn pipelines and Streamlit

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marcolomele/churn-bcgx

Solution for a customer churn prediction competition judged by BCG X. Includes data processing, model training, evaluation, and inference scripts. Project is completed.

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ragulpr/wtte-rnn

WTTE-RNN a framework for churn and time to event prediction

Language: Python - Size: 9.11 MB - Last synced at: 3 days ago - Pushed at: almost 5 years ago - Stars: 775 - Forks: 189

alex123m2r/customer-churn-dashboard

A snappy Flask dashboard to predict customer churn, save revenue, and sass you with an AI chatbot. Keep customers from ghosting! 📊🤖

Language: Python - Size: 289 KB - Last synced at: 6 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0

JoaquinCortezHub/churn-rate-prediction-model

Project that aims to build a model that predicts the churn rate of a company and offers business insights and recommendations to reduce losses.

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Harsh071202/Customer_Churn_Prediction_App

A Streamlit-based churn prediction app using a trained Random Forest model to analyze customer behavior and predict churn based on demographics, spending, interaction history, and service usage.

Language: Python - Size: 189 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0

cloudera/CML_AMP_Churn_Prediction

Build an scikit-learn model to predict churn using customer telco data.

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ItsTSH/Customer-Churn-Prediction

Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset

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KoradaPavani/Customer-Churn-ML-Project

Machine learning project to predict customer churn in telecom

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ReverendBayes/AI-Powered-Call-Center-Intelligence

Real-time behavioral intelligence for call centers. Transcribes support calls, redacts PII, extracts emotional tone, classifies issues, and delivers insight-rich dashboards — powered by GPT-3.5 (cheap tokens), Whisper, DuckDB, and a polished React+TypeScript frontend. No Azure. No Power BI. No vendor lock-in. Just full-stack AI that runs local.

Language: Python - Size: 1.59 MB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 3 - Forks: 0

taqi-jpg/customer-churn-dashboard

📉 Interactive Streamlit dashboard to visualize and predict customer churn using Telco dataset. Built with Python.

Language: Python - Size: 354 KB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

V41BH4VR4JPUT/Churm-Prediction

A machine learning-powered dashboard for predicting customer churn. This project covers everything from data preprocessing to model building, evaluation, and a Streamlit-based dashboard for visual insights and predictions.

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Akwardhan/Telco-Customer-Churn-Prediction-ML-Streamlit

End-to-end customer churn prediction pipeline on Telco data. Includes advanced EDA, domain-specific feature engineering, interpretable logistic regression model (~80% accuracy), and real-time Streamlit deployment to support retention strategy and minimize churn loss. Designed for business analysts and ML practitioners in telecom use cases.

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tuni56/customer-churn-prediction

customer churn prediction using AWS SageMaker

Size: 1.05 MB - Last synced at: 3 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0

chicolucio/churn-prediction

Predicting customer churn with machine learning

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Anusha-me/Customer_churn_analysis

Predict and analyze telecom customer churn using machine learning techniques and business dashboards. This end-to-end project includes data preprocessing, EDA, model evaluation (SVM, XGBoost), real-time Streamlit deployment, and Power BI dashboard reporting. Built for actionable insights and decision support.

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kagor4/Churn-Prediction-for-Beta-Bank

Модель прогнозирования ухода клиентов для Бета-Банка с F1-мерой 0.61, построенная на RandomForestClassifier с учетом дисбаланса данных. Использованы Python и Scikit-learn.

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ThongSheng/deeplearning-churnmodeling

This project builds and optimizes a PyTorch neural network to predict customer churn using a bank customer dataset.

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hareeson/customer_churn_prediction_for_E-commerce

This repository contains a machine learning project focused on predicting customer churn for e-commerce platforms. It features data preprocessing, model training, and an interactive web app built with Streamlit. 🛒💻

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Yasouimo/Data_Mining_Project_Market_and_Customer_Analysis_Telco_Customer_Churn

Data Mining Project for Customer Analysis and Churn Prediction

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tuni56/churn-prediction-streamlit

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dhanraj-parigi/customer_churn_prediction_for_E-commerce

🔍 Predict customer churn for an e-commerce platform using Logistic Regression and Decision Tree models. Built with Python, Streamlit, and ML tools for real-time insights.

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LouaiMuhammed/telecom-churn-prediction

End-to-end telecom customer churn analysis and prediction project, involving data cleaning, exploratory data analysis, and machine learning model development. This project was developed as part of the DEPI Internship.

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derrynknife/SurPyval

A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.

Language: Python - Size: 23.4 MB - Last synced at: 3 days ago - Pushed at: 8 months ago - Stars: 48 - Forks: 5

Onome-Joseph/Customer-Churn-Prediction

This project predicts whether a customer is likely to stop patronizing a business by making use of historical customer data.

Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

anonymo2239/Big-Data-Churn-Analyzer

Scalable customer churn prediction using PySpark. Includes EDA, feature engineering, modeling, and real-time inference on new data.

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sanchopedro/india-churn-analysis

O Projeto tem como objetivo prever a rotatividade de clientes (churn) no setor de telecomunicações indiano. Utilizando técnicas de ciência de dados e aprendizado de máquina, o projeto busca identificar padrões de comportamento que indicam a probabilidade de um cliente cancelar os serviços oferecidos pela empresa.

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zargiteddy/Bank-Customer-Churn-Prediction

Bank Customer Churn Prediction using Random Forest Classifier

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zhull1988/Telecom-Customer-Churn-Analysis

Exploratory data analysis of telecom customer churn using Python. Includes data cleaning, visualization, and statistical tests to understand churn behavior.

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rupesh40/mlflow-churn-prediction

A complete MLflow demo project for customer churn prediction with Random Forest, featuring experiment tracking, model packaging, and deployment.

Language: Python - Size: 4.47 MB - Last synced at: 8 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

deepak1400/Tele_Customer_Churn-

Comprehensive Telecom Customer Churn Analysis using SQL and Python . This project focuses on data cleaning , transformation , and visualization to uncover key insights into customer behaviour , churn pattern , and retention strategies. It include EDA, feature engineering , and predictive modelling to help telecom companies reduce churn

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Haonan-100/Yelp-User-Churn-Prediction-and-Business-Activity-Analysis

End-to-end churn prediction and business-activity analysis on the Yelp Open Dataset 2024 — XGBoost for user churn, heuristics for business decline, and four interactive Tableau dashboards.

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MadScie254/customer_churn

A dynamic and interactive web app for predicting customer churn using machine learning, with a user-friendly interface built with Streamlit. The app utilizes an XGBoost classifier to make churn predictions and provides real-time feedback with engaging animations.

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Cyberoctane29/Deutsche-Bank-Customer-Churn-Prediction-End-to-End-Analysis-and-Modeling

This project predicts customer churn for Deutsche Bank using supervised machine learning. It involves data exploration, feature engineering, and building Naive Bayes, Decision Tree, Random Forest, and XGBoost models. Models are tuned, evaluated, and compared to identify the best approach for churn prediction.

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susmnty/Client-IQ

The project focuses on predicting customer status using machine learning. It classifies customers as active, inactive, or at risk. Python and ML libraries are used for data analysis and modeling. The goal is to help businesses reduce churn. It supports better decision-making through predictive insights.

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ietimfon/Customer-Churn-Prediction-for-a-Telecom-Company

This project develops a machine learning system to predict customer churn for a Telecom company. The solution helps identify at-risk customers and provides actionable insights to reduce churn rates.

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ReverendBayes/Telecom-Churn-Predictor

Predicts which telecom customers are likely to churn with 95% accuracy using real-world data features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

Language: Python - Size: 242 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

Keerthi-muppulakunta/Telecom-customer-churn-analysis

Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn.

Size: 1.53 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

shyamal-bhatt/Customer-Churn-Prediction-Retention-Strategy-Using-SQL-Power-BI-Machine-Learning

End-to-end customer churn prediction pipeline using SQL, ML, and Power BI. Trained and tracked multiple models with MLflow, selected LightGBM with 0.90 F1 score on balanced data, and integrated predictions into a Power BI dashboard for actionable insights.

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veydantkatyal/churn-prediction

built using Multilayer Perceptrons (MLP) to predict customer churn for a business.

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gaurav-bhadane/ANN_Churn_Prediction

This project aims to predict customer churn using an Artificial Neural Network (ANN) model. The model is built using TensorFlow and Keras.

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Koldim2001/Binary_classification_of_users

Бинарная классификация пользователей образовательной платформы Stepic на тех, кто скорее всего пройдет курс до конца и тех, кто скорее всего покинет платформу. Модель способна давать предсказания по анализу поведения юзеров на сайте за первые 3 дня

Language: Jupyter Notebook - Size: 675 KB - Last synced at: 10 days ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

JamesCWeber/BCG-X-Data-Science-Project-Part-3-Churn-Prediction

The last task given to me while completing the BCG X Data Science microinternship. Create a Random Forest model using data from part 2. The model will predict which customers will churn and what features are influential to customer's decision to churn.

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JamesCWeber/PWC-Power-BI-Project-Part-2-Customer-Churn-Dashboard

The second task given to me while completing the PWC Power BI microinternship. Use the excel file and Power BI to create a dashboard to help identify potential reason for customer churn.

Size: 1.58 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

MohammedSaim-Quadri/ANN-Classification-Churn

Predict customer churn using a deep learning ANN model deployed with Streamlit. Interactive UI, real-time predictions, and model trained on a real-world banking dataset.

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Yashwardhan2519/Deployment_final

Customer_churn_Predictor

Language: Python - Size: 183 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

vijaykumar1799/Customer-Churn-Prediction-Retention-Strategy

Practical customer churn analysis and prediction using Python, XGBoost, and real-world business insights.

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ghoumbadji/Analyzing_Customer_Churn_for_a_Telecom_Company

The project involves utilizing various machine learning techniques, both supervised and unsupervised, to detect customer churn and identify the key factors contributing to it.

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EsraaKamel11/Predict-Customer-Churn

Predicting customer churn using ML with clean code, EDA, and model evaluation.

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ankitparwatkar/Customer-Churn-Prediction

📊 Customer Churn Prediction App A Streamlit-powered dashboard that predicts customer churn risk using a TensorFlow neural network. Input customer details (credit score, tenure, activity, etc.) and instantly see predictions with explainable AI insights. Built for businesses to reduce attrition proactively.

Language: Jupyter Notebook - Size: 282 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

cemdurakk/telco-customer-churn-prediction

An end-to-end machine learning project to predict customer churn in the telecom industry using XGBoost and SHAP explainability.

Language: Jupyter Notebook - Size: 484 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Halsted312/smurphcast

SmurphCast – percentage‑first time‑series forecasting (churn, CTR, conversion, retention) with additive + GBM + ES‑RNN stacking and automatic model selection. 100 % Python, CPU‑friendly, explainable.

Language: Python - Size: 85 KB - Last synced at: 3 days ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

Agungvpzz/Telco-Churn-Analysis

Identified patterns and reasons behind customer attrition.

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MasterMindRomii/Customer-Churn-Prediction-Final-Year-Project

Built an ML model to predict customer churn, enhancing retention strategies.

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nurulashraf/telco-customer-churn-prediction-model

This repository contains a Telco Customer Churn Prediction project using machine learning. It includes data preprocessing, exploratory data analysis, feature engineering, and model development to predict customer churn. Key tools used are Python, Pandas, NumPy, Matplotlib, Seaborn, and scikit-learn.

Language: Jupyter Notebook - Size: 539 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

evelyncy96/Customer_Churn_Prediction_Using_PySpark

This project aims to leverage big data technologies to help OTT platforms predict churn at a customer level in real-time. We use Amazon S3 as the data storage, Databricks for data processing, spark MLlib for machine learning, and Amazon Quicksight for visualization.

Language: Jupyter Notebook - Size: 1.69 MB - Last synced at: about 1 month ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 1

l1ght14/customer-churn-prediction

Predict customer churn using machine learning models like Logistic Regression and Random Forest. Includes data preprocessing, model evaluation, feature importance, and insights to drive retention strategies.

Language: Jupyter Notebook - Size: 2.75 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

abu14/churn-prediction

This project assesses the likelihood of customer churn using various performance metrics. It employs multiple algorithms, including Logistic Regression, Random Forest, and XGBoost Classifier, to achieve Accuracy of 80% & ROC-AUC score of 79%

Language: Jupyter Notebook - Size: 8.21 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 1

TheDataTenno/Churn-Prediction

A machine learning project to predict customer churn using classification models with SMOTE and hyperparameter tuning."

Language: Jupyter Notebook - Size: 1.73 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

a-memme/Customer_Churn_and_CLTV

BG/NBD and Gamma Gamma probabilistic models to evaluate and predict customer churn, retention, and lifetime value of an e-commerce business

Language: Jupyter Notebook - Size: 2.51 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 4 - Forks: 1

SaiLikith14/Churn_prediction

This project aims to predict employee churn using machine learning algorithms.

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xenon1919/Churn-Prediction-using-XGBoost

This project is an AI-powered web application built with Streamlit, utilizing XGBoost to predict customer churn. It analyzes customer data to determine whether a customer will stay or leave a company based on financial and demographic details.

Language: Jupyter Notebook - Size: 3.37 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

felipesbonatti/case-churn

Estudo de caso sobre previsão de churn em um serviço de streaming, utilizando machine learning e análise não supervisionada para identificar padrões e reduzir a evasão de clientes.

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luissancho/churn-prediction-model

A deep learning model for churn prediction in subscription services based on user events, usage momentum and behaviour.

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sawallesalfo/Retail-360

Customers knowledge, supply chain movement and sales forecasting, Customer Lifetime value, churn and survival analysis

Language: Python - Size: 5.79 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 0

Yash22222/Predicting-Customer-Churn-for-Subscription-Based-Services

A Flask-based web app that predicts customer churn using ML models and suggests retention strategies.

Language: Jupyter Notebook - Size: 1.38 MB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 0 - Forks: 1

pyramidheadshark/customer-churn-interactive-research

Interactive customern churn research utilizing lightgbm made for practice

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Pegah-Ardehkhani/Customer-Churn-Prediction-and-Analysis

Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library

Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: about 10 hours ago - Pushed at: over 2 years ago - Stars: 10 - Forks: 4

imsanjoykb/Sales-and-Marketing-Analytics

This repository consists of predicting dynamic pricing, churn predictions using sales and marketing data for understanding users' behaviour.

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ivanseldas/microcredit-churn-classifier Fork of ironhack-labs/project-1-ironhack-payments-es

Developed a machine learning pipeline to predict customer churn with over 90% accuracy, leveraging data preprocessing, feature engineering, and Random Forest modelling. Conducted exploratory data analysis to uncover key drivers of churn, such as customer recency and cohorts from first transations.

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sreyash1mohanty/E-COMMERCE_MARKETING_MACHINE_LEARNING

Machine Learning in Marketing using various machine learning algorithms.

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yeopster/churn-prediction-GCP

Churn Prediction Machine Learning Using Google Cloud Platform

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Aduobey/Telecom-Churn-Prediction

A machine learning project for predicting customer churn in the telecom industr

Language: Jupyter Notebook - Size: 262 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

sanskaryo/Churn-Prediction-Using_ANN

Banking customer churn prediction using ann

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sameer-at-git/InternIntelligence_Customer-Churn-Prediction

Predicting customer churn using machine learning techniques. It includes data preprocessing, model training, and evaluation using the Telco Customer Churn dataset. The repository contains a Jupyter Notebook, trained model files, and encoders for easy predictions on new data.

Language: Jupyter Notebook - Size: 5.25 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

mxagar/churn_model_monitoring

A dynamic risk assessment system in which a customer churn model is monitored after deployment.

Language: Python - Size: 456 KB - Last synced at: about 6 hours ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

subhanu-dev/Customer-Churn-Prediction---Bank

Bank Customer Churn Prediction Model for an European Bank

Language: Jupyter Notebook - Size: 32.2 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

Nishita76/Customer-Churn-Prediction

IBM Telco customer churn prediction

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awslabs/aws-customer-churn-pipeline

An End to End Customer Churn Prediction solution using AWS services.

Language: Jupyter Notebook - Size: 10.1 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 40 - Forks: 22

mslawsky/waze-user-analytics

Data-driven analysis of user churn patterns to optimize retention strategies and enhance user engagement

Language: Python - Size: 3.73 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

beenish-Ishtiaq/DEP-Task-3-Customer-Churn-Prediction

A machine learning project to predict customer churn using an Artificial Neural Network (ANN) model. The goal is to accurately classify customers who are likely to churn based on their demographic and service usage information.

Language: Jupyter Notebook - Size: 390 KB - Last synced at: 3 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

irkky/Customer-Churn-Prediction

Explore Customer Churn Prediction - LogisticRegression

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AnishRane-cox/Telecom-Churn-Case-Study

A machine learning project aimed at predicting customer churn in the telecom industry. Given the high churn rates (15-25% annually), telecom companies must focus on customer retention to minimize revenue loss. The project involves exploratory data analysis (EDA), feature engineering, and model building to classify customers

Language: Jupyter Notebook - Size: 29.6 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0