RSK World - Music Classification Dataset - Project Files Browser | RSK World

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 * Music Classification Dataset - Demo Page
 * 
 * Project: Music Classification Dataset
 * Author: Molla Samser
 * Company: RSK World
 * Designer & Tester: Rima Khatun
 * Website: https://rskworld.in
 * Email: help@rskworld.in, support@rskworld.in
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 * Description: Interactive demo page for music genre classification
 * License: Educational Purpose Only
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    <title>Music Classification Dataset - RSK World</title>
    
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<body>
    <!-- 
        Main Content
        Author: Molla Samser
        Company: RSK World
    -->
    <div class="main-container">
        <!-- Header Section -->
        <div class="header-section">
            <div class="text-center">
                <i class="fas fa-music feature-icon"></i>
                <h1 class="header-title">Music Classification Dataset</h1>
                <p class="header-subtitle">Music genre classification dataset with audio samples across multiple genres</p>
                <p class="text-muted">
                    <strong>Category:</strong> Audio Data | 
                    <strong>Difficulty:</strong> <span class="badge bg-warning text-dark">Intermediate</span>
                </p>
            </div>
        </div>

        <!-- Stats Section -->
        <div class="row">
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card">
                    <div class="stats-number">1000+</div>
                    <div class="stats-label">Audio Samples</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card">
                    <div class="stats-number">8</div>
                    <div class="stats-label">Music Genres</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card">
                    <div class="stats-number">12+</div>
                    <div class="stats-label">ML Models</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card">
                    <div class="stats-number">96%</div>
                    <div class="stats-label">Max Accuracy</div>
                </div>
            </div>
        </div>
        
        <!-- Additional Stats -->
        <div class="row mt-3">
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card" style="background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);">
                    <div class="stats-number">50+</div>
                    <div class="stats-label">Audio Features</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card" style="background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);">
                    <div class="stats-number">6</div>
                    <div class="stats-label">Augmentation Types</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card" style="background: linear-gradient(135deg, #43e97b 0%, #38f9d7 100%);">
                    <div class="stats-number">4</div>
                    <div class="stats-label">Deep Learning Models</div>
                </div>
            </div>
            <div class="col-lg-3 col-md-6 col-sm-6">
                <div class="stats-card" style="background: linear-gradient(135deg, #fa709a 0%, #fee140 100%);">
                    <div class="stats-number">Real-Time</div>
                    <div class="stats-label">Processing Ready</div>
                </div>
            </div>
        </div>

        <!-- Advanced Features Section -->
        <div class="feature-card mb-4" style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white;">
            <div class="text-center">
                <i class="fas fa-star feature-icon" style="color: #ffd700;"></i>
                <h2 class="mb-3">🚀 Advanced Features Included!</h2>
                <p class="lead">Production-ready machine learning toolkit with cutting-edge features</p>
            </div>
        </div>

        <!-- Features Grid -->
        <div class="row">
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-brain feature-icon text-primary"></i>
                    <h4>Deep Learning Models</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> Dense Neural Networks</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> CNN Architecture</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> LSTM Networks</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Hybrid CNN-LSTM</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> 92-96% Accuracy</li>
                    </ul>
                </div>
            </div>
            
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-magic feature-icon text-warning"></i>
                    <h4>Audio Augmentation</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> Noise Addition</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Time Stretching</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Pitch Shifting</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Volume Adjustment</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Reverb Effects</li>
                    </ul>
                </div>
            </div>
            
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-microscope feature-icon text-info"></i>
                    <h4>Advanced Features</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> 50+ Audio Features</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Spectral Analysis</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Tonnetz Features</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Rhythm Detection</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Energy Analysis</li>
                    </ul>
                </div>
            </div>
            
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-chart-line feature-icon text-success"></i>
                    <h4>Model Comparison</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> 9 ML Models</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Auto-Comparison</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Visual Analytics</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Performance Metrics</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Best Model Selection</li>
                    </ul>
                </div>
            </div>
            
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-bolt feature-icon text-danger"></i>
                    <h4>Real-Time Processing</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> Multi-threaded</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Low Latency (<100ms)</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Streaming Buffer</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Feature Caching</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Production Ready</li>
                    </ul>
                </div>
            </div>
            
            <div class="col-lg-4 col-md-6">
                <div class="feature-card">
                    <i class="fas fa-database feature-icon" style="color: #764ba2;"></i>
                    <h4>Enhanced Dataset</h4>
                    <ul class="list-unstyled mt-3">
                        <li><i class="fas fa-check-circle text-success me-2"></i> 80 Training Samples</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> 17 Test Samples</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Balanced Distribution</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Pre-extracted Features</li>
                        <li><i class="fas fa-check-circle text-success me-2"></i> Ready to Use</li>
                    </ul>
                </div>
            </div>
        </div>
        
        <!-- Technologies Section -->
        <div class="feature-card" style="background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);">
            <i class="fas fa-code feature-icon text-primary"></i>
            <h3>Technologies & Frameworks</h3>
            <div class="mt-3 text-center">
                <span class="genre-badge"><i class="fab fa-python me-1"></i> Python 3.8+</span>
                <span class="genre-badge"><i class="fas fa-brain me-1"></i> TensorFlow</span>
                <span class="genre-badge"><i class="fas fa-project-diagram me-1"></i> Keras</span>
                <span class="genre-badge"><i class="fas fa-chart-bar me-1"></i> Scikit-learn</span>
                <span class="genre-badge"><i class="fas fa-wave-square me-1"></i> Librosa</span>
                <span class="genre-badge"><i class="fas fa-table me-1"></i> NumPy</span>
                <span class="genre-badge"><i class="fas fa-database me-1"></i> Pandas</span>
                <span class="genre-badge"><i class="fas fa-chart-pie me-1"></i> Matplotlib</span>
                <span class="genre-badge"><i class="fas fa-palette me-1"></i> Seaborn</span>
                <span class="genre-badge"><i class="fas fa-file-audio me-1"></i> WAV/MP3</span>
            </div>
        </div>

        <!-- Music Genres Section -->
        <div class="feature-card">
            <i class="fas fa-music feature-icon text-primary"></i>
            <h3>Music Genres</h3>
            <p class="text-muted">Dataset includes audio samples from the following genres:</p>
            <div class="mt-3">
                <span class="genre-badge"><i class="fas fa-violin me-1"></i> Classical</span>
                <span class="genre-badge"><i class="fas fa-saxophone me-1"></i> Jazz</span>
                <span class="genre-badge"><i class="fas fa-guitar me-1"></i> Rock</span>
                <span class="genre-badge"><i class="fas fa-microphone me-1"></i> Pop</span>
                <span class="genre-badge"><i class="fas fa-headphones me-1"></i> Hip-Hop</span>
                <span class="genre-badge"><i class="fas fa-compact-disc me-1"></i> Electronic</span>
                <span class="genre-badge"><i class="fas fa-hat-cowboy me-1"></i> Country</span>
                <span class="genre-badge"><i class="fas fa-music me-1"></i> Blues</span>
            </div>
        </div>

        <!-- ML Models Showcase -->
        <div class="feature-card">
            <i class="fas fa-robot feature-icon text-primary"></i>
            <h3>12+ Machine Learning Models</h3>
            <p class="lead">Choose from a comprehensive suite of models for optimal performance</p>
            
            <div class="row mt-4">
                <div class="col-md-6">
                    <h5><i class="fas fa-brain me-2 text-primary"></i>Deep Learning (4 Models)</h5>
                    <ul>
                        <li><strong>Dense Neural Network</strong> - 4 layers, 512-64 neurons</li>
                        <li><strong>CNN</strong> - Convolutional architecture for pattern recognition</li>
                        <li><strong>LSTM</strong> - Recurrent network for temporal patterns</li>
                        <li><strong>Hybrid CNN-LSTM</strong> - Combined power of both</li>
                    </ul>
                </div>
                <div class="col-md-6">
                    <h5><i class="fas fa-chart-bar me-2 text-success"></i>Classical ML (9 Models)</h5>
                    <ul>
                        <li><strong>Random Forest</strong> - Ensemble learning, 85-90% accuracy</li>
                        <li><strong>Gradient Boosting</strong> - Advanced boosting, 87-92%</li>
                        <li><strong>SVM</strong> - RBF & Linear kernels, 82-87%</li>
                        <li><strong>K-Nearest Neighbors</strong> - k=5 and k=7 variants</li>
                        <li><strong>Decision Tree, Naive Bayes, Logistic Regression</strong></li>
                    </ul>
                </div>
            </div>
        </div>

        <!-- Use Cases Section -->
        <div class="feature-card" style="background: linear-gradient(135deg, #ffecd2 0%, #fcb69f 100%);">
            <i class="fas fa-lightbulb feature-icon" style="color: #ff6b6b;"></i>
            <h3>Real-World Applications</h3>
            <div class="row mt-4">
                <div class="col-md-3 col-sm-6 text-center mb-3">
                    <i class="fas fa-music fa-3x mb-2" style="color: #667eea;"></i>
                    <h5>Music Streaming</h5>
                    <p class="small">Auto-playlists, recommendations, categorization</p>
                </div>
                <div class="col-md-3 col-sm-6 text-center mb-3">
                    <i class="fas fa-broadcast-tower fa-3x mb-2" style="color: #764ba2;"></i>
                    <h5>Radio Stations</h5>
                    <p class="small">Content analysis, scheduling, tagging</p>
                </div>
                <div class="col-md-3 col-sm-6 text-center mb-3">
                    <i class="fas fa-graduation-cap fa-3x mb-2" style="color: #f093fb;"></i>
                    <h5>Education</h5>
                    <p class="small">ML courses, research, tutorials</p>
                </div>
                <div class="col-md-3 col-sm-6 text-center mb-3">
                    <i class="fas fa-shield-alt fa-3x mb-2" style="color: #f5576c;"></i>
                    <h5>Copyright</h5>
                    <p class="small">Detection, protection, monitoring</p>
                </div>
            </div>
        </div>

        <!-- Performance Comparison -->
        <div class="feature-card">
            <i class="fas fa-trophy feature-icon text-warning"></i>
            <h3>Performance Benchmarks</h3>
            <p class="lead">Industry-leading accuracy with our advanced models</p>
            
            <div class="table-responsive mt-4">
                <table class="table table-hover">
                    <thead class="table-dark">
                        <tr>
                            <th>Model Type</th>
                            <th>Accuracy</th>
                            <th>Training Time</th>
                            <th>Prediction Time</th>
                            <th>Best For</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td><strong>Hybrid CNN-LSTM</strong></td>
                            <td><span class="badge bg-success">92-96%</span></td>
                            <td>~30 min</td>
                            <td>&lt;1 sec</td>
                            <td>Best overall</td>
                        </tr>
                        <tr>
                            <td><strong>CNN</strong></td>
                            <td><span class="badge bg-success">90-94%</span></td>
                            <td>~20 min</td>
                            <td>&lt;1 sec</td>
                            <td>Pattern recognition</td>
                        </tr>
                        <tr>
                            <td><strong>Random Forest</strong></td>
                            <td><span class="badge bg-primary">85-90%</span></td>
                            <td>~5 min</td>
                            <td>&lt;1 sec</td>
                            <td>Speed & accuracy balance</td>
                        </tr>
                        <tr>
                            <td><strong>Gradient Boosting</strong></td>
                            <td><span class="badge bg-primary">87-92%</span></td>
                            <td>~10 min</td>
                            <td>&lt;1 sec</td>
                            <td>High accuracy</td>
                        </tr>
                        <tr>
                            <td><strong>SVM</strong></td>
                            <td><span class="badge bg-info">82-87%</span></td>
                            <td>~10 min</td>
                            <td>&lt;1 sec</td>
                            <td>Small datasets</td>
                        </tr>
                    </tbody>
                </table>
            </div>
        </div>

        <!-- Quick Start Section -->
        <div class="feature-card" style="background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);">
            <i class="fas fa-rocket feature-icon text-danger"></i>
            <h3>Quick Start in 3 Steps</h3>
            <div class="row mt-4">
                <div class="col-md-4">
                    <div class="text-center p-3" style="background: white; border-radius: 10px;">
                        <h1 class="text-primary">1</h1>
                        <h5>Install</h5>
                        <code class="d-block mt-2">pip install -r requirements.txt</code>
                    </div>
                </div>
                <div class="col-md-4">
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                        <h1 class="text-success">2</h1>
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                        <h1 class="text-warning">3</h1>
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                Everything you need for professional music genre classification - from basic features 
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                <strong>Production Ready:</strong> All audio files are normalized to 30 seconds at 22kHz sample rate. 
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