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fraud-scoring

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Unified ML platform serving two production risk models behind one API, fraud detection using a Logistic Regression pipeline at 92.4 percent accuracy and 0.90 F1, and churn prediction using a five-estimator hard-voting ensemble at 85.6 percent accuracy, with SMOTE balancing, sub-0.5 second inference, and CI-enforced 90 percent test coverage.

  • Updated Aug 5, 2026
  • Jupyter Notebook

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