Data Mining and Knowledge Discovery

  1. Deployment and Production Systems
    1. Model Deployment Strategies
      1. Batch Processing Systems
        1. Real-Time Scoring Systems
          1. Stream Processing Architectures
            1. Edge Computing Deployment
            2. Production Pipeline Design
              1. Data Ingestion Pipelines
                1. Feature Engineering Pipelines
                  1. Model Training Pipelines
                    1. Prediction Pipelines
                    2. Model Serving Infrastructure
                      1. REST API Development
                        1. Microservices Architecture
                          1. Container-Based Deployment
                            1. Cloud Platform Integration
                            2. Scalability Considerations
                              1. Horizontal vs Vertical Scaling
                                1. Load Balancing
                                  1. Caching Strategies
                                    1. Database Optimization
                                    2. Model Monitoring and Maintenance
                                      1. Performance Monitoring
                                        1. Accuracy Tracking
                                          1. Latency Monitoring
                                            1. Throughput Measurement
                                            2. Data Drift Detection
                                              1. Statistical Tests
                                                1. Distribution Monitoring
                                                  1. Feature Drift Analysis
                                                  2. Model Drift Detection
                                                    1. Concept Drift
                                                      1. Performance Degradation
                                                        1. Retraining Triggers
                                                        2. Model Versioning
                                                          1. A/B Testing for Models
                                                            1. Rollback Strategies
                                                            2. Quality Assurance
                                                              1. Model Testing Frameworks
                                                                1. Data Quality Monitoring
                                                                  1. Error Handling
                                                                    1. Logging and Auditing

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                                                                  10. Model Interpretation and Explainability

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                                                                  12. Ethics, Privacy, and Security