churn-analysis
There are 1 repository under churn-analysis topic.
klaudia-nazarko / iv-and-woe-python
This repository contains analysis of churn in telephone service company (using IV and WOE), comparison of effect size and information value and quick tutorial how to use information value module (created for this analysis).
Language:Jupyter Notebook 48TatevKaren / artificial-neural-network-business_case_study
Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)
Language:Python 47DataVisualizationExpert / Customer-Churn-Analysis-using-Power-BI
Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn. ➡️
TarikKaanKoc / MonoChurnAnalyzer
Churn Analyzer: Analyze and understand user churn rate in your PostgreSQL database effortlessly.
Language:Jupyter Notebook 7Kaendor / quality-time
Command line tool to generate actionable metrics for priorizing refactors on your rust project
Language:Rust 5yakhlebopros / ChurnDataVisualisation
visualisation of churn data of a bank
Language:Jupyter Notebook 5d0r1h / Churn-Analysis
Customer Churn Analysis for a website
Language:Jupyter Notebook 4richhuwtaylor / fighting-churn
A project demonstrating how to predict customer churn based on product usage behaviours.
Language:Jupyter Notebook 4aadimangla / Churn-Modelling-for-a-Bank
A churn model is a mathematical representation of how churn impacts your business. Churn calculations are built on existing data (the number of customers who left your service during a given time period). A predictive churn model extrapolates on this data to show future potential churn rates.
Language:Python 3AshNumpy / DL-Churn-Analysis
Churn rate analysis with artificial neural network.
Language:Jupyter Notebook 3AtashfarazNavid / MachineLearing-ChurnModeling
Machine-Learning-1
Language:Jupyter Notebook 3duartejr / challenge_data_science_alura_voz
Challenge de Data Science da Alura - Alura-Voz
Language:Jupyter Notebook 3santanukumar666 / Data-analysis-projects
Exploratory data analysis of datasets available in Kaggle.(IPL dataset, Zomato dataset, Loan dataset, Telecom customer churn dataset)
Language:Jupyter Notebook 3amrelauoty / Customer-Retention-PhoneNow
PhoneNow Customer Retention Analysis - PwC Switzerland virtual case experience
IST434 Big data analytics end of term paper
Language:TeX 2babaniyi / BCG
Used Random Forest model to predict customers likely to churn and recommended discount and pricing strategies to improve customers retention.
Language:Jupyter Notebook 2jimschacko / Churn-Modelling-using-XGBoost
Churn Modelling using XGBoost
Language:Jupyter Notebook 2Lacerdash / Alura_Challenge_Data_Science
Challenge de Data Science desenvolvido pela Alura, para montar um conjunto de análises e modelos de machine learning supervisionado para auxiliar o time de vendas da empresa Alura Voz a fidelizar clientes.
Language:Jupyter Notebook 2olucaslopes / customer-churn-analysis
Análise e predição do Churn de clientes de uma empresa de Telecomunicações.
Language:Jupyter Notebook 2raunak274 / Churn_Analysis
Importance of churn Analysis and some concept upon it
Language:Jupyter Notebook 2TayJen / Customer-Churn-Prediction
Customer Churn Prediction with data from Kaggle
Language:Jupyter Notebook 2yacine-ammi / Mobile-CCP
This repository is created to share the steps that were taken in making my Graduation Thesis for my Applied Statistics Diploma, the project is about creating a machine learning model to predict the churn in a telecom company, this repository includes: The dataset used in the project, the relevant code, and the theisis in pdf.
Language:Jupyter Notebook 2alessiococchieri / BDA-project-sparkify
This Git repo showcases my analysis of Sparkify dataset with PySpark on Apache Spark cluster mode and JupyterLab on Docker. The goal was to identify at-risk customers and develop retention strategies. The analysis tested multiple machine learning models and uncovered insights into customer behavior and churn patterns.
Language:Jupyter Notebook 1DataNomadX / Customer-Retention-and-Service-Optimization-
By undertaking this project, the company aims to gain valuable insights into customer behavior, enhance service quality, and implement targeted strategies for customer retention and satisfaction. The findings will contribute to informed decision-making and the development of customer-centric business strategies.
facf00 / Credit-Card---Churn-Rate
The credit churn data analysis aims to investigate the factors that contribute to customer attrition in a credit card company. The dataset used in this analysis contains information on customer demographics, credit card usage, and other relevant variables.
Language:HTML 1gabrielmotablima / DS002--churn-solutions--Telecom
✨ The current project is a basic approach of data analysis and machine learning modeling to get business insights and propose strategies of customer segmentation and churn prediction to mitigate the high churn rate.
Language:Jupyter Notebook 1Harshit-Sinha-49 / Customer-Churn-Analysis
Customer Churn Analysis in Telecom Industry
Language:Jupyter Notebook 1Hosseinglm / Uber_driver_churn_analysis_BigData
Driver churn analysis based on Uber dataset using big data tools such as Hive, PySpark, Pig, Hbase, and MongoDB.
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marbel89 / sql_churn_rate
Churn rate calculation with SQL of a fictional dataset, analysis and presentation. The PDF slide presentation contains the code, explanations and conclusions. The .sqlite file contains the code for the different objectives.
- Language:Jupyter Notebook 1
- Churn-Rate-Machine-Learning
npagrawal / Churn-Rate-Machine-Learning
How can we anticipate which customers will take their business elsewhere? Finding key predictors of customer churn via machine learning.
Language:Jupyter Notebook 1 rasmodev / Customer-Churn-Prediction-Machine-Learning-Classification-Project
This repository presents a machine learning classification project focused on predicting customer churn in the telecommunications industry.
Language:Jupyter Notebook 1Reign2121 / Survival-analysis
survival and churn analysis in biz domain
Language:R 1Rose-njeru / Credit-Card-Churn-Analysis
Analysing bank credit card data and predict which group of customers are more likely to get churned so that we can target them to provide better services and turn customers' decisions in the opposite direction using MySQL and Tableau
thanhhuyentran32 / HR-Analytics-Case-Study
The analysis delves into the factors that have the biggest impact on employee churn and need to be addressed immediately. It then suggests several changes the XYZ company should make in the workplace to retain more employees.
