Merge pull request #212064 from sdgilley/sdg-v2-workspace

Workspace update to v2

Author: tamarakhader

articles/machine-learning/how-to-manage-workspace-cli.md

@@ -15,7 +15,6 @@ ms.custom: devx-track-azurecli, cliv2, event-tier1-build-2022
 
 # Manage Azure Machine Learning workspaces using Azure CLI
 
-[!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 [!INCLUDE [cli v2](../../includes/machine-learning-cli-v2.md)]
 
 > [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK or CLI extension you are using:"]

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

@@ -111,7 +111,7 @@ For examples of creating the workspace with a customer-managed key, see the foll
 | Creation method | Article |
 | ----- | ----- |
 | CLI | [Create a workspace with Azure CLI](how-to-manage-workspace-cli.md#customer-managed-key-and-high-business-impact-workspace) |
-| Azure portal/</br>Python SDK | [Create and manage a workspace](how-to-manage-workspace.md#use-your-own-key) |
+| Azure portal/</br>Python SDK | [Create and manage a workspace](how-to-manage-workspace.md#use-your-own-data-encryption-key) |
 | Azure Resource Manager</br>template | [Create a workspace with a template](how-to-create-workspace-template.md#deploy-an-encrypted-workspace) |
 | REST API | [Create, run, and delete Azure ML resources with REST](how-to-manage-rest.md#create-a-workspace-using-customer-managed-encryption-keys) |
 
@@ -160,6 +160,6 @@ This process allows you to encrypt both the Data and the OS Disk of the deployed
 
 * [Customer-managed keys with Azure Machine Learning](concept-customer-managed-keys.md)
 * [Create a workspace with Azure CLI](how-to-manage-workspace-cli.md#customer-managed-key-and-high-business-impact-workspace) |
-* [Create and manage a workspace](how-to-manage-workspace.md#use-your-own-key) |
+* [Create and manage a workspace](how-to-manage-workspace.md#use-your-own-data-encryption-key) |
 * [Create a workspace with a template](how-to-create-workspace-template.md#deploy-an-encrypted-workspace) |
 * [Create, run, and delete Azure ML resources with REST](how-to-manage-rest.md#create-a-workspace-using-customer-managed-encryption-keys) |

articles/machine-learning/how-to-setup-customer-managed-keys.md

@@ -365,7 +365,7 @@ See the list of all your pipelines and their run details in the studio:
 
 1. Sign in to [Azure Machine Learning studio](https://ml.azure.com).
 
-1. [View your workspace](../how-to-manage-workspace.md#view).
+1. [View your workspace](../how-to-manage-workspace.md#find-a-workspace).
 
 1. On the left, select **Pipelines** to see all your pipeline runs.
  ![list of machine learning pipelines](../media/how-to-create-your-first-pipeline/pipelines.png)

articles/machine-learning/media/how-to-manage-workspace/configure.png

@@ -339,7 +339,7 @@ You can also run a published pipeline from the studio:
 
 1. Sign in to [Azure Machine Learning studio](https://ml.azure.com).
 
-1. [View your workspace](../how-to-manage-workspace.md#view).
+1. [View your workspace](../how-to-manage-workspace.md#find-a-workspace).
 
 1. On the left, select **Endpoints**.
 

articles/machine-learning/v1/how-to-create-machine-learning-pipelines.md

@@ -15,10 +15,9 @@ ms.custom: devx-track-azurecli, cliv1, event-tier1-build-2022
 
 # Manage Azure Machine Learning workspaces using Azure CLI extension v1
 
-[!INCLUDE [sdk v1](../../../includes/machine-learning-sdk-v1.md)]
 [!INCLUDE [cli v1](../../../includes/machine-learning-cli-v1.md)]
 
-> [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK or CLI extension you are using:"]
+> [!div class="op_single_selector" title1="Select the version of Azure Machine Learning CLI extension you are using:"]
 > * [v1](how-to-manage-workspace-cli.md)
 > * [v2 (current version)](../how-to-manage-workspace-cli.md)