index.yml

### YamlMime:Landing

title: Azure Machine Learning documentation
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. 

metadata:
  title: Azure Machine Learning documentation
  description: Learn how to train and deploy models and manage the ML lifecycle (MLOps) with Azure Machine Learning. Tutorials, code examples, API references, and more. 
 
  services: machine-learning
  ms.service: machine-learning
  ms.subservice: core
  ms.topic: landing-page
  ms.collection: collection
  ms.author: sgilley
  author: sdgilley
  ms.date: 02/04/2022
  ms.custom: jordan-changes, event-tier1-build-2022
# linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new

landingContent:
  - title: 'Overview'
    linkLists:
      - linkListType: overview
        links:  
          - text: "What is Azure Machine Learning?"       
            url: overview-what-is-azure-machine-learning.md
          - text: "What is Azure Machine Learning studio?"
            url:  overview-what-is-machine-learning-studio.md
          - text:  Key concepts (v2)
            url: concept-azure-machine-learning-v2.md 
          - text: What is CLI & SDK v2?
            url: concept-v2.md
  # Card
  - title: Get Started
    linkLists:
      - linkListType: tutorial
        links:   
        - text: Set up resources
          url: quickstart-create-resources.md
        - text: "Train with the v2 CLI"
          url: how-to-train-cli.md   
        - text: "Train with the v2 SDK (preview)"
          url: how-to-train-sdk.md   
        - text: "Day 1: Get started with Python"
          url: tutorial-1st-experiment-hello-world.md
        - text: "Migrate from ML Studio (classic)"
          url: migrate-overview.md
  # Card
  - title: Train models
    linkLists:
      - linkListType: how-to-guide
        links:            
          - text: Run training code in the cloud (v2 CLI)
            url: how-to-train-cli.md
          - text: Train and deploy a model in Jupyter notebook
            url:  tutorial-train-deploy-notebook.md
          - text: Tune hyperparameters for model training
            url: how-to-tune-hyperparameters.md
          - text: Build pipelines from reuseable components
            url: how-to-create-machine-learning-pipelines.md
          - text: "AutoML: Train a classification model"
            url: tutorial-first-experiment-automated-ml.md
  # Card
  - title: Deploy models
    linkLists:
      - linkListType: deploy
        links:
        - text: Streamline model deployment with endpoints (preview)
          url: concept-endpoints.md
        - text: Real-time scoring with a managed endpoint (preview)
          url: how-to-deploy-managed-online-endpoints.md
        - text: Batch scoring with managed endpoints (preview)
          url: how-to-use-batch-endpoint.md
        - text: Options for deploying models without using endpoints            
          url: how-to-deploy-and-where.md
  # Card
  - title: "Manage the ML lifecycle (MLOps)"
    linkLists:
    - linkListType: how-to-guide
      links:
      - text: Track, monitor, analyze training runs
        url: how-to-track-monitor-analyze-runs.md
      - text: Model management, deployment, lineage & monitoring
        url: concept-model-management-and-deployment.md
      - text: DevOps for a data ingestion pipeline
        url: how-to-cicd-data-ingestion.md
  # Card
  - title: "Security for ML projects"
    linkLists:
    - linkListType: how-to-guide
      links:
      - text: Create a secure workspace
        url: tutorial-create-secure-workspace.md
      - text: Connect to data sources 
        url: how-to-access-data.md
      - text: Enterprise security & governance
        url: concept-enterprise-security.md
  # Card
  - title: Reference docs     
    linkLists:
      - linkListType: reference
        links:
        - text: Python SDK
          url: /python/api/overview/azure/ml/
        - text: REST API 
          url: /rest/api/azureml/
        - text: V2 CLI (preview)
          url: /cli/azure/ml/
        - text: Algorithm & component reference 
          url: ./algorithm-module-reference/module-reference.md
  # Card
  - title: Resources
    linkLists:
      - linkListType: reference
        links:
        - text: Python SDK code examples
          url: https://github.com/Azure/azureml-examples/blob/main/python-sdk/README.md
        - text: v2 CLI code examples (preview)
          url: https://github.com/Azure/azureml-examples/blob/main/cli/README.md
        - text: ML Studio (classic) documentation
          url: ./classic/index.yml