Page Index - mortezakiadi/MLOPS GitHub Wiki
31 page(s) in this GitHub Wiki:
- Home
- CI/CD (deployment centric) vs. ML Pipeline (experiment centric) views:
- Feature Store idea:
- Experiments idea:
- Links:
- Now see the animation in this page:
- Machine Learning Development Lifecycle (MLDC)
- How different roles and tools interoperate in different MLOps maturity levels:
- Manual:
- Repeatable:
- Reliable:
- Optimized:
- Automation and Orchestration:
- Apache Airflow:
- KubeFlow:
- Kubeflow and SageMaker Integration:
- MLflow Components:
- ML Platform:
- MLOps can have many environments, pipelines and repositories:
- MLOps Workload Orchestrator:
- Repositories:
- SageMaker Projects:
- ML Model Formats:
- Packaging the model:
- Deployment Patterns:
- Inference infrastructures:
- Real time inference:
- Deployment Strategies
- NOTE: You can use production variant for A/B testing and Canary Testing
- Monitoring:
- Sample MLOPs Architectures