Fraud-Detection-Handbook/fraud-detection-handbook
Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook
Implements end-to-end benchmarking methodologies for imbalanced classification and sequential data analysis through executable Jupyter notebooks, addressing the lack of standardized evaluation frameworks in fraud detection research. Covers specialized techniques including deep learning architectures, performance metrics beyond accuracy, and model interpretability approaches—all reproducible via Google Colab or Binder for cloud execution without local setup.
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