Othniel74/xa-fraud-sense
<html> <head> <title>FraudSenseXAI</title> <style> body { font-family: 'Arial', sans-serif; margin: 0; padding: 0 0 100px; / Adjust bottom padding / background-color: #f4f4f4; color: #333; line-height: 1.6; } .container { width: 80%; margin: auto; overflow: hidden; padding-bottom: 120px; / Additional padding to push content up / } h1, h2 { color: #0056b3; } h1 { font-size: 2.5em; margin-bottom: 10px; } h2 { font-size: 1.8em; margin-top: 30px; } p { font-size: 1.1em; } ul { list-style-type: none; padding: 0; } ul li { background: #e9ecef; padding: 10px; margin-bottom: 10px; border-radius: 5px; } ul li strong { color: #007bff; } footer { background-color: #333; color: #fff; text-align: center; padding: 10px; position: fixed; left: 0; bottom: 0; width: 100%; } </style> </head> <body> <div class="container"> <h1>FraudSenseXAI</h1> <h2>Overview</h2> <p><strong>FraudSenseXAI</strong> is an innovative Machine Learning (ML) and Explainable Artificial Intelligence (XAI) application, developed as a part of an MSc final project by Othniel Obasi. This application is dedicated to detecting and analyzing fraudulent activities, with a strong emphasis on the interpretability and transparency of its AI models.</p> <h2>Key Features</h2> <ul> <li><strong>Robust Fraud Detection:</strong> Utilizes advanced ML techniques to identify fraudulent transactions accurately.</li> <li><strong>Explainable AI Elements:</strong> Employs XAI approaches to provide clear insights into the decision-making processes of the AI.</li> <li><strong>Interactive Web Interface:</strong> Features a user-friendly web application for easy access and interpretation of results.</li> <li><strong>Dynamic Visualizations:</strong> Integrates Plotly for interactive and insightful data visualizations.</li> <li><strong>Applicability Across Sectors:</strong> Suitable for use in finance, e-commerce, digital banking, and other sectors.</li> </ul> <h2>About the Author</h2> <p>This project is an MSc Dissertation on the XAI Application of Fraud Detection, authored by Othniel Obasi. It represents a significant contribution to the field of AI, offering practical solutions and valuable insights for the detection of fraudulent activities using AI.</p> </div> <footer> <p>FraudSenseXAI © 2024</p> </footer> </body> </html>
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference