RSK World - Fraud Detection Dataset - Project Files Browser | RSK World

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        Developer: Molla Samser
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        Description: Fraud Detection Dataset - Demo Page
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    <title>Fraud Detection Dataset - RSK World</title>
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                <h1><i class="fas fa-shield-alt text-warning"></i> Fraud Detection Dataset</h1>
                <p class="lead mt-3">Financial fraud detection dataset with transaction records, user behavior patterns, and fraud labels for building anti-fraud ML models.</p>
                <div class="mt-4">
                    <span class="badge bg-primary me-2">Tabular Data</span>
                    <span class="badge bg-warning text-dark">Intermediate</span>
                    <span class="badge bg-success">Machine Learning</span>
                </div>
            </div>
        </div>

        <!-- Statistics -->
        <div class="row">
            <div class="col-md-3">
                <div class="stats-card">
                    <h3>10,000</h3>
                    <p class="mb-0">Transactions</p>
                </div>
            </div>
            <div class="col-md-3">
                <div class="stats-card">
                    <h3>15+</h3>
                    <p class="mb-0">Features</p>
                </div>
            </div>
            <div class="col-md-3">
                <div class="stats-card">
                    <h3>5%</h3>
                    <p class="mb-0">Fraud Ratio</p>
                </div>
            </div>
            <div class="col-md-3">
                <div class="stats-card">
                    <h3>100%</h3>
                    <p class="mb-0">Ready to Use</p>
                </div>
            </div>
        </div>

        <!-- Description -->
        <div class="header-card">
            <h2><i class="fas fa-info-circle text-primary"></i> Description</h2>
            <p class="mt-3">This dataset contains transaction records with features like transaction amount, location, time, merchant information, and fraud labels. Perfect for building fraud detection models, anomaly detection, and financial security applications.</p>
        </div>

        <!-- Features -->
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                    <h4>Transaction Records</h4>
                    <p>Comprehensive transaction data with detailed information including amounts, timestamps, and merchant details.</p>
                </div>
            </div>
            <div class="col-md-6">
                <div class="feature-card">
                    <i class="fas fa-user-chart"></i>
                    <h4>User Behavior Features</h4>
                    <p>Features capturing user behavior patterns including transaction frequency, account age, and transaction history.</p>
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            </div>
            <div class="col-md-6">
                <div class="feature-card">
                    <i class="fas fa-flag"></i>
                    <h4>Fraud Labels</h4>
                    <p>Binary labels (fraud/normal) for supervised learning and model evaluation.</p>
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            </div>
            <div class="col-md-6">
                <div class="feature-card">
                    <i class="fas fa-balance-scale"></i>
                    <h4>Imbalanced Dataset</h4>
                    <p>Realistic imbalanced dataset (5% fraud) for practicing imbalanced classification techniques.</p>
                </div>
            </div>
            <div class="col-md-12">
                <div class="feature-card">
                    <i class="fas fa-robot"></i>
                    <h4>Ready for Classification Models</h4>
                    <p>Preprocessed and structured data ready for machine learning models including Random Forest, XGBoost, and Neural Networks.</p>
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            </div>
        </div>

        <!-- Dataset Features -->
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            <h2><i class="fas fa-table text-success"></i> Dataset Features</h2>
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                    <ul class="list-group">
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>transaction_id</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>user_id</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>amount</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>merchant_category</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>location</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>timestamp</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>device_type</li>
                    </ul>
                </div>
                <div class="col-md-6">
                    <ul class="list-group">
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>user_age</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>account_age_days</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>transaction_count_24h</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>avg_transaction_amount</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>is_foreign_transaction</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>is_weekend</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>hour_of_day</li>
                        <li class="list-group-item"><i class="fas fa-check-circle text-success me-2"></i>is_fraud (target)</li>
                    </ul>
                </div>
            </div>
        </div>

        <!-- Technologies -->
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            <h2><i class="fas fa-code text-info"></i> Technologies</h2>
            <div class="mt-3">
                <span class="tech-badge"><i class="fas fa-file-csv"></i> CSV</span>
                <span class="tech-badge"><i class="fas fa-file-excel"></i> Excel</span>
                <span class="tech-badge"><i class="fab fa-python"></i> Pandas</span>
                <span class="tech-badge"><i class="fas fa-chart-line"></i> Scikit-learn</span>
                <span class="tech-badge"><i class="fab fa-python"></i> NumPy</span>
                <span class="tech-badge"><i class="fas fa-chart-bar"></i> Matplotlib</span>
                <span class="tech-badge"><i class="fas fa-project-diagram"></i> Jupyter</span>
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        <!-- Download & Usage -->
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            <h2><i class="fas fa-download text-danger"></i> Get Started</h2>
            <p class="mt-3">Download the dataset and start building fraud detection models</p>
            <div class="mt-4">
                <a href="fraud_detection_dataset.csv" class="btn btn-custom me-3" download>
                    <i class="fas fa-download"></i> Download CSV
                </a>
                <a href="README.md" class="btn btn-outline-primary me-3">
                    <i class="fas fa-book"></i> Read Documentation
                </a>
                <a href="fraud_detection_analysis.ipynb" class="btn btn-outline-success">
                    <i class="fas fa-code"></i> View Notebook
                </a>
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            <h5>RSK World</h5>
            <p class="mb-2">Free Programming Resources & Source Code</p>
            <p class="mb-2">
                <i class="fas fa-globe me-2"></i>
                <a href="https://rskworld.in" target="_blank">https://rskworld.in</a>
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            <p class="mb-2">
                <i class="fas fa-envelope me-2"></i>
                <a href="mailto:help@rskworld.in">help@rskworld.in</a> | 
                <a href="mailto:support@rskworld.in">support@rskworld.in</a>
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            <p class="mb-0">
                <i class="fas fa-phone me-2"></i>
                <a href="tel:+919330539277">+91 93305 39277</a>
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            <p class="text-muted small mb-0">
                Developer: Molla Samser | Designer & Tester: Rima Khatun<br>
                Content used for educational purposes only.
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