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fraud-analytics

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ChaitanyaC22 / Fraud_Analytics_Credit_Card_Fraud_Detection

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The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

machine-learning-algorithms pipelines banking hyperparameter-optimization data-analysis logistic-regression hyperparameter-tuning decision-tree-classifier svm-classifier smote oversampling kneighborsclassifier random-forest-classifier power-transformers adasyn imblearn credit-card-fraud-detection randomoversampler xgboost-classifier fraud-analytics
  • Updated Jan 24, 2023
  • Jupyter Notebook

kamlesh-IY9 / Credit-Card-Transactions-Fraud-Detection-by-Afame-Technologies

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🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯

python security data-science machine-learning random-forest scikit-learn jupyter-notebook data-visualization classification logistic-regression fraud-detection creditcard-fraud model-deployment credit-card-fraud-detection financial-fraud fraud-analytics credit-card-fraud-detection-using-machine-learning fraud-detection-using-machine-learning
  • Updated Dec 31, 2024
  • Jupyter Notebook

kevin-titi / Fraud_Detection_Credit_Card_Transaction

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Credit card transaction fraud detection model that utilized credit card transaction data from 2010, incorporating data from both credit card companies and merchants.

python exploratory-data-analysis feature-selection logistic-regression feature-engineering decision-tree-classifier fraud-detection classification-algorithm random-forest-classifier lightgbm-classifier fraud-analytics
  • Updated Jan 3, 2024
  • Jupyter Notebook

iamaayushrivastava / Fraud-Analytics-Using-Predictive-and-Social-Network-Techniques

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This repository offers a comprehensive overview of various analytical techniques for fraud detection and provides implementation guidance for an effective fraud prevention solution to help you detect fraud early.

machine-learning deep-learning clustering transformers regression data-generation autoencoder cluster-analysis fraud-detection synthetic-data synthetic-data-generation fraud-analytics
  • Updated Jun 11, 2024
  • Jupyter Notebook

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