https://github.com/anushkundu/churn-prediction

Telecom Customer Churn Prediction Using Machine Learning!
https://github.com/anushkundu/churn-prediction

accuracy-score classification-algorithm classification-report data-analysis data-science deep-learning gradient-boosting-classifier keras-tensorflow logistic-regression machine-learning random-forest-classifier recall-precision roc-auc-score smote-sampling svm-classifier

Last synced: 7 months ago
JSON representation

Telecom Customer Churn Prediction Using Machine Learning!

• Host: GitHub
• URL: https://github.com/anushkundu/churn-prediction
• Owner: anushkundu
• Created: 2024-12-31T21:34:39.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-02-10T21:36:10.000Z (8 months ago)
• Last Synced: 2025-02-10T22:30:23.531Z (8 months ago)
• Topics: accuracy-score, classification-algorithm, classification-report, data-analysis, data-science, deep-learning, gradient-boosting-classifier, keras-tensorflow, logistic-regression, machine-learning, random-forest-classifier, recall-precision, roc-auc-score, smote-sampling, svm-classifier
• Language: Jupyter Notebook
• Homepage:
• Size: 603 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          

# Telecom Customer Churn Prediction Using Machine Learning!

The **Telco Customer Churn Dataset** is commonly used for predicting customer retention in the telecommunications industry. Here’s a breakdown of the dataset and its significance:

**Dataset Overview:**

*Rows:* Each row represents a unique customer.

*Columns:* Contain information about customer demographics, account details, services subscribed to, and whether the customer has churned (left the service).

**Key Features:**

*Demographic Information:* gender, SeniorCitizen, Partner, Dependents.

*Service Details:* PhoneService, MultipleLines, InternetService, 

OnlineSecurity, TechSupport, etc.

*Account Information:* tenure (how long the customer has been with the company), Contract, MonthlyCharges, TotalCharges.

*Target Variable:* Churn – whether the customer left the company or stayed (Yes/No).

**Objective:**

Main goal is to predict customer churn, which refers to whether a customer will leave the company based on their historical data.