1---2name: azure-machine-learning3description: 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, AutoML, online/batch endpoints, 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 HDInsight (use azure-hdinsight), Azure Data Science Virtual Machines (use azure-data-science-vm).4---5# Azure Machine Learning Skill67This 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.89## How to Use This Skill1011> **IMPORTANT for Agent**: Use the **Category Index** below to locate relevant sections. For categories with line ranges (e.g., `L35-L120`), use `read_file` with the specified lines. For categories with file links (e.g., `[security.md](security.md)`), use `read_file` on the linked reference file1213This skill requires **network access** to fetch documentation content:14- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch`. Returns Markdown.15- **Fallback**: Use `WebFetch`. Returns Markdown.1617## Category Index1819| Category | Lines | Description |20|----------|-------|-------------|21| Troubleshooting | L33-L67 | Diagnosing and fixing Azure ML errors: pipelines, AutoML, endpoints, networking, Kubernetes, environments, data access, prompt flow, and known issues/workspace diagnostics. |22| Best Practices | L68-L89 | Best practices for Azure ML experiments: model tuning, monitoring, cost and compute optimization, data prep, deployment scripts, GPU/distributed training, and prompt/model performance. |23| Decision Making | L90-L120 | 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. |24| Architecture & Design Patterns | L121-L127 | Designing Azure ML inference architectures: choosing endpoint types, planning real-time online endpoints, and structuring data movement and multistep pipeline components. |25| Limits & Quotas | L128-L136 | Info on Azure ML regional/sovereign availability, quotas and service limits, supported VM SKUs, and how to plan deployment capacity within those constraints |26| Security | L137-L190 | Securing Azure ML: encryption, keys, identity/RBAC, auth, secrets, network isolation/VNets, data exfil prevention, policy compliance, and securing endpoints, training, RAG, and prompt flows. |27| Configuration | L191-L451 | How to configure Azure ML components, compute, networking, data, monitoring, AutoML, Prompt Flow, and all CLI/YAML schemas for jobs, deployments, feature stores, and connections. |28| Integrations & Coding Patterns | L452-L509 | Patterns and how-tos for wiring Azure ML to data/compute (Synapse, Databricks, Fabric, ADF), using MLflow, REST/HTTP, Spark, Prompt Flow, and integrating LLMs, events, and external apps. |29| Deployment | L510-L551 | Deploying and operationalizing models and pipelines on Azure ML (online/batch endpoints, AKS/ACI, registries), plus CI/CD, blue‑green rollouts, and MLOps/GenAIOps with GitHub/DevOps and prompt flow. |3031### Troubleshooting32| Topic | URL |33|-------|-----|34| 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 |35| Resolve common Azure AutoML forecasting issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-automl-forecasting-faq?view=azureml-api-2 |36| 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 |37| 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 |38| 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 |39| Diagnose Azure ML pipeline performance issues with profiling | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-performance?view=azureml-api-2 |40| 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 |41| Troubleshoot Azure ML SDK v1 pipelines | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipelines?view=azureml-api-1 |42| Troubleshoot Azure automated ML experiment failures | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-auto-ml?view=azureml-api-2 |43| 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 |44| 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 |45| 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 |46| 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 |47| Troubleshoot Azure ML Kubernetes compute workloads | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-compute?view=azureml-api-2 |48| Troubleshoot Azure ML Kubernetes extension deployment | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-extension?view=azureml-api-2 |49| 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 |50| 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 |51| 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 |52| 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 |53| 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 |54| 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 |55| 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 |56| 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 |57| 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 |58| 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 |59| 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 |60| 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 |61| 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 |62| Troubleshoot Azure ML prompt flow issues | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 |63| Troubleshoot Azure ML prompt flow issues | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 |64| Troubleshoot Azure ML managed feature store errors | https://learn.microsoft.com/en-us/azure/machine-learning/troubleshooting-managed-feature-store?view=azureml-api-2 |6566### Best Practices67| Topic | URL |68|-------|-----|69| Mitigate overfitting and imbalance in Azure AutoML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-manage-ml-pitfalls?view=azureml-api-2 |70| Understand Azure ML model monitoring concepts and practices | https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2 |71| Optimize and manage Azure Machine Learning costs | https://learn.microsoft.com/en-us/azure/machine-learning/concept-plan-manage-cost?view=azureml-api-2 |72| Ethical best practices for sourcing human data | https://learn.microsoft.com/en-us/azure/machine-learning/concept-sourcing-human-data?view=azureml-api-2 |73| 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 |74| 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 |75| 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 |76| 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 |77| 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 |78| 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 |79| Optimize Azure Machine Learning compute costs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-optimize-cost?view=azureml-api-2 |80| 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 |81| 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 |82| 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 |83| 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 |84| 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 |85| Tune prompts using variants in Prompt Flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-tune-prompts-using-variants?view=azureml-api-2 |86| 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 |8788### Decision Making89| Topic | URL |90|-------|-----|91| Choose Azure ML designer algorithms with cheat sheet | https://learn.microsoft.com/en-us/azure/machine-learning/algorithm-cheat-sheet?view=azureml-api-1 |92| 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 |93| 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 |94| 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 |95| 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 |96| 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 |97| 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 |98| 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 |99| Move Azure ML workspaces between subscriptions | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-move-workspace?view=azureml-api-2 |100| Plan Azure ML network isolation architecture | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-planning?view=azureml-api-2 |101| Select appropriate Azure ML algorithms for tasks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-select-algorithms?view=azureml-api-1 |102| 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 |103| 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 |104| 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 |105| 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 |106| 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 |107| 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 |108| 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 |109| 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 |110| 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 |111| 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 |112| 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 |113| 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 |114| 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 |115| 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 |116| 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 |117| 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 |118119### Architecture & Design Patterns120| Topic | URL |121|-------|-----|122| 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 |123| Understand Azure ML endpoint types for inference | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints?view=azureml-api-2 |124| 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 |125126### Limits & Quotas127| Topic | URL |128|-------|-----|129| Check regional availability for standard model deployments | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoint-serverless-availability?view=azureml-api-2 |130| Manage Azure ML resource quotas and limits | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-quotas?view=azureml-api-2 |131| 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 |132| 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 |133| Plan capacity with Azure Machine Learning service limits | https://learn.microsoft.com/en-us/azure/machine-learning/resource-limits-capacity?view=azureml-api-2 |134135### Security136| Topic | URL |137|-------|-----|138| 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 |139| 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 |140| 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 |141| 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 |142| Plan enterprise security and governance for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-enterprise-security?view=azureml-api-2 |143| Secret injection concepts for AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secret-injection?view=azureml-api-2 |144| 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 |145| Network isolation concepts for AML managed endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-online-endpoint?view=azureml-api-2 |146| Manage vulnerabilities for Azure ML images and components | https://learn.microsoft.com/en-us/azure/machine-learning/concept-vulnerability-management?view=azureml-api-2 |147| Configure Azure ML managed network to reach on-premises | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-on-premises-resources?view=azureml-api-2 |148| 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 |149| 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 |150| 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 |151| Configure data authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-administrate-data-authentication?view=azureml-api-2 |152| 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 |153| 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 |154| 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 |155| 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 |156| 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 |157| 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 |158| 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 |159| 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 |160| 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 |161| 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 |162| 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 |163| 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 |164| 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 |165| 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 |166| 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 |167| 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 |168| 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 |169| 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 |170| 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 |171| 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 |172| 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 |173| 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 |174| 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 |175| 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 |176| 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 |177| 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 |178| Set up authentication to Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-authentication?view=azureml-api-2 |179| 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 |180| 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 |181| 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 |182| Apply built-in Azure Policy definitions for AML | https://learn.microsoft.com/en-us/azure/machine-learning/policy-reference?view=azureml-api-2 |183| 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 |184| 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 |185| Apply Azure Policy regulatory controls to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/security-controls-policy?view=azureml-api-2 |186| 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 |187| 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 |188189### Configuration190| Topic | URL |191|-------|-----|192| Configure AutoML Classification component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/classification?view=azureml-api-2 |193| Configure AutoML Forecasting component in designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/forecasting?view=azureml-api-2 |194| 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 |195| Configure AutoML Image Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification?view=azureml-api-2 |196| 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 |197| 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 |198| Configure AutoML Regression component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/regression?view=azureml-api-2 |199| 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 |200| Configure AutoML Text Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification?view=azureml-api-2 |201| 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 |202| Configure Add Columns component to concatenate datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-columns?view=azureml-api-2 |203| 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 |204| 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 |205| 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 |206| 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 |207| Configure Apply Transformation component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-transformation?view=azureml-api-2 |208| 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 |209| 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 |210| 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 |211| Configure Clip Values component to handle outliers | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clip-values?view=azureml-api-2 |212| 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 |213| 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 |214| 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 |215| 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 |216| 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 |217| 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 |218| 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 |219| 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 |220| 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 |221| Configure DenseNet image classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/densenet?view=azureml-api-2 |222| 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 |223| 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 |224| Configure Evaluate Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-model?view=azureml-api-2 |225| Configure Evaluate Recommender component for model accuracy | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-recommender?view=azureml-api-2 |226| 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 |227| 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 |228| 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 |229| 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 |230| 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 |231| 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 |232| 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 |233| 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 |234| 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 |235| 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 |236| 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 |237| Configure Join Data component to merge datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/join-data?view=azureml-api-2 |238| 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 |239| 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 |240| Configure Linear Regression component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/linear-regression?view=azureml-api-2 |241| 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 |242| 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 |243| 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 |244| 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 |245| 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 |246| Configure Normalize Data component for feature scaling | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/normalize-data?view=azureml-api-2 |247| 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 |248| 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 |249| 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 |250| 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 |251| 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 |252| 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 |253| Configure Preprocess Text component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/preprocess-text?view=azureml-api-2 |254| 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 |255| Configure ResNet image classification in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/resnet?view=azureml-api-2 |256| 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 |257| 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 |258| Configure Score SVD Recommender for predictions | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-svd-recommender?view=azureml-api-2 |259| 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 |260| 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 |261| 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 |262| 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 |263| Configure SMOTE component to oversample minority classes | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/smote?view=azureml-api-2 |264| 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 |265| 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 |266| Configure Summarize Data component for descriptive statistics | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/summarize-data?view=azureml-api-2 |267| 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 |268| 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 |269| 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 |270| Configure Train SVD Recommender in Azure ML designer | https://learn.microsoft.com/en-us/a271272…(truncated)
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