Azure ML E2E Workshop

Target Audience

Anyone who wants a comprehensive E2E understanding of Azure ML.

Key Goals

1. Understand the product E2E
2. Ensure that the work we are doing in Mn will address key gaps in usability / E2E user experience
3. Open bugs, fix docs & ensure commitments from product area leads on whether / how those bugs will be fixed

Agenda

(1 hour) Module 1, infra setup, ARM, workspace setup, computes, datastores, setup**

• https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-azure-machine-learning-architecture
• https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-manage-workspace
• https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-configure-environment
• https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-1st-experiment-sdk-setup

(2 hours) Module 2, Datasets, Model Training (AML, HyperDrive and AutoML), Model Interpretability**

Notebooks to run and research:

AML training, HyperDrive and Interpretability:

• Notebook for plain vanilla Scikit-Learn model training in AML local compute (AML VM)
• Notebook for Scikit-Learn model training in AML remote compute and HyperDrive
• Notebook for Model Interpretability in AML

Automated ML:

• Notebook for AutoML local compute
• Notebook for AutoML remote compute

Complementary tutorials and HowTo:

https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-version-track-datasets https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-train-with-datasets

Stretch Goal for Module 2: Get interpretability working on the scikit-learn training job.**

(2 hours) Module 3, MLOps (model management, deployment, inference, automation)

• https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-model-management-and-deployment
• https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where
• EventGrid https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-event-grid-integration

Tutorials for MLOps

• https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-pipeline-batch-scoring-classification
• https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-deploy-models-with-aml
• https://docs.microsoft.com/en-us/azure/machine-learning/service/tutorial-train-deploy-model-cli
• https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-use-event-grid

Stretch Goal for Module 3 - Set up automated training and deployment on a schedule.

(1 hour) Module 4, Enterprise Readiness**

• Azure Monitor https://docs.microsoft.com/en-us/azure/machine-learning/service/monitor-azure-machine-learning
• RBAC https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-enterprise-security
• https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-assign-roles
• Limits service https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-manage-quotas
• VNET https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-virtual-network