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version: "1.0.1" name: azure-machine-learning description: Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure ML workspaces, compute clusters, pipelines, endpoints, AutoML, or Prompt Flow, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Science Virtual Machines (use azure-data-science-vm), Azure HDInsight (use azure-hdinsight). compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation. metadata: generated_at: "2026-07-05" generator: "docs2skills/1.0.0"
Azure Machine Learning Skill
This skill provides expert guidance for Azure Machine Learning. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: Ifmetadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
- Preferred: Use
mcp_microsoftdocs:microsoft_docs_fetchwith query stringfrom=learn-agent-skill. Returns Markdown. - Fallback: Use
fetch_webpagewith query stringfrom=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
| Category | Lines | Description | |
|---|---|---|---|
| Troubleshooting | L37-L72 | Diagnosing and fixing Azure ML errors: pipelines, endpoints, AutoML, data access, environments, Kubernetes, networking, prompt flow, and known platform issues. | |
| Best Practices | L73-L92 | Best practices for Azure ML experiments: model tuning, monitoring, cost and compute optimization, data prep, deployment scripts, GPU/distributed training, and prompt/model performance. | |
| Decision Making | L93-L123 | Guidance for architectural and migration decisions in Azure ML: choosing algorithms, training and networking options, cost/DR strategies, and upgrading/migrating from AML v1, Prompt Flow, and legacy features. | |
| Architecture & Design Patterns | L124-L130 | Designing Azure ML inference architectures: choosing endpoint types, planning real-time online endpoints, and structuring data movement and multistep pipeline components. | |
| Limits & Quotas | L131-L139 | Info on Azure ML regional/sovereign availability, quotas and service limits, supported VM SKUs, and how to plan deployment capacity within those constraints | |
| Security | L140-L193 | Securing Azure ML: encryption, auth/RBAC, keys/secrets, managed identities, network isolation/VNets, data exfiltration, policies/compliance, and secure endpoints, training, and Prompt Flow. | |
| Configuration | L194-L455 | How to configure Azure ML components, compute, networking, monitoring, AutoML, Prompt Flow, feature stores, and YAML/CLI settings for training, deployment, and data workflows. | |
| Integrations & Coding Patterns | L456-L513 | Integrating Azure ML with data/storage, Spark/Databricks/Synapse, MLflow, REST APIs, batch endpoints, and prompt flow tools for LLM/RAG, deployment, logging, and pipelines. | |
| Deployment | L514-L555 | Deploying and operationalizing models, pipelines, and prompt flows to Azure ML endpoints (online/batch), plus CI/CD, MLOps, rollout strategies, and cross-workspace/registry deployments. |
Troubleshooting
| Topic | URL | |
|---|---|---|
| Troubleshoot Azure ML designer component error codes | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/designer-error-codes?view=azureml-api-2 | |
| Resolve common Azure AutoML forecasting issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-automl-forecasting-faq?view=azureml-api-2 | |
| Debug Azure ML online endpoints locally with VS Code | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-managed-online-endpoints-visual-studio-code?view=azureml-api-2 | |
| Troubleshoot ParallelRunStep failures in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-parallel-run-step?view=azureml-api-1 | |
| Debug Azure ML pipeline failures in studio | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-failure?view=azureml-api-2 | |
| Profile and fix Azure ML pipeline performance | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-performance?view=azureml-api-2 | |
| Diagnose and fix Azure ML pipeline reuse issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-reuse-issues?view=azureml-api-2 | |
| Troubleshoot Azure ML SDK v1 pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipelines?view=azureml-api-1 | |
| Debug and monitor Azure ML interactive jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-interactive-jobs?view=azureml-api-2 | |
| Troubleshoot Azure automated ML experiment failures | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-auto-ml?view=azureml-api-2 | |
| Troubleshoot Azure ML batch endpoints and jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-batch-endpoints?view=azureml-api-2 | |
| Troubleshoot data access issues in Azure ML SDK v2 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-data-access?view=azureml-api-2 | |
| Troubleshoot Azure ML data labeling project creation | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-data-labeling?view=azureml-api-2 | |
| Troubleshoot Azure ML environment image builds and packages | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-environments?view=azureml-api-2 | |
| Troubleshoot Azure ML Kubernetes compute workloads | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-compute?view=azureml-api-2 | |
| Troubleshoot Azure ML Kubernetes extension deployment | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-extension?view=azureml-api-2 | |
| Diagnose Azure ML managed virtual network issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-managed-network?view=azureml-api-2 | |
| Diagnose and fix Azure ML online endpoint errors | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-online-endpoints?view=azureml-api-2 | |
| Diagnose and fix Azure ML online endpoint errors | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-online-endpoints?view=azureml-api-2 | |
| Troubleshoot Azure ML online endpoint deployment and scoring errors | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-online-endpoints?view=azureml-api-2 | |
| Troubleshoot Azure ML prebuilt Docker inference images | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-prebuilt-docker-image-inference?view=azureml-api-1 | |
| Resolve 'descriptors cannot be created directly' in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-protobuf-descriptor-error?view=azureml-api-2 | |
| Troubleshoot Azure ML private endpoint connectivity | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-secure-connection-workspace?view=azureml-api-2 | |
| Fix SerializationError import issues in Azure ML SDK v1 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-serialization-error?view=azureml-api-1 | |
| Fix 'Validation for schema failed' errors in Azure ML CLI v2 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-validation-for-schema-failed-error?view=azureml-api-2 | |
| Use Azure ML workspace diagnostics for issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-workspace-diagnostic-api?view=azureml-api-2 | |
| Review Azure Machine Learning current known issues | https://learn.microsoft.com/en-us/azure/machine-learning/known-issues/azure-machine-learning-known-issues?view=azureml-api-2 | |
| Known issue: Invalid certificate during AKS deployment | https://learn.microsoft.com/en-us/azure/machine-learning/known-issues/inferencing-invalid-certificate?view=azureml-api-2 | |
| Known issue: Updating Azure ML Kubernetes compute fails | https://learn.microsoft.com/en-us/azure/machine-learning/known-issues/inferencing-updating-kubernetes-compute-appears-to-succeed?view=azureml-api-2 | |
| Troubleshoot prompt flow issues in Azure Machine Learning | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 | |
| Troubleshoot prompt flow issues in Azure Machine Learning | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 | |
| Troubleshoot Azure ML managed feature store errors | https://learn.microsoft.com/en-us/azure/machine-learning/troubleshooting-managed-feature-store?view=azureml-api-2 |
Best Practices
| Topic | URL | |
|---|---|---|
| Mitigate overfitting and imbalance in Azure AutoML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-manage-ml-pitfalls?view=azureml-api-2 | |
| Understand Azure ML model monitoring concepts and practices | https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2 | |
| Optimize and manage Azure Machine Learning costs | https://learn.microsoft.com/en-us/azure/machine-learning/concept-plan-manage-cost?view=azureml-api-2 | |
| Design feature set transformations in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/feature-set-specification-transformation-concepts?view=azureml-api-2 | |
| Author batch scoring scripts for AML batch deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-batch-scoring-script?view=azureml-api-2 | |
| Write advanced Azure ML entry scripts for inference | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-advanced-entry-script?view=azureml-api-1 | |
| Profile AML model CPU and memory usage before deployment | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-profile-model?view=azureml-api-1 | |
| Tune Azure ML Kubernetes inference router performance | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-kubernetes-inference-routing-azureml-fe?view=azureml-api-2 | |
| Manage Azure ML compute notebook and terminal sessions | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-compute-sessions?view=azureml-api-2 | |
| Optimize Azure Machine Learning compute costs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-optimize-cost?view=azureml-api-2 | |
| Prepare image datasets for Azure AutoML vision | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-prepare-datasets-for-automl-images?view=azureml-api-2 | |
| Choose storage locations for Azure ML experiment files | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-save-write-experiment-files?view=azureml-api-1 | |
| Apply best practices for distributed GPU training in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-distributed-gpu?view=azureml-api-2 | |
| Evaluate and compare Azure AutoML experiment results | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml?view=azureml-api-2 | |
| Optimize AutoML for small object detection in images | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-automl-small-object-detect?view=azureml-api-2 | |
| Optimize checkpoint performance for large Azure ML models with Nebula | https://learn.microsoft.com/en-us/azure/machine-learning/reference-checkpoint-performance-for-large-models?view=azureml-api-2 |
Decision Making
| Topic | URL | |
|---|---|---|
| Choose Azure ML designer algorithms with cheat sheet | https://learn.microsoft.com/en-us/azure/machine-learning/algorithm-cheat-sheet?view=azureml-api-1 | |
| Plan Azure ML registries for multi-environment MLOps | https://learn.microsoft.com/en-us/azure/machine-learning/concept-machine-learning-registries-mlops?view=azureml-api-2 | |
| Choose between managed and custom network isolation in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-network-isolation-configurations?view=azureml-api-2 | |
| Choose the right Azure ML training method | https://learn.microsoft.com/en-us/azure/machine-learning/concept-train-machine-learning-model?view=azureml-api-2 | |
| Choose migration paths from Azure ML Data Import to Fabric | https://learn.microsoft.com/en-us/azure/machine-learning/data-import-migration-guide?view=azureml-api-2 | |
| Plan failover and disaster recovery for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-high-availability-machine-learning?view=azureml-api-2 | |
| Manage and migrate imported data assets in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-imported-data-assets?view=azureml-api-2 | |
| Decide when and how to upgrade AML v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-migrate-from-v1?view=azureml-api-2 | |
| Move Azure ML workspaces between subscriptions | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-move-workspace?view=azureml-api-2 | |
| Plan Azure ML network isolation architecture | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-planning?view=azureml-api-2 | |
| Select appropriate Azure ML algorithms for tasks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-select-algorithms?view=azureml-api-1 | |
| Use low-priority VMs for AML batch inference cost savings | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-low-priority-batch?view=azureml-api-2 | |
| Map AML v1 datasets to v2 data assets | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-assets-data?view=azureml-api-2 | |
| Migrate Azure ML model management from SDK v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-assets-model?view=azureml-api-2 | |
| Upgrade Azure ML script runs to v2 command jobs | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-command-job?view=azureml-api-2 | |
| Migrate Azure ML deployment endpoints from SDK v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-deploy-endpoints?view=azureml-api-2 | |
| Upgrade Azure ML AutoML workflows from SDK v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-execution-automl?view=azureml-api-2 | |
| Migrate Azure ML hyperparameter tuning to v2 sweep jobs | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-execution-hyperdrive?view=azureml-api-2 | |
| Migrate Azure ML parallel run step to SDK v2 parallel job | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-execution-parallel-run-step?view=azureml-api-2 | |
| Upgrade Azure ML pipelines from SDK v1 to v2 jobs | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-execution-pipeline?view=azureml-api-2 | |
| Migrate Azure ML local runs from SDK v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-local-runs?view=azureml-api-2 | |
| Upgrade ACI web services to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-managed-online-endpoints?view=azureml-api-2 | |
| Evaluate compute management changes from AML v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-compute?view=azureml-api-2 | |
| Migrate datastore management from AML v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-datastore?view=azureml-api-2 | |
| Decide how to upgrade Azure ML workspaces to SDK v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-workspace?view=azureml-api-2 | |
| Plan migration from Prompt Flow to Agent Framework | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/migrate-prompt-flow-to-agent-framework?view=azureml-api-2 | |
| Plan around Azure ML prompt flow retirement and usage | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/overview-what-is-prompt-flow?view=azureml-api-2 |
Architecture & Design Patterns
| Topic | URL | |
|---|---|---|
| Plan real-time inference with Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online?view=azureml-api-2 | |
| Understand Azure ML endpoint types for inference | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints?view=azureml-api-2 | |
| Design data movement patterns in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-move-data-in-out-of-pipelines?view=azureml-api-1 |
Limits & Quotas
| Topic | URL | |
|---|---|---|
| Check regional availability for standard model deployments | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoint-serverless-availability?view=azureml-api-2 | |
| Manage Azure ML resource quotas and limits | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-quotas?view=azureml-api-2 | |
| Check Azure ML feature availability by sovereign cloud | https://learn.microsoft.com/en-us/azure/machine-learning/reference-machine-learning-cloud-parity?view=azureml-api-2 | |
| Supported VM SKUs for Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/reference-managed-online-endpoints-vm-sku-list?view=azureml-api-2 | |
| Plan capacity with Azure Machine Learning service limits | https://learn.microsoft.com/en-us/azure/machine-learning/resource-limits-capacity?view=azureml-api-2 |
Security
| Topic | URL | |
|---|---|---|
| Configure customer-managed keys for Azure Machine Learning | https://learn.microsoft.com/en-us/azure/machine-learning/concept-customer-managed-keys?view=azureml-api-2 | |
| Understand data encryption for Azure ML compute and storage | https://learn.microsoft.com/en-us/azure/machine-learning/concept-data-encryption?view=azureml-api-2 | |
| Understand data handling and privacy for Azure ML Model Catalog | https://learn.microsoft.com/en-us/azure/machine-learning/concept-data-privacy?view=azureml-api-2 | |
| Understand auth and RBAC for AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online-auth?view=azureml-api-2 | |
| Plan enterprise security and governance for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-enterprise-security?view=azureml-api-2 | |
| Secret injection concepts for AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secret-injection?view=azureml-api-2 | |
| Understand secure network traffic flow in Azure ML VNets | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-network-traffic-flow?view=azureml-api-2 | |
| Network isolation concepts for AML managed endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-online-endpoint?view=azureml-api-2 | |
| Manage vulnerabilities in Azure Machine Learning images | https://learn.microsoft.com/en-us/azure/machine-learning/concept-vulnerability-management?view=azureml-api-2 | |
| Securely connect Azure ML managed VNet to on-premises | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-on-premises-resources?view=azureml-api-2 | |
| Access Azure resources from AML endpoints via managed identity | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-resources-from-endpoints-managed-identities?view=azureml-api-2 | |
| Grant limited access to Azure ML labeling projects | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-add-users?view=azureml-api-2 | |
| Administer data access and authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-administrate-data-authentication?view=azureml-api-2 | |
| Configure data authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-administrate-data-authentication?view=azureml-api-2 | |
| Manage Azure RBAC roles for Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-assign-roles?view=azureml-api-2 | |
| Authorize access to Azure ML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-batch-endpoint?view=azureml-api-2 | |
| Configure authentication for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-online-endpoint?view=azureml-api-2 | |
| Configure authentication for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-online-endpoint?view=azureml-api-2 | |
| Configure authentication for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-online-endpoint?view=azureml-api-2 | |
| Use built-in Azure Policy to govern AI model deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-built-in-policy-model-deployment?view=azureml-api-2 | |
| Rotate Azure ML workspace storage account access keys | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-change-storage-access-key?view=azureml-api-2 | |
| Create custom Azure Policies to restrict AI model deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-custom-policy-model-deployment?view=azureml-api-2 | |
| Use secret injection to access secrets in AML deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoint-with-secret-injection?view=azureml-api-2 | |
| Disable shared key access for Azure ML workspace storage | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-disable-local-auth-storage?view=azureml-api-2 | |
| Configure identity-based service authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-identity-based-service-authentication?view=azureml-api-2 | |
| Configure identity-based service authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-identity-based-service-authentication?view=azureml-api-2 | |
| Enforce Azure ML workspace compliance with Azure Policy | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-integrate-azure-policy?view=azureml-api-2 | |
| Configure managed virtual network isolation for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-managed-network?view=azureml-api-2 | |
| Configure Model Catalog access with workspace managed virtual networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-model-catalog?view=azureml-api-2 | |
| Secure Azure ML workspaces with virtual networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-security-overview?view=azureml-api-2 | |
| Configure data exfiltration prevention for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-prevent-data-loss-exfiltration?view=azureml-api-2 | |
| Secure Azure ML batch endpoints with private networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-batch-endpoint?view=azureml-api-2 | |
| Secure Azure ML online inferencing with VNets | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-inferencing-vnet?view=azureml-api-2 | |
| Secure AKS inferencing environments for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-kubernetes-inferencing-environment?view=azureml-api-2 | |
| Configure TLS/SSL for Azure ML Kubernetes endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-kubernetes-online-endpoint?view=azureml-api-2 | |
| Secure Azure ML managed online endpoints with network isolation | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-online-endpoint?view=azureml-api-2 | |
| Secure Azure ML RAG workflows with network isolation | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-rag-workflows?view=azureml-api-2 | |
| Secure Azure ML training with virtual networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-training-vnet?view=azureml-api-2 | |
| Secure Azure ML workspace using virtual networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-workspace-vnet?view=azureml-api-2 | |
| Configure RBAC access to Azure ML feature store | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-access-control-feature-store?view=azureml-api-2 | |
| Set up authentication to Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-authentication?view=azureml-api-2 | |
| Configure customer-managed keys for Azure ML resources | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-customer-managed-keys?view=azureml-api-2 | |
| Securely use private Python packages in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-private-python-packages?view=azureml-api-1 | |
| Securely use Key Vault secrets in Azure ML runs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-secrets-in-runs?view=azureml-api-2 | |
| Apply built-in Azure Policy definitions for AML | https://learn.microsoft.com/en-us/azure/machine-learning/policy-reference?view=azureml-api-2 | |
| Manage credentials with connections in Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/concept-connections?view=azureml-api-2 | |
| Secure Prompt Flow with virtual network isolation | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-secure-prompt-flow?view=azureml-api-2 | |
| Apply Azure Policy regulatory controls to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/security-controls-policy?view=azureml-api-2 | |
| Secure Azure ML workspace with custom VNet | https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-create-secure-workspace-vnet?view=azureml-api-2 | |
| Create secure Azure ML workspace with managed VNet | https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-create-secure-workspace?view=azureml-api-2 |
Configuration
| Topic | URL | |
|---|---|---|
| Configure AutoML Classification component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/classification?view=azureml-api-2 | |
| Configure AutoML Forecasting component in designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/forecasting?view=azureml-api-2 | |
| Configure AutoML Image Multi-label Classification | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification-multilabel?view=azureml-api-2 | |
| Configure AutoML Image Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification?view=azureml-api-2 | |
| Configure AutoML Image Instance Segmentation component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-instance-segmentation?view=azureml-api-2 | |
| Configure AutoML Image Object Detection component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-object-detection?view=azureml-api-2 | |
| Configure AutoML Regression component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/regression?view=azureml-api-2 | |
| Configure AutoML Text Multi-label Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification-multilabel?view=azureml-api-2 | |
| Configure AutoML Text Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification?view=azureml-api-2 | |
| Configure AutoML Text NER component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-ner?view=azureml-api-2 | |
| Configure Add Columns component to concatenate datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-columns?view=azureml-api-2 | |
| Configure Add Rows component to append dataset records | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-rows?view=azureml-api-2 | |
| Configure Apply Image Transformation in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-image-transformation?view=azureml-api-2 | |
| Configure Apply Math Operation component for column calculations | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-math-operation?view=azureml-api-2 | |
| Configure Apply SQL Transformation component using SQLite | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-sql-transformation?view=azureml-api-2 | |
| Configure Apply Transformation component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-transformation?view=azureml-api-2 | |
| Configure Assign Data to Clusters in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/assign-data-to-clusters?view=azureml-api-2 | |
| Configure Boosted Decision Tree Regression component (LightGBM) | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/boosted-decision-tree-regression?view=azureml-api-2 | |
| Configure Clean Missing Data component for handling nulls | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clean-missing-data?view=azureml-api-2 | |
| Configure Clip Values component to handle outliers | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clip-values?view=azureml-api-2 | |
| Configure and use Azure ML designer algorithm components | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/component-reference?view=azureml-api-2 | |
| Configure Convert to CSV component for dataset export | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-csv?view=azureml-api-2 | |
| Configure Convert to Dataset component for internal format | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-dataset?view=azureml-api-2 | |
| Configure Convert to Image Directory in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-image-directory?view=azureml-api-2 | |
| Configure Convert to Indicator Values for categorical encoding | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-indicator-values?view=azureml-api-2 | |
| Configure Convert Word to Vector component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-word-to-vector?view=azureml-api-2 | |
| Configure Create Python Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/create-python-model?view=azureml-api-2 | |
| Configure Cross Validate Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/cross-validate-model?view=azureml-api-2 | |
| Configure Decision Forest Regression in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/decision-forest-regression?view=azureml-api-2 | |
| Configure DenseNet image classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/densenet?view=azureml-api-2 | |
| Configure Edit Metadata component to adjust column roles | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/edit-metadata?view=azureml-api-2 | |
| Set up Enter Data Manually component for small datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/enter-data-manually?view=azureml-api-2 | |
| Configure Evaluate Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-model?view=azureml-api-2 | |
| Configure Evaluate Recommender component for model accuracy | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-recommender?view=azureml-api-2 | |
| Configure Execute Python Script in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/execute-python-script?view=azureml-api-2 | |
| Configure Execute R Script component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/execute-r-script?view=azureml-api-2 | |
| Configure Export Data component to save pipeline outputs | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/export-data?view=azureml-api-2 | |
| Configure Extract N-Gram Features from Text in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/extract-n-gram-features-from-text?view=azureml-api-2 | |
| Configure Fast Forest Quantile Regression in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/fast-forest-quantile-regression?view=azureml-api-2 | |
| Configure Feature Hashing text component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/feature-hashing?view=azureml-api-2 | |
| Configure Filter Based Feature Selection for predictive columns | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/filter-based-feature-selection?view=azureml-api-2 | |
| Use graph search query syntax in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/graph-search-syntax?view=azureml-api-2 | |
| Configure Group Data into Bins component for discretization | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/group-data-into-bins?view=azureml-api-2 | |
| Configure Import Data component for Azure ML designer pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/import-data?view=azureml-api-2 | |
| Configure Init Image Transformation in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/init-image-transformation?view=azureml-api-2 | |
| Configure Join Data component to merge datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/join-data?view=azureml-api-2 | |
| Configure K-Means Clustering component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/k-means-clustering?view=azureml-api-2 | |
| Configure Latent Dirichlet Allocation component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/latent-dirichlet-allocation?view=azureml-api-2 | |
| Configure Linear Regression component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/linear-regression?view=azureml-api-2 | |
| Configure Multiclass Boosted Decision Tree in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-boosted-decision-tree?view=azureml-api-2 | |
| Configure Multiclass Decision Forest in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-decision-forest?view=azureml-api-2 | |
| Configure Multiclass Logistic Regression in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-logistic-regression?view=azureml-api-2 | |
| Configure Multiclass Neural Network in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-neural-network?view=azureml-api-2 | |
| Set up Neural Network Regression in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/neural-network-regression?view=azureml-api-2 | |
| Configure Normalize Data component for feature scaling | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/normalize-data?view=azureml-api-2 | |
| Configure One-vs-All Multiclass component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/one-vs-all-multiclass?view=azureml-api-2 | |
| Configure One-vs-One Multiclass component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/one-vs-one-multiclass?view=azureml-api-2 | |
| Configure Partition and Sample component for dataset splitting | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/partition-and-sample?view=azureml-api-2 | |
| Configure deprecated PCA-Based Anomaly Detection component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/pca-based-anomaly-detection?view=azureml-api-2 | |
| Configure Permutation Feature Importance component for model insights | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/permutation-feature-importance?view=azureml-api-2 | |
| Use Poisson Regression component in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/poisson-regression?view=azureml-api-2 | |
| Configure Preprocess Text component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/preprocess-text?view=azureml-api-2 | |
| Configure Remove Duplicate Rows component for deduplication | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/remove-duplicate-rows?view=azureml-api-2 | |
| Configure ResNet image classification in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/resnet?view=azureml-api-2 | |
| Configure Score Image Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-image-model?view=azureml-api-2 | |
| Configure Score Model component in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-model?view=azureml-api-2 | |
| Configure Score SVD Recommender for predictions | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-svd-recommender?view=azureml-api-2 | |
| Configure Score Vowpal Wabbit Model in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-vowpal-wabbit-model?view=azureml-api-2 | |
| Configure Score Wide & Deep Recommender component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-wide-and-deep-recommender?view=azureml-api-2 | |
| Configure Select Columns in Dataset to subset features | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/select-columns-in-dataset?view=azureml-api-2 | |
| Configure Select Columns Transform for stable feature sets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/select-columns-transform?view=azureml-api-2 | |
| Configure SMOTE component to oversample minority classes | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/smote?view=azureml-api-2 | |
| Configure Split Data component for train-test partitioning | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/split-data?view=azureml-api-2 | |
| Configure Split Image Directory component for datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/split-image-directory?view=azureml-api-2 | |
| Configure Summarize Data component for descriptive statistics | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/summarize-data?view=azureml-api-2 | |
| Configure Train Anomaly Detection Model component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-anomaly-detection-model?view=azureml-api-2 | |
| Configure Train Clustering Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-clustering-model?view=azureml-api-2 | |
| Configure Train PyTorch Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-pytorch-model?view=azureml-api-2 | |
| Configure Train SVD Recommender in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-svd-recommender?view=azureml-api-2 | |
| Configure Train Vowpal Wabbit Model in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-vowpal-wabbit-model?view=azureml-api-2 | |
| Configure Train Wide & Deep Recommender component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-wide-and-deep-recommender?view=azureml-api-2 | |
| Configure Tune Model Hyperparameters in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/tune-model-hyperparameters?view=azureml-api-2 | |
| Configure Two-Class Averaged Perceptron in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-averaged-perceptron?view=azureml-api-2 | |
| Configure Two-Class Boosted Decision Tree in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-boosted-decision-tree?view=azureml-api-2 | |
| Configure Two-Class Decision Forest in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-decision-forest?view=azureml-api-2 | |
| Configure Two-Class Logistic Regression in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-logistic-regression?view=azureml-api-2 | |
| Configure Two-Class Neural Network in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-neural-network?view=azureml-api-2 | |
| Configure Two-Class SVM component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/two-class-support-vector-machine?view=azureml-api-2 | |
| Configure Web Service Input and Output components | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/web-service-input-output?view=azureml-api-2 | |
| Configure inference data collection for Azure ML endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-data-collection?view=azureml-api-2 | |
| Use expressions in Azure ML SDK and CLI v2 jobs | https://learn.microsoft.com/en-us/azure/machine-learning/concept-expressions?view=azureml-api-2 | |
| Specify models for Azure ML online deployments | https://learn.microsoft.com/en-us/azure/machine-learning/concept-online-deployment-model-specification?view=azureml-api-2 | |
| Use Azure ML prebuilt Docker images for inference | https://learn.microsoft.com/en-us/azure/machine-learning/concept-prebuilt-docker-images-inference?view=azureml-api-2 | |
| Configure and use Azure ML Responsible AI dashboard | https://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai-dashboard?view=azureml-api-2 | |
| Use workspace soft delete and recovery in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-soft-delete?view=azureml-api-2 | |
| Configure and use vector stores in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-vector-stores?view=azureml-api-2 | |
| Link OneLake tables to Azure ML via UI datastores | https://learn.microsoft.com/en-us/azure/machine-learning/create-datastore-with-user-interface?view=azureml-api-2 | |
| Configure feature retrieval specs for training and inference | https://learn.microsoft.com/en-us/azure/machine-learning/feature-retrieval-concepts?view=azureml-api-2 | |
| Configure feature set materialization in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/feature-set-materialization-concepts?view=azureml-api-2 | |
| Configure inbound and outbound traffic for secure Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-azureml-behind-firewall?view=azureml-api-2 | |
| Access Azure cloud storage data during interactive ML development | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-data-interactive?view=azureml-api-2 | |
| Configure Kubernetes compute targets for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-anywhere?view=azureml-api-2 | |
| Configure Kubernetes compute targets for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-anywhere?view=azureml-api-2 | |
| Configure Kubernetes compute targets for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-anywhere?view=azureml-api-2 | |
| Attach AKS or Arc Kubernetes clusters to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace?view=azureml-api-2 | |
| Configure Azure AutoML for time-series forecasting | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-forecast?view=azureml-api-2 | |
| Configure AutoML computer vision training in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models?view=azureml-api-2 | |
| Configure Azure AutoML for custom NLP training | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models?view=azureml-api-2 | |
| Configure autoscaling for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-autoscale-endpoints?view=azureml-api-2 | |
| Configure custom Azure Container for PyTorch environments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-azure-container-for-pytorch-environment?view=azureml-api-2 | |
| Enable production inference data collection for Azure ML endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-collect-production-data?view=azureml-api-2 | |
| Customize AutoML data featurization settings in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-features?view=azureml-api-1 | |
| Configure Azure AutoML tabular training with SDK v2 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-train?view=azureml-api-2 | |
| Configure data splits and cross-validation in Azure AutoML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-cross-validation-data-splits?view=azureml-api-1 | |
| Maintain network isolation with Azure ML v2 API | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-network-isolation-with-v2?view=azureml-api-2 | |
| Configure private endpoints for Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-private-link?view=azureml-api-2 | |
| Configure Azure storage connections in ML Studio (v1) | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-connect-data-ui?view=azureml-api-1 | |
| Configure Azure ML connections to external data and services | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-connection?view=azureml-api-2 | |
| Create and manage Azure ML compute clusters | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-cluster?view=azureml-api-2 | |
| Configure and manage Azure ML compute in studio | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-studio?view=azureml-api-2 | |
| Create Azure ML compute instances for development | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-compute-instance?view=azureml-api-2 | |
| Create Azure ML compute instances for development | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-compute-instance?view=azureml-api-2 | |
| Create and manage Azure ML data assets | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-data-assets?view=azureml-api-2 | |
| Create and manage Azure ML data assets | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-data-assets?view=azureml-api-2 | |
| Configure image labeling projects in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-image-labeling-projects?view=azureml-api-2 | |
| Configure text labeling projects in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-text-labeling-projects?view=azureml-api-2 | |
| Configure and use vector indexes in Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-vector-index?view=azureml-api-2 | |
| Create Azure ML workspaces with ARM templates | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-workspace-template?view=azureml-api-2 | |
| Set up custom DNS for private Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-custom-dns?view=azureml-api-2 | |
| Customize Azure ML compute instances with startup scripts | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-customize-compute-instance?view=azureml-api-2 | |
| Configure and use Azure ML datastores for storage access | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?view=azureml-api-2 | |
| Deploy Azure ML extension on Kubernetes clusters | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-kubernetes-extension?view=azureml-api-2 | |
| Enable Azure ML studio access within a virtual network | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-enable-studio-virtual-network?view=azureml-api-2 | |
| Export or delete Azure ML workspace data | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-export-delete-data?view=azureml-api-2 | |
| Customize Azure ML prebuilt Docker images for inference | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-extend-prebuilt-docker-image-inference?view=azureml-api-1 | |
| Import external data into Azure ML (preview) | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-import-data-assets?view=azureml-api-2 | |
| Label images and text in Azure ML projects | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-label-data?view=azureml-api-2 | |
| Link Synapse and Azure ML workspaces with Spark pools | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-link-synapse-ml-workspaces?view=azureml-api-1 | |
| Log MLflow models as first-class models in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-mlflow-models?view=azureml-api-2 | |
| Send Azure ML distributed training logs to Application Insights | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-search?view=azureml-api-2 | |
| Configure model interpretability in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability?view=azureml-api-2 | |
| Manage Azure ML compute instances and lifecycle | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-compute-instance?view=azureml-api-2 | |
| Configure Azure ML environments with CLI and SDK | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-environments-v2?view=azureml-api-2 | |
| Configure Azure ML environments with CLI and SDK | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-environments-v2?view=azureml-api-2 | |
| Create Azure ML hub workspaces with Bicep templates | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-hub-workspace-template?view=azureml-api-2 | |
| Manage component and pipeline inputs/outputs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-inputs-outputs-pipeline?view=azureml-api-2 | |
| Create and manage Azure ML Kubernetes instance types | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-kubernetes-instance-types?view=azureml-api-2 | |
| Administer and export Azure ML labeling projects | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-labeling-projects?view=azureml-api-2 | |
| Configure Azure ML deployment templates for models | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models-deployment-templates?view=azureml-api-2 | |
| Manage Azure ML model registry using MLflow | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models-mlflow?view=azureml-api-2 | |
| Register and manage models with Azure ML CLI and SDK | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models?view=azureml-api-2 | |
| Create and manage Azure ML registries | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-registries?view=azureml-api-2 | |
| Manage Azure ML resources using VS Code extension | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-resources-vscode?view=azureml-api-2 | |
| Attach and manage Synapse Spark pools in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-synapse-spark-pool?view=azureml-api-2 | |
| Provision Azure ML workspaces using Terraform | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace-terraform?view=azureml-api-2 | |
| Configure data drift monitors in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-datasets?view=azureml-api-1 | |
| Collect and monitor Kubernetes endpoint inference logs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-kubernetes-online-enpoint-inference-server-log?view=azureml-api-2 | |
| Configure Azure ML model performance monitoring in production | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-model-performance?view=azureml-api-2 | |
| Configure monitoring and logging for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-online-endpoints?view=azureml-api-2 | |
| Configure monitoring and logging for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-online-endpoints?view=azureml-api-2 | |
| Extend Azure ML prebuilt inference images with Python | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-prebuilt-docker-images-inference-python-extensibility?view=azureml-api-1 | |
| Use R and RStudio on Azure ML compute instances | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-r-interactive-development?view=azureml-api-2 | |
| Configure network isolation for Azure ML registries | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-registry-network-isolation?view=azureml-api-2 | |
| Use Responsible AI dashboard tools in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-dashboard?view=azureml-api-2 | |
| Generate Responsible AI insights in Azure ML studio | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-insights-ui?view=azureml-api-2 | |
| Configure and export Responsible AI scorecards in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-scorecard?view=azureml-api-2 | |
| Schedule recurring data imports in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-schedule-data-import?view=azureml-api-2 | |
| Share models and components across Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-share-models-pipelines-across-workspaces-with-registries?view=azureml-api-2 | |
| Query and compare MLflow experiments and runs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-track-experiments-mlflow?view=azureml-api-2 | |
| Submit MLflow Projects training jobs to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-mlflow-projects?view=azureml-api-2 | |
| Configure and submit Azure ML training jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-model?view=azureml-api-2 | |
| Configure and submit Azure ML training jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-model?view=azureml-api-2 | |
| Train Azure ML models using custom Docker images (v1) | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-with-custom-image?view=azureml-api-1 | |
| Configure hyperparameter sweep jobs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters?view=azureml-api-2 | |
| Configure AutoMLStep in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-automlstep-in-pipelines?view=azureml-api-1 | |
| Use MLflow to track Azure ML experiments and runs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-cli-runs?view=azureml-api-2 | |
| Configure MLflow tracking with Azure Machine Learning workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-configure-tracking?view=azureml-api-2 | |
| Configure and run parallel jobs in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-parallel-job-in-pipeline?view=azureml-api-2 | |
| Configure pipeline parameters in Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-pipeline-parameter?view=azureml-api-1 | |
| Run training jobs on Azure ML serverless compute | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-serverless-compute?view=azureml-api-2 | |
| Configure hyperparameter sweep in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-sweep-in-pipeline?view=azureml-api-2 | |
| Configure dataset versioning in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-version-track-datasets?view=azureml-api-1 | |
| View and tag costs for Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-view-online-endpoints-costs?view=azureml-api-2 | |
| Configure VS Code remote sessions to Azure ML compute | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-work-in-vs-code-remote?view=azureml-api-2 | |
| Configure serverless Spark compute for Azure ML notebooks | https://learn.microsoft.com/en-us/azure/machine-learning/interactive-data-wrangling-with-apache-spark-azure-ml?view=azureml-api-2 | |
| Reference Azure Machine Learning monitoring metrics and logs | https://learn.microsoft.com/en-us/azure/machine-learning/monitor-azure-machine-learning-reference?view=azureml-api-2 | |
| Run batch evaluations for Prompt Flow at scale | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-bulk-test-evaluate-flow?view=azureml-api-2 | |
| Customize compute session base images for Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-customize-session-base-image?view=azureml-api-2 | |
| Create and customize evaluation flows and metrics | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2 | |
| Configure streaming mode for prompt flow endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-enable-streaming-mode?view=azureml-api-2 | |
| Configure tracing and feedback for prompt flow deployments | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-enable-trace-feedback-for-deployment?view=azureml-api-2 | |
| Configure and manage Prompt Flow compute sessions | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-manage-compute-session?view=azureml-api-2 | |
| Configure Automated ML forecasting jobs via YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automated-ml-forecasting?view=azureml-api-2 | |
| Author AutoML image classification jobs in YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-classification?view=azureml-api-2 | |
| Define AutoML image instance segmentation YAML jobs | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-instance-segmentation?view=azureml-api-2 | |
| Configure AutoML image multilabel classification YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-multilabel-classification?view=azureml-api-2 | |
| Author AutoML image object detection YAML jobs | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-object-detection?view=azureml-api-2 | |
| Configure AutoML vision hyperparameters in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters?view=azureml-api-2 | |
| Format JSONL data for AutoML computer vision | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-schema?view=azureml-api-2 | |
| Configure AutoML multilabel text classification YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-nlp-cli-multilabel-classification?view=azureml-api-2 | |
| Author AutoML NLP NER jobs using YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-nlp-cli-ner?view=azureml-api-2 | |
| Define AutoML text classification jobs with YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-nlp-cli-text-classification?view=azureml-api-2 | |
| Reference configuration for Kubernetes with Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-kubernetes?view=azureml-api-2 | |
| Define command components via Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-command?view=azureml-api-2 | |
| Author pipeline components using Azure ML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-pipeline?view=azureml-api-2 | |
| Configure Spark components in Azure ML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-spark?view=azureml-api-2 | |
| Configure AmlCompute clusters via YAML in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-aml?view=azureml-api-2 | |
| Define Azure ML compute instances with YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-instance?view=azureml-api-2 | |
| Configure attached Kubernetes clusters in Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-kubernetes?view=azureml-api-2 | |
| Attach and configure VMs via Azure ML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-vm?view=azureml-api-2 | |
| Configure AI Content Safety connections in AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-content-safety?view=azureml-api-2 | |
| Author AI Search connection YAML for AML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-search?view=azureml-api-2 | |
| Configure Foundry Tools connections with Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-services?view=azureml-api-2 | |
| Define API key connections via AML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-api-key?view=azureml-api-2 | |
| Define Azure OpenAI connections via AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-azure-openai?view=azureml-api-2 | |
| Define blob datastore connections in AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-blob?view=azureml-api-2 | |
| Configure Azure Container Registry connections in AML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-container-registry?view=azureml-api-2 | |
| Author custom key connections in Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-custom-key?view=azureml-api-2 | |
| Configure Data Lake Gen2 connections via AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-data-lake?view=azureml-api-2 | |
| Configure Git repository connections in AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-git?view=azureml-api-2 | |
| Set up OneLake connections using AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-onelake?view=azureml-api-2 | |
| Configure OpenAI service connections in AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-openai?view=azureml-api-2 | |
| Set up Python feed connections using AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-python-feed?view=azureml-api-2 | |
| Define Serp connections via Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-serp?view=azureml-api-2 | |
| Author serverless connection YAML for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-serverless?view=azureml-api-2 | |
| Configure AI Speech Services connections in AML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-speech?view=azureml-api-2 | |
| Understand core Azure ML CLI v2 YAML syntax | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-core-syntax?view=azureml-api-2 | |
| Reference schema for Azure ML data YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-data?view=azureml-api-2 | |
| Define Azure Blob datastores via YAML in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-blob?view=azureml-api-2 | |
| Author Azure Data Lake Gen1 datastore YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-data-lake-gen1?view=azureml-api-2 | |
| Configure Azure Data Lake Gen2 datastores in YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-data-lake-gen2?view=azureml-api-2 | |
| Configure Azure Files datastores using YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-files?view=azureml-api-2 | |
| Author batch deployment YAML for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-batch?view=azureml-api-2 | |
| Define Kubernetes online deployments in Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-kubernetes-online?view=azureml-api-2 | |
| Configure managed online deployments via Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-managed-online?view=azureml-api-2 | |
| Configure Azure ML CLI v2 deployment template YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-template?view=azureml-api-2 | |
| Author batch endpoint YAML for Azure ML CLI v2 | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-endpoint-batch?view=azureml-api-2 | |
| Configure Azure ML online endpoints with YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-endpoint-online?view=azureml-api-2 | |
| Reference schema for Azure ML environment YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-environment?view=azureml-api-2 | |
| Author feature entity definitions via Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-entity?view=azureml-api-2 | |
| Create feature retrieval specs with Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-retrieval-spec?view=azureml-api-2 | |
| Configure feature sets in Azure ML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-set?view=azureml-api-2 | |
| Define feature stores in Azure ML using YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-store?view=azureml-api-2 | |
| Define feature set specifications using YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-featureset-spec?view=azureml-api-2 | |
| Configure Azure ML CLI v2 command job YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-command?view=azureml-api-2 | |
| Create parallel jobs in Azure ML pipeline YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-parallel?view=azureml-api-2 | |
| Author pipeline job definitions with AML YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-pipeline?view=azureml-api-2 | |
| Configure Azure ML pipeline jobs using YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-pipeline?view=azureml-api-2 | |
| Configure Spark jobs in Azure ML with YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-spark?view=azureml-api-2 | |
| Define sweep (hyperparameter) jobs with Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-sweep?view=azureml-api-2 | |
| Reference schema for Azure ML MLTable YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-mltable?view=azureml-api-2 | |
| Define Azure ML models with CLI v2 YAML schema | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-model?view=azureml-api-2 | |
| Create model monitoring schedules with Azure ML YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-monitor?view=azureml-api-2 | |
| Navigate Azure ML CLI v2 YAML schema references | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-overview?view=azureml-api-2 | |
| Define Azure ML registries using CLI v2 YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-registry?view=azureml-api-2 | |
| Author data import schedule YAML for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-schedule-data-import?view=azureml-api-2 | |
| Configure Azure ML job schedules with YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-schedule?view=azureml-api-2 | |
| Reference schema for Azure ML workspace YAML | https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-workspace?view=azureml-api-2 |
Integrations & Coding Patterns
| Topic | URL | |
|---|---|---|
| Configure input data sources for AML batch endpoint jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-data-batch-endpoints-jobs?view=azureml-api-2 | |
| Set up Azure Databricks with AutoML in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-databricks-automl-environment?view=azureml-api-1 | |
| Author Azure ML CLI component-based pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-component-pipelines-cli?view=azureml-api-2 | |
| Ingest data to Azure ML with Data Factory | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-data-ingest-adf?view=azureml-api-1 | |
| Wrangle data using Synapse Spark with Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-data-prep-synapse-spark-pool?view=azureml-api-1 | |
| Configure Azure ML datastores for storage access | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?view=azureml-api-2 | |
| Configure Azure ML datastores for storage access | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?view=azureml-api-2 | |
| Run MLflow models in Azure ML Spark jobs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-model-spark-jobs?view=azureml-api-2 | |
| Deploy AML models as custom skills for Azure AI Search | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-model-cognitive-search?view=azureml-api-1 | |
| Deploy Hugging Face transformer models to Azure ML endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-from-huggingface?view=azureml-api-2 | |
| Use Azure ML REST API for online deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-with-rest?view=azureml-api-2 | |
| Import data into Azure ML designer | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-designer-import-data?view=azureml-api-1 | |
| Run custom Python code in Azure ML designer pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-designer-python?view=azureml-api-1 | |
| Run local ONNX inference for Azure AutoML image models | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-inference-onnx-automl-image-models?view=azureml-api-2 | |
| Use Azure ML inference HTTP server for local debugging | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-inference-server-http?view=azureml-api-2 | |
| Log metrics and artifacts with MLflow in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-view-metrics?view=azureml-api-2 | |
| Manage Azure ML resources using REST APIs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-rest?view=azureml-api-2 | |
| Define and use MLTable data in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-mltable?view=azureml-api-2 | |
| Securely integrate Azure Synapse with Azure ML via VNets | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-private-endpoint-integration-synapse?view=azureml-api-2 | |
| Read and write data in Azure ML jobs (v2 SDK) | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-read-write-data-v2?view=azureml-api-2 | |
| Read and write data in Azure ML jobs (v2 SDK) | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-read-write-data-v2?view=azureml-api-2 | |
| Generate Responsible AI dashboards with Azure ML SDK | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-insights-sdk-cli?view=azureml-api-2 | |
| Attach secured Azure Databricks to Azure ML via private endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-securely-attach-databricks?view=azureml-api-2 | |
| Submit standalone and pipeline Spark jobs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-submit-spark-jobs?view=azureml-api-2 | |
| Log metrics in Azure ML designer pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-track-designer-experiments?view=azureml-api-1 | |
| Train PyTorch models using Azure ML SDK v2 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorch?view=azureml-api-2 | |
| Use Azure AutoML ONNX models with ML.NET in .NET apps | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-automl-onnx-model-dotnet?view=azureml-api-2 | |
| Invoke Azure ML batch endpoints from Azure Data Factory | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-azure-data-factory?view=azureml-api-2 | |
| Access Azure ML batch endpoints from Microsoft Fabric | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-fabric?view=azureml-api-2 | |
| Trigger Azure ML batch endpoints from Event Grid | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-event-grid-batch?view=azureml-api-2 | |
| Integrate Azure ML events with Azure Event Grid | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-event-grid?view=azureml-api-2 | |
| Use labeled datasets from Azure ML labeling | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-labeled-dataset?view=azureml-api-1 | |
| Integrate Azure Databricks MLflow tracking with Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-databricks?view=azureml-api-2 | |
| Configure MLflow tracking from Azure Synapse to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-synapse?view=azureml-api-2 | |
| Integrate Azure Synapse Spark in Azure ML pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-synapsesparkstep?view=azureml-api-1 | |
| Create and use custom tool packages in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-custom-tool-package-creation-and-usage?view=azureml-api-2 | |
| Develop Prompt Flow and chat flows in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-flow?view=azureml-api-2 | |
| Evaluate Semantic Kernel using Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-evaluate-semantic-kernel?view=azureml-api-2 | |
| Integrate LangChain with Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-integrate-with-langchain?view=azureml-api-2 | |
| Rebuild Prompt Flow workflows using Microsoft Agent Framework | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-migrate-prompt-flow-to-agent-framework?view=azureml-api-2 | |
| Use images within Azure ML prompt flows | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-process-image?view=azureml-api-2 | |
| Use Azure OpenAI GPT-4 Turbo with Vision tool in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/azure-open-ai-gpt-4v-tool?view=azureml-api-2 | |
| Use Content Safety text tool in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/content-safety-text-tool?view=azureml-api-2 | |
| Configure the embedding tool for prompt flow RAG | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/embedding-tool?view=azureml-api-2 | |
| Configure Index Lookup tool for vector search in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/index-lookup-tool?view=azureml-api-2 | |
| Configure and use the LLM tool in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/llm-tool?view=azureml-api-2 | |
| Configure Open Model LLM tool for open-source models | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/open-model-llm-tool?view=azureml-api-2 | |
| Integrate OpenAI GPT-4V vision model via prompt flow tool | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/openai-gpt-4v-tool?view=azureml-api-2 | |
| Use the prompt tool templates in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/prompt-tool?view=azureml-api-2 | |
| Build and configure Python tools in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/python-tool?view=azureml-api-2 | |
| Set up the rerank tool for prompt flow search | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/rerank-tool?view=azureml-api-2 | |
| Integrate SerpAPI search results via prompt flow tool | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/tools-reference/serp-api-tool?view=azureml-api-2 | |
| Quickstart: Configure Spark jobs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/quickstart-spark-jobs?view=azureml-api-2 | |
| Map Azure ML v1 logging APIs to MLflow tracking | https://learn.microsoft.com/en-us/azure/machine-learning/reference-migrate-sdk-v1-mlflow-tracking?view=azureml-api-2 |
Deployment
| Topic | URL | |
|---|---|---|
| Consume Azure ML standard deployments across workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-connect-models-serverless?view=azureml-api-2 | |
| Convert ML notebooks to production scripts with MLOpsPython | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-convert-ml-experiment-to-production?view=azureml-api-1 | |
| Deploy AutoML models to AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-automl-endpoint?view=azureml-api-2 | |
| Deploy AML models to Azure Container Instances with CLI v1 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-container-instance?view=azureml-api-1 | |
| Deploy AML models to Azure Kubernetes Service with SDK/CLI v1 | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-azure-kubernetes-service?view=azureml-api-1 | |
| Deploy custom-container models to AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-custom-container?view=azureml-api-2 | |
| Progressively deploy MLflow models to Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-models-online-progressive?view=azureml-api-2 | |
| Deploy MLflow models to Azure ML endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-models?view=azureml-api-2 | |
| Customize batch deployment outputs in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-model-custom-output?view=azureml-api-2 | |
| Deploy Azure ML registry models using deployment templates | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-deployment-template?view=azureml-api-2 | |
| Deploy catalog models as standard deployments in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-serverless?view=azureml-api-2 | |
| Deploy models to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2 | |
| Deploy models to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2 | |
| Deploy models to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2 | |
| Deploy models to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2 | |
| Deploy models to Azure ML managed online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints?view=azureml-api-2 | |
| Publish and run Azure ML pipelines in production | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-pipelines?view=azureml-api-1 | |
| Deploy ONNX models with Triton on Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-with-triton?view=azureml-api-2 | |
| Create GitHub Actions CI/CD for Azure ML training | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-github-actions-machine-learning?view=azureml-api-2 | |
| Deploy image-processing models with AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-image-processing-batch?view=azureml-api-2 | |
| Deploy MLflow models to Azure ML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-mlflow-batch?view=azureml-api-2 | |
| Retrain Azure ML designer models via published pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-retrain-designer?view=azureml-api-1 | |
| Run Azure ML RAG prompt flows locally with VS Code | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-retrieval-augmented-generation-cloud-to-local?view=azureml-api-2 | |
| Deploy and trigger batch prediction pipelines in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-run-batch-predictions-designer?view=azureml-api-1 | |
| Perform safe blue-green rollouts for Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-safely-rollout-online-endpoints?view=azureml-api-2 | |
| Set up end-to-end MLOps with Azure DevOps and Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-mlops-azureml?view=azureml-api-2 | |
| Set up end-to-end MLOps with GitHub and Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-mlops-github-azure-ml?view=azureml-api-2 | |
| Trigger published Azure ML pipelines automatically | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-trigger-published-pipeline?view=azureml-api-1 | |
| Deploy models for batch scoring with AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-model-deployments?view=azureml-api-2 | |
| Run Azure OpenAI embeddings via AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-model-openai-embeddings?view=azureml-api-2 | |
| Deploy and invoke pipelines via AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-pipeline-deployments?view=azureml-api-2 | |
| Convert existing AML pipeline jobs to batch endpoint deployments | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-pipeline-from-job?view=azureml-api-2 | |
| Operationalize scoring pipelines on AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-scoring-pipeline?view=azureml-api-2 | |
| Operationalize training pipelines on AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-training-pipeline?view=azureml-api-2 | |
| Build RAG pipelines with Azure ML and prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-pipelines-prompt-flow?view=azureml-api-2 | |
| Deploy migrated Agent Framework workflows to Azure | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-migrated-agent-framework-workflow?view=azureml-api-2 | |
| Deploy prompt flows to Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-to-code?view=azureml-api-2 | |
| Implement GenAIOps pipelines with Azure DevOps and prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-end-to-end-azure-devops-with-prompt-flow?view=azureml-api-2 | |
| Integrate prompt flow with DevOps for LLM apps | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-integrate-with-llm-app-devops?view=azureml-api-2 |