Merge pull request #208545 from ssalgadodev/dataChangeFileName

Data | file name change to remove register

Author: denrea

articles/machine-learning/.openpublishing.redirection.machine-learning.json

@@ -16,6 +16,11 @@
         "redirect_url": "/azure/machine-learning/v1/how-to-extend-prebuilt-docker-image-inference",
         "redirect_document_id": true
     },
+    {
+        "source_path_from_root": "/articles/machine-learning/how-to-create-register-data-assets.md",
+        "redirect_url": "/azure/machine-learning/how-to-create-data-assets",
+        "redirect_document_id": true
+    },
     {
         "source_path_from_root": "/articles/machine-learning/how-to-prebuilt-docker-images-inference-python-extensibility.md",
         "redirect_url": "/azure/machine-learning/v1/how-to-prebuilt-docker-images-inference-python-extensibility",

articles/machine-learning/concept-data.md

@@ -345,6 +345,6 @@ Just like `uri_file` and `uri_folder`, you can create a data asset with `mltable
 
 - [Install and set up the CLI (v2)](how-to-configure-cli.md#install-and-set-up-the-cli-v2)
 - [Create datastores](how-to-datastore.md#create-datastores)
-- [Create data assets](how-to-create-register-data-assets.md#create-data-assets)
+- [Create data assets](how-to-create-data-assets.md#create-data-assets)
 - [Read and write data in a job](how-to-read-write-data-v2.md#read-and-write-data-in-a-job)
 - [Data administration](how-to-administrate-data-authentication.md#data-administration)

articles/machine-learning/how-to-create-register-data-assets.md renamed to articles/machine-learning/how-to-create-data-assets.md

@@ -20,14 +20,14 @@ ms.date: 05/24/2022
 
 > [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK you are using:"]
 > * [v1](./v1/how-to-create-register-datasets.md)
-> * [v2 (current version)](how-to-create-register-data-assets.md)
+> * [v2 (current version)](how-to-create-data-assets.md)
 
 [!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 [!INCLUDE [CLI v2](../../includes/machine-learning-CLI-v2.md)]
 
-In this article, you learn how to create a Data asset in Azure Machine Learning. By creating a Data asset, you create a *reference* to the data source location, along with a copy of its metadata. Because the data remains in its existing location, you incur no extra storage cost, and don't risk the integrity of your data sources. You can create Data from Datastores, Azure Storage, public URLs, and local files.
+In this article, you learn how to create a data asset in Azure Machine Learning. By creating a data asset, you create a *reference* to the data source location, along with a copy of its metadata. Because the data remains in its existing location, you incur no extra storage cost, and don't risk the integrity of your data sources. You can create Data from datastores, Azure Storage, public URLs, and local files.
 
-The benefits of creating Data assets are:
+The benefits of creating data assets are:
 
 * You can **share and reuse data** with other members of the team such that they do not need to remember file locations.
 
@@ -38,7 +38,7 @@ The benefits of creating Data assets are:
 
 ## Prerequisites
 
-To create and work with Data assets, you need:
+To create and work with data assets, you need:
 
 * An Azure subscription. If you don't have one, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/).
 

articles/machine-learning/how-to-datastore.md

@@ -423,5 +423,5 @@ ml_client.create_or_update(store)
 ## Next steps
 
 - [Read data in a job](how-to-read-write-data-v2.md#read-data-in-a-job)
-- [Create data assets](how-to-create-register-data-assets.md#create-data-assets)
+- [Create data assets](how-to-create-data-assets.md#create-data-assets)
 - [Data administration](how-to-administrate-data-authentication.md#data-administration)

articles/machine-learning/how-to-migrate-from-v1.md

@@ -15,7 +15,7 @@ ms.custom: devx-track-azurecli, devplatv2
 
 # How to migrate from v1 to v2
 
-Azure Machine Learning's v2 REST APIs, Azure CLI extension, and Python SDK (preview) introduce consistency and a set of new features to accelerate the production machine learning lifecycle. In this article, we'll overview migrating from v1 to v2 with recommendations to help you decide on v1, v2, or both.
+Azure Machine Learning's v2 REST APIs, Azure CLI extension, and Python SDK (preview) introduce consistency and a set of new features to accelerate the production machine learning lifecycle. This article provides an overview of migrating from v1 to v2 with recommendations to help you decide on v1, v2, or both.
 
 ## Prerequisites
 
@@ -58,7 +58,7 @@ In v2 interfaces via REST API, CLI, and Python SDK (preview) are available. The
 
 |API|Notes|
 |-|-|
-|REST|Fewest dependencies and overhead. Use for building applications on Azure ML as a platform, directly in programming languages without a SDK provided, or per personal preference.|
+|REST|Fewest dependencies and overhead. Use for building applications on Azure ML as a platform, directly in programming languages without an SDK provided, or per personal preference.|
 |CLI|Recommended for automation with CI/CD or per personal preference. Allows quick iteration with YAML files and straightforward separation between Azure ML and ML model code.|
 |Python SDK|Recommended for complicated scripting (for example, programmatically generating large pipeline jobs) or per personal preference. Allows quick iteration with YAML files or development solely in Python.|
 
@@ -110,9 +110,9 @@ You can continue using your existing v1 model deployments. For new model deploym
 |-|-|-|
 |Local|ACI|Quick test of model deployment locally; not for production.|
 |Managed online endpoint|ACI, AKS|Enterprise-grade managed model deployment infrastructure with near real-time responses and massive scaling for production.|
-|Managed batch endpoint|ParallelRunStep in a pipeline for batch scoring|Enterprise-grade managed model deployment infrastructure with massively-parallel batch processing for production.|
+|Managed batch endpoint|ParallelRunStep in a pipeline for batch scoring|Enterprise-grade managed model deployment infrastructure with massively parallel batch processing for production.|
 |Azure Kubernetes Service (AKS)|ACI, AKS|Manage your own AKS cluster(s) for model deployment, giving flexibility and granular control at the cost of IT overhead.|
-|Azure Arc Kubernetes|N/A|Manage your own Kubernetes cluster(s) in other clouds or on-prem, giving flexibility and granular control at the cost of IT overhead.|
+|Azure Arc Kubernetes|N/A|Manage your own Kubernetes cluster(s) in other clouds or on-premises, giving flexibility and granular control at the cost of IT overhead.|
 
 ### Jobs (experiments, runs, pipelines in v1)
 
@@ -134,7 +134,7 @@ Data assets in v2 (or File Datasets in v1) are *references* to files in object s
 
 For details on data in v2, see the [data concept article](concept-data.md).
 
-We recommend migrating the code for [creating data assets](how-to-create-register-data-assets.md) to v2.
+We recommend migrating the code for [creating data assets](how-to-create-data-assets.md) to v2.
 
 ### Model
 

articles/machine-learning/how-to-use-automated-ml-for-ml-models.md

@@ -47,7 +47,7 @@ Otherwise, you'll see a list of your recent automated  ML experiments, including
 
 1. Select **+ New automated ML job** and populate the form.
 
-1. Select a data asset from your storage container, or create a new data asset. Data asset can be created from local files, web urls, datastores, or Azure open datasets. Learn more about [data asset creation](how-to-create-register-data-assets.md).  
+1. Select a data asset from your storage container, or create a new data asset. Data asset can be created from local files, web urls, datastores, or Azure open datasets. Learn more about [data asset creation](how-to-create-data-assets.md).  
 
     >[!Important]
     > Requirements for training data:

articles/machine-learning/toc.yml

@@ -354,7 +354,7 @@
           href: how-to-datastore.md
         - name: Create data assets
           displayName: Create data assets
-          href: how-to-create-register-data-assets.md
+          href: how-to-create-data-assets.md
         - name: Read & write data in jobs
           displayName: Read & write data in jobs
           href: how-to-read-write-data-v2.md

articles/machine-learning/v1/how-to-create-register-datasets.md

@@ -18,7 +18,7 @@ ms.date: 05/11/2022
 
 > [!div class="op_single_selector" title1="Select the version of Azure Machine Learning SDK you are using:"]
 > * [v1](how-to-create-register-datasets.md)
-> * [v2 (current version)](../how-to-create-register-data-assets.md)
+> * [v2 (current version)](../how-to-create-data-assets.md)
 
 [!INCLUDE [sdk v1](../../../includes/machine-learning-sdk-v1.md)]