FREE PROJECTS(CUSTOMER CHURN PREDICTION PROJECT)

CUSTOMER CHURN PREDICTION PROJECT:

Predicting customer turnover is an essential issue for organizations who want to keep their clients. Let's examine a few intriguing projects that are connected to this subject:

Attrition Prediction and Customer Survival Analysis: 

In this project, survival analysis models are utilized to determine how the probability of customer attrition varies over time. Furthermore, a Random Forest model forecasts the likelihood of a consumer leaving. One Flask web application is used to deploy the model1.

Tools: 

• Flask Random Forest
•  Survival Analysis.

Prediction of Telecom Customer Churn: 

This research, which focuses on the telecom sector, predicts churn using machine learning classification methods. It assists in identifying high-risk clients who may transfer service providers by evaluating data.1. Tools: Plotly, Pandas, scikit-learn, Python.

Client Churn Analysis using Power BI: 

This Power BI project offers useful information to increase client loyalty. It uses DAX expressions and Power BI as tools to proactively avoid churn and visualize risk factors1.

 
Completely Customer Churn Prediction: 

This project forecasts customer churn by using a gradient boost classifier. Gradient Boosting and Flask are the tools used. Preprocessing, model fitting, hyperparameter adjustment, and deployment via Flask API1 are all involved.

 
Kaggle Dataset Forecast for Customer Churn:

 This research forecasts whether a customer will join, stay, or churn based on data from a telecommunications firm. It's a fantastic illustration of practice1.
Tools: Kaggle dataset, data science.

Remember, understanding why customers churn is essential. Conduct exit interviews and test hypotheses against customer data to build effective prediction models 

GIT HUB LINK : CLICK HERE

https://drive.google.com/file/d/1mS_wMLotgUhU0ILVOwHthSBX2xBLP6Fd/view?usp=sharing