Machine Learning in Production

  1. Model Deployment
    1. Deployment Architecture Design
      1. System Architecture Patterns
        1. Scalability Considerations
          1. Security Requirements
          2. Deployment Patterns
            1. Online Prediction
              1. Low-latency Serving
                1. Synchronous APIs
                  1. Real-time Inference
                  2. Batch Prediction
                    1. Scheduled Batch Jobs
                      1. Large-scale Data Processing
                        1. Offline Inference
                        2. Streaming Prediction
                          1. Real-time Data Streams
                            1. Event-driven Inference
                              1. Stream Processing
                              2. Edge Deployment
                                1. Mobile Deployment
                                  1. IoT Device Deployment
                                    1. Offline Inference
                                  2. Serving Infrastructure
                                    1. Model Serialization
                                      1. Serialization Formats
                                        1. Pickle
                                          1. ONNX
                                            1. TensorFlow SavedModel
                                              1. PyTorch TorchScript
                                              2. Compatibility Considerations
                                                1. Performance Optimization
                                                2. Creating Prediction Services
                                                  1. REST APIs
                                                    1. API Design Principles
                                                      1. Authentication and Authorization
                                                        1. Rate Limiting
                                                        2. gRPC Services
                                                          1. Protocol Buffers
                                                            1. Performance Considerations
                                                              1. Streaming Support
                                                              2. GraphQL APIs
                                                                1. Schema Design
                                                                  1. Query Optimization
                                                                2. Model Servers
                                                                  1. Dedicated Model Serving Frameworks
                                                                    1. TensorFlow Serving
                                                                      1. TorchServe
                                                                        1. MLflow Models
                                                                        2. Scaling Model Servers
                                                                          1. Load Balancing
                                                                            1. Caching Strategies
                                                                          2. Containerization and Orchestration
                                                                            1. Docker for ML Applications
                                                                              1. Building Docker Images
                                                                                1. Managing Dependencies in Containers
                                                                                  1. Multi-stage Builds
                                                                                    1. Image Optimization
                                                                                    2. Kubernetes for ML Workloads
                                                                                      1. Deploying Containers to Kubernetes
                                                                                        1. Autoscaling and Load Balancing
                                                                                          1. Managing Deployments and Rollbacks
                                                                                            1. Resource Management
                                                                                            2. Service Mesh
                                                                                              1. Traffic Management
                                                                                                1. Security Policies
                                                                                                  1. Observability
                                                                                                2. Deployment Strategies
                                                                                                  1. Blue-Green Deployment
                                                                                                    1. Traffic Switching
                                                                                                      1. Rollback Procedures
                                                                                                        1. Testing Strategies
                                                                                                        2. Canary Releases
                                                                                                          1. Gradual Traffic Shifting
                                                                                                            1. Monitoring Canary Performance
                                                                                                              1. Automated Rollback
                                                                                                              2. Shadow Deployment
                                                                                                                1. Parallel Inference
                                                                                                                  1. No-impact Testing
                                                                                                                    1. Performance Comparison
                                                                                                                    2. A/B Testing
                                                                                                                      1. Experiment Design
                                                                                                                        1. Statistical Analysis of Results
                                                                                                                          1. Multi-armed Bandit Testing
                                                                                                                          2. Rolling Deployments
                                                                                                                            1. Incremental Updates
                                                                                                                              1. Zero-downtime Deployment
                                                                                                                                1. Health Checks
                                                                                                                              2. Continuous Integration and Continuous Delivery for ML
                                                                                                                                1. CI/CD Pipeline Design
                                                                                                                                  1. Pipeline Stages
                                                                                                                                    1. Artifact Flow
                                                                                                                                      1. Quality Gates
                                                                                                                                      2. Automated Testing
                                                                                                                                        1. Unit Tests for ML Code
                                                                                                                                          1. Integration Tests for Pipelines
                                                                                                                                            1. Model Validation Tests
                                                                                                                                              1. Performance Tests
                                                                                                                                              2. Automated Build Processes
                                                                                                                                                1. Automated Build Pipelines
                                                                                                                                                  1. Artifact Generation
                                                                                                                                                    1. Dependency Management
                                                                                                                                                    2. Automated Deployment
                                                                                                                                                      1. Deployment Automation Tools
                                                                                                                                                        1. Rollback and Recovery Automation
                                                                                                                                                          1. Environment Promotion
                                                                                                                                                          2. Infrastructure as Code
                                                                                                                                                            1. Terraform
                                                                                                                                                              1. CloudFormation
                                                                                                                                                                1. Ansible

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                                                                                                                                                            4. Model Development for Production

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                                                                                                                                                            6. Monitoring, Logging, and Maintenance