Merge pull request #177643 from aahill/ref-links

project creation to how-to, service limits updates

Author: v-shils

articles/cognitive-services/language-service/custom-classification/faq.md

@@ -24,7 +24,7 @@ Generally, diverse and representative [tagged data](how-to/tag-data.md) leads to
 
 ## What are the service limits?
 
-See the [service limits article](concepts/data-limits.md) for more information.
+See the [service limits article](service-limits.md) for more information.
 
 ## What to do if my model scores poorly?
 

articles/cognitive-services/language-service/custom-classification/definitions.md renamed to articles/cognitive-services/language-service/custom-classification/glossary.md

@@ -21,7 +21,7 @@ Learn about definitions used in custom text classification.
 
 A project is a work area for building your custom AI models based on your data. Your project can only be accessed by you and others who have contributor access to the Azure resource being used.
 As a prerequisite to creating a Custom text classification project, you have to [connect your resource to a storage account](how-to/create-project.md).
-As part of the project creation flow, you need connect it to a blob container where you have uploaded your dataset. Your project automatically includes all the `.txt` files available in your container. You can have multiple models within your project all built on the same dataset. See the [service limits](concepts/data-limits.md) article for more information.
+As part of the project creation flow, you need connect it to a blob container where you have uploaded your dataset. Your project automatically includes all the `.txt` files available in your container. You can have multiple models within your project all built on the same dataset. See the [service limits](service-limits.md) article for more information.
 
 Within your project you can do the following operations:
 

articles/cognitive-services/language-service/custom-classification/how-to/create-project.md

@@ -1,5 +1,5 @@
 ---
-title: Using Azure resources in custom classification 
+title: How to create custom text classification projects
 titleSuffix: Azure Cognitive Services
 description: Learn about the steps for using Azure resources with custom classification.
 services: cognitive-services
@@ -13,7 +13,7 @@ ms.author: aahi
 ms.custom: "language-service-custom-classification, references_regions"
 ---
 
-# Text classification project requirements
+# How to create custom text classification projects
 
 Use this article to learn how to set up these requirements and create a project. 
 
@@ -142,10 +142,7 @@ To set proper roles on your storage account:
 
 ## Create a project
 
-Once your Azure resource and storage account are configured, you can create a project, using the [Language studio](../quickstart.md?pivots=language-studio#create-a-custom-classification-project) or [REST API](../quickstart.md?pivots=rest-api#create-project).
-
->[!NOTE]
-> If your dataset contains files of different languages or if you expect different languages during runtime, you can enable the multi-lingual option.
+[!INCLUDE [Language Studio project creation](../includes/create-project.md)]
 
 ## Next steps
 

articles/cognitive-services/language-service/custom-classification/includes/create-project.md

@@ -0,0 +1,32 @@
+---
+author: aahill
+manager: nitinme
+ms.service: cognitive-services
+ms.subservice: language-service
+ms.topic: include
+ms.date: 11/02/2021
+ms.author: aahi 
+---
+
+Once your resource and storage container are configured, create a new text classification project. A project is a work area for building your custom AI models based on your data. Your project can only be accessed by you and others who have contributor access to the Azure resource being used.
+
+1. Log in to [Language Studio](https://aka.ms/languageStudio). A window will appear to let you select your subscription and Language resource. Select the resource you created in the above step.
+
+2. Under the **Classify text** section of Language Studio, select **custom text classification** from the available services, and select it.
+
+3. Select **Create new project** from the top menu in your projects page. Creating a project will let you tag data, train, evaluate, improve, and deploy your models. 
+
+    :::image type="content" source="../media/create-project.png" alt-text="A screenshot of the project creation page." lightbox="../media/create-project.png":::
+
+4. If you have created your resource using the steps above, you will need to add information about your project, like a name, and select your storage container.
+
+    1. Select your project type. For this quickstart, we will create a multi label classification project. Then click **Next**.
+
+    2. Enter the project information, including a name, description, and the language of the files in your project. You will not be able to change the name of your project later.
+
+        >[!TIP]
+        > Your dataset doesn't have to be entirely in the same language. You can have multiple files, each with different supported languages. If your dataset contains files of different languages or if you expect different languages during runtime, select **enable multi-lingual dataset** when you enter the basic information for your project.
+
+    3. Select the container where you have uploaded your data. For this quickstart, we will use the existing tags file available in the container. Then click **Next**.
+ 
+    4. Review the data you entered and select **Create Project**.

articles/cognitive-services/language-service/custom-classification/includes/quickstarts/language-studio.md

@@ -52,32 +52,8 @@ The provided sample dataset contains around 200 movie summaries that belong to o
 
 ## Create a custom classification project
 
-Once your resource and storage container are configured, create a new text classification project. A project is a work area for building your custom AI models based on your data. Your project can only be accessed by you and others who have contributor access to the Azure resource being used.
+[!INCLUDE [Language Studio project creation](../create-project.md)]
 
-1. Log in to [Language Studio](https://aka.ms/languageStudio). A window will appear to let you select your subscription and Language resource. Select the resource you created in the above step.
-
-2. Under the **Classify text** section of Language Studio, select **custom text classification** from the available services, and select it.
-
-3. Select **Create new project** from the top menu in your projects page. Creating a project will let you tag data, train, evaluate, improve, and deploy your models. 
-
-    :::image type="content" source="../../media/create-project.png" alt-text="A screenshot of the project creation page." lightbox="../../media/create-project.png":::
-<!--
-4. If you have created your resource using the steps above, the **Connect storage** step will be completed already. You only need to do this step once for each resource you use and it is irreversible. If you connect a storage account to your resource, you cannot disconnect it later.
-
-    :::image type="content" source="../../../custom-named-entity-recognition/media/connect-storage.png" alt-text="A screenshot showing the storage connection screen." lightbox="../../../custom-named-entity-recognition/media/connect-storage.png":::
--->
-4. If you have created your resource using the steps above, you will need to add information about your project, like a name, and select your storage container.
-
-    1. Select your project type. For this quickstart, we will create a multi label classification project. Then click **Next**.
-
-    2. Enter the project information, including a name, description, and the language of the files in your project. You will not be able to change the name of your project later.
-
-        >[!TIP]
-        > Your dataset doesn't have to be entirely in the same language. You can have multiple files, each with different supported languages. If your dataset contains files of different languages or if you expect different languages during runtime, select **enable multi-lingual dataset** when you enter the basic information for your project.
-
-    3. Select the container where you have uploaded your data. For this quickstart, we will use the existing tags file available in the container. Then click **Next**.
- 
-    4. Review the data you entered and select **Create Project**.
 
 ## Train your model
 

articles/cognitive-services/language-service/custom-classification/language-support.md

@@ -41,4 +41,4 @@ Custom text classification supports `.txt` files in the following languages:
 ## Next steps
 
 * [Custom text classification overview](overview.md)
-* [Data limits](concepts/data-limits.md)
+* [Data limits](service-limits.md)

articles/cognitive-services/language-service/custom-classification/overview.md

@@ -58,6 +58,8 @@ Follow these steps to get the most out of your model:
 
 ## Next steps
 
-* Use the [quickstart article](quickstart.md) to start sending requests using Language Studio.  
+* Use the [quickstart article](quickstart.md) to start using custom text classification.  
 
-* As you go through the application development lifecycle, review the [glossary](definitions.md) to learn more about the terms used throughout the documentation for this feature. 
+* As you go through the application development lifecycle, review the [glossary](glossary.md) to learn more about the terms used throughout the documentation for this feature. 
+
+* Remember to view the [service limits](service-limits.md) for information such as [regional availability](service-limits.md#regional-availability).

articles/cognitive-services/language-service/custom-classification/concepts/data-limits.md renamed to articles/cognitive-services/language-service/custom-classification/service-limits.md

@@ -10,7 +10,7 @@ ms.subservice: language-service
 ms.topic: overview
 ms.date: 11/02/2021
 ms.author: aahi 
-ms.custom: language-service-custom-classification
+ms.custom: "language-service-custom-classification, references_regions"
 ---
 
 # Custom text classification limits
@@ -25,7 +25,7 @@ Use this article to learn about the data and rate limits when using custom text
 
 * All files should be available at the root of your container.
 
-* Your [training dataset](../how-to/train-model.md#data-splits) should include at least 10 files and no more than 1,000,000 files.
+* Your [training dataset](how-to/train-model.md#data-splits) should include at least 10 files and no more than 1,000,000 files.
 
 ## API limits
 
@@ -50,6 +50,12 @@ Use this article to learn about the data and rate limits when using custom text
 
 * Project names have to be unique within the same resource, across both the custom Named Entity Recognition (NER) and custom text classification features.
 
+## Regional availability 
+
+Custom text classification is only available select Azure regions. When you create an [Azure resource](how-to/create-project.md), it must be deployed into one of the following regions:
+* **West US 2**
+* **West Europe**
+
 ## Project limits
 
 * You can only connect 1 storage container for each project. This process is irreversible, if you connect a container to your project you can't disconnect it later.

articles/cognitive-services/language-service/custom-named-entity-recognition/faq.md

@@ -24,7 +24,7 @@ Generally, diverse and representative [tagged data](how-to/tag-data.md) leads to
 
 ## What are the service limits?
 
-See the [service limits article](limits.md) for more information.
+See the [service limits article](service-limits.md) for more information.
 
 ## What to do if my model scores poorly?
 

articles/cognitive-services/language-service/custom-named-entity-recognition/glossary.md

@@ -53,5 +53,5 @@ For example, in the sentence "*John borrowed 25,000 USD from Fred.*" the entitie
 
 ## Next steps
 
-* [Data and service limits](limits.md).
+* [Data and service limits](service-limits.md).
 * [Custom NER overview](../overview.md).