This web application is designed to predict customer churn using an Artificial Neural Network (ANN). The app is built using Streamlit, a Python library for creating interactive web applications.
A live demo of the application is available at https://prajuktadey-customer-churn-prediction.streamlit.app/.
Customer churn refers to the phenomenon of customers discontinuing their business relationship with a company. Predicting customer churn is crucial for businesses to understand customer behavior and take proactive measures to retain them.
This app provides a user-friendly interface to input customer data and predict the likelihood of churn using an Artificial Neural Network model. The app takes various customer-related features as inputs, such as customer demographics, usage patterns, and service history, and generates a churn prediction based on the trained model.
To run the application locally, follow these steps:
-
Clone the repository:
git clone https://github.com/your-username/customer-churn-prediction.git -
Install the required dependencies:
-
pip install -r requirements.txt -
Run the Streamlit app:
streamlit run main.py -
Access the app in your web browser by visiting
http://localhost:8501.
The project directory contains the following files and directories:
main.py: The main application file that defines the Streamlit app and its user interface.model.sav: The pre-trained ANN model used for churn prediction.requirements.txt: The list of required Python packages and their versions.
The following Python packages are used in this project:
- Streamlit:
streamlit - NumPy:
numpy - Pandas:
pandas - Scikit-learn:
scikit-learn - TensorFlow:
tensorflow - Keras:
keras
You can find the complete list of dependencies and their versions in the requirements.txt file.