🛒 Customer Churn Prediction.

Telecom Customer segmentation and Churn Prediction

Predict whether a particular Telecom Customer will Churn or Not ?

Customer Churn Analysis with Neural Network

Build and evaluate logistic regression model using PySpark 3.0.1 library.

Prediction whether the customer will resign from the services of a telecommunication company.

Customer Churn Analysis

Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.

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.

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.

Customer Churn Prediction in the Banking sector

Customer retention is a critical stage for customer relationship management (CRM), especially for established businesses after their initial exponential growth. Churn management or attrition management is important as when customers leave, there arenegative impacts on revenues. Churn analytics has been widely applied to proactive customer retent…

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

My solution for DataCamp case study "Analyzing Customer Churn in Power BI".

This project involves helping a telecoms company better understand its customer churns.

Repo consists the customer behaviors in order to select the business areas of improvements, recommendation and revenue increments factor. As per market demand, we need to analyse out customers, so that we can optimize company revenue as per customer segmentations.

Challenge 2 of the FGA Data Science program where we have to predict whether a customer will stop using an ISP's service or not using machine learning model

A customer churn predictor using Watson Studio and Jupyter Notebooks