Classification, Catboost, Fastapi, Docker, Streamlit.
[payment_method], "MonthlyCharges": [monthly_charges], "TotalCharges": [total_charges] }) # Predict churn probability using the model churn_probability = model.predict_proba(new_customer_data)[:, 1] # Format churn probability formatted_churn_probability = "{:.2%}".format(churn_probability.item())