Merge pull request #800 from fbsolo-ms1/document-freshness-maintenance

Remove PII from the .PNG files . . .

Author: Stacyrch140

articles/machine-learning/data-science-virtual-machine/dsvm-ubuntu-intro.md

@@ -7,7 +7,7 @@ author: fbsolo-ms1
 ms.author: franksolomon 
 ms.topic: quickstart
 ms.reviewer: jeffshep
-ms.date: 04/23/2024
+ms.date: 10/14/2024
 ms.custom: mode-other, linux-related-content
 #Customer intent: As a data scientist, I want to learn how to provision the Linux DSVM so that I can move my existing workflow to the cloud.
 ---
@@ -26,23 +26,23 @@ Azure free accounts don't support GPU-enabled virtual machine (VM) SKUs.
 
 To create an instance of either the Ubuntu 20.04 DSVM or the Azure DSVM for PyTorch:
 
-1. Go to the [Azure portal](https://portal.azure.com). You might get a prompt to sign in to your Azure account if you haven't signed in yet.
+1. Go to the [Azure portal](https://portal.azure.com). You might get a prompt to sign in to your Azure account if you didn't yet sign in.
 1. Find the VM listing by entering **data science virtual machine**. Then select **Data Science Virtual Machine- Ubuntu 20.04** or **Azure DSVM for PyTorch**.
 
 1. Select **Create**.
 
 1. On the **Create a virtual machine** pane, fill in the **Basics** tab:
 
-      * **Subscription**: If you have more than one subscription, select the one on which the machine will be created and billed. You must have resource creation privileges for this subscription.
+      * **Subscription**: If you have more than one subscription, select the one on which the machine is created and billed. You must have resource creation privileges for this subscription.
       * **Resource group**: Create a new group or use an existing one.
       * **Virtual machine name**: Enter the name of the VM. This name is used in your Azure portal.
-      * **Region**: Select the datacenter that's most appropriate. For fastest network access, the datacenter that hosts most of your data or is located closest to your physical location is the best choice. For more information, refer to [Azure regions](https://azure.microsoft.com/global-infrastructure/regions/).
+      * **Region**: Select the datacenter that's most appropriate. For fastest network access, the datacenter that hosts most of your data or is located closest to your physical location is the best choice. For more information, visit [Azure regions](https://azure.microsoft.com/global-infrastructure/regions/).
       * **Image**: Don't change the default value.
-      * **Size**: This option should autopopulate with a size that's appropriate for general workloads. For more information, refer to [Linux VM sizes in Azure](/azure/virtual-machines/sizes).
+      * **Size**: This option should autopopulate with an appropriate size for general workloads. For more information, visit [Linux VM sizes in Azure](/azure/virtual-machines/sizes).
       * **Authentication type**: For quicker setup, select **Password**.
 
          > [!NOTE]
-         > If you plan to use JupyterHub, make sure to select **Password** because JupyterHub is *not* configured to use Secure Shell (SSH) Protocol public keys.
+         > If you plan to use JupyterHub, be sure to select **Password** because JupyterHub is *not* configured to use Secure Shell (SSH) Protocol public keys.
 
       * **Username**: Enter the administrator username. You use this username to sign in to your VM. It doesn't need to match your Azure username. Don't use capital letters.
 
@@ -69,7 +69,7 @@ You can access the Ubuntu DSVM in one of four ways:
 
 ### SSH
 
-If you configured your VM with SSH authentication, you can sign in with the account credentials that you created in the **Basics** section of step 4 for the text shell interface. For more information, refer to [Learn more about connecting to a Linux VM](/azure/virtual-machines/linux-vm-connect).
+If you configured your VM with SSH authentication, you can sign in with the account credentials that you created in the **Basics** section of step 4 for the text shell interface. For more information, visit [Learn more about connecting to a Linux VM](/azure/virtual-machines/linux-vm-connect).
 
 ### xrdp
 The standard tool for accessing Linux graphical sessions is xrdp. While the distribution doesn't include this tool by default, [these instructions](/azure/virtual-machines/linux/use-remote-desktop) explain how to install it.
@@ -78,14 +78,14 @@ The standard tool for accessing Linux graphical sessions is xrdp. While the dist
 > [!NOTE]
 > In testing, the X2Go client performed better than X11 forwarding. We recommend use of the X2Go client for a graphical desktop interface.
 
-The Linux VM is already provisioned with X2Go Server and is ready to accept client connections. To connect to the Linux VM graphical desktop, complete the following procedure on your client:
+The Linux VM is already provisioned with X2Go Server and is ready to accept client connections. To connect to the Linux VM graphical desktop, complete the following procedures on your client:
 
 1. Download and install the X2Go client for your client platform from [X2Go](https://wiki.x2go.org/doku.php/doc:installation:x2goclient).
 1. Note the public IP address of the VM. In the Azure portal, open the VM you created to find this information.
 
    :::image type="content" source="./media/dsvm-ubuntu-intro/ubuntu-ip-address.png" alt-text="Screenshot that shows the public IP address of the VM." lightbox= "./media/dsvm-ubuntu-intro/ubuntu-ip-address.png":::
 
-1. Run the X2Go client. If the **New Session** pane doesn't automatically pop up, select **Session** > **New Session**.
+1. Run the X2Go client. If the **New Session** pane doesn't automatically open, select **Session** > **New Session**.
 
 1. On the resulting configuration pane, enter these configuration parameters:
    * **Session**:
@@ -98,7 +98,7 @@ The Linux VM is already provisioned with X2Go Server and is ready to accept clie
 
    :::image type="content" source="./media/dsvm-ubuntu-intro/x2go-ubuntu.png" alt-text="Screenshot that shows preferences for a new X2Go session." lightbox= "./media/dsvm-ubuntu-intro/x2go-ubuntu.png":::
 1. Select **OK**.
-1. Select the box in the right pane of the X2Go pane to bring up the sign-in pane for your VM.
+1. To bring up the sign-in pane for your VM, select the box in the right pane of the X2Go pane.
 1. Enter the password for your VM.
 1. Select **OK**.
 1. You might need to give X2Go permission to bypass your firewall to finish the connection process.
@@ -115,16 +115,15 @@ The Ubuntu DSVM runs [JupyterHub](https://github.com/jupyterhub/jupyterhub), whi
    1. From your local machine, open a web browser and go to `https://your-vm-ip:8000`. Replace **your-vm-ip** with the IP address you noted earlier.
    1. Your browser will probably prevent you from opening the pane directly. It might tell you that there's a certificate error. The DSVM provides security with a self-signed certificate. Most browsers will allow you to select through after this warning. Many browsers will continue to provide some kind of visual warning about the certificate throughout your web session.
 
-      If you see the `ERR_EMPTY_RESPONSE` error message in your browser, make sure you access the machine by explicit use of the *HTTPS* protocol. *HTTP* or just the web address don't work for this step. If you enter the web address without `https://` in the address line, most browsers will default to `http` and the error will appear.
+      If you see the `ERR_EMPTY_RESPONSE` error message in your browser, be sure you access the machine by explicit use of the *HTTPS* protocol. *HTTP* or just the web address don't work for this step. If you enter the web address without `https://` in the address line, most browsers default to `http` and the error will appear.
 
    1. Enter the username and password that you used to create the VM and sign in, as shown in this screenshot.
 
       :::image type="content" source="./media/dsvm-ubuntu-intro/jupyter-login.png" alt-text="Screenshot that shows the JupyterHub sign-in pane." lightbox= "./media/dsvm-ubuntu-intro/jupyter-login.png":::
 
+      If you receive a **500** error at this stage, you probably used capital letters in your username. This issue is a known interaction between JupyterHub and the PAM authenticator it uses.
 
-      If you receive a 500 error at this stage, you probably used capital letters in your username. This issue is a known interaction between JupyterHub and the PAM authenticator it uses.
-   
-      If you receive a "Can't reach this page" error, it's likely that your network security group (NSG) permissions need adjustment. In the Azure portal, find the NSG resource within your resource group. To access JupyterHub from the public internet, you must have port 8000 open. (The image shows that this VM is configured for just-in-time access, which we highly recommend. For more information, refer to [Secure your management ports with just-in time access](/azure/security-center/security-center-just-in-time).)
+      If you receive a **Can't reach this page** error, it's likely that your network security group (NSG) permissions need adjustment. In the Azure portal, find the NSG resource within your resource group. To access JupyterHub from the public internet, you must have port 8000 open. (The image shows that this VM is configured for just-in-time access, which we highly recommend. For more information, visit [Secure your management ports with just-in time access](/azure/security-center/security-center-just-in-time).)
       >
       > :::image type="content" source="./media/dsvm-ubuntu-intro/nsg-permissions.png" alt-text="Screenshot that shows NSG configuration values." lightbox= "./media/dsvm-ubuntu-intro/nsg-permissions.png":::
 
@@ -140,8 +139,7 @@ c.Spawner.default_url = '/lab'
 
 ## Next steps
 
-* See the [Data science on the Data Science Virtual Machine for Linux](linux-dsvm-walkthrough.md) walkthrough to learn how to do several common data science tasks with the Linux DSVM provisioned here.
+* Visit the [Data science on the Data Science Virtual Machine for Linux](linux-dsvm-walkthrough.md) walkthrough to learn how to do several common data science tasks with the Linux DSVM provisioned here.
 * Try out the tools this article describes to explore the various data science tools on the DSVM. You can also run `dsvm-more-info` on the shell within the VM for a basic introduction and pointers to more information about the tools installed on the VM.
 * Learn how to systematically build analytical solutions with the [Team Data Science Process](/azure/architecture/data-science-process/overview).
-* See the [Azure AI Gallery](https://gallery.azure.ai/) for machine learning and data analytics samples that use the Azure AI services.
-* See the appropriate [reference documentation](./reference-ubuntu-vm.md) for this VM.
+* Visit the appropriate [reference documentation](./reference-ubuntu-vm.md) for this VM.