Merge pull request #34 from tchristiani/master

fixes to README files

Author: HeidiSteen

AzureML-Custom-Skill/README.md

@@ -43,16 +43,16 @@ There are two datasets provided. If you wish to train the model yourself, the `h
 
 ## Setup
 
-1. Clone or download the contents of this repository.
-1. Extract contents if the download is a zip file. Make sure the files are read-write.
-1. While setting up the Azure accounts and services, copy the names and keys to an easily accessed text file. The names and keys will be added to the first cell in the notebook where variables for accessing the Azure services are defined.
-1. If you are unfamiliar with Azure Machine Learning and its requirements, you will want to review these documents before getting started:
+* Clone or download the contents of this repository.
+* Extract contents if the download is a zip file. Make sure the files are read-write.
+* While setting up the Azure accounts and services, copy the names and keys to an easily accessed text file. The names and keys will be added to the first cell in the notebook where variables for accessing the Azure services are defined.
+* If you are unfamiliar with Azure Machine Learning and its requirements, you will want to review these documents before getting started:
 
 * [Configure a development environment for Azure Machine Learning](https://docs.microsoft.com/azure/machine-learning/how-to-configure-environment)
 * [Create and manage Azure Machine Learning workspaces in the Azure portal](https://docs.microsoft.com/azure/machine-learning/how-to-manage-workspace)
 * When configuring the development environment for Azure Machine Learning, consider using the [cloud-based compute instance](https://docs.microsoft.com/azure/machine-learning/how-to-configure-environment#compute-instance) for speed and ease in getting started.
 
-1. Upload the dataset file to a container in the storage account. The [larger file](datasets\hotel_reviews_1000.csv) is necessary if you wish to perform the training step in the notebook. If you prefer to skip the training step, the [smaller file](datasets\hotel_reviews_100.csv) is recommended.
+* Upload the dataset file to a container in the storage account. The [larger file](datasets\hotel_reviews_1000.csv) is necessary if you wish to perform the training step in the notebook. If you prefer to skip the training step, the [smaller file](datasets\hotel_reviews_100.csv) is recommended.
 
 ### Running the tutorial
 

README.md

@@ -8,4 +8,8 @@ This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and que
 
 ## Tutorial - Add AI enrichments to an indexing pipeline
 
-This sample is also a Jupyter Python3 .ipynb file. It's used in the [Python Tutorial: Call Cognitive Services APIs in an Azure Cognitive Search indexing pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). This sample demonstrates cognitive search functionality, adding AI enrichments from Cognitive Services to extract, detect, and analyze information from image files or large unstructured document files.
+This sample is a Jupyter Python3 .ipynb file. It's used in the [Python Tutorial: Call Cognitive Services APIs in an Azure Cognitive Search indexing pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). This sample demonstrates cognitive search functionality, adding AI enrichments from Cognitive Services to extract, detect, and analyze information from image files or large unstructured document files.
+
+## Tutorial - Train and deploy a custom skill with Azure Machine Learning
+
+This sample is a Jupyter Python3 .ipynb file. It's used in the [Tutorial: Build and deploy a custom skill with Azure Machine Learning](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-aml-custom-skill). This sample provides an end-to-end walk through for training and deploying an aspect-based sentiment model to an Azure Kubernetes cluster for consumption as a custom skill in a Cognitive Search enrichment pipeline. Azure Machine Learning is used to train and deploy the model.