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---
title: FraudSenseXAI
emoji: 🏃
colorFrom: yellow
colorTo: yellow
sdk: gradio
sdk_version: 4.13.0
app_file: app.py
pinned: false
---
<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
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