Merge pull request #5018 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-ai-docs (branch main)

Author: Taojunshen

articles/ai-services/cognitive-services-data-loss-prevention.md

@@ -24,7 +24,7 @@ There are two parts to enable data loss prevention. First, the resource property
 >[!NOTE]
 >
 > * The `allowedFqdnList`  property value supports a maximum of 1000 URLs.
-> * The property supports both IP addresses (IPv4 only) and fully qualified domain names (i.e., `www.microsoft.com`) as values.
+> * The property supports fully qualified domain names (i.e., `www.microsoft.com`) as values.
 > * It can take up to 15 minutes for the updated list to take effect. 
 
 # [Azure CLI](#tab/azure-cli)

articles/ai-services/openai/use-your-data-quickstart.md

@@ -22,11 +22,7 @@ In this quickstart, you can use your own data with Azure OpenAI models. Using Az
 ## Prerequisites
 
 The following resources: 
-- [Azure OpenAI](https://portal.azure.com/#create/Microsoft.CognitiveServicesOpenAI)
-- [Azure Blob Storage](https://portal.azure.com/#create/Microsoft.StorageAccount-ARM)
-- [Azure AI Search](https://portal.azure.com/#create/Microsoft.Search)
-- An [Azure OpenAI resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesOpenAI) deployed in a [supported region and with a supported model](./concepts/use-your-data.md#regional-availability-and-model-support).
-    - Be sure that you're assigned at least the [Cognitive Services Contributor](./how-to/role-based-access-control.md#cognitive-services-contributor) role for the Azure OpenAI resource.
+- 
 - Download the example data from [GitHub](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/openai/contoso_benefits_document_example.pdf) if you don't have your own data.
 
 
@@ -41,11 +37,7 @@ The following resources:
 ## Prerequisites
 
 The following resources: 
-- [Azure OpenAI](https://portal.azure.com/#create/Microsoft.CognitiveServicesOpenAI)
-- [Azure Blob Storage](https://portal.azure.com/#create/Microsoft.StorageAccount-ARM)
-- [Azure AI Search](https://portal.azure.com/#create/Microsoft.Search)
-- An [Azure OpenAI resource](https://portal.azure.com/#create/Microsoft.CognitiveServicesOpenAI) deployed in a [supported region and with a supported model](./concepts/use-your-data.md#regional-availability-and-model-support).
-    - Be sure that you're assigned at least the [Cognitive Services Contributor](./how-to/role-based-access-control.md#cognitive-services-contributor) role for the Azure OpenAI resource.
+- An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
 - Download the example data from [GitHub](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/openai/contoso_benefits_document_example.pdf) if you don't have your own data.
 - The [.NET 8 SDK](https://dotnet.microsoft.com/download/dotnet/8.0)
 

articles/machine-learning/reference-managed-online-endpoints-vm-sku-list.md

@@ -104,7 +104,7 @@ The following table shows the virtual machine (VM) stock keeping units (SKUs) th
 |  standardNDv5H100Family  | STANDARD_ND96ISR_H100_v5 | Yes | NvidiaGpu | 8 | 96 | Yes |
 
 > [!CAUTION]
-> Small VM SKUs such as `Standard_DS1_v2` and `Standard_F2s_v2` may be too small for bigger models and may lead to container termination due to insufficient memory, not enough space on the disk, or probe failure as it takes too long to initiate the container. If you face [OutOfQuota errors](how-to-troubleshoot-online-endpoints.md?tabs=cli#error-outofquota) or [ReourceNotReady errors](how-to-troubleshoot-online-endpoints.md?tabs=cli#error-resourcenotready), try bigger VM SKUs. If you want to reduce the cost of deploying multiple models with managed online endpoint, see [Deployment for several local models](concept-online-deployment-model-specification.md#deployment-for-several-local-models).
+> Small VM SKUs such as `Standard_DS1_v2` and `Standard_F2s_v2` may be too small for bigger models and may lead to container termination due to insufficient memory, not enough space on the disk, or probe failure as it takes too long to initiate the container. If you face [OutOfQuota errors](how-to-troubleshoot-online-endpoints.md?tabs=cli#error-outofquota) or [ResourceNotReady errors](how-to-troubleshoot-online-endpoints.md?tabs=cli#error-resourcenotready), try bigger VM SKUs. If you want to reduce the cost of deploying multiple models with managed online endpoint, see [Deployment for several local models](concept-online-deployment-model-specification.md#deployment-for-several-local-models).
 
 > [!NOTE]
 > We recommend having more than 3 instances for deployments in production scenarios. In addition, Azure Machine Learning reserves 20% of your compute resources for performing upgrades on some VM SKUs as described in [Virtual machine quota allocation for deployment](how-to-manage-quotas.md#virtual-machine-quota-allocation-for-deployment). VM SKUs that are exempted from this extra quota reservation are specified in the "Skip 20% Reservation" column.

articles/machine-learning/reference-yaml-connection-python-feed.md

@@ -34,8 +34,8 @@ ms.reviewer: ambadal
 | `credentials` | object | Credential-based authentication to access the storage account. A [personal access token](https://docs.github.com/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens) or username and password can be used. Do not specify `credentials` when using a public Python feed. | | |
 | `credentials.type` | string | The type of authentication to use. | `pat`, `username_password` | |
 | `credentials.pat` | string | The personal access token to authenticate with. | | |
-| `credentials_username` | string | The username to authenticate with. | | |
-| `credentials_password` | string | The password to authenticate with. | | |
+| `credentials.username` | string | The username to authenticate with. | | |
+| `credentials.password` | string | The password to authenticate with. | | |
 
 ## Remarks
 

articles/search/search-security-rbac.md

@@ -531,7 +531,7 @@ These steps create a custom role that augments search query rights to include li
 
 ### [**Azure PowerShell**](#tab/custom-role-ps)
 
-The PowerShell example shows the JSON syntax for creating a custom role that's a clone of **Search Index Data Reader**, but withe ability to list all indexes by name.
+The PowerShell example shows the JSON syntax for creating a custom role that's a clone of **Search Index Data Reader**, but with ability to list all indexes by name.
 
 1. Review the [list of atomic permissions](/azure/role-based-access-control/resource-provider-operations#microsoftsearch) to determine which ones you need. For this example, you'll need the following: