There are 7 repositories under customer-churn-analysis topic.
Customers in the telecom industry can choose from a variety of service providers and actively switch from one to the next. With the help of ML classification algorithms, we are going to predict the Churn.
Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn. ➡️
The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022. We need to predict whether the customer will churn, stay or join the company based on the parameters of the dataset.
Analysis and Prediction of the Customer Churn Using Machine Learning Models (Highest Accuracy) and Plotly Library
Customer Analytics
Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.
Customer Churn Analysis Report using powerbi
Build and evaluate logistic regression model using PySpark 3.0.1 library.
Customer Churn Analysis with Neural Network
Telecom Customer segmentation and Churn Prediction
This project focuses on a fictitious software company, Churn Buster, that is pitching their tool to Telecom Inc., a fictitious wireless service company. Churn Buster has built a predictive model to reduce Telecom Inc.'s customer churn
We utilize customer account data to visualize churn rate based on various factors. Additionally, we predict customer churn using a logistic regression model provided by scikit-learn.
A customer churn predictor using Watson Studio and Jupyter Notebooks
Derive insights of factors contributing to customer churn in the Telecom Industry.
In this project, we embark on an exciting journey to explore and analyze customer churn within the Telecom network service using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework.
Hello, this is my final project with my friend when I joined Fresh Graduate Academy Program at Binar Academy in 2023.
Customer Churn Analysis
My solution for DataCamp case study "Analyzing Customer Churn in Power BI".
This Python report is designed for a business which is worried by high customer churn.
Prediction of whether or not a customer leaves in an specific period of time, deployed to GCP
Precision-driven customer churn analysis using CatBoost for accurate predictions and insightful model evaluation.
Analyzing e-Commerce company customer churn and providing business recommendations
This project aims to predict bank customer churn using a dataset derived from the Bank Customer Churn Prediction dataset available on Kaggle. The dataset for this competition has been generated from a deep learning model trained on the original dataset, with feature distributions being similar but not identical to the original data.
Predictive model of customer churn of Bank and Marketing
This contains some of the data analysis projects I have worked on in excel.
Tree methods for customer churn prediction. Creating a model to predict whether or not a customer will Churn .
Analysis of Bank customers Data to know custmer churn.
Repositorio del proyecto de predicción del problema Telco Customer Churn (kaggle)
Perform exploratory data analysis and develop machine learning models to a telecom customer churning dataset
Customer churn analysis on the Telco dataset in R
Performed predictive analysis of customer churn in the banking industry and identify the factors that led customers to churn. Customer churn or customer attrition is the phenomenon where customers of a business no longer purchase or interact with the business.
This project aims to aims to predict the customer churn (likelihood of a customer leaving the company) for a telecom company using a variety of ML classification algorithms.
Built a churn prediction model to retain subscription customers. Expertly preprocessed data, engineered features, and optimized models for accuracy. Deployed the model via Flask for real-time predictions, showcasing end-to-end data science skills.