standardize tab names

Author: sdgilley

articles/machine-learning/data-science-virtual-machine/dsvm-tutorial-bicep.md

@@ -41,7 +41,7 @@ The following resources are defined in the Bicep file:
 1. Save the Bicep file as **main.bicep** to your local computer.
 1. Deploy the Bicep file using either Azure CLI or Azure PowerShell.
 
-    # [CLI](#tab/CLI)
+    # [Azure CLI](#tab/CLI)
 
     ```azurecli
     az group create --name exampleRG --location eastus
@@ -66,7 +66,7 @@ The following resources are defined in the Bicep file:
 
 Use the Azure portal, Azure CLI, or Azure PowerShell to list the deployed resources in the resource group.
 
-# [CLI](#tab/CLI)
+# [Azure CLI](#tab/CLI)
 
 ```azurecli-interactive
 az resource list --resource-group exampleRG
@@ -84,7 +84,7 @@ Get-AzResource -ResourceGroupName exampleRG
 
 When no longer needed, use the Azure portal, Azure CLI, or Azure PowerShell to delete the resource group and its resources.
 
-# [CLI](#tab/CLI)
+# [Azure CLI](#tab/CLI)
 
 ```azurecli-interactive
 az group delete --name exampleRG

articles/machine-learning/how-to-deploy-kubernetes-extension.md

@@ -86,7 +86,7 @@ If you plan to deploy AzureML extension for real-time inference workload and wan
 
 ## AzureML extension deployment - CLI examples and Azure portal
 
-### [CLI](#tab/deploy-extension-with-cli)
+### [Azure CLI](#tab/deploy-extension-with-cli)
 To deploy AzureML extension with CLI, use `az k8s-extension create` command passing in values for the mandatory parameters.
 
 We list four typical extension deployment scenarios for reference. To deploy extension for your production usage, carefully read the complete list of [configuration settings](#review-azureml-extension-configuration-settings).