https://github.com/lakshitalearning/churninsight

Customer Churn prediction means knowing which customers are likely to leave or unsubscribe from your service.
https://github.com/lakshitalearning/churninsight

churn-prediction data-science flask google-colab machine-learning predictive-analytics python scikit-learn user-retention web-development

Last synced: about 2 months ago
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Customer Churn prediction means knowing which customers are likely to leave or unsubscribe from your service.

• Host: GitHub
• URL: https://github.com/lakshitalearning/churninsight
• Owner: Lakshitalearning
• Created: 2024-07-29T08:27:59.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-09T12:12:00.000Z (5 months ago)
• Last Synced: 2024-08-23T14:50:19.756Z (4 months ago)
• Topics: churn-prediction, data-science, flask, google-colab, machine-learning, predictive-analytics, python, scikit-learn, user-retention, web-development
• Language: Jupyter Notebook
• Homepage:
• Size: 5.38 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.txt

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README

        

Churn Prediction App

Predicting user churn with machine learning and web development

Overview

This repository contains the code for a Churn Prediction App, built as part of my internship at Codsoft. The app uses machine learning algorithms to identify users at risk of leaving a platform, and provides actionable recommendations to reduce churn rates.

Features

- User-friendly interface for uploading data and viewing predictions

- Interactive visualizations for exploring user behavior and churn trends

- Robust machine learning model for accurate predictions

- Seamless web development for a smooth user experience

Tech Stack

- Python for backend development and data analysis

- Flask for web application development

- Scikit-learn for machine learning tasks

- Pandas, NumPy for data manipulation

- HTML, CSS, JavaScript for frontend development

Usage

1. Clone the repository and install dependencies

2. Upload your dataset to the app

3. View predictions and explore user behavior with interactive visualizations

4. Use actionable recommendations to reduce churn rates

Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

License

This project is licensed under the MIT License. See LICENSE for details.