Merge pull request #235134 from MicrosoftDocs/release-azrueml-tutorials

Release azrueml tutorials--scheduled release at 10 am of 4/20

Author: huypub

articles/machine-learning/.openpublishing.redirection.machine-learning.json

@@ -40,6 +40,11 @@
         "redirect_url": "/azure/machine-learning/v1/how-to-configure-databricks-automl-environment",
         "redirect_document_id": true
     },
+    {
+        "source_path_from_root": "/articles/machine-learning/quickstart-run-notebooks.md",
+        "redirect_url": "/azure/machine-learning/tutorial-cloud-workstation",
+        "redirect_document_id": true
+    },
     {
         "source_path_from_root": "/articles/machine-learning/reference-checkpoint-performance-with-Nebula.md",
         "redirect_url": "/azure/machine-learning/reference-checkpoint-performance-for-large-models",

articles/machine-learning/concept-compute-instance.md

@@ -108,7 +108,7 @@ You can also mount [datastores and datasets](v1/concept-azure-machine-learning-a
 :::moniker-end
 ## Create
 
-Follow the steps in the [Quickstart: Create workspace resources you need to get started with Azure Machine Learning](quickstart-create-resources.md) to create a basic compute instance.  
+Follow the steps in [Create resources you need to get started](quickstart-create-resources.md) to create a basic compute instance.  
 
 For more options, see [create a new compute instance](how-to-create-manage-compute-instance.md?tabs=azure-studio#create).
 
@@ -145,5 +145,5 @@ You can use compute instance as a local inferencing deployment target for test/d
 
 ## Next steps
 
-* [Quickstart: Create workspace resources you need to get started with Azure Machine Learning](quickstart-create-resources.md).
+* [Create resources you need to get started](quickstart-create-resources.md).
 * [Tutorial: Train your first ML model](tutorial-1st-experiment-sdk-train.md) shows how to use a compute instance with an integrated notebook.

articles/machine-learning/concept-workspace.md

@@ -151,6 +151,6 @@ To get started with Azure Machine Learning, see:
 + [What is Azure Machine Learning?](overview-what-is-azure-machine-learning.md)
 + [Create and manage a workspace](how-to-manage-workspace.md)
 + [Recover a workspace after deletion (soft-delete)](concept-soft-delete.md)
-+ [Tutorial: Get started with Azure Machine Learning](quickstart-create-resources.md)
++ [Get started with Azure Machine Learning](quickstart-create-resources.md)
 + [Tutorial: Create your first classification model with automated machine learning](tutorial-first-experiment-automated-ml.md) 
 + [Tutorial: Predict automobile price with the designer](tutorial-designer-automobile-price-train-score.md)

articles/machine-learning/how-to-configure-environment.md

@@ -143,7 +143,7 @@ The Azure Machine Learning [compute instance](concept-compute-instance.md) is a
 
 There's nothing to install or configure for a compute instance.  
 
-Create one anytime from within your Azure Machine Learning workspace. Provide just a name and specify an Azure VM type. Try it now with this [Tutorial: Setup environment and workspace](quickstart-create-resources.md).
+Create one anytime from within your Azure Machine Learning workspace. Provide just a name and specify an Azure VM type. Try it now with [Create resources to get started](quickstart-create-resources.md).
 
 To learn more about compute instances, including how to install packages, see [Create and manage an Azure Machine Learning compute instance](how-to-create-manage-compute-instance.md).
 

articles/machine-learning/how-to-create-attach-compute-cluster.md

@@ -75,9 +75,8 @@ The dedicated cores per region per VM family quota and total regional quota, whi
 
 The compute autoscales down to zero nodes when it isn't used.   Dedicated VMs are created to run your jobs as needed.
 
-The fastest way to create a compute cluster is to follow the [Quickstart: Create workspace resources you need to get started with Azure Machine Learning](quickstart-create-resources.md). 
 
-Or use the following examples to create a compute cluster with more options:
+Use the following examples to create a compute cluster:
 
 # [Python SDK](#tab/python)
 

articles/machine-learning/how-to-create-component-pipeline-python.md

@@ -39,7 +39,7 @@ If you don't have an Azure subscription, create a free account before you begin.
 
 ## Prerequisites
 
-* Complete the [Quickstart: Get started with Azure Machine Learning](quickstart-create-resources.md) if you don't already have an Azure Machine Learning workspace.
+* Complete the [Create resources to get started](quickstart-create-resources.md) if you don't already have an Azure Machine Learning workspace.
 * A Python environment in which you've installed Azure Machine Learning Python SDK v2 - [install instructions](https://github.com/Azure/azureml-examples/tree/sdk-preview/sdk#getting-started) - check the getting started section. This environment is for defining and controlling your Azure Machine Learning resources and is separate from the environment used at runtime for training.
 * Clone examples repository
 

articles/machine-learning/how-to-create-manage-compute-instance.md

@@ -58,7 +58,7 @@ Creating a compute instance is a one time process for your workspace. You can re
 
 The dedicated cores per region per VM family quota and total regional quota, which applies to compute instance creation, is unified and shared with Azure Machine Learning training compute cluster quota. Stopping the compute instance doesn't release quota to ensure you'll be able to restart the compute instance. It isn't possible to change the virtual machine size of compute instance once it's created.
 
-The fastest way to create a compute instance is to follow the [Quickstart: Create workspace resources you need to get started with Azure Machine Learning](quickstart-create-resources.md). 
+The fastest way to create a compute instance is to follow the [Create resources you need to get started](quickstart-create-resources.md). 
 
 Or use the following examples to create a compute instance with more options:
 

articles/machine-learning/how-to-devops-machine-learning.md

@@ -30,10 +30,11 @@ This tutorial uses [Azure Machine Learning Python SDK v2](/python/api/overview/a
 
 ## Prerequisites
 
-Complete the [Quickstart: Get started with Azure Machine Learning](quickstart-create-resources.md) to:
-* Create a workspace
-* Create a cloud-based compute instance to use for your development environment
-* Create a cloud-based compute cluster to use for training your model
+* Complete the [Create resources to get started](quickstart-create-resources.md) to:
+    * Create a workspace
+    * Create a cloud-based compute instance to use for your development environment
+
+* [Create a cloud-based compute cluster](how-to-create-attach-compute-cluster.md#create) to use for training your model
 
 ## Step 1: Get the code
 

articles/machine-learning/how-to-enable-preview-features.md

@@ -30,7 +30,7 @@ Some preview features provide access to entire new functionality while others ma
 
 ## Prerequisites
 
-* An Azure Machine Learning workspace. For more information, see [Quickstart: Create workspace resources](quickstart-create-resources.md).
+* An Azure Machine Learning workspace. For more information, see [Create resources to get started](quickstart-create-resources.md).
 
 ## How do I enable preview features?
 

articles/machine-learning/how-to-manage-files.md

@@ -69,8 +69,6 @@ For example, choose "Indent using spaces" if you want your editor to auto-indent
 
 Your workspace contains a **Samples** folder with notebooks designed to help you explore the SDK and serve as examples for your own machine learning projects.   Clone these notebooks into your own folder to run and edit them.  
 
-For an example, see [Quickstart: Run Jupyter notebooks in studio](quickstart-run-notebooks.md#clone-tutorials-folder).
-
 ## Share files
 
 Copy and paste the URL to share a file.  Only other users of the workspace can access this URL.  Learn more about [granting access to your workspace](how-to-assign-roles.md).