An intelligent system to detect and prevent credit card fraud in real-time. By leveraging machine learning techniques and advanced algorithms, the system analyzes various features and patterns in credit card transactions to identify and flag suspicious activities.

Due to the ongoing pandemic, there is a sudden boom in the E-commerce industry and hence many online sites have increased the online payment modes, increasing the risk for online frauds. Increase in fraud rates, researchers started using different machine learning methods to detect and analyse frauds in online transactions. The main aim of the project is to design and develop a fraud detection model based on the given Dataset.

Trained on kaggle competition dataset with an accuracy of 97.974 %

Credit card fraud detector using Autoencoders

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Credit card Fraud transaction DetectorModel​ in Using Machine learning Algorithm

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Fraud Credit Card Detector

Implemented a credit card fraud detector using logistic regression algorithm in python with scikit-learn package

My first project in data science with Python and JupyterNotebook.

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Credit Card Fraud Detector is a React web app that predicts if a credit card transaction is fraudulent using a Python machine learning model. Users can input transaction data, and Flask facilitates communication between the backend and frontend. Backend files are located in the res folder. This app provides simple UI for user interaction.

Python script that uses Kaggle's credit card transaction dataset to detect future fraudulent credit card transactions.

Machine Learning-based Credit Card Fraud Detection using Label Encoding, One-Hot Encoding, Frequency Encoding, SMOTE, Random Forest, and XGBoost.

💳 End-to-end machine learning project for credit card fraud detection using Python, scikit-learn, and Google Colab. Includes training pipeline, evaluation reports, and an interactive demo app.

Making of a Credit Card Fraud Detector using a Fully-Connected Neural Network in PyTorch

Model to detect malicious transactions with credit cards

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Credit Card Fraud Detection

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Implementation of a credit card fraud detection model that classifies transactions with 95% accuracy

ML project detecting credit card fraud using Logistic Regression with real anonymized transaction data.

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To detect fraudent tranctions like amount and time etc

An end-to-end machine learning web app to detect fraudulent credit card transactions, built with Streamlit and deployed on Streamlit Cloud.