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azure-ai-ml-pylisted

Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines. Triggers: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
aiskillstore/marketplace · ★ 329 · AI & Automation · score 82
Install: claude install-skill aiskillstore/marketplace
# Azure Machine Learning SDK v2 for Python Client library for managing Azure ML resources: workspaces, jobs, models, data, and compute. ## Installation ```bash pip install azure-ai-ml ``` ## Environment Variables ```bash AZURE_SUBSCRIPTION_ID=<your-subscription-id> AZURE_RESOURCE_GROUP=<your-resource-group> AZURE_ML_WORKSPACE_NAME=<your-workspace-name> ``` ## Authentication ```python from azure.ai.ml import MLClient from azure.identity import DefaultAzureCredential ml_client = MLClient( credential=DefaultAzureCredential(), subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"], resource_group_name=os.environ["AZURE_RESOURCE_GROUP"], workspace_name=os.environ["AZURE_ML_WORKSPACE_NAME"] ) ``` ### From Config File ```python from azure.ai.ml import MLClient from azure.identity import DefaultAzureCredential # Uses config.json in current directory or parent ml_client = MLClient.from_config( credential=DefaultAzureCredential() ) ``` ## Workspace Management ### Create Workspace ```python from azure.ai.ml.entities import Workspace ws = Workspace( name="my-workspace", location="eastus", display_name="My Workspace", description="ML workspace for experiments", tags={"purpose": "demo"} ) ml_client.workspaces.begin_create(ws).result() ``` ### List Workspaces ```python for ws in ml_client.workspaces.list(): print(f"{ws.name}: {ws.location}") ``` ## Data Assets ### Register Data ```python from azure.ai.ml.entities import Data from