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[!INCLUDE [Create a Cognitive Services Anomaly Detector resource](../includes/create-anomaly-detector-resource.md)]
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[!INCLUDE [Create an Anomaly Detector container on Azure Container Instances](../../containers/includes/create-container-instances-resource-from-azure-cli.md)]
For a full description of available tags, such as `latest` used in the preceding command, see [anomaly-detector](https://go.microsoft.com/fwlink/?linkid=2083827&clcid=0x409) on Docker Hub.
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### Docker pull for the Anomaly Detector container
Copy file name to clipboardExpand all lines: articles/cognitive-services/LUIS/luis-container-limitations.md
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@@ -18,7 +18,7 @@ The LUIS containers have a few notable limitations. From unsupported dependencie
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## Supported dependencies for `latest` container
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The latest LUIS container, released at [//build/ 2019](https://news.microsoft.com/build2019/), will support:
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The latest LUIS container supports:
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*[New prebuilt domains](luis-reference-prebuilt-domains.md): these enterprise-focused domains include entities, example utterances, and patterns. Extend these domains for your own use.
Copy file name to clipboardExpand all lines: articles/cognitive-services/Speech-Service/speech-container-howto.md
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@@ -8,7 +8,7 @@ manager: nitinme
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ms.service: cognitive-services
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ms.subservice: speech-service
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ms.topic: conceptual
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ms.date: 04/29/2020
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ms.date: 05/05/2020
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ms.author: aahi
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---
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## Request access to the container registry
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Fill out and submit the [Cognitive Services Speech Containers Request form](https://aka.ms/speechcontainerspreview/) to request access to the container.
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Fill out and submit the [Cognitive Services containers request form](https://aka.ms/cognitivegate) to request access to the container.
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[!INCLUDE [Request access to the container registry](../../../includes/cognitive-services-containers-request-access-only.md)]
Copy file name to clipboardExpand all lines: articles/cognitive-services/cognitive-services-container-support.md
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ms.custom: seodec18
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ms.service: cognitive-services
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ms.topic: article
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ms.date: 04/01/2020
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ms.date: 05/07/2020
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ms.author: aahi
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#As a potential customer, I want to know more about how Cognitive Services provides and supports Docker containers for each service.
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Azure Cognitive Services containers provide the following set of Docker containers, each of which contains a subset of functionality from services in Azure Cognitive Services:
|[Anomaly detector][ad-containers]|F0, S0|**Anomaly-Detector**|The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning.<br>[Request access](https://aka.ms/adcontainer)|
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|[Computer Vision][cv-containers]|F0, S1|**Read**|Extracts printed text from images of various objects with different surfaces and backgrounds, such as receipts, posters, and business cards. The Read container also detects *handwritten text* in images and provides PDF/TIFF/multi-page support.<br/><br/>**Important:** The Read container currently works only with English.|
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|[Face][fa-containers]|F0, S0|**Face**|Detects human faces in images, and identifies attributes, including face landmarks (such as noses and eyes), gender, age, and other machine-predicted facial features. In addition to detection, Face can check if two faces in the same image or different images are the same by using a confidence score, or compare faces against a database to see if a similar-looking or identical face already exists. It can also organize similar faces into groups, using shared visual traits.<br>[Request access](Face/face-how-to-install-containers.md#request-access-to-the-private-container-registry)|
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|[Form recognizer][fr-containers]|F0, S0|**Form Recognizer**|Form Understanding applies machine learning technology to identify and extract key-value pairs and tables from forms.<br>[Request access](https://aka.ms/FormRecognizerContainerRequestAccess)|
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|[LUIS][lu-containers]|F0, S0|**LUIS** ([image](https://go.microsoft.com/fwlink/?linkid=2043204&clcid=0x409))|Loads a trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints. You can collect query logs from the container and upload these back to the [LUIS portal](https://www.luis.ai) to improve the app's prediction accuracy.|
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|[Speech Service API][sp-containers-stt]|F0, S0|**Speech-to-text**|Transcribes continuous real-time speech into text.|
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|[Speech Service API][sp-containers-cstt]|F0, S0|**Custom Speech-to-text**|Transcribes continuous real-time speech into text using a custom model.|
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|[Speech Service API][sp-containers-tts]|F0, S0|**Text-to-speech**|Converts text to natural-sounding speech.|
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|[Speech Service API][sp-containers-ctts]|F0, S0|**Custom Text-to-speech**|Converts text to natural-sounding speech using a custom model.|
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|[Text Analytics][ta-containers-keyphrase]|F0, S|**Key Phrase Extraction** ([image](https://go.microsoft.com/fwlink/?linkid=2018757&clcid=0x409)) |Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". |
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|[Text Analytics][ta-containers-language]|F0, S|**Language Detection** ([image](https://go.microsoft.com/fwlink/?linkid=2018759&clcid=0x409)) |For up to 120 languages, detects which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score. |
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|[Text Analytics][ta-containers-sentiment]|F0, S|**Sentiment Analysis** ([image](https://go.microsoft.com/fwlink/?linkid=2018654&clcid=0x409)) |Analyzes raw text for clues about positive or negative sentiment. This API returns a sentiment score between 0 and 1 for each document, where 1 is the most positive. The analysis models are pre-trained using an extensive body of text and natural language technologies from Microsoft. For [selected languages](./text-analytics/language-support.md), the API can analyze and score any raw text that you provide, directly returning results to the calling application. |
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|--|--|--|--|
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|[Anomaly detector][ad-containers]|F0, S0|**Anomaly-Detector**|The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning.<br>[Request access][request-access]|
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|[Computer Vision][cv-containers]|F0, S1|**Read**|Extracts printed text from images of various objects with different surfaces and backgrounds, such as receipts, posters, and business cards. The Read container also detects *handwritten text* in images and provides PDF/TIFF/multi-page support.<br/><br/>**Important:** The Read container currently works only with English.|
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|[Face][fa-containers]|F0, S0|**Face**|Detects human faces in images, and identifies attributes, including face landmarks (such as noses and eyes), gender, age, and other machine-predicted facial features. In addition to detection, Face can check if two faces in the same image or different images are the same by using a confidence score, or compare faces against a database to see if a similar-looking or identical face already exists. It can also organize similar faces into groups, using shared visual traits.<br>[Request access][request-access]|
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|[Form recognizer][fr-containers]|F0, S0|**Form Recognizer**|Form Understanding applies machine learning technology to identify and extract key-value pairs and tables from forms.<br>[Request access][request-access]|
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|[LUIS][lu-containers]|F0, S0|**LUIS** ([image](https://go.microsoft.com/fwlink/?linkid=2043204&clcid=0x409))|Loads a trained or published Language Understanding model, also known as a LUIS app, into a docker container and provides access to the query predictions from the container's API endpoints. You can collect query logs from the container and upload these back to the [LUIS portal](https://www.luis.ai) to improve the app's prediction accuracy.|
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|[Speech Service API][sp-containers-stt]|F0, S0|**Speech-to-text**|Transcribes continuous real-time speech into text.|
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|[Speech Service API][sp-containers-cstt]|F0, S0|**Custom Speech-to-text**|Transcribes continuous real-time speech into text using a custom model.|
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|[Speech Service API][sp-containers-tts]|F0, S0|**Text-to-speech**|Converts text to natural-sounding speech.|
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|[Speech Service API][sp-containers-ctts]|F0, S0|**Custom Text-to-speech**|Converts text to natural-sounding speech using a custom model.|
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|[Text Analytics][ta-containers-keyphrase]|F0, S|**Key Phrase Extraction** ([image](https://go.microsoft.com/fwlink/?linkid=2018757&clcid=0x409)) |Extracts key phrases to identify the main points. For example, for the input text "The food was delicious and there were wonderful staff", the API returns the main talking points: "food" and "wonderful staff". |
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|[Text Analytics][ta-containers-language]|F0, S|**Language Detection** ([image](https://go.microsoft.com/fwlink/?linkid=2018759&clcid=0x409)) |For up to 120 languages, detects which language the input text is written in and report a single language code for every document submitted on the request. The language code is paired with a score indicating the strength of the score. |
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|[Text Analytics][ta-containers-sentiment]|F0, S|**Sentiment Analysis v3** ([image](https://go.microsoft.com/fwlink/?linkid=2018654&clcid=0x409)) |Analyzes raw text for clues about positive or negative sentiment. This version of sentiment analysis returns sentiment labels (for example *positive* or *negative*) for each document and sentence within it. |
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<!--
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|[Personalizer](https://go.microsoft.com/fwlink/?linkid=2083923&clcid=0x409) |F0, S0|**Personalizer** ([image](https://go.microsoft.com/fwlink/?linkid=2083928&clcid=0x409))|Azure Personalizer is a cloud-based API service that allows you to choose the best experience to show to your users, learning from their real-time behavior.|
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Azure Cognitive Services containers are publicly available through your Azure subscription, and Docker container images can be pulled from either the Microsoft Container Registry or Docker Hub. You can use the [docker pull](https://docs.docker.com/engine/reference/commandline/pull/) command to download a container image from the appropriate registry.
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> [!IMPORTANT]
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> Currently, you must complete a sign-up process to access the following containers, in which you fill out and submit a questionnaire with questions about you, your company, and the use case for which you want to implement the containers. Once you're granted access and provided credentials, you can then pull the container images from a private container registry hosted by Azure Container Registry.
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