🛰️ Production-ready ML system for geomagnetic storm prediction | 98% AUC, 70% recall | Threshold-optimized ensemble with real-time inference | 29-year dataset (1996-2025) | NOAA SWPC operational standards | Complete MLOps pipeline

B2B sales lead quality prediction using XGBoost classifier. Achieves 81.06% ROC AUC and 84.74% recall on 7,420 IT sales leads. Handles class imbalance, high-cardinality categoricals, and missing data through frequency encoding and threshold optimization. Includes statistical analysis, cross-validation, feature importance, and business insights.

Visualize binary classifier performance with operating profile plots: score histograms + TPR/FPR/accuracy metrics across all decision thresholds. Python tool for model validation, threshold tuning, ROC analysis, calibration audits