Built a machine learning pipeline to detect fraudulent credit card transactions using real-world data (1M+ rows). Explored fraud patterns, validated key hypotheses, and optimized models like KNN, Random Forest, and SVM with 98%+ recall. Strong focus on data insights & impact.
python data-science machine-learning random-forest svm scikit-learn eda classification data-analysis feature-engineering financial-data knn binary-classification imbalanced-data model-evaluation fraud-detection credit-card-transactions recall-optimization fraudulent-activity real-world-dataset
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Updated
May 24, 2025 - Python