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Issues. Pull requests. Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent transactions. Credit card fraud refers to the physical loss of a credit card or the loss of sensitive credit card information.
Credit Card Fraud Detection: Leveraging Machine Learning algorithms to detect and prevent fraudulent transactions in real-time. Our repository offers a comprehensive suite of models, including Random Forest, Logistic Regression, and Neural Networks, coupled with robust preprocessing techniques and anomaly detection methods.
This repository provides TensorFlow source code for building and training credit card fraud models using an LSTM and a GRU. The models included in this repository are multi-layer LSTM or GRU models that analyze time series data to predict whether a credit card transaction is fraudulent. The models ...
"Combatting financial threats, the Credit Card Fraud Detection Capstone Project empowers learners to build robust models using data analysis and machine learning. Tackling real-world challenges, it culminates in a deployable system to safeguard transactions, showcasing skills in fraud prevention and data-driven security.
Credit Card Fraud Detection App built with Streamlit, FastAPI and Docker An end-to-end Machine Learning Project carried out by Group 3 Zummit Africa AI/ML Team to detect fraudulent credit card transactions.
This machine learning (Unsupervised learning) project uses the Isolation Forest Algorithm to detect credit card fraud detection with the Kaggle credit card data sets. Later we alternatively use Neural networks to compare the results
To create data science project using real Payments data focusing on detecting credit card fraud using advanced machine learning techniques. Aimed to enhance fraud detection accuracy and provide actionable insights for mitigating fraud risks. The project involves building a machine learning model to detect credit card fraud. The steps include:
Together, we can strengthen the defenses against credit card fraud. Enhance your credit card transaction security with Credit Card Anomaly Detection using Power BI. Empower your organization to stay vigilant and respond swiftly to potential threats in the dynamic landscape of financial transactions.
Credit Card Fraud Detection Application. This application leverages machine learning to detect fraudulent credit card transactions. This project contains a Fraud Detection application that includes a FastAPI server for the backend and a Gradio interface for the frontend. The application can predict if a transaction is fraudulent using either ...
Credit card fraud detection is one of the most important issues for credit card companies to deal with in order to earn trust from its customers. As machine learning techniques are robust to many tackle classification problems settings such as image recognition, we aim to explore various machine learning classification algorithms on this ...