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Co-authored-by: Larry Franks <[email protected]>

Author: AbeOmor

articles/machine-learning/how-to-setup-mlops-azureml.md

@@ -1,7 +1,7 @@
 ---
-title: Setup MLOps with Azure DevOps
+title: Set up MLOps with Azure DevOps
 titleSuffix: Azure Machine Learning
-description: Learn how to setup a sample MLOps environment in AzureML
+description: Learn how to set up a sample MLOps environment in AzureML
 services: machine-learning
 author: abeomor
 ms.author: osomorog
@@ -12,7 +12,7 @@ ms.topic: conceptual
 ms.custom: cli-v2, sdk-v2
 ---
 
-# Setup MLOps with Azure DevOps
+# Set up MLOps with Azure DevOps
 
 [!INCLUDE [dev v2](../../includes/machine-learning-dev-v2.md)]
 
@@ -24,10 +24,10 @@ Azure Machine Learning allows you to integration with [Azure DevOps pipeline](/a
 * Deployment of machine learning models as public or private web services
 * Monitoring deployed machine learning models (such as for performance analysis)
 
-In this article, you learn about using Azure Machine Learning to setup an end-to-end MLOps pipeline which runs a linear regression to predict taxi fares in NYC. The pipeline is made up of components, each serving  different functions, which can be registered with the workspace, versioned, and reused with various inputs and outputs. you are going to be using the [recommended Azure architecture for MLOps](/azure/architecture/data-guide/technology-choices/machine-learning-operations-v2) and [Azure MLOps (v2) solution accelerator](https://github.com/Azure/mlops-v2) to quickly set up an MLOps project in AzureML.
+In this article, you learn about using Azure Machine Learning to set up an end-to-end MLOps pipeline that runs a linear regression to predict taxi fares in NYC. The pipeline is made up of components, each serving  different functions, which can be registered with the workspace, versioned, and reused with various inputs and outputs. you are going to be using the [recommended Azure architecture for MLOps](/azure/architecture/data-guide/technology-choices/machine-learning-operations-v2) and [Azure MLOps (v2) solution accelerator](https://github.com/Azure/mlops-v2) to quickly set up an MLOps project in AzureML.
 
 > [!TIP]
-> We recommend you understand some of the [recommended Azure architectures](/azure/architecture/data-guide/technology-choices/machine-learning-operations-v2) for MLOps before implementing any solution. You will need to pick the best architecture for your given Machine learning project
+> We recommend you understand some of the [recommended Azure architectures](/azure/architecture/data-guide/technology-choices/machine-learning-operations-v2) for MLOps before implementing any solution. You'll need to pick the best architecture for your given Machine learning project.
 
 ## Prerequisites
 
@@ -47,12 +47,12 @@ In this article, you learn about using Azure Machine Learning to setup an end-to
 > [!IMPORTANT]
 >The CLI commands in this article were tested using Bash. If you use a different shell, you may encounter errors.
 
-## Setup authentication with Azure and DevOps
+## Set up authentication with Azure and DevOps
 
 Before you can setup an MLOps project with AzureML you need to make sure you have the correct authentication setup for Azure DevOps.
 
 ### Create service principal
-   For the use of the demo, the creation of one or two service principles is required, depending on how many environments, you want to work on (Dev or Prod or Both). These principles can be created using one of the methods below:
+   For the use of the demo, the creation of one or two service principles is required, depending on how many environments, you want to work on (Dev or Prod or Both). These principles can be created using one of the following methods:
 
 # [Create from Azure Cloud Shell](#tab/azure-shell)