fix links

Author: sdgilley

articles/machine-learning/concept-train-machine-learning-model.md

@@ -17,7 +17,7 @@ ms.devlang: azurecli
 
 [!INCLUDE [sdk v2](../../includes/machine-learning-sdk-v2.md)]
 > [!div class="op_single_selector" title1="Select the Azure Machine Learning version you are using:"]
-> * [v1](v1/concept-train-machine-learning-model-v1.md>)
+> * [v1](v1/concept-train-machine-learning-model-v1.md)
 > * [v2 (preview)](concept-train-machine-learning-model.md)
 
 Azure Machine Learning provides several ways to train your models, from code-first solutions using the SDK to low-code solutions such as automated machine learning and the visual designer. Use the following list to determine which training method is right for you:
@@ -40,7 +40,7 @@ Each of these training methods can use different types of compute resources for
 
 The Azure Machine Learning SDK for Python allows you to build and run machine learning workflows with Azure Machine Learning. You can interact with the service from an interactive Python session, Jupyter Notebooks, Visual Studio Code, or other IDE.
 
-* [Install/update the SDK](/python/api/overview/azure/ml/installv2?view=azure-ml-py)
+* [Install/update the SDK](/python/api/overview/azure/ml/installv2)
 * [Configure a development environment for Azure Machine Learning](how-to-configure-environment.md)
 
 ### Submit a command

articles/machine-learning/v1/concept-train-machine-learning-model-v1.md

@@ -17,7 +17,7 @@ ms.devlang: azurecli
 
 [!INCLUDE [sdk v1](../../../includes/machine-learning-sdk-v1.md)]
 > [!div class="op_single_selector" title1="Select the Azure Machine Learning version you are using:"]
-> * [v1](concept-train-machine-learning-model-v1.md>)
+> * [v1](concept-train-machine-learning-model-v1.md)
 > * [v2 (preview)](../concept-train-machine-learning-model.md)
 
 Azure Machine Learning provides several ways to train your models, from code-first solutions using the SDK to low-code solutions such as automated machine learning and the visual designer. Use the following list to determine which training method is right for you:
@@ -34,15 +34,15 @@ Azure Machine Learning provides several ways to train your models, from code-fir
 
 + **Azure CLI**: The machine learning CLI provides commands for common tasks with Azure Machine Learning, and is often used for **scripting and automating tasks**. For example, once you've created a training script or pipeline, you might use the Azure CLI to start a training job on a schedule or when the data files used for training are updated. For training models, it provides commands that submit training jobs. It can submit jobs using run configurations or pipelines.
 
-Each of these training methods can use different types of compute resources for training. Collectively, these resources are referred to as [__compute targets__](v1/concept-azure-machine-learning-architecture.md#compute-targets). A compute target can be a local machine or a cloud resource, such as an Azure Machine Learning Compute, Azure HDInsight, or a remote virtual machine.
+Each of these training methods can use different types of compute resources for training. Collectively, these resources are referred to as [__compute targets__](concept-azure-machine-learning-architecture.md#compute-targets). A compute target can be a local machine or a cloud resource, such as an Azure Machine Learning Compute, Azure HDInsight, or a remote virtual machine.
 
 ## Python SDK
 
 The Azure Machine Learning SDK for Python allows you to build and run machine learning workflows with Azure Machine Learning. You can interact with the service from an interactive Python session, Jupyter Notebooks, Visual Studio Code, or other IDE.
 
 * [What is the Azure Machine Learning SDK for Python](/python/api/overview/azure/ml/intro)
 * [Install/update the SDK](/python/api/overview/azure/ml/install)
-* [Configure a development environment for Azure Machine Learning](how-to-configure-environment.md)
+* [Configure a development environment for Azure Machine Learning](../how-to-configure-environment.md)
 
 ### Run configuration
 
@@ -75,7 +75,7 @@ Machine learning pipelines can use the previously mentioned training methods. Pi
 
 * [What are ML pipelines in Azure Machine Learning?](../concept-ml-pipelines.md)
 * [Create and run machine learning pipelines with Azure Machine Learning SDK](how-to-create-machine-learning-pipelines.md)
-* [Tutorial: Use Azure Machine Learning Pipelines for batch scoring](tutorial-pipeline-batch-scoring-classification.md)
+* [Tutorial: Use Azure Machine Learning Pipelines for batch scoring](tutorial-pipeline-python-sdk.md)
 * [Examples: Jupyter Notebook examples for machine learning pipelines](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/machine-learning-pipelines)
 * [Examples: Pipeline with automated machine learning](https://aka.ms/pl-automl)
 
@@ -118,4 +118,4 @@ The machine learning CLI is an extension for the Azure CLI. It provides cross-pl
 
 ## Next steps
 
-Learn how to [Configure a training run](v1/how-to-set-up-training-targets.md).
+Learn how to [Configure a training run](how-to-set-up-training-targets.md).