Customer Churn Prediction App

Overview

The Customer Churn Prediction App is a Streamlit-based web application that predicts whether a customer is likely to churn based on input data. This tool provides insights for businesses to take proactive measures to retain customers, leveraging machine learning models trained on customer data.

Features

• Predict Customer Churn: Predict churn probabilities for individual customers.

Project Highlights

• Built using Python and deployed with Streamlit.
• Trained using a machine learning model to ensure accurate predictions.
• Easy-to-use interface suitable for non-technical users.

Setup and Installation

Prerequisites

• Python 3.8 or higher
• Required libraries listed in requirements.txt

Installation Steps

1. Clone the repository:

   git clone https://github.com/sdameer/Customer-Churn-Prediction
   cd Customer-Churn-Prediction

2. Install the dependencies:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run app.py

video

sample.video.mp4

Usage

1. Launch the app locally using the steps above or access the deployed version at click-here
2. Enter your data
3. Click on the "Predict" button to view the churn predictions.

Project Structure

customer-churn-prediction/
├── app.py               # Main application script
├── requirements.txt     # Python dependencies      
├── csv/                 # csv files
└── README.md            # Project documentation

Technologies Used

• Frontend: Streamlit
• Backend: Python
• Libraries: pandas, scikit-learn, numpy, matplotlib

Acknowledgments

• Streamlit for the web app framework.
• scikit-learn for machine learning tools.
• matplotlib for data visualization.

Contact

For questions or suggestions, feel free to reach out:

• GitHub: sdameer

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Start predicting customer churn today with the Customer Churn Prediction App!

link : click-here