Merge pull request #25 from HeidiSteen/heidist-master

Edits for consistency and readability

Author: HeidiSteen

Quickstart/README.md

@@ -8,12 +8,14 @@ products:
   - azure
   - azure-search
 description: |
-  Jupyter Python3 notebook, demonstrating index definition, data ingestion, and query execution in Azure Search using the REST APIs.
+  Learn basic steps for creating, loading, and querying an Azure Search index using REST APIs and a Jupyter Python3 notebook.
 urlFragment: python-sample-quickstart
 ---
 
 # Quickstart sample for Azure Search using Python
 
+![Flask sample MIT license badge](https://img.shields.io/badge/license-MIT-green.svg)
+
 Demonstrates connecting to Azure Search, creating and loading an index consisting of fictitious hotel data, and running queries. A Jupyter Python Notebook is used to run this code. Calls to Azure Search are through the REST APIs.
 
 This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and query an Azure Search index using a Jupyter Python notebook](https://docs.microsoft.com/azure/search/search-get-started-python)
@@ -43,3 +45,7 @@ This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and que
 1. Open the azure-search-quickstart.ipynb file in Jupyter Notebook
 1. Replace <YOUR-SERVICE-NAME> and <YOUR-ADMIN-API-KEY> with the service and api-key details of your Azure Search service
 1. Run each step individually
+
+## Next steps
+
+You can learn more about Azure Search on the [official documentation site](https://docs.microsoft.com/azure/search).

Tutorial-AI-Enrichment/README.md

@@ -6,9 +6,9 @@ languages:
 products:
   - azure
   - azure-search
-name: Cognitive search AI-enriched pipeline
+name: Build a cognitive search AI-enriched pipeline
 description: |
-  Jupyter Python3 notebook, demonstrating AI enrichment using Cognitive Services in an Azure Search indexing pipeline. Calls to Azure Search are made using REST APIs.
+  Demonstrates AI enrichment using Cognitive Services in an Azure Search indexing pipeline. Calls to Azure Search are made using REST APIs in Jupyter Python3 notebook.
 urlFragment: python-tutorial-cognitive-search
 ---