Merge pull request #233108 from jboback/AnomalyDetectorMetadata

Anomaly Detector Metadata

Author: JamesJBarnett

articles/cognitive-services/Anomaly-Detector/How-to/prepare-data.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: conceptual
+ms.topic: how-to
 ms.date: 11/01/2022
 ms.author: mbullwin
 ---

articles/cognitive-services/Anomaly-Detector/How-to/streaming-inference.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: conceptual
+ms.topic: how-to
 ms.date: 11/01/2022
 ms.author: mbullwin
 ---

articles/cognitive-services/Anomaly-Detector/How-to/train-model.md

@@ -7,14 +7,14 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: conceptual
+ms.topic: how-to
 ms.date: 11/01/2022
 ms.author: mbullwin
 ---
 
 # Train a Multivariate Anomaly Detection model
 
-To test out Multivariate Anomaly Detection quickly, try the [Code Sample](https://github.com/Azure-Samples/AnomalyDetector)! For more instructions on how to run a jupyter notebook, please refer to [Install and Run a Jupyter Notebook](https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/install.html#).
+To test out Multivariate Anomaly Detection quickly, try the [Code Sample](https://github.com/Azure-Samples/AnomalyDetector)! For more instructions on how to run a Jupyter notebook, please refer to [Install and Run a Jupyter Notebook](https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/install.html#).
 
 ## API Overview
 
@@ -31,9 +31,9 @@ There are 7 APIs provided in Multivariate Anomaly Detection:
 | ------ | ---- | ----------- | ------ | 
 |**Train Model**| POST       |  `{endpoint}`/anomalydetector/v1.1/multivariate/models    |   Create and train a model          |
 |**Get Model Status**|     GET   |   `{endpoint}`anomalydetector/v1.1/multivariate/models/`{modelId}`   |     Get model status and model metadata with `modelId`   |
-|**Batch Inference**|    POST    |  `{endpoint}`/anomalydetector/v1.1/multivariate/models/`{modelId}`: detect-batch    |          Trigger an asynchronous inference with `modelId` which works in a batch scenario   |
+|**Batch Inference**|    POST    |  `{endpoint}`/anomalydetector/v1.1/multivariate/models/`{modelId}`: detect-batch    |          Trigger an asynchronous inference with `modelId`, which works in a batch scenario   |
 |**Get Batch Inference Results**|     GET   |  `{endpoint}`/anomalydetector/v1.1/multivariate/detect-batch/`{resultId}`    |       Get batch inference results with `resultId`      |
-|**Streaming Inference**|   POST     |   `{endpoint}`/anomalydetector/v1.1/multivariate/models/`{modelId}`: detect-last   |      Trigger a synchronous inference with `modelId` which works in a streaming scenario       |
+|**Streaming Inference**|   POST     |   `{endpoint}`/anomalydetector/v1.1/multivariate/models/`{modelId}`: detect-last   |      Trigger a synchronous inference with `modelId`, which works in a streaming scenario       |
 |**List Model**|     GET   |  `{endpoint}`/anomalydetector/v1.1/multivariate/models    |      List all models       |
 |**Delete Model**|     DELET   |  `{endpoint}`/anomalydetector/v1.1/multivariate/models/`{modelId}`    |     Delete model with `modelId`       |
 
@@ -141,7 +141,7 @@ Other parameters for training API are optional:
     | `Zero`       | Fill `nan` values with 0.                                                                           |
     | `Fixed`      | Fill `nan` values with a specified valid value that should be provided in `paddingValue`.          |
 
-* **paddingValue**: Padding value is used to fill `nan` when `fillNAMethod` is `Fixed` and must be provided in that case. In other cases it's optional.
+* **paddingValue**: Padding value is used to fill `nan` when `fillNAMethod` is `Fixed` and must be provided in that case. In other cases, it's optional.
 
 * **displayName**: This is an optional parameter, which is used to identify models. For example, you can use it to mark parameters, data sources, and any other metadata about the model and its input data. The default value is an empty string.
 
@@ -450,4 +450,4 @@ The response contains four fields, `models`, `currentCount`, `maxCount`, and `ne
 
 ## Next steps
 
-* [Best practices of multivariate anomaly detection](../concepts/best-practices-multivariate.md)
+* [Best practices of multivariate anomaly detection](../concepts/best-practices-multivariate.md)

articles/cognitive-services/Anomaly-Detector/concepts/anomaly-detection-best-practices.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: conceptual
+ms.topic: best-practice
 ms.custom: cogserv-non-critical-anomaly-detector
 ms.date: 01/22/2021
 ms.author: mbullwin

articles/cognitive-services/Anomaly-Detector/concepts/best-practices-multivariate.md

@@ -7,7 +7,7 @@ author: mrbullwinkle
 manager: nitinme
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: conceptual
+ms.topic: best-practice
 ms.date: 06/07/2022
 ms.custom: cogserv-non-critical-anomaly-detector
 ms.author: mbullwin

articles/cognitive-services/Anomaly-Detector/whats-new.md

@@ -3,20 +3,20 @@ title: What's New - Anomaly Detector
 description: This article is regularly updated with news about the Azure Cognitive Services Anomaly Detector.
 ms.service: cognitive-services
 ms.subservice: anomaly-detector
-ms.topic: overview
+ms.topic: whats-new
 ms.date: 12/15/2022
 ---
 
 # What's new in Anomaly Detector
 
 Learn what's new in the service. These items include release notes, videos, blog posts, papers, and other types of information. Bookmark this page to keep up to date with the service.
 
-We've also added links to some user-generated content. Those items will be marked with **[UGC]** tag. Some of them are hosted on websites that are external to Microsoft and Microsoft is not responsible for the content there. Use discretion when you refer to these resources. Contact [email protected] or raise an issue on GitHub if you'd like us to remove the content.
+We have also added links to some user-generated content. Those items will be marked with **[UGC]** tag. Some of them are hosted on websites that are external to Microsoft and Microsoft isn't responsible for the content there. Use discretion when you refer to these resources. Contact [email protected] or raise an issue on GitHub if you'd like us to remove the content.
 
 ## Release notes
 
 ### Jan 2023
-* Multivariate Anomaly Detection will begin charging as of January 10th, 2023. For pricing details see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/anomaly-detector/).
+* Multivariate Anomaly Detection will begin charging as of January 10th, 2023. For pricing details, see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/anomaly-detector/).
 
 ### Dec 2022
 * Multivariate Anomaly Detection SDK is updated to match with GA API for four languages.
@@ -36,7 +36,7 @@ We've also added links to some user-generated content. Those items will be marke
 
 ### June 2022
 
-* New blog released: [4 sets of best practices to use Multivariate Anomaly Detector when monitoring your equipment](https://techcommunity.microsoft.com/t5/ai-cognitive-services-blog/4-sets-of-best-practices-to-use-multivariate-anomaly-detector/ba-p/3490848#footerContent).
+* New blog released: [Four sets of best practices to use Multivariate Anomaly Detector when monitoring your equipment](https://techcommunity.microsoft.com/t5/ai-cognitive-services-blog/4-sets-of-best-practices-to-use-multivariate-anomaly-detector/ba-p/3490848#footerContent).
 
 ### May 2022