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Update README.md
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README.md
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@@ -9,4 +9,83 @@ app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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pinned: false
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---
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<html>
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<head>
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<title>FraudSenseXAI</title>
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<style>
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body {
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font-family: 'Arial', sans-serif;
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margin: 0;
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padding: 0 0 100px; /* Adjust bottom padding */
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background-color: #f4f4f4;
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color: #333;
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line-height: 1.6;
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}
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.container {
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width: 80%;
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margin: auto;
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overflow: hidden;
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padding-bottom: 120px; /* Additional padding to push content up */
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}
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h1, h2 {
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color: #0056b3;
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}
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h1 {
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font-size: 2.5em;
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margin-bottom: 10px;
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}
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h2 {
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font-size: 1.8em;
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margin-top: 30px;
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}
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p {
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font-size: 1.1em;
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}
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ul {
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list-style-type: none;
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padding: 0;
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}
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ul li {
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background: #e9ecef;
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padding: 10px;
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margin-bottom: 10px;
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border-radius: 5px;
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}
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ul li strong {
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color: #007bff;
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}
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footer {
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background-color: #333;
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color: #fff;
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text-align: center;
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padding: 10px;
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position: fixed;
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left: 0;
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bottom: 0;
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width: 100%;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<h1>FraudSenseXAI</h1>
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<h2>Overview</h2>
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<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>
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<h2>Key Features</h2>
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<ul>
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<li><strong>Robust Fraud Detection:</strong> Utilizes advanced ML techniques to identify fraudulent transactions accurately.</li>
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<li><strong>Explainable AI Elements:</strong> Employs XAI approaches to provide clear insights into the decision-making processes of the AI.</li>
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<li><strong>Interactive Web Interface:</strong> Features a user-friendly web application for easy access and interpretation of results.</li>
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<li><strong>Dynamic Visualizations:</strong> Integrates Plotly for interactive and insightful data visualizations.</li>
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<li><strong>Applicability Across Sectors:</strong> Suitable for use in finance, e-commerce, digital banking, and other sectors.</li>
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</ul>
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<h2>About the Author</h2>
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<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>
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</div>
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<footer>
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<p>FraudSenseXAI © 2024</p>
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</footer>
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</body>
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</html>
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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