fixing some broken links

Author: Larry Franks

articles/machine-learning/how-to-deploy-custom-docker-image.md

@@ -43,7 +43,7 @@ This document is broken into two sections:
 * The [Azure CLI](https://docs.microsoft.com/cli/azure/install-azure-cli?view=azure-cli-latest).
 * The [CLI extension for Azure Machine Learning](reference-azure-machine-learning-cli.md).
 * An [Azure Container Registry](/azure/container-registry) or other Docker registry that is accessible on the internet.
-* The steps in this document assume that you are familiar with creating and using an __inference configuration__ object as part of model deployment. For more information, see the "prepare to deploy" section of [Where to deploy and how](how-to-deploy-and-where.md#prepare-to-deploy).
+* The steps in this document assume that you are familiar with creating and using an __inference configuration__ object as part of model deployment. For more information, see the "prepare to deploy" section of [Where to deploy and how](how-to-deploy-and-where.md#prepare-deployment-artifacts).
 
 ## Create a custom base image
 

articles/machine-learning/tutorial-train-deploy-model-cli.md

@@ -376,7 +376,7 @@ This command deploys a new service named `myservice`, using version 1 of the mod
 
 The `inferenceConfig.yml` file provides information on how to use the model for inference. For example, it references the entry script (`score.py`) and software dependencies. 
 
-For more information on the structure of this file, see the [Inference configuration schema](reference-azure-machine-learning-cli.md#inference-configuration-schema). For more information on entry scripts, see [Deploy models with the Azure Machine Learning](how-to-deploy-and-where.md#prepare-to-deploy).
+For more information on the structure of this file, see the [Inference configuration schema](reference-azure-machine-learning-cli.md#inference-configuration-schema). For more information on entry scripts, see [Deploy models with the Azure Machine Learning](how-to-deploy-and-where.md#prepare-deployment-artifacts).
 
 The `aciDeploymentConfig.yml` describes the deployment environment used to host the service. The deployment configuration is specific to the compute type that you use for the deployment. In this case, an Azure Container Instance is used. For more information, see the [Deployment configuration schema](reference-azure-machine-learning-cli.md#deployment-configuration-schema).