Merge pull request #204880 from atikmapari/Broken-link-larryfr

Broken link fixed

Author: PRMerger5

articles/machine-learning/how-to-use-mlflow-azure-databricks.md

@@ -84,7 +84,7 @@ with mlflow.start_run():
 If you prefer to manage your tracked experiments in a centralized location, you can set MLflow tracking  to **only** track in your Azure Machine Learning workspace. This configuration has the advantage of enabling easier path to deployment using Azure Machine Learning deployment options.
 
 > [!WARNING]
-> For [private link enabled Azure Machine Learning workspace](how-to-configure-private-link.md), you have to [deploy Azure Databricks in your own network (VNet injection)](/azure/databricks/administration-guide/cloud-configurations/azure/vnet-inject.md) to ensure proper connectivity.
+> For [private link enabled Azure Machine Learning workspace](how-to-configure-private-link.md), you have to [deploy Azure Databricks in your own network (VNet injection)](/azure/databricks/administration-guide/cloud-configurations/azure/vnet-inject) to ensure proper connectivity.
 
 You have to configure the MLflow tracking URI to point exclusively to Azure Machine Learning, as it is demonstrated in the following example: