Merge pull request #105491 from lvovanms/patch-2

Fixed broken link to "How to customize compute instance"

Author: Court72

includes/machine-learning-public-internet-access.md

@@ -63,7 +63,7 @@ You may also need to allow __outbound__ traffic to Visual Studio Code and non-Mi
 | **raw.githubusercontent.com/microsoft/vscode-tools-for-ai/master/azureml_remote_websocket_server/\*** | Used to retrieve websocket server bits, which are installed on the compute instance. The websocket server is used to transmit requests from Visual Studio Code client (desktop application) to Visual Studio Code server running on the compute instance.|
 
 > [!NOTE]
-> When using the [Azure Machine Learning VS Code extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-ai) the remote compute instance will require an access to public repositories to install the packages required by the extension. If the compute instance requires a proxy to access these public repositories or the Internet, you will need to set and export the `HTTP_PROXY` and `HTTPS_PROXY` environment variables in the `~/.bashrc` file of the compute instance. This process can be automated at provisioning time by using a [custom script](/machine-learning/how-to-customize-compute-instance).
+> When using the [Azure Machine Learning VS Code extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-ai) the remote compute instance will require an access to public repositories to install the packages required by the extension. If the compute instance requires a proxy to access these public repositories or the Internet, you will need to set and export the `HTTP_PROXY` and `HTTPS_PROXY` environment variables in the `~/.bashrc` file of the compute instance. This process can be automated at provisioning time by using a [custom script](../articles/machine-learning/how-to-customize-compute-instance.md).
 
 When using Azure Kubernetes Service (AKS) with Azure Machine Learning, allow the following traffic to the AKS VNet: