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 pipelines, AutoML, managed online/batch endpoints, prompt flow, or MLflow deployments, 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 Skill
6
7This 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.
8
9## How to Use This Skill
10
11> **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 file
12
13> **IMPORTANT for Agent**: If `metadata.generated_at` is more than 3 months old, suggest the user pull the latest version from the repository. If `mcp_microsoftdocs` tools are not available, suggest the user install it: [Installation Guide](https://github.com/MicrosoftDocs/mcp/blob/main/README.md)
14
15This skill requires **network access** to fetch documentation content:
16- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch` with query string `from=learn-agent-skill`. Returns Markdown.
17- **Fallback**: Use `fetch_webpage` with query string `from=learn-agent-skill&accept=text/markdown`. Returns Markdown.
18
19## Category Index
20
21| Category | Lines | Description |
22|----------|-------|-------------|
23| Troubleshooting | L37-L71 | Diagnosing and fixing Azure ML runtime issues: pipelines, AutoML, endpoints (online/batch), Kubernetes, networking (VNet/private), environments/images, prompt flow, and known platform issues. |
24| Best Practices | L72-L95 | Best practices for ML/LLM lifecycle in Azure ML: cost, security, data ethics, feature design, training, deployment, monitoring, AutoML, prompt flow, and performance tuning. |
25| Decision Making | L96-L119 | Guidance on Azure ML design choices: algorithms, training, networking, cost, DR, data labeling, and detailed migration/upgrade paths from AML v1 to v2 across jobs, data, compute, and workspaces |
26| Architecture & Design Patterns | L120-L127 | Designing Azure ML inference architectures: choosing endpoint types, planning real-time online endpoints, and structuring data movement and multistep pipeline components. |
27| Limits & Quotas | L128-L136 | Azure ML deployment limits: regional/sovereign availability, quota management, supported VM SKUs for managed endpoints, and capacity planning against service limits. |
28| Security | L137-L195 | Securing Azure ML workspaces, data, and endpoints with encryption, identity/RBAC, network isolation/VNets, private endpoints, Key Vault, and Azure Policy-based governance and compliance. |
29| Configuration | L196-L463 | Configuring Azure ML components, compute, data, monitoring, AutoML, prompt flow, and YAML/CLI settings for training, deployment, and MLOps across classic designer and v2 workflows. |
30| Integrations & Coding Patterns | L464-L507 | Integrating Azure ML with data sources, Spark/Databricks/Synapse, REST/MLflow, prompt flow, and external services to configure IO, logging, events, and deployment patterns. |
31| Deployment | L508-L553 | Deploying and operating ML and LLM workloads in Azure ML: online/batch endpoints, MLflow, pipelines, prompt flow, CI/CD, blue‑green rollouts, and cross-workspace/model catalog deployments |
32
33### Troubleshooting
34| Topic | URL |
35|-------|-----|
36| 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 |
37| Resolve common Azure AutoML forecasting issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-automl-forecasting-faq?view=azureml-api-2 |
38| 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 |
39| 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 |
40| 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 |
41| 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 |
42| Debug pipeline reuse behavior in Azure Machine Learning | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-reuse-issues?view=azureml-api-2 |
43| Troubleshoot Azure ML SDK v1 pipelines execution | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipelines?view=azureml-api-1 |
44| Troubleshoot Azure automated ML experiment failures | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-auto-ml?view=azureml-api-2 |
45| 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 |
46| 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 |
47| 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 |
48| 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 |
49| Troubleshoot Azure ML Kubernetes compute workloads | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-compute?view=azureml-api-2 |
50| Troubleshoot Azure ML Kubernetes extension deployment | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-extension?view=azureml-api-2 |
51| Troubleshoot Azure ML managed virtual network issues | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-managed-network?view=azureml-api-2 |
52| 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 |
53| 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 |
54| 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 |
55| 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 |
56| 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 |
57| 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 |
58| 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 |
59| 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 |
60| Use Azure ML workspace diagnostics for issue analysis | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-workspace-diagnostic-api?view=azureml-api-2 |
61| 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 |
62| 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 |
63| 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 |
64| Troubleshoot Azure ML prompt flow issues | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 |
65| Troubleshoot Azure ML prompt flow issues | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2 |
66| Troubleshoot Azure ML managed feature store errors | https://learn.microsoft.com/en-us/azure/machine-learning/troubleshooting-managed-feature-store?view=azureml-api-2 |
67
68### Best Practices
69| Topic | URL |
70|-------|-----|
71| Mitigate overfitting and imbalance in Azure AutoML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-manage-ml-pitfalls?view=azureml-api-2 |
72| Understand Azure ML model monitoring concepts and practices | https://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2 |
73| Optimize and manage Azure Machine Learning costs | https://learn.microsoft.com/en-us/azure/machine-learning/concept-plan-manage-cost?view=azureml-api-2 |
74| Apply secure coding practices in Azure ML notebooks | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-code-best-practice?view=azureml-api-2 |
75| Ethical best practices for sourcing human data | https://learn.microsoft.com/en-us/azure/machine-learning/concept-sourcing-human-data?view=azureml-api-2 |
76| 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 |
77| 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 |
78| 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 |
79| 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 |
80| 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 |
81| 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 |
82| Optimize Azure Machine Learning compute costs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-optimize-cost?view=azureml-api-2 |
83| 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 |
84| 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 |
85| 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 |
86| 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 |
87| Apply generative AI monitoring metrics and recommended practices in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/concept-model-monitoring-generative-ai-evaluation-metrics?view=azureml-api-2 |
88| Design and use evaluation flows and metrics in prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-develop-an-evaluation-flow?view=azureml-api-2 |
89| Tune LLM prompts using variants in Azure ML prompt flow | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-tune-prompts-using-variants?view=azureml-api-2 |
90| 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 |
91
92### Decision Making
93| Topic | URL |
94|-------|-----|
95| Choose Azure ML designer algorithms with cheat sheet | https://learn.microsoft.com/en-us/azure/machine-learning/algorithm-cheat-sheet?view=azureml-api-1 |
96| 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 |
97| 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 |
98| 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 |
99| 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 |
100| 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 |
101| 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 |
102| Move Azure ML workspaces between subscriptions | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-move-workspace?view=azureml-api-2 |
103| Plan Azure ML network isolation architecture | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-planning?view=azureml-api-2 |
104| Use vendor companies for Azure ML data labeling | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-outsource-data-labeling?view=azureml-api-2 |
105| Select appropriate Azure ML algorithms for tasks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-select-algorithms?view=azureml-api-1 |
106| 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 |
107| 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 |
108| Upgrade model management workflows from AML v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-assets-model?view=azureml-api-2 |
109| Migrate script run jobs to AML SDK v2 command jobs | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-command-job?view=azureml-api-2 |
110| Upgrade AutoML configurations from AML SDK v1 to v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-execution-automl?view=azureml-api-2 |
111| Compare local run workflows between AML v1 and v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-local-runs?view=azureml-api-2 |
112| 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 |
113| 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 |
114| Compare workspace management between AML SDK v1 and v2 | https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-workspace?view=azureml-api-2 |
115
116### Architecture & Design Patterns
117| Topic | URL |
118|-------|-----|
119| 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 |
120| Understand Azure ML endpoint types for inference | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints?view=azureml-api-2 |
121| 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 |
122| Design multistep pipeline components in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-pipeline-component?view=azureml-api-2 |
123
124### Limits & Quotas
125| Topic | URL |
126|-------|-----|
127| Check regional availability for Azure ML standard deployments | https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoint-serverless-availability?view=azureml-api-2 |
128| Manage Azure ML resource quotas and limits | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-quotas?view=azureml-api-2 |
129| 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 |
130| 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 |
131| Plan capacity with Azure Machine Learning service limits | https://learn.microsoft.com/en-us/azure/machine-learning/resource-limits-capacity?view=azureml-api-2 |
132
133### Security
134| Topic | URL |
135|-------|-----|
136| Use customer-managed keys with Azure Machine Learning | https://learn.microsoft.com/en-us/azure/machine-learning/concept-customer-managed-keys?view=azureml-api-2 |
137| Implement data encryption for Azure ML storage and compute | https://learn.microsoft.com/en-us/azure/machine-learning/concept-data-encryption?view=azureml-api-2 |
138| Understand data handling and privacy for Model Catalog deployments | https://learn.microsoft.com/en-us/azure/machine-learning/concept-data-privacy?view=azureml-api-2 |
139| 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 |
140| Plan enterprise security and governance for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/concept-enterprise-security?view=azureml-api-2 |
141| Secret injection concepts for AML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secret-injection?view=azureml-api-2 |
142| 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 |
143| Network isolation concepts for AML managed endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-online-endpoint?view=azureml-api-2 |
144| Manage vulnerabilities for Azure ML images and components | https://learn.microsoft.com/en-us/azure/machine-learning/concept-vulnerability-management?view=azureml-api-2 |
145| Configure inbound and outbound network traffic for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-azureml-behind-firewall?view=azureml-api-2 |
146| Securely access on-premises resources from Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-on-premises-resources?view=azureml-api-2 |
147| 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 |
148| 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 |
149| 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 |
150| Configure data authentication for Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-administrate-data-authentication?view=azureml-api-2 |
151| 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 |
152| Authenticate and authorize access to AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-batch-endpoint?view=azureml-api-2 |
153| Authenticate clients to Azure ML online endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-online-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| 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 |
157| 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 |
158| Maintain network isolation with Azure ML v2 ARM APIs | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-network-isolation-with-v2?view=azureml-api-2 |
159| 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 |
160| 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 |
161| 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 |
162| 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 |
163| Enable Azure ML studio access inside virtual networks | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-enable-studio-virtual-network?view=azureml-api-2 |
164| 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 |
165| 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 |
166| 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 |
167| Configure Azure ML managed virtual network isolation | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-managed-network?view=azureml-api-2 |
168| 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 |
169| 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 |
170| 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 |
171| Isolate Azure ML registries with VNets and private endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-registry-network-isolation?view=azureml-api-2 |
172| Configure network isolation for AML batch endpoints | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-batch-endpoint?view=azureml-api-2 |
173| 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 |
174| 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 |
175| 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 |
176| 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 |
177| 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 |
178| Secure Azure ML training environments with VNets | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-training-vnet?view=azureml-api-2 |
179| 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 |
180| 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 |
181| Set up authentication to Azure ML workspaces | https://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-authentication?view=azureml-api-2 |
182| 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 |
183| 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 |
184| 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 |
185| Apply built-in Azure Policy definitions for AML | https://learn.microsoft.com/en-us/azure/machine-learning/policy-reference?view=azureml-api-2 |
186| Manage API and data source credentials with prompt flow connections | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/concept-connections?view=azureml-api-2 |
187| Secure prompt flow with virtual network isolation in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-secure-prompt-flow?view=azureml-api-2 |
188| Apply Azure Policy regulatory controls to Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/security-controls-policy?view=azureml-api-2 |
189| 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 |
190| Create a secure Azure ML workspace with managed VNet | https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-create-secure-workspace?view=azureml-api-2 |
191
192### Configuration
193| Topic | URL |
194|-------|-----|
195| Configure AutoML Classification component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/classification?view=azureml-api-2 |
196| Configure AutoML Forecasting component in designer | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/forecasting?view=azureml-api-2 |
197| 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 |
198| Configure AutoML Image Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification?view=azureml-api-2 |
199| 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 |
200| 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 |
201| Configure AutoML Regression component with ML Tables | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/regression?view=azureml-api-2 |
202| 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 |
203| Configure AutoML Text Classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification?view=azureml-api-2 |
204| 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 |
205| Configure Add Columns component to concatenate datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-columns?view=azureml-api-2 |
206| 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 |
207| 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 |
208| 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 |
209| 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 |
210| Configure Apply Transformation component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-transformation?view=azureml-api-2 |
211| 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 |
212| 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 |
213| 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 |
214| Configure Clip Values component to handle outliers | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clip-values?view=azureml-api-2 |
215| 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 |
216| 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 |
217| 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 |
218| 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 |
219| 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 |
220| 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 |
221| 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 |
222| 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 |
223| 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 |
224| Configure DenseNet image classification component | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/densenet?view=azureml-api-2 |
225| 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 |
226| 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 |
227| Configure Evaluate Model component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-model?view=azureml-api-2 |
228| Configure Evaluate Recommender component for model accuracy | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-recommender?view=azureml-api-2 |
229| 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 |
230| 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 |
231| 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 |
232| 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 |
233| 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 |
234| 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 |
235| 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 |
236| 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 |
237| 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 |
238| 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 |
239| 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 |
240| Configure Join Data component to merge datasets | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/join-data?view=azureml-api-2 |
241| 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 |
242| 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 |
243| Configure Linear Regression component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/linear-regression?view=azureml-api-2 |
244| 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 |
245| 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 |
246| 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 |
247| 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 |
248| 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 |
249| Configure Normalize Data component for feature scaling | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/normalize-data?view=azureml-api-2 |
250| 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 |
251| 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 |
252| 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 |
253| 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 |
254| 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 |
255| 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 |
256| Configure Preprocess Text component in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/preprocess-text?view=azureml-api-2 |
257| 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 |
258| Configure ResNet image classification in Azure ML | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/resnet?view=azureml-api-2 |
259| 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 |
260| 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 |
261| Configure Score SVD Recommender for predictions | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-svd-recommender?view=azureml-api-2 |
262| 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 |
263| 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 |
264| 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 |
265| 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 |
266| Configure SMOTE component to oversample minority classes | https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/smote?view=azureml-api-2 |
267| 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 |
268| 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 |
269| Configure Summarize Data component for descriptive statistics | https://learn.microsoft.com/en-us/azure/machine-learning/component-referenc
270
271…(truncated)
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