Quick Links: Helpful Resources
Quick Links: Helpful Resources
**ML Ops **
Upscale ML Lifecycle with MLOps: Whitepaper https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/mlops-technical-paper
Azure MLOps Accelerator https://microsoft.github.io/azureml-ops-accelerator/
ML Ops principles https://ml-ops.org/content/mlops-principles
Special Intereste Group (SIG) MLOps: https://lists.cd.foundation/g/sig-mlops
AWS MLOps
Amazon SageMaker MLOps https://aws.amazon.com/sagemaker/mlops/
What is MLOps https://aws.amazon.com/what-is/mlops/
Automate MLOps with SageMaker Projects: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-projects.html
MLFlow: Manage machine learning experiments using Amazon SageMaker with MLflow https://docs.aws.amazon.com/sagemaker/latest/dg/mlflow.html
SageMaker Pipelines https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines.html
ML Lineage Tracking https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking.html
MLOps Workload Orchestrator on AWS https://aws.amazon.com/solutions/implementations/mlops-workload-orchestrator/
Azure MLOps
ML Pipelines https://learn.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines?view=azureml-api-2
ML Registry for MLOps https://learn.microsoft.com/en-us/azure/machine-learning/concept-machine-learning-registries-mlops?view=azureml-api-2
CI/CD Pipelines for ML using Azure DevOps https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/mlops-python
Azure DevOps of Machine Learning https://techcommunity.microsoft.com/t5/microsoft-developer-community/introduction-to-azure-devops-for-machine-learning/ba-p/857829
MLOps for Python Model https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/mlops-python
Machine Learning Operations in Azure https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/machine-learning-operations-v2
Classical MLOps Architecture Diagram on Azure https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/_images/classical-ml-architecture.png