[migrate-content] Fix links

Author: Learn-Build-Service

.openpublishing.redirection.json

@@ -4,6 +4,16 @@
       "source_path": "articles/ai-studio/how-to/commitment-tier.md",
       "redirect_url": "/azure/ai-services/commitment-tier.md",
       "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/open-datasets/service/how-to-create-dataset-from-open-dataset.md",
+      "redirect_url": "/azure/open-datasets/how-to-create-azure-machine-learning-dataset-from-open-dataset",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/open-datasets/tutorial-opendatasets-automl.md",
+      "redirect_url": "/azure/machine-learning/tutorial-auto-train-models",
+      "redirect_document_id": false
     }
   ]
 }

.openpublishing.redirection.security-benchmark.json

@@ -0,0 +1,14 @@
+{
+  "redirections": [
+    {
+      "source_path_from_root": "/articles/search/security-baseline.md",
+      "redirect_url": "/security/benchmark/azure/baselines/cognitive-search-security-baseline",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/machine-learning/security-baseline.md",
+      "redirect_url": "/security/benchmark/azure/baselines/machine-learning-security-baseline",
+      "redirect_document_id": false
+    }
+  ]
+}

articles/machine-learning/apache-spark-azure-ml-concepts.md

@@ -131,7 +131,7 @@ To access data and other resources, a Spark job can use either a managed identit
 
 > [!NOTE]
 > - To ensure successful Spark job execution, assign **Contributor** and **Storage Blob Data Contributor** roles (on the Azure storage account used for data input and output) to the identity that will be used for the Spark job submission.
-> - If an [attached Synapse Spark pool](./how-to-manage-synapse-spark-pool.md) points to a Synapse Spark pool in an Azure Synapse workspace, and that workspace has an associated managed virtual network, [configure a managed private endpoint to a storage account](../synapse-analytics/security/connect-to-a-secure-storage-account.md). This configuration will help ensure data access.
+> - If an [attached Synapse Spark pool](./how-to-manage-synapse-spark-pool.md) points to a Synapse Spark pool in an Azure Synapse workspace, and that workspace has an associated managed virtual network, [configure a managed private endpoint to a storage account](/azure/synapse-analytics/security/connect-to-a-secure-storage-account). This configuration will help ensure data access.
 
 ## Next steps
 

articles/machine-learning/apache-spark-environment-configuration.md

@@ -21,7 +21,7 @@ In this quickstart guide, you learn how to perform interactive data wrangling wi
 ## Prerequisites
 - An Azure subscription; if you don't have an Azure subscription, [create a free account](https://azure.microsoft.com/free) before you start.
 - An Azure Machine Learning workspace. Visit [Create workspace resources](./quickstart-create-resources.md).
-- An Azure Data Lake Storage (ADLS) Gen 2 storage account. Visit [Create an Azure Data Lake Storage (ADLS) Gen 2 storage account](../storage/blobs/create-data-lake-storage-account.md).
+- An Azure Data Lake Storage (ADLS) Gen 2 storage account. Visit [Create an Azure Data Lake Storage (ADLS) Gen 2 storage account](/azure/storage/blobs/create-data-lake-storage-account).
 
 ## Store Azure storage account credentials as secrets in Azure Key Vault
 
@@ -105,7 +105,7 @@ assign **Reader** and **Storage Blob Data Reader** roles to the user identity of
 Once the user identity has the appropriate roles assigned, data in the Azure storage account should become accessible.
 
 > [!NOTE]
-> If an [attached Synapse Spark pool](./how-to-manage-synapse-spark-pool.md) points to a Synapse Spark pool, in an Azure Synapse workspace, that has a managed virtual network associated with it, [you should configure a managed private endpoint to a storage account](../synapse-analytics/security/connect-to-a-secure-storage-account.md) to ensure data access.
+> If an [attached Synapse Spark pool](./how-to-manage-synapse-spark-pool.md) points to a Synapse Spark pool, in an Azure Synapse workspace, that has a managed virtual network associated with it, [you should configure a managed private endpoint to a storage account](/azure/synapse-analytics/security/connect-to-a-secure-storage-account) to ensure data access.
 
 ## Ensuring resource access for Spark jobs
 

articles/machine-learning/azure-machine-learning-glossary.md

@@ -17,7 +17,7 @@ monikerRange: 'azureml-api-2'
 
 The Azure Machine Learning glossary is a short dictionary of terminology for the Machine Learning platform. For general Azure terminology, see also:
 
-* [Microsoft Azure glossary: A dictionary of cloud terminology on the Azure platform](../azure-glossary-cloud-terminology.md)
+* [Microsoft Azure glossary: A dictionary of cloud terminology on the Azure platform](/azure/azure-glossary-cloud-terminology)
 * [Cloud computing terms](https://azure.microsoft.com/overview/cloud-computing-dictionary/): General industry cloud terms
 * [Azure fundamental concepts](/azure/cloud-adoption-framework/ready/considerations/fundamental-concepts): Microsoft Cloud Adoption Framework for Azure
 

articles/machine-learning/component-reference-v2/text-ner.md

@@ -18,7 +18,7 @@ This article describes a component in Azure Machine Learning designer.
 
 Use this component to create a machine learning model that is based on the AutoML Text NER.
 
-Named Entity Recognition (NER) is one of the features offered by Azure AI Language. The NER feature can identify and categorize entities in unstructured text. For [more information on NER](../../ai-services/language-service/named-entity-recognition/overview.md)
+Named Entity Recognition (NER) is one of the features offered by Azure AI Language. The NER feature can identify and categorize entities in unstructured text. For [more information on NER](/azure/ai-services/language-service/named-entity-recognition/overview)
 
 ## How to configure 
 

articles/machine-learning/component-reference/designer-error-codes.md

@@ -900,7 +900,7 @@ Another reason you might get this error if you try to use a column containing fl
 
  This error in Azure Machine Learning occurs if the key used to access the Azure storage account is incorrect. For example, you might see this error if the Azure storage key was truncated when copied and pasted, or if the wrong key was used.  
 
- For more information about how to get the key for an Azure storage account, see [View, copy, and regenerate storage access keys](../../storage/common/storage-account-create.md).  
+ For more information about how to get the key for an Azure storage account, see [View, copy, and regenerate storage access keys](/azure/storage/common/storage-account-create).  
 
 **Resolution:**
  Revisit the component and verify that the Azure storage key is correct for the account; copy the key again from the Azure classic portal if necessary.  

articles/machine-learning/concept-automated-ml.md

@@ -221,4 +221,4 @@ Deepen your expertise of SDK design patterns and class specifications with the [
 > [!NOTE]
 > Automated machine learning capabilities are also available in other Microsoft solutions, such as
 [ML.NET](/dotnet/machine-learning/automl-overview),
-[HDInsight](../hdinsight/spark/apache-spark-run-machine-learning-automl.md), [Power BI](/power-bi/service-machine-learning-automated), and [SQL Server](https://cloudblogs.microsoft.com/sqlserver/2019/01/09/how-to-automate-machine-learning-on-sql-server-2019-big-data-clusters/).
+[HDInsight](/azure/hdinsight/spark/apache-spark-run-machine-learning-automl), [Power BI](/power-bi/service-machine-learning-automated), and [SQL Server](https://cloudblogs.microsoft.com/sqlserver/2019/01/09/how-to-automate-machine-learning-on-sql-server-2019-big-data-clusters/).

articles/machine-learning/concept-automl-forecasting-deep-learning.md

@@ -18,7 +18,7 @@ show_latex: true
 
 This article focuses on the deep learning methods for time series forecasting in AutoML. Instructions and examples for training forecasting models in AutoML can be found in our [set up AutoML for time series forecasting](./how-to-auto-train-forecast.md) article.
 
-Deep learning has numerous use cases in fields ranging from [language modeling](../ai-services/openai/concepts/models.md) to [protein folding](https://www.deepmind.com/research/highlighted-research/alphafold), among many others. Time series forecasting also benefits from recent advances in deep learning technology. For example, deep neural network (DNN) models feature prominently in the top performing models from the [fourth](https://www.uber.com/blog/m4-forecasting-competition/) and [fifth](https://www.sciencedirect.com/science/article/pii/S0169207021001874) iterations of the high-profile Makridakis forecasting competition.
+Deep learning has numerous use cases in fields ranging from [language modeling](/azure/ai-services/openai/concepts/models) to [protein folding](https://www.deepmind.com/research/highlighted-research/alphafold), among many others. Time series forecasting also benefits from recent advances in deep learning technology. For example, deep neural network (DNN) models feature prominently in the top performing models from the [fourth](https://www.uber.com/blog/m4-forecasting-competition/) and [fifth](https://www.sciencedirect.com/science/article/pii/S0169207021001874) iterations of the high-profile Makridakis forecasting competition.
 
 In this article, we describe the structure and operation of the TCNForecaster model in AutoML to help you best apply the model to your scenario. 
 

articles/machine-learning/concept-compute-instance.md

@@ -36,7 +36,7 @@ A compute instance is a fully managed cloud-based workstation optimized for your
 |Key benefits|Description|
 |----|----|
 |Productivity|You can build and deploy models using integrated notebooks and the following tools in Azure Machine Learning studio:<br/>-  Jupyter<br/>-  JupyterLab<br/>-  VS Code (preview)<br/>Compute instance is fully integrated with Azure Machine Learning workspace and studio. You can share notebooks and data with other data scientists in the workspace.<br/> 
-|Managed & secure|Reduce your security footprint and add compliance with enterprise security requirements. Compute instances  provide robust management policies and secure networking configurations such as:<br/><br/>- Autoprovisioning from Resource Manager templates or Azure Machine Learning SDK<br/>- [Azure role-based access control (Azure RBAC)](../role-based-access-control/overview.md)<br/>- [Virtual network support](./how-to-secure-training-vnet.md)<br/> - Azure policy to disable SSH access<br/> - Azure policy to enforce creation in a virtual network <br/> - Auto-shutdown/auto-start based on schedule <br/>- TLS 1.2 enabled |
+|Managed & secure|Reduce your security footprint and add compliance with enterprise security requirements. Compute instances  provide robust management policies and secure networking configurations such as:<br/><br/>- Autoprovisioning from Resource Manager templates or Azure Machine Learning SDK<br/>- [Azure role-based access control (Azure RBAC)](/azure/role-based-access-control/overview)<br/>- [Virtual network support](./how-to-secure-training-vnet.md)<br/> - Azure policy to disable SSH access<br/> - Azure policy to enforce creation in a virtual network <br/> - Auto-shutdown/auto-start based on schedule <br/>- TLS 1.2 enabled |
 |Preconfigured&nbsp;for&nbsp;ML|Save time on setup tasks with pre-configured and up-to-date ML packages, deep learning frameworks, GPU drivers.|
 |Fully customizable|Broad support for Azure VM types including GPUs and persisted low-level customization such as installing packages and drivers makes advanced scenarios a breeze. You can also use setup scripts to automate customization |