1704856, incorporated SME feedback.

Author: john-par

articles/machine-learning/team-data-science-process/apps-anomaly-detection-api.md

@@ -19,7 +19,7 @@ ms.custom: seodec18, previous-author=alokkirpal, previous-ms.author=alok
 > This item is under maintenance. We encourage you to use the [Anomaly Detector API service](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) powered by a gallery of Machine Learning algorithms under Azure Cognitive Services to detect anomalies from business, operational, and IoT metrics.
 
 ## Overview
-[Anomaly Detection API](https://gallery.cortanaintelligence.com/MachineLearningAPI/Anomaly-Detection-2) is an example built with Azure Machine Learning that detects anomalies in time series data with numerical values that are uniformly spaced in time.
+[Anomaly Detection API](https://gallery.azure.ai/MachineLearningAPI/Anomaly-Detection-2) is an example built with Azure Machine Learning that detects anomalies in time series data with numerical values that are uniformly spaced in time.
 
 This API can detect the following types of anomalous patterns in time series data:
 
@@ -34,14 +34,14 @@ The Anomaly Detection offering comes with useful tools to get you started.
 * The [web application](https://anomalydetection-aml.azurewebsites.net/) helps you evaluate and visualize the results of anomaly detection APIs on your data.
 
 > [!NOTE]
-> Try **IT Anomaly Insights solution** powered by [this API](https://gallery.cortanaintelligence.com/MachineLearningAPI/Anomaly-Detection-2)
+> Try **IT Anomaly Insights solution** powered by [this API](https://gallery.azure.ai/MachineLearningAPI/Anomaly-Detection-2)
 >
 <!-- This Solution is no longer available
 > To get this end to end solution deployed to your Azure subscription <a href="https://gallery.cortanaintelligence.com/Solution/Anomaly-Detection-Pre-Configured-Solution-1" target="_blank">**Start here >**</a>
 -->
 
 ## API Deployment
-In order to use the API, you must deploy it to your Azure subscription where it will be hosted as an Azure Machine Learning web service.  You can do this from the [Azure AI Gallery](https://gallery.cortanaintelligence.com/MachineLearningAPI/Anomaly-Detection-2).  This will deploy two Azure Machine Learning Studio (classic) Web Services (and their related resources) to your Azure subscription - one for anomaly detection with seasonality detection, and one without seasonality detection.  Once the deployment has completed, you will be able to manage your APIs from the [Azure Machine Learning Studio (classic) web services](https://services.azureml.net/webservices/) page.  From this page, you will be able to find your endpoint locations, API keys, as well as sample code for calling the API.  More detailed instructions are available [here](/azure/machine-learning/studio/manage-new-webservice).
+In order to use the API, you must deploy it to your Azure subscription where it will be hosted as an Azure Machine Learning web service.  You can do this from the [Azure AI Gallery](https://gallery.azure.ai/MachineLearningAPI/Anomaly-Detection-2).  This will deploy two Azure Machine Learning Studio (classic) Web Services (and their related resources) to your Azure subscription - one for anomaly detection with seasonality detection, and one without seasonality detection.  Once the deployment has completed, you will be able to manage your APIs from the [Azure Machine Learning Studio (classic) web services](https://services.azureml.net/webservices/) page.  From this page, you will be able to find your endpoint locations, API keys, as well as sample code for calling the API.  More detailed instructions are available [here](/azure/machine-learning/studio/manage-new-webservice).
 
 ## Scaling the API
 By default, your deployment will have a free Dev/Test billing plan that includes 1,000 transactions/month and 2 compute hours/month.  You can upgrade to another plan as per your needs.  Details on the pricing of different plans are available [here](https://azure.microsoft.com/pricing/details/machine-learning/) under "Production Web API pricing".