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Merge pull request #187550 from sdgilley/sdg-landing
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‎articles/machine-learning/index.yml

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### YamlMime:Hub
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### YamlMime:Landing
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title: Azure Machine Learning documentation
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summary: Learn how to train and deploy models and manage the ML lifecycle (MLOps) with Azure Machine Learning. Tutorials, code examples, API references, and more.
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services: machine-learning
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ms.service: machine-learning
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ms.subservice: core
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ms.topic: hub-page
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ms.topic: landing-page
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ms.collection: collection
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ms.author: sgilley
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author: sdgilley
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ms.date: 10/21/2021
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ms.date: 02/04/2022
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ms.custom: jordan-changes
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# highlightedContent section
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highlightedContent:
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# itemType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | sample | tutorial | video | whats-new
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items:
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# Card
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- title: What is Azure Machine Learning?
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itemType: overview
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url: overview-what-is-azure-machine-learning.md
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# Card
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- title: Set up resources
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itemType: get-started
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url: quickstart-create-resources.md
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# Card
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- title: 'Preview: Train models with v2 CLI'
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itemType: tutorial
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url: how-to-train-cli.md
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# Card
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- title: Architecture & terms
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itemType: overview
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url: concept-azure-machine-learning-architecture.md
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# Card
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- title: 'Day 1: Get started with Python'
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itemType: get-started
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url: tutorial-1st-experiment-hello-world.md
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# Card
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- title: "Migrate from ML Studio (classic)"
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itemType: how-to-guide
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url: migrate-overview.md
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# linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
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conceptualContent:
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# Supports up to 3 sections
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# itemType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | sample | tutorial | video | whats-new
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items:
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# Card
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- title: Train models
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landingContent:
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- title: 'Overview'
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linkLists:
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- linkListType: overview
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links:
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- text: "What is Azure Machine Learning?"
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url: overview-what-is-azure-machine-learning.md
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- text: "What is Azure Machine Learning studio?"
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url: overview-what-is-machine-learning-studio.md
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- text: Architecture & terms
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url: concept-azure-machine-learning-architecture.md
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# Card
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- title: Get Started
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linkLists:
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- linkListType: tutorial
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links:
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- text: Set up resources
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url: quickstart-create-resources.md
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- text: "Train with the v2 CLI (preview)"
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url: how-to-train-cli.md
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- text: "Day 1: Get started with Python"
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url: tutorial-1st-experiment-hello-world.md
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- text: "Migrate from ML Studio (classic)"
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url: migrate-overview.md
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# Card
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- title: Train models
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linkLists:
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- linkListType: how-to-guide
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links:
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- text: Run training code in the cloud (v2 CLI preview)
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url: how-to-train-cli.md
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- text: Train and deploy a model in Jupyter notebook
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url: tutorial-train-deploy-notebook.md
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- text: Tune hyperparameters for model training
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url: how-to-tune-hyperparameters.md
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- text: Build pipelines from reuseable components
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url: how-to-create-machine-learning-pipelines.md
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- text: "AutoML: Train a classification model"
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url: tutorial-first-experiment-automated-ml.md
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# Card
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- title: Deploy models
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linkLists:
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- linkListType: deploy
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links:
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- text: Streamline model deployment with endpoints (preview)
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url: concept-endpoints.md
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- text: Real-time scoring with a managed endpoint (preview)
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url: how-to-deploy-managed-online-endpoints.md
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- text: Batch scoring with managed endpoints (preview)
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url: how-to-use-batch-endpoint.md
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- text: Options for deploying models without using endpoints
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url: how-to-deploy-and-where.md
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# Card
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- title: "Manage the ML lifecycle (MLOps)"
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linkLists:
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- linkListType: how-to-guide
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links:
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- url: how-to-train-cli.md
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itemType: how-to-guide
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text: Run training code in the cloud (v2 CLI preview)
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- url: how-to-tune-hyperparameters.md
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itemType: how-to-guide
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text: Tune hyperparameters for model training
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- url: how-to-create-machine-learning-pipelines.md
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itemType: how-to-guide
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text: Build pipelines from reuseable components
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- url: tutorial-first-experiment-automated-ml.md
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itemType: tutorial
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text: 'AutoML: Train a classification model'
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# Card
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- title: Deploy models
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links:
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- url: concept-endpoints.md
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itemType: concept
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text: Streamline model deployment with endpoints (preview)
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- url: how-to-deploy-managed-online-endpoints.md
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itemType: how-to-guide
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text: Real-time scoring with a managed endpoint (preview)
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- url: how-to-use-batch-endpoint.md
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itemType: how-to-guide
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text: Batch scoring with managed endpoints (preview)
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- url: how-to-deploy-and-where.md
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itemType: how-to-guide
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text: Options for deploying models without using endpoints
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# Card
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- title: Manage the ML lifecycle (MLOps)
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links:
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- url: how-to-track-monitor-analyze-runs.md
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itemType: how-to-guide
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text: Track, monitor, analyze training runs
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- url: concept-model-management-and-deployment.md
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itemType: concept
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text: Model management, deployment, lineage & monitoring
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- url: how-to-cicd-data-ingestion.md
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itemType: how-to-guide
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text: DevOps for a data ingestion pipeline
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# Card
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- title: Security for ML projects
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links:
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- url: tutorial-create-secure-workspace.md
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itemType: tutorial
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text: Create a secure workspace
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- url: how-to-access-data.md
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itemType: how-to-guide
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text: Connect to data sources
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- url: concept-enterprise-security.md
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itemType: concept
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text: Enterprise security & governance
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# Card
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- title: Reference
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links:
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- url: /python/api/overview/azure/ml/
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itemType: reference
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text: Python SDK
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- url: /rest/api/azureml/
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itemType: reference
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text: REST API
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- url: /cli/azure/ml/
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itemType: reference
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text: V2 CLI (preview)
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- url: ./algorithm-module-reference/module-reference.md
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itemType: reference
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text: Algorithm & module reference
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# Card
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- title: Resources
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- text: Track, monitor, analyze training runs
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url: how-to-track-monitor-analyze-runs.md
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- text: Model management, deployment, lineage & monitoring
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url: concept-model-management-and-deployment.md
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- text: DevOps for a data ingestion pipeline
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url: how-to-cicd-data-ingestion.md
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# Card
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- title: "Security for ML projects"
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linkLists:
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- linkListType: how-to-guide
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links:
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- url: https://github.com/Azure/azureml-examples/blob/main/python-sdk/README.md
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itemType: sample
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text: Python SDK code examples
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- url: https://github.com/Azure/azureml-examples/blob/main/cli/README.md
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itemType: sample
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text: v2 CLI code examples (preview)
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- url: ./classic/index.yml
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itemType: overview
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text: ML Studio (classic) documentation
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- text: Create a secure workspace
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url: tutorial-create-secure-workspace.md
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- text: Connect to data sources
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url: how-to-access-data.md
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- text: Enterprise security & governance
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url: concept-enterprise-security.md
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# Card
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- title: Reference docs
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linkLists:
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- linkListType: reference
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links:
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- text: Python SDK
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url: /python/api/overview/azure/ml/
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- text: REST API
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url: /rest/api/azureml/
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- text: V2 CLI (preview)
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url: /cli/azure/ml/
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- text: Algorithm & component reference
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url: ./algorithm-module-reference/module-reference.md
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# Card
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- title: Resources
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linkLists:
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- linkListType: reference
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links:
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- text: Python SDK code examples
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url: https://github.com/Azure/azureml-examples/blob/main/python-sdk/README.md
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- text: v2 CLI code examples (preview)
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url: https://github.com/Azure/azureml-examples/blob/main/cli/README.md
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- text: ML Studio (classic) documentation
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url: ./classic/index.yml

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