Sweep of my articles for 'studio' -> AML

Author: lobrien

articles/machine-learning/service/how-to-create-labeling-projects.md

@@ -14,7 +14,7 @@ ms.date: 11/04/2019
 
 Labeling large amounts of data has often been a headache in machine learning projects. ML projects with a computer vision component, such as image classification or object detection, generally require thousands of images and corresponding labels. 
 
-Azure Machine Learning studio gives you a central location to create, manage, and monitor labeling projects. Labeling projects help coordinate the data, labels, and team members, allowing you to more efficiently manage the labeling tasks. Currently supported tasks are image classification, either multi-label or multi-class, and object identification using bounded boxes.
+Azure Machine Learning gives you a central location to create, manage, and monitor labeling projects. Labeling projects help coordinate the data, labels, and team members, allowing you to more efficiently manage the labeling tasks. Currently supported tasks are image classification, either multi-label or multi-class, and object identification using bounded boxes.
 
 Azure tracks progress and maintains the queue of incomplete labeling tasks. Labelers don't require an Azure account to participate. Once authenticated with their Microsoft Account (MSA) or [Azure Active Directory](https://docs.microsoft.com/azure/active-directory/active-directory-whatis), they can do as much or as little labeling as their time allows. They can assign and change labels using keyboard shortcuts. 
 
@@ -39,7 +39,7 @@ In this article, you'll learn how to:
 
 ## Create a labeling project
 
-Labeling projects are administered from [Azure Machine Learning studio](https://ml.azure.com/). The **Labeling projects** page allows you to manage your projects, teams, and people. A project has one or more teams assigned to it, and a team has one or more people assigned to it. 
+Labeling projects are administered from [Azure Machine Learning](https://ml.azure.com/). The **Labeling projects** page allows you to manage your projects, teams, and people. A project has one or more teams assigned to it, and a team has one or more people assigned to it. 
 
 If your data are already stored in Azure blob storage, you should make them available as a datastore before creating your labeling project. For information, see [Create and register datastores](https://docs.microsoft.com/azure/machine-learning/service/how-to-access-data#create-and-register-datastores). 
 
@@ -145,7 +145,7 @@ You can label data directly from the **Project details** page by selecting **Lab
 
 At any time, you may export the label data for machine learning experimentation. Image labels can be exported in [COCO format](http://cocodataset.org/#format-data) or as an Azure ML dataset. You will find the **Export** button on the **Project details** page of your labeling project.
 
-The COCO file is created in the default blob store of the Azure ML workspace in a folder within **export/coco**. You can access the exported Azure ML dataset under the **Datasets** section of studio. Dataset details page also provides sample code to access your labels from Python.
+The COCO file is created in the default blob store of the Azure ML workspace in a folder within **export/coco**. You can access the exported Azure ML dataset under the **Datasets** section of Azure Machine Learning. Dataset details page also provides sample code to access your labels from Python.
 
 ![Exported dataset](media/how-to-create-labeling-projects/exported-dataset.png)
 

articles/machine-learning/service/how-to-create-your-first-pipeline.md

@@ -407,14 +407,14 @@ response = requests.post(published_pipeline1.endpoint,
 ### View results of a published pipeline
 
 See the list of all your published pipelines and their run details:
-1. Sign in to [Azure Machine Learning studio](https://ml.azure.com).
+1. Sign in to [Azure Machine Learning](https://ml.azure.com).
 
 1. [View your workspace](how-to-manage-workspace.md#view) to find the list of pipelines.
  ![list of machine learning pipelines](./media/how-to-create-your-first-pipeline/list_of_pipelines.png)
 
 1. Select a specific pipeline to see the run results.
 
-These results are also available in your workspace in [Azure Machine Learning studio]](https://ml.azure.com).
+These results are also available in your workspace in [Azure Machine Learning](https://ml.azure.com).
 
 ### Disable a published pipeline
 

articles/machine-learning/service/how-to-label-images.md

@@ -12,7 +12,7 @@ ms.date: 11/04/2019
 
 # How to tag images in a labeling project
 
-Once your project administrator has created a labeling project in Azure Machine Learning studio, you can use the labeling tool to rapidly prepare data for a machine learning project. 
+Once your project administrator has created a labeling project in Azure Machine Learning, you can use the labeling tool to rapidly prepare data for a machine learning project. 
 
 > [!div class="checklist"]
 > * How to access your labeling projects

articles/machine-learning/service/how-to-schedule-pipelines.md

@@ -91,9 +91,9 @@ In addition to the arguments discussed previously, you may set the `status` argu
 
 ## View your scheduled pipelines
 
-In your Web browser, navigate to the studio. From the **Endpoints** section of the navigation panel, choose **Pipeline endpoints**. This takes you to a list of the pipelines published in the Workspace.
+In your Web browser, navigate to Azure Machine Learning. From the **Endpoints** section of the navigation panel, choose **Pipeline endpoints**. This takes you to a list of the pipelines published in the Workspace.
 
-![Pipelines page of studio](media/how-to-schedule-pipelines/scheduled-pipelines.png)
+![Pipelines page of AML](media/how-to-schedule-pipelines/scheduled-pipelines.png)
 
 In this page you can see summary information about all the pipelines in the Workspace: names, descriptions, status, and so forth. Drill in by clicking in your pipeline. On the resulting page, there are more details about your pipeline and you may drill down into individual runs.