add image; fix links

Author: sdgilley

articles/machine-learning/how-to-train-sdk.md

@@ -4,7 +4,7 @@ titleSuffix: Azure Machine Learning
 description: Configure and submit Azure Machine Learning jobs to train your models with SDK v2.
 services: machine-learning
 author: balapv
-ms.author: balapb
+ms.author: balapv
 ms.reviewer: sgilley
 ms.service: machine-learning
 ms.subservice: core
@@ -20,12 +20,12 @@ ms.custom: sdkv2
 > * [v1](v1/how-to-attach-compute-targets.md)
 > * [v2 (preview)](how-to-attach-compute-targets.md)
 
-In this article, you learn how to configure and submit Azure Machine Learning jobs to train your models. Snippets of code explain the key parts of configuration and submission of a training job. Then use one of the [example notebooks](https://github.com/Azure/azureml-examples/tree/sdk-preview/sdk) to find the full end-to-end working examples.
+In this article, you learn how to configure and submit Azure Machine Learning jobs to train your models. Snippets of code explain the key parts of configuration and submission of a training     job. Then use one of the [example notebooks](https://github.com/Azure/azureml-examples/tree/sdk-preview/sdk) to find the full end-to-end working examples.
 
 ## Prerequisites
 
 * If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/) today
-* The Azure Machine Learning SDK v2 for Python - [install SDKv2](./install-sdkv2.md)
+* The Azure Machine Learning SDK v2 for Python - [install SDKv2]()
 * An Azure Machine Learning workspace
 
 ### Clone examples repository
@@ -217,7 +217,7 @@ As seen above, the `sweep` function allows user to configure the following key a
 
 Once this job completes, you can look at the metrics and the job details in the [Azure ML Portal](https://ml.azure.com/). The job details page will identify the best performing child run.
 
-:::image type="content" source="sweep-best-run.jpg" alt-text="Best run of the sweep":::
+:::image type="content" source="media/how-to-train-sdk/sweep-best-run.jpg" alt-text="Best run of the sweep":::
 
 ## Distributed training
 
@@ -241,4 +241,4 @@ job.distribution = MpiDistribution(process_count_per_instance=3)
 
 Try these next steps to learn how to use the Azure Machine Learning SDK (v2) for Python:
 
-1. [Use pipelines with the Azure ML Python SDK (v2)](../pipeline-sdkv2.md)
+1. Use pipelines with the Azure ML Python SDK (v2)

articles/machine-learning/media/how-to-train-sdk/sweep-best-run.jpg

@@ -20,7 +20,7 @@ ms.custom: devx-track-python, contperf-fy21q1, ignite-fall-2021, sdkv1
 > * [v1](how-to-attach-compute-targets.md)
 > * [v2 (preview)](../how-to-attach-compute-targets.md)
 	 
-Learn how to attach Azure compute resources to your Azure Machine Learning workspace with SDK v1.  Then you can use these resources as training and inference [compute targets](concept-compute-target.md) in your machine learning tasks.
+Learn how to attach Azure compute resources to your Azure Machine Learning workspace with SDK v1.  Then you can use these resources as training and inference [compute targets](../concept-compute-target.md) in your machine learning tasks.
 
 In this article, learn how to set up your workspace to use these compute resources:
 
@@ -29,7 +29,7 @@ In this article, learn how to set up your workspace to use these compute resourc
 * Apache Spark pools (powered by Azure Synapse Analytics)
 * Azure HDInsight
 * Azure Batch
-* Azure Databricks - used as a training compute target only in [machine learning pipelines](how-to-create-machine-learning-pipelines.md)
+* Azure Databricks - used as a training compute target only in [machine learning pipelines](../how-to-create-machine-learning-pipelines.md)
 * Azure Data Lake Analytics
 * Azure Container Instance
 * Azure Kubernetes Service & Azure Arc-enabled Kubernetes (preview)
@@ -44,7 +44,7 @@ To use compute targets managed by Azure Machine Learning, see:
 
 * An Azure Machine Learning workspace. For more information, see [Create an Azure Machine Learning workspace](../how-to-manage-workspace.md).
 
-* The [Azure CLI extension for Machine Learning service](reference-azure-machine-learning-cli.md), [Azure Machine Learning Python SDK](/python/api/overview/azure/ml/intro), or the [Azure Machine Learning Visual Studio Code extension](how-to-setup-vs-code.md).
+* The [Azure CLI extension for Machine Learning service](reference-azure-machine-learning-cli.md), [Azure Machine Learning Python SDK](/python/api/overview/azure/ml/intro), or the [Azure Machine Learning Visual Studio Code extension](../how-to-setup-vs-code.md).
 
 ## Limitations
 
@@ -130,13 +130,13 @@ Azure Machine Learning also supports attaching an Azure Virtual Machine. The VM
 
 ## <a id="synapse"></a>Apache Spark pools
 
-The Azure Synapse Analytics integration with Azure Machine Learning (preview) allows you to attach an Apache Spark pool backed by Azure Synapse for interactive data exploration and preparation. With this integration, you can have a dedicated compute for data wrangling at scale. For more information, see [How to attach Apache Spark pools powered by Azure Synapse Analytics](how-to-link-synapse-ml-workspaces.md#attach-synapse-spark-pool-as-a-compute).
+The Azure Synapse Analytics integration with Azure Machine Learning (preview) allows you to attach an Apache Spark pool backed by Azure Synapse for interactive data exploration and preparation. With this integration, you can have a dedicated compute for data wrangling at scale. For more information, see [How to attach Apache Spark pools powered by Azure Synapse Analytics](../how-to-link-synapse-ml-workspaces.md#attach-synapse-spark-pool-as-a-compute).
 
 ## <a id="hdinsight"></a>Azure HDInsight 
 
 Azure HDInsight is a popular platform for big-data analytics. The platform provides Apache Spark, which can be used to train your model.
 
-1. **Create**:  Azure Machine Learning cannot create an HDInsight cluster for you. Instead, you must create the cluster and then attach it to your Azure Machine Learning workspace. For more information, see [Create a Spark Cluster in HDInsight](../hdinsight/spark/apache-spark-jupyter-spark-sql.md). 
+1. **Create**:  Azure Machine Learning cannot create an HDInsight cluster for you. Instead, you must create the cluster and then attach it to your Azure Machine Learning workspace. For more information, see [Create a Spark Cluster in HDInsight](../../hdinsight/spark/apache-spark-jupyter-spark-sql.md). 
 
     > [!WARNING]
     > Azure Machine Learning requires the HDInsight cluster to have a __public IP address__.
@@ -342,7 +342,7 @@ For a more detailed example, see an [example notebook](https://aka.ms/pl-adla) o
 
 ## <a id="aci"></a>Azure Container Instance
 
-Azure Container Instances (ACI) are created dynamically when you deploy a model. You cannot create or attach ACI to your workspace in any other way. For more information, see [Deploy a model to Azure Container Instances](v1/how-to-deploy-azure-container-instance.md).
+Azure Container Instances (ACI) are created dynamically when you deploy a model. You cannot create or attach ACI to your workspace in any other way. For more information, see [Deploy a model to Azure Container Instances](how-to-deploy-azure-container-instance.md).
 
 ## <a id="kubernetes"></a>Kubernetes (preview)
 

articles/machine-learning/v1/how-to-attach-compute-targets.md

@@ -25,7 +25,7 @@ You can use any of the following resources for a training compute target for mos
 |[Azure Databricks](../articles/machine-learning/v1/how-to-attach-compute-targets.md#databricks)| Yes (SDK local mode only) | Yes |   |
 |[Azure Data Lake Analytics](../articles/machine-learning/v1/how-to-attach-compute-targets.md#adla) |   | Yes |   |
 |[Azure HDInsight](../articles/machine-learning/v1/how-to-attach-compute-targets.md#hdinsight) |   | Yes |   |
-|[Azure Batch](../articles/machine-learning/hv1/ow-to-attach-compute-targets.md#azbatch) |   | Yes |   |
+|[Azure Batch](../articles/machine-learning/v1/how-to-attach-compute-targets.md#azbatch) |   | Yes |   |
 |[Azure Kubernetes Service](../articles/machine-learning/v1/how-to-attach-compute-targets.md#kubernetes) (preview) | Yes | Yes | Yes |
 |[Azure Arc-enabled Kubernetes](../articles/machine-learning/v1/how-to-attach-compute-targets.md#kubernetes) (preview) | Yes | Yes | Yes |