This project focuses on predicting customer churn using machine learning. The dataset is preprocessed to handle categorical variables, and a logistic regression model is trained for prediction. The model is deployed as a Streamlit app, allowing real-time predictions and insights. This tool empowers businesses to take proactive measures to reduce customer churn and enhance profitability.

1. Clone the repository.
2. Install the required packages using pip install -r requirements.txt.
3. Run the Streamlit app using streamlit run Churn.py.

• Churn.py: The main Streamlit app for user interaction.
• model.pkl: The trained logistic regression model.
• requirements.txt: A list of required Python packages.