Churn Prediction Model + Action Plan
Build a churn prediction model with gradient boosting. The classic but still highly relevant DS project.
Pythonpandasscikit-learnXGBoost or LightGBMSHAP
About this project
Churn prediction is the canonical DS portfolio piece. What makes this one stand out: feature engineering depth, proper validation (no leakage), interpretability (SHAP), and an action plan — what should the business do with these predictions? Use a public dataset (telecom churn, customer dataset). Model is one part; the business writeup is the other.
Why build this in 2026?
Tree-based models still beat deep learning on tabular data — and tabular is 80% of business ML.
What you'll ship
- Jupyter notebook
Model card (interpretability + risks)
Business action plan (2 pages)
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Skills you'll practice
pythonmachine learningscikit-learnpandas