Merge pull request #21 from HeidiSteen/heidist-master

Removing links from first paragraph

Author: HeidiSteen

Quickstart/README.md

@@ -2,16 +2,19 @@
 page_type: sample
 languages:
   - python
+  - rest
 products:
   - azure
   - azure-search
-description: "This sample demonstrates a connection to Azure Search, creating and loading an index, and query execution."
+description: "This Python sample demonstrates a connection to Azure Search, creating and loading an index, and query execution. Calls to Azure Search are made using REST APIs."
 urlFragment: python-sample-quickstart
 ---
 
 # Python sample for an Azure Search quickstart
 
-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). It demonstrates a connection to Azure Search, creating and loading an index, and query execution.
+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)
 
 ## Contents
 

Tutorial-AI-Enrichment/README.md

@@ -12,9 +12,9 @@ description: "This Python sample Jupyter notebook demonstrates AI enrichment usi
 
 # Get started with cognitive search AI enrichment in Azure Search
 
-This sample is a Jupyter Python3 .ipynb file used in [Python Tutorial: Call Cognitive Services APIs in an Azure Search indexing pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). 
+Demonstrates AI enrichment by building a cognitive search indexing pipeline that detects and extracts text and text representations of images and scanned documents stored as blobs in Azure Blob storage. This sample leverages cognitive skills from the Azure Cognitive Services API, such as entity recognition and language detection. It uses the REST APIs to make calls to Azure Search, including index definition, data ingestion and AI enrichment, and query execution.
 
-This sample demonstrates AI enrichment by building a cognitive search indexing pipeline that detects and extracts text and text representations of images and scanned documents stored as blobs in Azure Blob storage. This sample leverages cognitive skills from the Azure Cognitive Services API, such as entity recognition and language detection.
+This sample is a Jupyter Python3 .ipynb file used in [Python Tutorial: Call Cognitive Services APIs in an Azure Search indexing pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). 
 
 ## Contents