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

An artificial intelegence implemented using Ensemble Learning to detect frauds in card transactions.

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ID Fraud Detector uses machine learning and computer vision (OpenCV, image analysis) to automatically check whether an ID card is tampered or fraudulent

Credit card Fraud transaction DetectorModel​ in Using Machine learning Algorithm

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Fraud Credit Card Detector

This project tackles credit card fraud detection using ML with Scikit-Learn and Snap ML on a highly imbalanced dataset (0.172% fraud). It compares Decision Tree and SVM models after preprocessing and standardization. Snap ML shows faster training than Scikit-Learn with similar ROC-AUC performance, detecting fraud while handling class imbalance.

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Credit Card Fraud Detection

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Model to detect malicious transactions with credit cards

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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.

Image processing and computer vision project to help detect identity card fraud

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My first project in data science with Python and JupyterNotebook.

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

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Real-time credit card fraud detection system using Random Forest ML with 100% accuracy. Includes REST API, Gradio demo, and production-ready deployment tools. 💳🔒

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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💳 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.