Srinikesh18/Credit-Card-Fraud-Detection-ML
End-to-end Credit Card Fraud Detection using Machine Learning with SMOTE, Random Forest, and ROC-AUC evaluation.
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What it does
This repository provides an end-to-end machine learning solution for detecting credit card fraud using techniques like SMOTE and Random Forest. It addresses the critical issue of fraud in financial systems with a robust evaluation methodology.
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Tracking
- Last trending
- 2026-02-21
Creator kit
Hook
Explore how to combat credit card fraud with this comprehensive ML project using Random Forest and SMOTE!
Content angles
- Create a tutorial on implementing SMOTE for imbalanced datasets in machine learning.
- Discuss the importance of ROC-AUC in evaluating model performance for fraud detection.
- Share insights on how to improve model accuracy with hyperparameter tuning and advanced algorithms.
Who should care
Data scientists, machine learning enthusiasts, and financial analysts interested in fraud detection.