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200+ TELECOM CUSTOMER CHURN PREDICTION Q&A | DATA MINING & MACHINE LEARNING PROJECT | EDA, FEATURE ENGINEERING, SMOTE, XGBOOST, SHAP, MODEL EVALUATION & BUSINESS IMPACT | 2026 COMPLETE GUIDE
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137

May 2026

2025/2026

A+
Master telecom customer churn prediction with this 2026 project-based practice guide featuring 200+ realistic questions and detailed rationales. Covers the complete data science pipeline: business problem framing, EDA (contract type, tenure, payment method, add-on services), data preprocessing (missing values, one-hot encoding), feature engineering (aggregates, interactions), class imbalance (SMOTE), model training (Logistic Regression, Random Forest, XGBoost), evaluation (recall, precision, F1,...
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