Add a function parameter to MLClient.from_config() function calls in these files. . .

Author: fbsolo-ms1

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

@@ -7,24 +7,24 @@ ms.service: machine-learning
 ms.subservice: core
 ms.author: deeikele
 author: deeikele
-ms.reviewer: sgilley
-ms.date: 01/19/2024
+ms.reviewer: fsolomon
+ms.date: 02/06/2024
 ms.topic: how-to
-ms.custom: fasttrack-edit, sdkv2, devx-track-python
+ms.custom: fasttrack-edit, FY21Q4-aml-seo-hack, contperf-fy21q4, sdkv2, event-tier1-build-2022, ignite-2022, devx-track-python
 ---
 
 # Manage Azure Machine Learning workspaces in the portal or with the Python SDK (v2)
 
 [!INCLUDE [sdk v2](includes/machine-learning-sdk-v2.md)]
 
-In this article, you create, view, and delete [**Azure Machine Learning workspaces**](concept-workspace.md) for [Azure Machine Learning](overview-what-is-azure-machine-learning.md), using the [Azure portal](https://portal.azure.com) or the [SDK for Python](https://aka.ms/sdk-v2-install).  
+In this article, you create, view, and delete [**Azure Machine Learning workspaces**](concept-workspace.md) for [Azure Machine Learning](overview-what-is-azure-machine-learning.md), using the [Azure portal](https://portal.azure.com) or the [SDK for Python](https://aka.ms/sdk-v2-install).
 
 As your needs change or requirements for automation increase you can also manage workspaces [using the CLI](how-to-manage-workspace-cli.md), [Azure PowerShell](how-to-manage-workspace-powershell.md),  or [via the VS Code extension](how-to-setup-vs-code.md).
 
 ## Prerequisites
 
 * An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/) today.
-* If using the Python SDK: 
+* If using the Python SDK:
    1. [Install the SDK v2](https://aka.ms/sdk-v2-install).
    1. Install azure-identity: `pip install azure-identity`.  If in a notebook cell, use `%pip install azure-identity`.
    1. Provide your subscription details
@@ -84,7 +84,7 @@ If you have problems in accessing your subscription, see [Set up authentication
 
 # [Portal](#tab/azure-portal)
 
-1. Sign in to the [Azure portal](https://portal.azure.com/) by using the credentials for your Azure subscription. 
+1. Sign in to the [Azure portal](https://portal.azure.com/) by using the credentials for your Azure subscription.
 
 1. In the upper-left corner of Azure portal, select **+ Create a resource**.
 
@@ -131,25 +131,24 @@ If you have problems in accessing your subscription, see [Set up authentication
 > [!IMPORTANT]
 > For more information on using a private endpoint and virtual network with your workspace, see [Network isolation and privacy](how-to-network-security-overview.md).
 
-
 # [Python SDK](#tab/python)
 
 [!INCLUDE [sdk v2](includes/machine-learning-sdk-v2.md)]
 
 [!notebook-python[](~/azureml-examples-main/sdk/python/resources/workspace/workspace.ipynb?name=basic_private_link_workspace_name)]
- 
+
 This class requires an existing virtual network.
 
 # [Portal](#tab/azure-portal)
 
 1. The default network configuration is to use a **Public endpoint**, which is accessible on the public internet. To limit access to your workspace to an Azure Virtual Network you've created, under **Networking** you can instead select **Private with Internet Outbound** or **Private with Approved Outbound**.  Then scroll down to configure the settings.
 
-   :::image type="content" source="media/how-to-manage-workspace/select-private-endpoint.png" alt-text="Private endpoint selection":::    
+   :::image type="content" source="media/how-to-manage-workspace/select-private-endpoint.png" alt-text="Private endpoint selection":::
 
 1. Under **Workspace Inbound access** select **Add** to open the **Create private endpoint** form.
 1. On the **Create private endpoint** form, set the location, name, and virtual network to use. If you'd like to use the endpoint with a Private DNS Zone, select **Integrate with private DNS zone** and select the zone using the **Private DNS Zone** field. Select **OK** to create the endpoint.
 
-   :::image type="content" source="media/how-to-manage-workspace/create-private-endpoint.png" alt-text="Private endpoint creation":::    
+   :::image type="content" source="media/how-to-manage-workspace/create-private-endpoint.png" alt-text="Private endpoint creation":::
 
 1. If you selected **Private with Internet Outbound**, use the **Workspace Outbound access** section to configure the network and outbound rules.
 
@@ -163,8 +162,6 @@ This class requires an existing virtual network.
 
 By default, metadata for the workspace is stored in an Azure Cosmos DB instance that Microsoft maintains. This data is encrypted using Microsoft-managed keys.
 
-
-
 #### Use your own data encryption key
 
 You can provide your own key for data encryption. Doing so creates the Azure Cosmos DB instance that stores metadata in your Azure subscription. For more information, see [Customer-managed keys](concept-customer-managed-keys.md).
@@ -254,7 +251,7 @@ You can turn off all feedback opportunities for a workspace.  When off, users of
    1. Go to workspace resource in the Azure portal
    1. Open **Tags** from left navigation panel
    1. Add the key value pair "ADMIN_HIDE_SURVEY: TRUE"
-   1. Select **Apply**.  
+   1. Select **Apply**.
 
 :::image type="content" source="media/how-to-manage-workspace/tags.png" alt-text="Screenshot shows setting tags to prevent feedback in the workspace.":::
 
@@ -283,7 +280,7 @@ When running machine learning tasks using the SDK, you require a MLClient object
     from azure.ai.ml import MLClient
 
     # read the config from the current directory
-    ws_from_config = MLClient.from_config()
+    ws_from_config = MLClient.from_config(credential=DefaultAzureCredential())
     ```
 * **From parameters**: There's no need to have a config.json file available if you use this approach.
 
@@ -293,9 +290,7 @@ If you have problems in accessing your subscription, see [Set up authentication
 
 ## Find a workspace
 
-See a list of all the workspaces you can use.  
-You can also search for workspace inside studio.  See [Search for Azure Machine Learning assets (preview)](how-to-search-assets.md).
-
+See a list of all the workspaces you can use. You can also search for workspace inside studio. See [Search for Azure Machine Learning assets (preview)](how-to-search-assets.md).
 
 # [Python SDK](#tab/python)
 
@@ -308,27 +303,25 @@ To get details of a specific workspace:
 
 [!notebook-python[](~/azureml-examples-main/sdk/python/resources/workspace/workspace.ipynb?name=ws_location)]
 
-
 # [Portal](#tab/azure-portal)
 
 1. Sign in to the [Azure portal](https://portal.azure.com/).
 
-1. In the top search field, type **Machine Learning**.  
+1. In the top search field, type **Machine Learning**.
 
 1. Select **Machine Learning**.
 
    ![Search for Azure Machine Learning workspace](./media/how-to-manage-workspace/find-workspaces.png)
 
-1. Look through the list of workspaces found. You can filter based on subscription, resource groups, and locations.  
+1. Look through the list of workspaces found. You can filter based on subscription, resource groups, and locations.
 
 1. Select a workspace to display its properties.
 
 ---
 
-
 ## Delete a workspace
 
-When you no longer need a workspace, delete it.  
+When you no longer need a workspace, delete it.
 
 [!INCLUDE [machine-learning-delete-workspace](includes/machine-learning-delete-workspace.md)]
 
@@ -365,7 +358,7 @@ In the [Azure portal](https://portal.azure.com/), select **Delete**  at the top
   * Chrome (latest version)
   * Firefox (latest version)
 
-* **Azure portal**: 
+* **Azure portal**:
   * If you go directly to your workspace from a share link from the SDK or the Azure portal, you can't view the standard **Overview** page that has subscription information in the extension. In this scenario, you also can't switch to another workspace. To view another workspace, go directly to [Azure Machine Learning studio](https://ml.azure.com) and search for the workspace name.
   * All assets (Data, Experiments, Computes, and so on) are available only in [Azure Machine Learning studio](https://ml.azure.com). They're *not* available from the Azure portal.
   * Attempting to export a template for a workspace from the Azure portal may return an error similar to the following text: `Could not get resource of the type <type>. Resources of this type will not be exported.` As a workaround, use one of the templates provided at [https://github.com/Azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices](https://github.com/Azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices) as the basis for your template.
@@ -377,7 +370,6 @@ In the [Azure portal](https://portal.azure.com/), select **Delete**  at the top
 ### Resource provider errors
 
 [!INCLUDE [machine-learning-resource-provider](includes/machine-learning-resource-provider.md)]
- 
 
 ### Deleting the Azure Container Registry
 
@@ -397,6 +389,4 @@ To learn more about planning a workspace for your organization's requirements, s
 
 * If you need to move a workspace to another Azure subscription, see [How to move a workspace](how-to-move-workspace.md).
 
-
-
-For information on how to keep your Azure Machine Learning up to date with the latest security updates, see [Vulnerability management](concept-vulnerability-management.md).
+For information on how to keep your Azure Machine Learning up to date with the latest security updates, see [Vulnerability management](concept-vulnerability-management.md).

articles/machine-learning/how-to-read-write-data-v2.md

@@ -9,11 +9,13 @@ ms.topic: how-to
 ms.author: yogipandey
 author: ynpandey
 ms.reviewer: franksolomon
-ms.date: 06/20/2023
+ms.date: 02/06/2024
 ms.custom:
   - devplatv2
   - sdkv2
   - cliv2
+  - event-tier1-build-2022
+  - ignite-2022
   - build-2023
   - ignite-2023
 #Customer intent: As an experienced Python developer, I need to read my data, to make it available to a remote compute resource, to train my machine learning models.
@@ -23,7 +25,6 @@ ms.custom:
 
 [!INCLUDE [dev v2](includes/machine-learning-dev-v2.md)]
 
-
 In this article you learn:
 
 > [!div class="checklist"]
@@ -985,6 +986,8 @@ In the `Input` object, specify the `type` as `AssetTypes.MLTABLE` and `mode` as
 > [!NOTE]
 > To use [serverless compute](how-to-use-serverless-compute.md), delete `compute="cpu-cluster",` in this code.
 
+For more information about the MLClient object, MLClient object initialization options, and how to connect to a workspace, visit [Connect to a workspace](./how-to-manage-workspace.md#connect-to-a-workspace).
+
 ```python
 from azure.ai.ml import command
 from azure.ai.ml.entities import Data