rebranding

articles/data-factory/compute-linked-services.md

@@ -386,11 +386,11 @@ You create an Azure Machine Learning Studio linked service to register a Machine
 | tenant                 | Specify the tenant information (domain name or tenant ID) under which your application resides. You can retrieve it by hovering the mouse in the upper-right corner of the Azure portal. | Required if updateResourceEndpoint is specified |
 | connectVia             | The Integration Runtime to be used to dispatch the activities to this linked service. You can use Azure Integration Runtime or Self-hosted Integration Runtime. If not specified, it uses the default Azure Integration Runtime. | No                                       |
 
-## Azure Machine Learning Service linked service
-You create an Azure Machine Learning Service linked service to connect an Azure Machine Learning service workspace to a data factory.
+## Azure Machine Learning linked service
+You create an Azure Machine Learning linked service to connect an Azure Machine Learning workspace to a data factory.
 
 > [!NOTE]
-> Currently only service principal authentication is supported for the Azure Machine Learning Service linked service.
+> Currently only service principal authentication is supported for the Azure Machine Learning linked service.
 
 ### Example
 
@@ -424,7 +424,7 @@ You create an Azure Machine Learning Service linked service to connect an Azure
 | Type                   | The type property should be set to: **AzureMLService**. | Yes                                      |
 | subscriptionId         | Azure subscription ID              | Yes                                      |
 | resourceGroupName      | name | Yes                                      |
-| mlWorkspaceName        | Azure Machine Learning Service workspace name | Yes  |
+| mlWorkspaceName        | Azure Machine Learning workspace name | Yes  |
 | servicePrincipalId     | Specify the application's client ID.     | No |
 | servicePrincipalKey    | Specify the application's key.           | No |
 | tenant                 | Specify the tenant information (domain name or tenant ID) under which your application resides. You can retrieve it by hovering the mouse in the upper-right corner of the Azure portal. | Required if updateResourceEndpoint is specified | No |

articles/iot-edge/TOC.yml

@@ -45,7 +45,7 @@
       href: tutorial-deploy-function.md
     - name: Find averages with Azure Stream Analytics
       href: tutorial-deploy-stream-analytics.md
-    - name: Score data with Azure Machine Learning service
+    - name: Score data with Azure Machine Learning
       href: tutorial-deploy-machine-learning.md
     - name: Classify images with Custom Vision
       href: tutorial-deploy-custom-vision.md

articles/iot-edge/tutorial-deploy-machine-learning.md

@@ -53,7 +53,7 @@ Cloud resources:
 In this section, you convert trained machine learning model files and into an Azure Machine Learning service container. All the components required for the Docker image are in the [AI Toolkit for Azure IoT Edge Git repo](https://github.com/Azure/ai-toolkit-iot-edge/tree/master/IoT%20Edge%20anomaly%20detection%20tutorial). Follow these steps to upload that repository into Microsoft Azure Notebooks to create the container and push it to Azure Container Registry.
 
 
-1. Navigate to your Azure Notebooks projects. You can get there from your Azure Machine Learning service workspace in the [Azure portal](https://portal.azure.com) or by signing in to [Microsoft Azure Notebooks](https://notebooks.azure.com/home/projects) with your Azure account.
+1. Navigate to your Azure Notebooks projects. You can get there from your Azure Machine Learning workspace in the [Azure portal](https://portal.azure.com) or by signing in to [Microsoft Azure Notebooks](https://notebooks.azure.com/home/projects) with your Azure account.
 
 2. Select **Upload GitHub Repo**.
 
@@ -67,7 +67,7 @@ In this section, you convert trained machine learning model files and into an Az
 
 6. Open the **aml_config/config.json** file.
 
-7. Edit the config file to include the values for your Azure subscription ID, a resource group in your subscription, and your Azure Machine Learning service workspace name. You can get all these values from the **Overview** section of your workspace in Azure. 
+7. Edit the config file to include the values for your Azure subscription ID, a resource group in your subscription, and your Azure Machine Learning workspace name. You can get all these values from the **Overview** section of your workspace in Azure. 
 
 8. Save the config file.
 

articles/iot-edge/tutorial-machine-learning-edge-04-train-model.md

@@ -15,7 +15,7 @@ services: iot-edge
 > [!NOTE]
 > This article is part of a series for a tutorial about using Azure Machine Learning on IoT Edge. If you have arrived at this article directly, we encourage you to begin with the [first article](tutorial-machine-learning-edge-01-intro.md) in the series for the best results.
 
-In this article, we use Azure Notebooks first to train a machine learning model using Azure Machine Learning and then package that model as a container image that can be deployed as an Azure IoT Edge Module. The Azure Notebooks take advantage of an Azure Machine Learning service workspace, which is a foundational block used to experiment, train, and deploy machine learning models.
+In this article, we use Azure Notebooks first to train a machine learning model using Azure Machine Learning and then package that model as a container image that can be deployed as an Azure IoT Edge Module. The Azure Notebooks take advantage of an Azure Machine Learning workspace, which is a foundational block used to experiment, train, and deploy machine learning models.
 
 The activities in this portion of the tutorial are broken up across two notebooks.
 

articles/notebooks/use-machine-learning-services-jupyter-notebooks.md

@@ -1,6 +1,6 @@
 ---
 title: Use Azure Machine Learning Services in Azure Notebooks
-description: An overview of the sample notebooks for Azure Machine Learning Services that you can use with Azure Notebooks.
+description: An overview of the sample notebooks for Azure Machine Learnings that you can use with Azure Notebooks.
 services: app-service
 documentationcenter: ''
 author: kraigb
@@ -42,7 +42,7 @@ Azure Notebooks comes pre-configured with the necessary environment to work with
 The Azure Machine Learning documentation contains a variety of other resources that guide you through working with Machine Learning within notebooks:
 
 - [Quickstart: Use Python to get started with Azure Machine Learning](https://docs.microsoft.com/azure/machine-learning/service/quickstart-create-workspace-with-python)
-- [Tutorial #1: Train an image classification model with Azure Machine Learning service](https://docs.microsoft.com/azure/machine-learning/service/tutorial-train-models-with-aml)
+- [Tutorial #1: Train an image classification model with Azure Machine Learning](https://docs.microsoft.com/azure/machine-learning/service/tutorial-train-models-with-aml)
 - [Tutorial #2: Deploy an image classification model in Azure Container Instance (ACI)](https://docs.microsoft.com/azure/machine-learning/service/tutorial-deploy-models-with-aml)
 - [Tutorial: Train a classification model with automated machine learning in Azure Machine Learning service](https://docs.microsoft.com/azure/machine-learning/service/tutorial-auto-train-models)
 

articles/open-datasets/overview-what-are-open-datasets.md

@@ -42,7 +42,7 @@ Following are examples of datasets available.
 ## Access to datasets  
 With an Azure account, you can access open datasets using code or through the Azure service interface. The data is colocated with Azure cloud compute resources for use in your machine learning solution.  
 
-Open Datasets provides Azure Notebooks and Azure Databricks notebooks you can use to connect data to Azure Machine Learning service and Azure Databricks. Datasets can also be accessed through a Python SDK. 
+Open Datasets provides Azure Notebooks and Azure Databricks notebooks you can use to connect data to Azure Machine Learning and Azure Databricks. Datasets can also be accessed through a Python SDK. 
 
 However, you don't need an Azure account to access Open Datasets; you can access them from any Python environment with or without Spark.
 

markdown templates/aml-templates/template-howto.md

@@ -1,5 +1,5 @@
 ---
-title: Verb action for Azure Machine Learning service in 59 chars or less. Include the name Azure Machine Learning. Test title here https://moz.com/learn/seo/title-tag  (EXAMPLE - Deploying web services in Python with Azure Machine Learning service)
+title: Verb action for Azure Machine Learning in 59 chars or less. Include the name Azure Machine Learning. Test title here https://moz.com/learn/seo/title-tag  (EXAMPLE - Deploying web services in Python with Azure Machine Learning)
 description: Learn how to do this and that using customer words in Azure Machine Learning. This string describes the article in 115 to 145 characters. Use SEO kind of action verbs here. This info is displayed on the search page inline with the article date stamp. If your intro para describes your article's intent, you can use it here edited for length.
 services: machine-learning
 ms.service: machine-learning

markdown templates/aml-templates/template-quickstart.md

@@ -1,5 +1,5 @@
 ---
-title: Verb action quickstart for Azure Machine Learning service in 59 chars or less. Include the name Azure Machine Learning. Test title here https://moz.com/learn/seo/title-tag [Example - Create an Azure Machine Learning service account and get started]
+title: Verb action quickstart for Azure Machine Learning in 59 chars or less. Include the name Azure Machine Learning. Test title here https://moz.com/learn/seo/title-tag [Example - Create an Azure Machine Learning service account and get started]
 description: This string describes the article in 115 to 145 characters. Use SEO kind of action verbs here. such as - Learn how to do this and that using customer words. This info is displayed on the search page inline with the article date stamp. If your intro para describes your article's intent, you can use it here edited for length.
 services: machine-learning
 ms.service: machine-learning

markdown templates/aml-templates/template-tutorial.md

@@ -1,5 +1,5 @@
 ---
-title: Verb action tutorial for Azure Machine Learning service  in 59 chars or less. Include the name Azure Machine Learning. Include the word 'tutorial'. Test title here https://moz.com/learn/seo/title-tag 
+title: Verb action tutorial for Azure Machine Learning  in 59 chars or less. Include the name Azure Machine Learning. Include the word 'tutorial'. Test title here https://moz.com/learn/seo/title-tag 
 description: This tutorial …blah blah blah. This string describes the article in 115 to 145 characters. Include the word 'tutorial' in your description. Use SEO kind of action verbs here. such as - Learn how to do this and that using customer words. This info is displayed on the search page inline with the article date stamp. If your intro para describes your article's intent, you can use it here edited for length.
 services: machine-learning
 ms.service: machine-learning