Merge pull request #26 from HeidiSteen/heidist-master

Updated product name reference

Author: HeidiSteen

Quickstart/CONTRIBUTING.md

@@ -1,4 +1,4 @@
-# Contributing to the Python quickstart for Azure Search
+# Contributing to Azure Cognitive Search samples
 
 This project welcomes contributions and suggestions.  Most contributions require you to agree to a
 Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us

Quickstart/README.md

@@ -3,22 +3,22 @@ page_type: sample
 languages:
   - python
   - rest
-name: Azure Search Quickstart in Python
+name: Azure Cognitive Search Quickstart in Python
 products:
   - azure
-  - azure-search
+  - cognitive-search
 description: |
-  Learn basic steps for creating, loading, and querying an Azure Search index using REST APIs and a Jupyter Python3 notebook.
+  Learn basic steps for creating, loading, and querying a search index using REST APIs and a Jupyter Python3 notebook.
 urlFragment: python-sample-quickstart
 ---
 
-# Quickstart sample for Azure Search using Python
+# Quickstart sample for Azure Cognitive 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.
+Demonstrates connecting to Azure Cognitive 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 Cognitive 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)
+This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and query a search index using a Jupyter Python notebook](https://docs.microsoft.com/azure/search/search-get-started-python)
 
 ## Contents
 
@@ -33,7 +33,7 @@ This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and que
 ## Prerequisites
 
 - [Anaconda 3.x](https://www.anaconda.com/distribution/#download-section) providing Python 3.x and Jupyter Notebooks
-- [Azure Search service](https://docs.microsoft.com/azure/search/search-create-service-portal)
+- [Azure Cognitive Search service](https://docs.microsoft.com/azure/search/search-create-service-portal)
 
 ## Setup
 
@@ -43,9 +43,9 @@ This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and que
 ## Running the sample
 1. On the Windows Start menu, select Anaconda3, and then select Jupyter Notebook.
 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. Replace <YOUR-SERVICE-NAME> and <YOUR-ADMIN-API-KEY> with the service and api-key details of your 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).
+You can learn more about Azure Cognitive Search on the [official documentation site](https://docs.microsoft.com/azure/search).

README.md

@@ -1,20 +1,11 @@
----
-languages:
-  - python
-  - rest
-products:
-  - azure
-  - azure-search
----
+# Python sample repository for Azure Cognitive Search
 
-# Python sample repository for Azure Search
+This repository contains Python sample code used in Azure Cognitive Search quickstarts, tutorials, and examples. You can use the shared (free) Azure Cognitive Search service to run any sample in this repository. Samples are in individual folders in this repository.
 
-This repository contains Python sample code used in Azure Search quickstarts, tutorials, and examples. You can use the shared (free) Azure Search service to run any sample in this repository. Samples are in individual folders in this repository.
+## Quickstart - Azure Cognitive Search
 
-## Quickstart - Azure Search
-
-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). Use this sample to learn service connections, index creation, data ingestion, and basic queries.
+This sample is a Jupyter Python3 .ipynb file used in [Quickstart: Create and query an Azure Cognitive Search index using a Jupyter Python notebook](https://docs.microsoft.com/azure/search/search-get-started-python). Use this sample to learn service connections, index creation, data ingestion, and basic queries.
 
 ## 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 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 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.

Tutorial-AI-Enrichment/CONTRIBUTING.md

@@ -1,4 +1,4 @@
-# Contributing to the Python tutorial for AI enrichment in Azure Searh.
+# Contributing to Azure Cognitive Search samples
 
 This project welcomes contributions and suggestions.  Most contributions require you to agree to a
 Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us

Tutorial-AI-Enrichment/README.md

@@ -5,18 +5,18 @@ languages:
   - rest
 products:
   - azure
-  - azure-search
-name: Build a cognitive search AI-enriched pipeline
+  - cognitive-search
+name: Build an AI enrichment pipeline
 description: |
-  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.
+  Demonstrates AI enrichment using Cognitive Services in an Azure Cognitive Search indexing pipeline. Calls are made using REST APIs in Jupyter Python3 notebook.
 urlFragment: python-tutorial-cognitive-search
 ---
 
-# Get started with cognitive search AI enrichment in Azure Search
+# Get started with skillsets and AI enrichment in Azure Cognitive Search
 
-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.
+Demonstrates AI enrichment by building an 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 Cognitive Services APIs, such as entity recognition and language detection. It uses the REST APIs to make calls to Azure Cognitive Search, including index definition, data ingestion and AI enrichment, and query execution.
 
-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). 
+This sample is a Jupyter Python3 .ipynb file used in [Python Tutorial: Call Cognitive Services APIs in an enrichment pipeline](https://docs.microsoft.com/azure/search/cognitive-search-tutorial-blob-python). 
 
 ## Contents
 
@@ -32,8 +32,8 @@ This sample is a Jupyter Python3 .ipynb file used in [Python Tutorial: Call Cogn
 
 - [Anaconda 3.x](https://www.anaconda.com/distribution/#download-section) providing Python 3.x and Jupyter Notebooks
 - [Sample file set (mixed content types)](https://github.com/Azure-Samples/azure-search-sample-data/tree/master/mixedContent)
-- [Azure storage account](https://docs.microsoft.com/azure/storage/common/storage-quickstart-create-account) 
-- [Azure Search service](https://docs.microsoft.com/en-us/azure/search/search-create-service-portal)
+- [Azure Storage account](https://docs.microsoft.com/azure/storage/common/storage-quickstart-create-account) 
+- [Azure Cognitive Search service](https://docs.microsoft.com/en-us/azure/search/search-create-service-portal)
 
 ## Setup
 
@@ -43,7 +43,7 @@ This sample is a Jupyter Python3 .ipynb file used in [Python Tutorial: Call Cogn
 ## Running the sample
 1. On the Windows Start menu, select Anaconda3, and then select Jupyter Notebook.
 2. Open the PythonTutorial-AzureSearch-AIEnrichment.ipynb file in Jupyter Notebook.
-3. Replace <YOUR-SERVICE-NAME> and <YOUR-ADMIN-API-KEY> with the service and api-key details of your Azure Search service.
+3. Replace <YOUR-SERVICE-NAME> and <YOUR-ADMIN-API-KEY> with the service and api-key details of your search service.
 4. Replace <YOUR-BLOB-RESOURCE-CONNECTION-STRING> with a connection string to an Azure Blob storage resource that you created, and to which you uploaded [content files](https://github.com/Azure-Samples/azure-search-sample-data/tree/master/mixedContent) of various file types.
 5. Run each step individually.