fix blocking issues

Author: laurenhughes

.openpublishing.redirection.json

@@ -48591,6 +48591,11 @@
       "redirect_url": "/azure/virtual-machines/sizes-b-series-burstable",
       "redirect_document_id": false
     },
+    {
+      "source_path": "articles/virtual-machines/linux/b-series-burstable.md",
+      "redirect_url": "/azure/virtual-machines/sizes-b-series-burstable",
+      "redirect_document_id": false
+    },
     {
        "source_path": "articles/cognitive-services/Bing-News-Search/vs-bing-news-search-connected-service.md",
        "redirect_url": "/azure/cognitive-services/bing-news-search/search-the-web",

articles/batch/batch-pool-compute-intensive-sizes.md

@@ -99,7 +99,7 @@ To run CUDA applications on a pool of Windows NC nodes, you need to install NVDI
 
 1. Download a setup package for the GPU drivers on Windows Server 2016 from the [NVIDIA website](https://www.nvidia.com/Download/index.aspx) - for example, [version 411.82](https://us.download.nvidia.com/Windows/Quadro_Certified/411.82/411.82-tesla-desktop-winserver2016-international.exe). Save the file locally using a short name like *GPUDriverSetup.exe*.
 2. Create a zip file of the package.
-3. Upload the package to your Batch account. For steps, see the [application packages](batch-application-packages.md) guidance. Specify an application id such as *GPUDriver*, and a version such as *411.82*.
+3. Upload the package to your Batch account. For steps, see the [application packages](batch-application-packages.md) guidance. Specify an application ID such as *GPUDriver*, and a version such as *411.82*.
 1. Using the Batch APIs or Azure portal, create a pool in the virtual machine configuration with the desired number of nodes and scale. The following table shows sample settings to install the NVIDIA GPU drivers silently using a start task:
 
 | Setting | Value |

articles/iot-edge/tutorial-machine-learning-edge-02-prepare-environment.md

@@ -29,7 +29,7 @@ The development VM will be set up with:
 * [Docker Desktop for Windows](https://www.docker.com/products/docker-desktop)
 * [Git for Windows](https://gitforwindows.org/)
 * [Git Credential Manager for Windows](https://github.com/Microsoft/Git-Credential-Manager-for-Windows)
-* [.Net Core SDK](https://dotnet.microsoft.com/)
+* [.NET Core SDK](https://dotnet.microsoft.com/)
 * [Python 3](https://www.python.org/)
 * [Visual Studio Code](https://code.visualstudio.com/)
 * [Azure PowerShell](https://docs.microsoft.com/powershell/azure/overview?view=azps-1.1.0)
@@ -46,7 +46,7 @@ It takes about 30 minutes to create and configure the virtual machine.
 
 1. Clone or download the [Machine Learning and IoT Edge](https://github.com/Azure-Samples/IoTEdgeAndMlSample) sample repository to your local computer.
 
-1. Open Powershell as an administrator and navigate to the **\IoTEdgeAndMlSample\DevVM** directory located under the root directory where you downloaded the code. We will refer to the root directory for your source as `srcdir`.
+1. Open PowerShell as an administrator and navigate to the **\IoTEdgeAndMlSample\DevVM** directory located under the root directory where you downloaded the code. We will refer to the root directory for your source as `srcdir`.
 
     ```powershell
     cd c:\srcdir\IoTEdgeAndMlSample\DevVM