This advanced data science project predicts customer churn using a real-world telecom dataset. The goal is to identify high-risk customers and enable actionable retention strategies using machine learning and model interpretability.
Customer churn significantly impacts revenue. By identifying patterns and drivers behind churn, businesses can proactively retain customers. This project focuses on predicting which customers are likely to leave based on historical data.
Customer-Churn-Prediction/ ├── data/ │ ├── raw/ │ └── processed/ ├── notebooks/ │ ├── 01_data_preprocessing.ipynb │ ├── 02_modeling.ipynb │ └── 03_inference.ipynb ├── reports/ │ ├── figures/ │ └── churn_analysis.pdf ├── src/ │ ├── preprocessing.py │ ├── modeling.py │ └── utils.py ├── .gitignore ├── README.md ├── requirements.txt └── LICENSE