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Official agent skill

Azure Machine Learning

by MicrosoftDocs in MicrosoftDocs/Agent-Skills

Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration…

OfficialCC-BY-4.0Auto-check passedDevelopment

Install Azure Machine Learning

skills CLI
$ npx skills add MicrosoftDocs/Agent-Skills --skill azure-machine-learning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install MicrosoftDocs/Agent-Skills azure-machine-learning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/MicrosoftDocs/Agent-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/azure-machine-learning .claude/skills/azure-machine-learning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-machine-learning
GitHub stars
775
Used in
1 other repo
Token cost
~19k tokens
SKILL.md length
4,040 words
Files
1
Skills in repo
149
Repo updated
First seen
Licence
CC-BY-4.0

At a glance

Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration…

  • Online/batch endpoints
  • SKILL.md covers How to Use This Skill and Category Index
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Vector stores/RAG

What it does

Azure Machine Learning is an agent skill from MicrosoftDocs/Agent-Skills, published by the product's own GitHub organization. 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 AutoML, Prompt Flow, online/batch endpoints, vector stores/RAG, or MLflow/ONNX deployments, and other Azure Machine Learning related development tasks. Not for Azure Databricks (use azure-databricks), Azure Synapse Analytics (use azure-synapse-analytics), Azure…

Its SKILL.md is about 19k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires network access. Uses mcpmicrosoftdocs:microsoftdocsfetch or fetchwebpage to retrieve documentation.

It sits in Development, covering Deployment, Design patterns and Vector databases. It works with Azure Machine Learning, Microsoft Azure, Databricks and MLflow. The repository describes itself as: Curated Agent Skills for Microsoft & Azure – giving AI coding assistants structured, real-time expertise from Microsoft Learn docs. The licence is CC-BY-4.0.

When your agent uses it

  • Online/batch endpoints
  • Vector stores/RAG
  • MLflow/ONNX deployments
  • Other Azure Machine Learning related development tasks

Example prompts

  • “/azure-machine-learning”

Requirements

  • Compatibility (from SKILL.md): Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.

What it can do on your machine

Read from SKILL.md and the folder at commit ba74e8f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • learn.microsoft.com
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.

    From compatibility in the SKILL.md frontmatter.

Context cost

Azure Machine Learning loads about 19k tokens when it runs. Until then it costs about 159 tokens; SKILL.md has 4,040 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~159
When it runs · the whole SKILL.md, loaded when a task matches
~19k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from MicrosoftDocs/Agent-Skills at commit ba74e8f, republished under its CC-BY-4.0 licence (© MicrosoftDocs). 4,040 words, ~18,647 tokens.

Download SKILL.mdSave it as .claude/skills/azure-machine-learning/SKILL.md (or your agent's skills folder).
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 AutoML, Prompt Flow, online/batch endpoints, vector stores/RAG, or MLflow/ONNX deployments, 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
2026-10-04
metadata.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), 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

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

This skill requires network access to fetch documentation content:

  • Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
  • Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

CategoryLinesDescription
TroubleshootingL37-L65Diagnosing and fixing Azure ML failures and errors across pipelines, endpoints, AutoML, networking, Kubernetes, environments, data access, prompt flow, and known platform issues.
Best PracticesL66-L80Guidance on optimizing AutoML and training, handling imbalance/overfitting, preparing data, batch/inference performance, monitoring models, and reducing Azure ML compute and cost.
Decision MakingL81-L108Guides for planning and making migration, upgrade, networking, DR, data, compute, deployment, and monitoring decisions across Azure ML v1/v2, Fabric, Prompt Flow, and Agent Framework.
Architecture & Design PatternsL109-L114Designing real-time inference architectures with online endpoints and building RAG solutions using Azure ML vector stores, including deployment, scaling, and integration patterns.
Limits & QuotasL115-L124Limits, quotas, and availability for Azure ML: regional/sovereign support, VM SKUs, workspace soft delete, and capacity planning for managed online endpoints.
SecurityL125-L174Securing Azure ML workspaces, endpoints, and data: encryption, identity/RBAC, network isolation/VNet, Key Vault secrets, policies, compliance, and secure access to other Azure/on-prem resources.
ConfigurationL175-L408Configuring Azure ML components, compute, networking, AutoML, YAML schemas, monitoring, and Prompt Flow so you can build, train, deploy, and manage ML workflows and infrastructure.
Integrations & Coding PatternsL409-L451Integrating Azure ML with data platforms, REST/MLflow APIs, Spark, Databricks/Synapse/Fabric, and building/debugging prompt flow/RAG tools and deployments.
DeploymentL452-L481Deploying and operationalizing models and pipelines on Azure ML (online/batch endpoints, CI/CD, MLOps, prompt flow, RAG, HF/MLflow/ONNX), including rollout strategies and cross-workspace/registry use.
Troubleshooting
TopicURL
Troubleshoot Azure ML designer component error codeshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/designer-error-codes?view=azureml-api-2
Resolve common Azure AutoML forecasting issueshttps://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 Codehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-managed-online-endpoints-visual-studio-code?view=azureml-api-2
Diagnose and fix Azure ML pipeline failures in studiohttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-failure?view=azureml-api-2
Troubleshoot Azure ML pipeline performance with profilinghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-performance?view=azureml-api-2
Diagnose and fix Azure ML pipeline reuse issueshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-debug-pipeline-reuse-issues?view=azureml-api-2
Troubleshoot Azure automated ML experiment failureshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-auto-ml?view=azureml-api-2
Troubleshoot Azure ML batch endpoints and jobshttps://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 v2https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-data-access?view=azureml-api-2
Troubleshoot Azure ML data labeling project creationhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-data-labeling?view=azureml-api-2
Troubleshoot Azure ML environment image build failureshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-environments?view=azureml-api-2
Troubleshoot Azure ML Kubernetes compute workloadshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-compute?view=azureml-api-2
Troubleshoot Azure ML Kubernetes extension deploymenthttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-kubernetes-extension?view=azureml-api-2
Diagnose Azure ML managed virtual network issueshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-managed-network?view=azureml-api-2
Troubleshoot Azure ML online endpoint deployment and scoring errorshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-online-endpoints?view=azureml-api-2
Resolve 'descriptors cannot be created directly' in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-protobuf-descriptor-error?view=azureml-api-2
Troubleshoot private endpoint access to Azure ML workspaceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-secure-connection-workspace?view=azureml-api-2
Fix 'Validation for schema failed' errors in Azure ML CLI v2https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-validation-for-schema-failed-error?view=azureml-api-2
Diagnose and fix Azure ML workspace issueshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-workspace-diagnostic-api?view=azureml-api-2
Review Azure Machine Learning current known issueshttps://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 deploymenthttps://learn.microsoft.com/en-us/azure/machine-learning/known-issues/inferencing-invalid-certificate?view=azureml-api-2
Known issue: Updating Azure ML Kubernetes compute failshttps://learn.microsoft.com/en-us/azure/machine-learning/known-issues/inferencing-updating-kubernetes-compute-appears-to-succeed?view=azureml-api-2
Troubleshoot common prompt flow issues in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2
Troubleshoot common prompt flow issues in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/troubleshoot-guidance?view=azureml-api-2
Troubleshoot Azure ML managed feature store errorshttps://learn.microsoft.com/en-us/azure/machine-learning/troubleshooting-managed-feature-store?view=azureml-api-2
Best Practices
TopicURL
Mitigate overfitting and imbalance in Azure AutoMLhttps://learn.microsoft.com/en-us/azure/machine-learning/concept-manage-ml-pitfalls?view=azureml-api-2
Understand Azure ML model monitoring concepts and practiceshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-model-monitoring?view=azureml-api-2
Optimize and manage Azure Machine Learning costshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-plan-manage-cost?view=azureml-api-2
Design feature set transformations in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/feature-set-specification-transformation-concepts?view=azureml-api-2
Author batch scoring scripts for AML batch deploymentshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-batch-scoring-script?view=azureml-api-2
Tune Azure ML Kubernetes inference router performancehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-kubernetes-inference-routing-azureml-fe?view=azureml-api-2
Optimize Azure Machine Learning compute costshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-optimize-cost?view=azureml-api-2
Prepare image datasets for Azure AutoML visionhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-prepare-datasets-for-automl-images?view=azureml-api-2
Apply distributed GPU training patterns in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-distributed-gpu?view=azureml-api-2
Optimize AutoML for small object detection in imageshttps://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 Nebulahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-checkpoint-performance-for-large-models?view=azureml-api-2
Decision Making
TopicURL
Choose between managed and custom network isolation in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/concept-network-isolation-configurations?view=azureml-api-2
Choose migration paths from Azure ML Data Import to Fabrichttps://learn.microsoft.com/en-us/azure/machine-learning/data-import-migration-guide?view=azureml-api-2
Plan failover and disaster recovery for Azure MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-imported-data-assets?view=azureml-api-2
Decide and plan migration from Azure ML v1 to v2https://learn.microsoft.com/en-us/azure/machine-learning/how-to-migrate-from-v1?view=azureml-api-2
Move Azure ML workspaces between subscriptionshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-move-workspace?view=azureml-api-2
Plan Azure ML network isolation architecturehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-planning?view=azureml-api-2
Select and use vendor companies for Azure ML data labelinghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-outsource-data-labeling?view=azureml-api-2
Map Azure ML v1 datasets to v2 data assetshttps://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 v2https://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 jobshttps://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 v2https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-deploy-endpoints?view=azureml-api-2
Upgrade Azure ML pipeline endpoints from v1 to v2https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-deploy-pipelines?view=azureml-api-2
Upgrade Azure ML AutoML workflows from SDK v1 to v2https://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 jobshttps://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 jobhttps://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 jobshttps://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 v2https://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-managed-online-endpoints?view=azureml-api-2
Compare and migrate Azure ML compute management v1 to v2https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-compute?view=azureml-api-2
Migrate datastore management from AML v1 to v2https://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 v2https://learn.microsoft.com/en-us/azure/machine-learning/migrate-to-v2-resource-workspace?view=azureml-api-2
Select and interpret Azure ML generative AI monitoring metricshttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/concept-model-monitoring-generative-ai-evaluation-metrics?view=azureml-api-2
Plan migration from Prompt Flow to Agent Frameworkhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/migrate-prompt-flow-to-agent-framework?view=azureml-api-2
Architecture & Design Patterns
TopicURL
Plan real-time inference with Azure ML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online?view=azureml-api-2
Use Azure ML vector stores for RAG architectureshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-vector-stores?view=azureml-api-2
Limits & Quotas
TopicURL
Check regional availability for standard model deploymentshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoint-serverless-availability?view=azureml-api-2
Understand soft delete retention for ML workspaceshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-soft-delete?view=azureml-api-2
Manage Azure ML resource quotas and limitshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-quotas?view=azureml-api-2
Check Azure ML feature availability by sovereign cloudhttps://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 endpointshttps://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 limitshttps://learn.microsoft.com/en-us/azure/machine-learning/resource-limits-capacity?view=azureml-api-2
Security
TopicURL
Configure customer-managed keys for Azure Machine Learninghttps://learn.microsoft.com/en-us/azure/machine-learning/concept-customer-managed-keys?view=azureml-api-2
Understand data encryption for Azure ML compute and storagehttps://learn.microsoft.com/en-us/azure/machine-learning/concept-data-encryption?view=azureml-api-2
Understand data handling and privacy for Azure ML Model Cataloghttps://learn.microsoft.com/en-us/azure/machine-learning/concept-data-privacy?view=azureml-api-2
Understand auth and RBAC for AML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online-auth?view=azureml-api-2
Plan enterprise security and governance for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/concept-enterprise-security?view=azureml-api-2
Secret injection concepts for AML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-secret-injection?view=azureml-api-2
Understand secure network traffic flow for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-network-traffic-flow?view=azureml-api-2
Network isolation concepts for AML managed endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-secure-online-endpoint?view=azureml-api-2
Manage vulnerabilities in Azure Machine Learning imageshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-vulnerability-management?view=azureml-api-2
Configure inbound and outbound traffic for secure Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-azureml-behind-firewall?view=azureml-api-2
Securely connect Azure ML managed VNet to on-premiseshttps://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 identityhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-resources-from-endpoints-managed-identities?view=azureml-api-2
Assign users and roles for Azure ML data labelinghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-add-users?view=azureml-api-2
Administer data access and authentication for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-administrate-data-authentication?view=azureml-api-2
Manage Azure ML workspace access with RBAC roleshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-assign-roles?view=azureml-api-2
Authorize access to Azure ML batch endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-batch-endpoint?view=azureml-api-2
Configure authentication for Azure ML online endpointshttps://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 deploymentshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-built-in-policy-model-deployment?view=azureml-api-2
Rotate Azure ML workspace storage access keys securelyhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-change-storage-access-key?view=azureml-api-2
Configure custom DNS for private Azure ML endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-custom-dns?view=azureml-api-2
Create custom Azure Policies to restrict AI model deploymentshttps://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 deploymentshttps://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 storagehttps://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 MLhttps://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 Policyhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-integrate-azure-policy?view=azureml-api-2
Configure managed virtual network isolation for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-managed-network?view=azureml-api-2
Configure Model Catalog access with workspace managed virtual networkshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-isolation-model-catalog?view=azureml-api-2
Secure Azure ML workspaces with VNets and isolationhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-network-security-overview?view=azureml-api-2
Configure data exfiltration prevention for Azure MLhttps://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 networkshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-batch-endpoint?view=azureml-api-2
Secure Azure ML online inferencing with VNetshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-inferencing-vnet?view=azureml-api-2
Secure AKS inferencing environments for Azure MLhttps://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 endpointshttps://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 isolationhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-online-endpoint?view=azureml-api-2
Secure Azure ML RAG workflows with network isolationhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-rag-workflows?view=azureml-api-2
Secure Azure ML training with virtual networkshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-training-vnet?view=azureml-api-2
Secure Azure ML workspace using virtual networkshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-secure-workspace-vnet?view=azureml-api-2
Configure RBAC access to Azure ML feature storehttps://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 workspaceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-authentication?view=azureml-api-2
Configure customer-managed keys for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-customer-managed-keys?view=azureml-api-2
Securely use Key Vault secrets in Azure ML runshttps://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 AMLhttps://learn.microsoft.com/en-us/azure/machine-learning/policy-reference?view=azureml-api-2
Manage credentials with connections in Azure ML prompt flowhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/concept-connections?view=azureml-api-2
Configure network isolation for Prompt flow in Azure MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/security-controls-policy?view=azureml-api-2
Create secure Azure ML workspace with managed VNethttps://learn.microsoft.com/en-us/azure/machine-learning/tutorial-create-secure-workspace?view=azureml-api-2
Configuration
TopicURL
Configure AutoML Classification component with ML Tableshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/classification?view=azureml-api-2
Configure AutoML Forecasting component in designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/forecasting?view=azureml-api-2
Configure AutoML Image Multi-label Classificationhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification-multilabel?view=azureml-api-2
Configure AutoML Image Classification componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-classification?view=azureml-api-2
Configure AutoML Image Instance Segmentation componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-instance-segmentation?view=azureml-api-2
Configure AutoML Image Object Detection componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/image-object-detection?view=azureml-api-2
Configure AutoML Regression component with ML Tableshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/regression?view=azureml-api-2
Configure AutoML Text Multi-label Classification componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification-multilabel?view=azureml-api-2
Configure AutoML Text Classification componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-classification?view=azureml-api-2
Configure AutoML Text NER component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference-v2/text-ner?view=azureml-api-2
Configure Add Columns component to concatenate datasetshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-columns?view=azureml-api-2
Configure Add Rows component to append dataset recordshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/add-rows?view=azureml-api-2
Configure Apply Image Transformation in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-image-transformation?view=azureml-api-2
Configure Apply Math Operation component for column calculationshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-math-operation?view=azureml-api-2
Configure Apply SQL Transformation component using SQLitehttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-sql-transformation?view=azureml-api-2
Configure Apply Transformation component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/apply-transformation?view=azureml-api-2
Configure Assign Data to Clusters in Azure MLhttps://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 nullshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clean-missing-data?view=azureml-api-2
Configure Clip Values component to handle outliershttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/clip-values?view=azureml-api-2
Configure and use Azure ML designer algorithm componentshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/component-reference?view=azureml-api-2
Configure Convert to CSV component for dataset exporthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-csv?view=azureml-api-2
Configure Convert to Dataset component for internal formathttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/convert-to-dataset?view=azureml-api-2
Configure Convert to Image Directory in Azure MLhttps://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 encodinghttps://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 MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/create-python-model?view=azureml-api-2
Configure Cross Validate Model component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/cross-validate-model?view=azureml-api-2
Configure Decision Forest Regression in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/decision-forest-regression?view=azureml-api-2
Configure DenseNet image classification componenthttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/densenet?view=azureml-api-2
Configure Edit Metadata component to adjust column roleshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/edit-metadata?view=azureml-api-2
Set up Enter Data Manually component for small datasetshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/enter-data-manually?view=azureml-api-2
Configure Evaluate Model component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-model?view=azureml-api-2
Configure Evaluate Recommender component for model accuracyhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/evaluate-recommender?view=azureml-api-2
Configure Execute Python Script in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/execute-python-script?view=azureml-api-2
Configure Execute R Script component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/execute-r-script?view=azureml-api-2
Configure Export Data component to save pipeline outputshttps://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 MLhttps://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 MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/feature-hashing?view=azureml-api-2
Configure Filter Based Feature Selection for predictive columnshttps://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 designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/graph-search-syntax?view=azureml-api-2
Configure Group Data into Bins component for discretizationhttps://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 pipelineshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/import-data?view=azureml-api-2
Configure Init Image Transformation in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/init-image-transformation?view=azureml-api-2
Configure Join Data component to merge datasetshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/join-data?view=azureml-api-2
Configure K-Means Clustering component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/k-means-clustering?view=azureml-api-2
Configure Latent Dirichlet Allocation component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/latent-dirichlet-allocation?view=azureml-api-2
Configure Linear Regression component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/linear-regression?view=azureml-api-2
Configure Multiclass Boosted Decision Tree in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-boosted-decision-tree?view=azureml-api-2
Configure Multiclass Decision Forest in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-decision-forest?view=azureml-api-2
Configure Multiclass Logistic Regression in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-logistic-regression?view=azureml-api-2
Configure Multiclass Neural Network in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/multiclass-neural-network?view=azureml-api-2
Set up Neural Network Regression in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/neural-network-regression?view=azureml-api-2
Configure Normalize Data component for feature scalinghttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/normalize-data?view=azureml-api-2
Configure One-vs-All Multiclass component in Azure MLhttps://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 MLhttps://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 splittinghttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/partition-and-sample?view=azureml-api-2
Configure deprecated PCA-Based Anomaly Detection componenthttps://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 insightshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/permutation-feature-importance?view=azureml-api-2
Use Poisson Regression component in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/poisson-regression?view=azureml-api-2
Configure Preprocess Text component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/preprocess-text?view=azureml-api-2
Configure Remove Duplicate Rows component for deduplicationhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/remove-duplicate-rows?view=azureml-api-2
Configure ResNet image classification in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/resnet?view=azureml-api-2
Configure Score Image Model component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-image-model?view=azureml-api-2
Configure Score Model component in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-model?view=azureml-api-2
Configure Score SVD Recommender for predictionshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-svd-recommender?view=azureml-api-2
Configure Score Vowpal Wabbit Model in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/score-vowpal-wabbit-model?view=azureml-api-2
Configure Score Wide & Deep Recommender componenthttps://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 featureshttps://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 setshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/select-columns-transform?view=azureml-api-2
Configure SMOTE component to oversample minority classeshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/smote?view=azureml-api-2
Configure Split Data component for train-test partitioninghttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/split-data?view=azureml-api-2
Configure Split Image Directory component for datasetshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/split-image-directory?view=azureml-api-2
Configure Summarize Data component for descriptive statisticshttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/summarize-data?view=azureml-api-2
Configure Train Anomaly Detection Model componenthttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-clustering-model?view=azureml-api-2
Configure Train PyTorch Model component in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-pytorch-model?view=azureml-api-2
Configure Train SVD Recommender in Azure ML designerhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-svd-recommender?view=azureml-api-2
Configure Train Vowpal Wabbit Model in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/train-vowpal-wabbit-model?view=azureml-api-2
Configure Train Wide & Deep Recommender componenthttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/component-reference/tune-model-hyperparameters?view=azureml-api-2
Configure Two-Class Averaged Perceptron in Azure MLhttps://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 MLhttps://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 MLhttps://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 MLhttps://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 MLhttps://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 MLhttps://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 componentshttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-data-collection?view=azureml-api-2
Use expressions in Azure ML SDK and CLI v2 jobshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-expressions?view=azureml-api-2
Specify models for Azure ML online deploymentshttps://learn.microsoft.com/en-us/azure/machine-learning/concept-online-deployment-model-specification?view=azureml-api-2
Use Azure ML prebuilt Docker images for inferencehttps://learn.microsoft.com/en-us/azure/machine-learning/concept-prebuilt-docker-images-inference?view=azureml-api-2
Configure and use Azure ML Responsible AI dashboardhttps://learn.microsoft.com/en-us/azure/machine-learning/concept-responsible-ai-dashboard?view=azureml-api-2
Configure feature retrieval specs for training and inferencehttps://learn.microsoft.com/en-us/azure/machine-learning/feature-retrieval-concepts?view=azureml-api-2
Configure feature set materialization in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/feature-set-materialization-concepts?view=azureml-api-2
Access Azure cloud storage data during interactive ML developmenthttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-data-interactive?view=azureml-api-2
Configure Kubernetes compute targets for Azure MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace?view=azureml-api-2
Configure Azure AutoML for time-series forecastinghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-forecast?view=azureml-api-2
Configure AutoML computer vision training in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models?view=azureml-api-2
Configure Azure AutoML for custom NLP traininghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models?view=azureml-api-2
Configure autoscaling for Azure ML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-autoscale-endpoints?view=azureml-api-2
Configure custom Azure Container for PyTorch environmentshttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-collect-production-data?view=azureml-api-2
Configure Azure ML AutoML training jobs with Pythonhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-train?view=azureml-api-2
Maintain network isolation with Azure ML v2 APIhttps://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 workspaceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-configure-private-link?view=azureml-api-2
Configure Azure ML connections to external data and serviceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-connection?view=azureml-api-2
Create and manage Azure ML compute clustershttps://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 studiohttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-studio?view=azureml-api-2
Create Azure ML compute instances for developmenthttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-compute-instance?view=azureml-api-2
Configure and use vector indexes in Azure ML prompt flowhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-vector-index?view=azureml-api-2
Create Azure ML workspaces with ARM templateshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-workspace-template?view=azureml-api-2
Customize Azure ML compute instances with startup scriptshttps://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 accesshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-datastore?view=azureml-api-2
Configure Azure ML Kubernetes extension settingshttps://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 networkhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-enable-studio-virtual-network?view=azureml-api-2
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
Log MLflow models as first-class models in Azure MLhttps://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 Insightshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-search?view=azureml-api-2
Configure model interpretability in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-machine-learning-interpretability?view=azureml-api-2
Manage Azure ML compute instances and lifecyclehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-compute-instance?view=azureml-api-2
Configure Azure ML environments with CLI and SDKhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-environments-v2?view=azureml-api-2
Create Azure ML hub workspaces with Bicep templateshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-hub-workspace-template?view=azureml-api-2
Configure and manage Azure ML Kubernetes instance typeshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-kubernetes-instance-types?view=azureml-api-2
Configure Azure ML deployment templates for modelshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models-deployment-templates?view=azureml-api-2
Manage Azure ML model registry using MLflowhttps://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 SDKhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models?view=azureml-api-2
Create and manage Azure ML registrieshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-registries?view=azureml-api-2
Attach and manage Synapse Spark pools in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-synapse-spark-pool?view=azureml-api-2
Provision Azure ML workspaces using Terraformhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace-terraform?view=azureml-api-2
Define and use MLTable schemas in Azure Machine Learninghttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-mltable?view=azureml-api-2
Collect and monitor Kubernetes endpoint inference logshttps://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 productionhttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-online-endpoints?view=azureml-api-2
Use R and RStudio on Azure ML compute instanceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-r-interactive-development?view=azureml-api-2
Configure network isolation for Azure ML registrieshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-registry-network-isolation?view=azureml-api-2
Use Responsible AI dashboard tools in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-dashboard?view=azureml-api-2
Generate Responsible AI insights in Azure ML studiohttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-responsible-ai-scorecard?view=azureml-api-2
Schedule recurring data imports in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-schedule-data-import?view=azureml-api-2
Share models and components across Azure ML workspaceshttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-track-experiments-mlflow?view=azureml-api-2
Submit MLflow Projects training jobs to Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-mlflow-projects?view=azureml-api-2
Configure and submit Azure ML training jobshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-model?view=azureml-api-2
Configure and submit Azure ML training jobshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-train-model?view=azureml-api-2
Configure Azure ML hyperparameter sweep jobshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters?view=azureml-api-2
Configure low-priority and Spot VMs for Azure ML batchhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-low-priority-batch?view=azureml-api-2
Use MLflow to track Azure ML experiments and runshttps://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 workspaceshttps://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 pipelineshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-parallel-job-in-pipeline?view=azureml-api-2
Run training jobs on Azure ML serverless computehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-serverless-compute?view=azureml-api-2
Configure hyperparameter sweep in Azure ML pipelineshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-sweep-in-pipeline?view=azureml-api-2
View and tag costs for Azure ML managed online endpointshttps://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 computehttps://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 notebookshttps://learn.microsoft.com/en-us/azure/machine-learning/interactive-data-wrangling-with-apache-spark-azure-ml?view=azureml-api-2
Reference monitoring metrics for Azure Machine Learninghttps://learn.microsoft.com/en-us/azure/machine-learning/monitor-azure-machine-learning-reference?view=azureml-api-2
Run batch evaluations for Prompt Flow at scalehttps://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 flowhttps://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 metricshttps://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 endpointshttps://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 deploymentshttps://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 sessionshttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-manage-compute-session?view=azureml-api-2
Configure monitoring for generative AI endpoints in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-monitor-generative-ai-applications?view=azureml-api-2
Configure Automated ML forecasting jobs via YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automated-ml-forecasting?view=azureml-api-2
Author AutoML image classification jobs in YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-classification?view=azureml-api-2
Define AutoML image instance segmentation YAML jobshttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-instance-segmentation?view=azureml-api-2
Configure AutoML image multilabel classification YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-multilabel-classification?view=azureml-api-2
Author AutoML image object detection YAML jobshttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-cli-object-detection?view=azureml-api-2
Configure AutoML vision hyperparameters in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters?view=azureml-api-2
Format JSONL data for AutoML computer visionhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-images-schema?view=azureml-api-2
Configure AutoML multilabel text classification YAMLhttps://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 schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-nlp-cli-ner?view=azureml-api-2
Define AutoML text classification jobs with YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-automl-nlp-cli-text-classification?view=azureml-api-2
Reference configuration for Kubernetes with Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-kubernetes?view=azureml-api-2
Define command components via Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-command?view=azureml-api-2
Author pipeline components using Azure ML YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-pipeline?view=azureml-api-2
Configure Spark components in Azure ML YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-component-spark?view=azureml-api-2
Configure AmlCompute clusters via YAML in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-aml?view=azureml-api-2
Define Azure ML compute instances with YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-instance?view=azureml-api-2
Configure attached Kubernetes clusters in Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-kubernetes?view=azureml-api-2
Attach and configure VMs via Azure ML YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-compute-vm?view=azureml-api-2
Configure AI Content Safety connections in AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-content-safety?view=azureml-api-2
Author AI Search connection YAML for AMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-search?view=azureml-api-2
Configure Foundry Tools connections with Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-ai-services?view=azureml-api-2
Define API key connections via AML YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-api-key?view=azureml-api-2
Define Azure OpenAI connections via AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-azure-openai?view=azureml-api-2
Define blob datastore connections in AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-blob?view=azureml-api-2
Configure Azure Container Registry connections in AMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-container-registry?view=azureml-api-2
Author custom key connections in Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-custom-key?view=azureml-api-2
Configure Data Lake Gen2 connections via AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-data-lake?view=azureml-api-2
Configure Git repository connections in AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-git?view=azureml-api-2
Set up OneLake connections using AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-onelake?view=azureml-api-2
Configure OpenAI service connections in AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-openai?view=azureml-api-2
Set up Python feed connections using AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-python-feed?view=azureml-api-2
Define Serp connections via Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-serp?view=azureml-api-2
Author serverless connection YAML for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-serverless?view=azureml-api-2
Configure AI Speech Services connections in AML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-connection-speech?view=azureml-api-2
Understand core Azure ML CLI v2 YAML syntaxhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-core-syntax?view=azureml-api-2
Reference schema for Azure ML data YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-data?view=azureml-api-2
Define Azure Blob datastores via YAML in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-blob?view=azureml-api-2
Author Azure Data Lake Gen1 datastore YAMLhttps://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 YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-data-lake-gen2?view=azureml-api-2
Configure Azure Files datastores using YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-datastore-files?view=azureml-api-2
Author batch deployment YAML for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-batch?view=azureml-api-2
Define Kubernetes online deployments in Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-kubernetes-online?view=azureml-api-2
Configure managed online deployments via Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-managed-online?view=azureml-api-2
Configure Azure ML CLI v2 deployment template YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-deployment-template?view=azureml-api-2
Author batch endpoint YAML for Azure ML CLI v2https://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-endpoint-batch?view=azureml-api-2
Configure Azure ML online endpoints with YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-endpoint-online?view=azureml-api-2
Reference schema for Azure ML environment YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-environment?view=azureml-api-2
Author feature entity definitions via Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-entity?view=azureml-api-2
Create feature retrieval specs with Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-retrieval-spec?view=azureml-api-2
Configure feature sets in Azure ML YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-set?view=azureml-api-2
Define feature stores in Azure ML using YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-feature-store?view=azureml-api-2
Define feature set specifications using YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-featureset-spec?view=azureml-api-2
Configure Azure ML CLI v2 command job YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-command?view=azureml-api-2
Configure Azure ML parallel job YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-parallel?view=azureml-api-2
Configure Azure ML pipeline jobs using YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-pipeline?view=azureml-api-2
Configure Spark jobs in Azure ML with YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-spark?view=azureml-api-2
Define sweep (hyperparameter) jobs with Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-job-sweep?view=azureml-api-2
Reference schema for Azure ML MLTable YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-mltable?view=azureml-api-2
Define Azure ML models with CLI v2 YAML schemahttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-model?view=azureml-api-2
Create model monitoring schedules with Azure ML YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-monitor?view=azureml-api-2
Navigate Azure ML CLI v2 YAML schema referenceshttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-overview?view=azureml-api-2
Define Azure ML registries using CLI v2 YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-registry?view=azureml-api-2
Author data import schedule YAML for Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-schedule-data-import?view=azureml-api-2
Configure Azure ML job schedules with YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-schedule?view=azureml-api-2
Reference schema for Azure ML workspace YAMLhttps://learn.microsoft.com/en-us/azure/machine-learning/reference-yaml-workspace?view=azureml-api-2
Show full SKILL.md (626 more words)Show less
Integrations & Coding Patterns
TopicURL
Copy Fabric OneLake tables into Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/create-datastore-with-user-interface?view=azureml-api-2
Configure input data sources for AML batch endpoint jobshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-access-data-batch-endpoints-jobs?view=azureml-api-2
Run MLflow models in Azure ML Spark jobshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-model-spark-jobs?view=azureml-api-2
Use Azure ML REST API for online deploymentshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-with-rest?view=azureml-api-2
Run local ONNX inference for Azure AutoML image modelshttps://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 debugginghttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-log-view-metrics?view=azureml-api-2
Manage Azure ML resources using REST APIshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-rest?view=azureml-api-2
Securely integrate Azure Synapse with Azure ML via VNetshttps://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
Generate Responsible AI dashboards with Azure ML SDKhttps://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 endpointshttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-submit-spark-jobs?view=azureml-api-2
Train PyTorch models using Azure ML SDK v2https://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 appshttps://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 Factoryhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-azure-data-factory?view=azureml-api-2
Integrate Fabric with Azure ML batch endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-fabric?view=azureml-api-2
Trigger Azure ML batch endpoints from Event Gridhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-event-grid-batch?view=azureml-api-2
Integrate Azure ML events with Event Grid workflowshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-event-grid?view=azureml-api-2
Integrate Azure Databricks MLflow tracking with Azure MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-azure-synapse?view=azureml-api-2
Set up RAG prompt flow samples in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-retrieval-augmented-generation?view=azureml-api-2
Create and use custom tool packages in prompt flowhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-custom-tool-package-creation-and-usage?view=azureml-api-2
Integrate LangChain workflows into Azure ML prompt flowhttps://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 Frameworkhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-migrate-prompt-flow-to-agent-framework?view=azureml-api-2
Process and use images within Azure ML prompt flowshttps://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 flowhttps://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 flowhttps://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 RAGhttps://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 flowhttps://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 flowhttps://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 modelshttps://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 toolhttps://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 flowhttps://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 flowhttps://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 searchhttps://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 toolhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/quickstart-spark-jobs?view=azureml-api-2
Map Azure ML v1 logging APIs to MLflow trackinghttps://learn.microsoft.com/en-us/azure/machine-learning/reference-migrate-sdk-v1-mlflow-tracking?view=azureml-api-2
Deployment
TopicURL
Consume Azure ML standard deployments across workspaceshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-connect-models-serverless?view=azureml-api-2
Deploy AutoML models to AML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-automl-endpoint?view=azureml-api-2
Deploy custom-container models to AML online endpointshttps://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 endpointshttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-models?view=azureml-api-2
Customize batch deployment outputs in Azure MLhttps://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 templateshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-deployment-template?view=azureml-api-2
Deploy Hugging Face models to Azure ML endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-from-huggingface?view=azureml-api-2
Deploy catalog models as standard serverless endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-models-serverless?view=azureml-api-2
Deploy ONNX models with Triton on Azure MLhttps://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 traininghttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-image-processing-batch?view=azureml-api-2
Deploy MLflow models to Azure ML batch endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-mlflow-batch?view=azureml-api-2
Run Azure ML RAG prompt flows locally with VS Codehttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-retrieval-augmented-generation-cloud-to-local?view=azureml-api-2
Perform safe blue-green rollouts for Azure ML online endpointshttps://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 MLhttps://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 MLhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-setup-mlops-github-azure-ml?view=azureml-api-2
Run Azure OpenAI embeddings via AML batch endpointshttps://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 endpointshttps://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 deploymentshttps://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 endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-batch-scoring-pipeline?view=azureml-api-2
Operationalize training pipelines on AML batch endpointshttps://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 flowhttps://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-pipelines-prompt-flow?view=azureml-api-2
Set up and deploy prompt flow in Azure MLhttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/get-started-prompt-flow?view=azureml-api-2
Deploy migrated Agent Framework workflows to Azurehttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-migrated-agent-framework-workflow?view=azureml-api-2
Deploy prompt flow to Azure ML online endpointshttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-deploy-to-code?view=azureml-api-2
Set up GenAIOps pipelines with prompt flow and Azure DevOpshttps://learn.microsoft.com/en-us/azure/machine-learning/prompt-flow/how-to-end-to-end-azure-devops-with-prompt-flow?view=azureml-api-2

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Osmo Lerobot Trainingmicrosoft/physical-ai-toolchain122—~3.8kAutomated safety check: NotesMIT
Databricks Model Servingdatabricks/databricks-agent-skills3451 repos~3.3kAutomated safety check: PassCustom licence
Environment Deploymentmicrosoft/physical-ai-toolchain122—~5.8kAutomated safety check: PassMIT
Kouchou AI Developmentdigitaldemocracy2030/kouchou-ai171—~540Automated safety check: NotesAGPL-3.0

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    775 GitHub stars~608 tokensUpdated 2 days ago
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  • Azure Anomaly Detector

    MicrosoftDocs/Agent-Skills

    Official

    Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, limits & quotas, configuration, and deployment.

    775 GitHub stars~1.1k tokensUpdated 2 days ago
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Questions about Azure Machine Learning

What does Azure Machine Learning do?

Expert knowledge for Azure Machine Learning development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration…. Azure Machine Learning is an agent skill from MicrosoftDocs/Agent-Skills, published by the product's own GitHub organization. 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.

When should I use Azure Machine Learning?

Azure Machine Learning fits situations like: online/batch endpoints; vector stores/RAG; MLflow/ONNX deployments; other Azure Machine Learning related development tasks.

How do I install Azure Machine Learning in Claude Code?

Run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-machine-learning -a claude-code`. Or copy the skill folder (skills/azure-machine-learning in MicrosoftDocs/Agent-Skills) into .claude/skills/azure-machine-learning in your project. Claude Code loads it when a task matches its description.

How do I install Azure Machine Learning in Codex?

Run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-machine-learning -a codex`. Or copy the skill folder (skills/azure-machine-learning in MicrosoftDocs/Agent-Skills) into .agents/skills/azure-machine-learning in your project. Codex loads it when a task matches its description.

Can I use Azure Machine Learning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MicrosoftDocs/Agent-Skills --skill azure-machine-learning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-machine-learning, .gemini/skills/azure-machine-learning, .github/skills/azure-machine-learning and .opencode/skills/azure-machine-learning in your project.

What does Azure Machine Learning need to run?

SKILL.md names no scripts, command-line tools or credentials: Azure Machine Learning is instructions for the agent only. Compatibility (from SKILL.md): Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation..

Does Azure Machine Learning access the network?

SKILL.md names 2 domains. As links in the text: learn.microsoft.com and github.com. This is read from the text; nothing was executed.

Is Azure Machine Learning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Machine Learning use?

Azure Machine Learning is published under the CC-BY-4.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure Machine Learning use?

About 19k tokens (SKILL.md is roughly 75k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azure Machine Learning?

Skills that share tags, products or a category with Azure Machine Learning: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Osmo Lerobot Training (microsoft/physical-ai-toolchain, 122 stars), Databricks Model Serving (databricks/databricks-agent-skills, 345 stars) and Environment Deployment (microsoft/physical-ai-toolchain, 122 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Machine Learning?

MicrosoftDocs (a GitHub organization, an official publisher) maintains it in MicrosoftDocs/Agent-Skills, which has 775 GitHub stars. The repository holds 149 skills in this directory. The repository was last updated on October 5, 2026.

Source: MicrosoftDocs/Agent-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.