From ce635ce4fe35554b7079112871dd22289e330a47 Mon Sep 17 00:00:00 2001 From: Akshaya Annavajhala Date: Wed, 18 Sep 2019 13:25:41 -0400 Subject: [PATCH] add the word mlflow --- how-to-use-azureml/azure-databricks/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/how-to-use-azureml/azure-databricks/README.md b/how-to-use-azureml/azure-databricks/README.md index 813bfe5f..2983e43f 100644 --- a/how-to-use-azureml/azure-databricks/README.md +++ b/how-to-use-azureml/azure-databricks/README.md @@ -25,7 +25,7 @@ Learn more about [how to use Azure Databricks as a development environment](http You can use Azure Databricks as a compute target from [Azure Machine Learning Pipelines](https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-ml-pipelines). Take a look at this notebook for details: [aml-pipelines-use-databricks-as-compute-target.ipynb](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/azure-databricks/databricks-as-remote-compute-target/aml-pipelines-use-databricks-as-compute-target.ipynb). # Linked Azure Databricks and Azure ML Workspaces (Preview) -Customers can now link Azure Databricks and AzureML Workspaces to better enable MLOps scenarios by managing their tracking data in a single place - the Azure ML workspace. +Customers can now link Azure Databricks and AzureML Workspaces to better enable MLOps scenarios by [managing their tracking data in a single place when using the MLflow client](https://mlflow.org/docs/latest/tracking.html#mlflow-tracking) - the Azure ML workspace. ## Linking the Workspaces (Admin operation)