Machine Learning for Developers

  1. Model Deployment and MLOps
    1. Model Packaging and Serialization
      1. Model Serialization Formats
        1. Pickle and Joblib
          1. ONNX Format
            1. SavedModel Format
            2. Containerization
              1. Docker Fundamentals
                1. Container Optimization
                  1. Multi-Stage Builds
                  2. Model Versioning
                    1. Semantic Versioning
                      1. Model Registry
                        1. Artifact Management
                      2. Serving Architectures
                        1. Batch Inference
                          1. Scheduled Processing
                            1. Large-Scale Batch Jobs
                              1. Result Storage
                              2. Real-Time Inference
                                1. REST API Design
                                  1. gRPC Services
                                    1. WebSocket Connections
                                    2. Streaming Inference
                                      1. Event-Driven Processing
                                        1. Stream Processing Frameworks
                                      2. Deployment Platforms
                                        1. Cloud Platforms
                                          1. AWS SageMaker
                                            1. Google Vertex AI
                                              1. Azure Machine Learning
                                                1. Platform Comparison
                                                2. Edge Deployment
                                                  1. Mobile Deployment
                                                    1. IoT Deployment
                                                      1. Optimization Techniques
                                                      2. On-Premises Deployment
                                                        1. Kubernetes Deployment
                                                          1. Traditional Server Deployment
                                                        2. CI/CD for Machine Learning
                                                          1. Automated Testing
                                                            1. Unit Testing for ML
                                                              1. Integration Testing
                                                                1. Model Testing
                                                                2. Deployment Automation
                                                                  1. Pipeline Orchestration
                                                                    1. Blue-Green Deployment
                                                                      1. Canary Deployment
                                                                      2. Infrastructure as Code
                                                                        1. Terraform for ML
                                                                          1. CloudFormation Templates

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                                                                      7. Pre-trained Models and Transfer Learning

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                                                                      9. Production Monitoring and Maintenance