Merge branch 'master' of https://github.com/MicrosoftDocs/azure-docs-pr into quickstarts1

Author: v-thepet

articles/active-directory-b2c/tutorial-register-applications.md

@@ -84,7 +84,7 @@ Once the application registration is complete, enable the implicit grant flow:
 
 ## Create a client secret
 
-If your application exchanges a code for a token, you need to create an application secret.
+If your application exchanges an authorization code for an access token, you need to create an application secret.
 
 #### [Applications](#tab/applications/)
 

articles/azure-databricks/TOC.yml

@@ -1682,6 +1682,9 @@
           - name: Databricks Runtime 6.3 ML
             href: /azure/databricks/release-notes/runtime/6.3ml
             maintainContext: true
+          - name: Databricks Runtime 6.3 Genomics
+            href: /azure/databricks/release-notes/runtime/6.3genomics
+            maintainContext: true
           - name: Databricks Runtime 6.2
             href: /azure/databricks/release-notes/runtime/6.2
             maintainContext: true

articles/azure-functions/functions-reference-node.md

@@ -228,7 +228,7 @@ You can choose to define output binding data using the `context.done` method ins
 context.bindingData
 ```
 
-Returns a named object that contains trigger metadata and function invocation data (`invocationId`, `sys.methodName`, `sys.utcNow`, `sys.randGuid`). For an example of trigger metadata, see this [event hubs example](functions-bindings-event-hubs.md#trigger---javascript-example).
+Returns a named object that contains trigger metadata and function invocation data (`invocationId`, `sys.methodName`, `sys.utcNow`, `sys.randGuid`). For an example of trigger metadata, see this [event hubs example](functions-bindings-event-hubs.md#trigger).
 
 ### context.done method
 

articles/azure-resource-manager/management/resources-without-resource-group-limit.md

@@ -2,7 +2,7 @@
 title: Resources without 800 count limit
 description: Lists the Azure resource types that can have more than 800 instances in a resource group.
 ms.topic: conceptual
-ms.date: 11/07/2019
+ms.date: 01/23/2020
 ---
 
 # Resources not limited to 800 instances per resource group
@@ -21,6 +21,7 @@ For some resource types, you need to contact support to have the 800 instance li
 * registrations
 * registrations/customerSubscriptions
 * registrations/products
+* verificationKeys
 
 ## Microsoft.BotService
 
@@ -77,6 +78,7 @@ For some resource types, you need to contact support to have the 800 instance li
 
 ## Microsoft.GuestConfiguration
 
+* autoManagedVmConfigurationProfiles
 * configurationProfileAssignments
 * guestConfigurationAssignments
 * software
@@ -173,6 +175,10 @@ For some resource types, you need to contact support to have the 800 instance li
 * apiManagementAccounts/apis
 * sites
 
+## microsoft.insights
+
+* metricalerts
+
 ## Next steps
 
-For a complete list of quotas and limits, see [Azure subscription and service limits, quotas, and constraints](../../azure-resource-manager/management/azure-subscription-service-limits.md).
+For a complete list of quotas and limits, see [Azure subscription and service limits, quotas, and constraints](azure-subscription-service-limits.md).

articles/cognitive-services/LUIS/luis-concept-review-endpoint-utterances.md

@@ -9,30 +9,34 @@ ms.custom: seodec18
 ms.service: cognitive-services
 ms.subservice: language-understanding
 ms.topic: conceptual
-ms.date: 10/10/2019
+ms.date: 01/23/2020
 ms.author: diberry
 ---
 # Concepts for enabling active learning by reviewing endpoint utterances
 Active learning is one of three strategies to improve prediction accuracy and the easiest to implement. With active learning, your review endpoint utterances for correct intent and entity. LUIS chooses endpoint utterances it is unsure of.
 
 ## What is active learning
-Active learning is a two-step process. First, LUIS selects utterances it receives at the app's endpoint that need validation. The second step is performed by the app owner or collaborator to validate the selected utterances for [review](luis-how-to-review-endpoint-utterances.md), including the correct intent and any entities within the intent. After reviewing the utterances, train and publish the app again. 
+Active learning is a two-step process. First, LUIS selects utterances it receives at the app's endpoint that need validation. The second step is performed by the app owner or collaborator to validate the selected utterances for [review](luis-how-to-review-endpoint-utterances.md), including the correct intent and any entities within the intent. After reviewing the utterances, train and publish the app again.
 
 ## Which utterances are on the review list
-LUIS adds utterances to the review list when the top firing intent has a low score or the top two intents' scores are too close. 
+LUIS adds utterances to the review list when the top firing intent has a low score or the top two intents' scores are too close.
 
 ## Single pool for utterances per app
-The **Review endpoint utterances** list doesn't change based on the version. There is a single pool of utterances to review, regardless of which version the utterance you are actively editing or which version of the app was published at the endpoint. 
+The **Review endpoint utterances** list doesn't change based on the version. There is a single pool of utterances to review, regardless of which version the utterance you are actively editing or which version of the app was published at the endpoint.
 
 ## Where are the utterances from
-Endpoint utterances are taken from end-user queries on the application’s HTTP endpoint. If your app is not published or has not received hits yet, you do not have any utterances to review. If no endpoint hits are received for a specific intent or entity, you do not have utterances to review that contain them. 
+Endpoint utterances are taken from end-user queries on the application’s HTTP endpoint. If your app is not published or has not received hits yet, you do not have any utterances to review. If no endpoint hits are received for a specific intent or entity, you do not have utterances to review that contain them.
 
 ## Schedule review periodically
-Reviewing suggested utterances doesn't need to be done every day but should be part of your regular maintenance of LUIS. 
+Reviewing suggested utterances doesn't need to be done every day but should be part of your regular maintenance of LUIS.
 
 ## Delete review items programmatically
 Use the **[delete unlabeled utterances](https://westus.dev.cognitive.microsoft.com/docs/services/5890b47c39e2bb17b84a55ff/operations/58b6f32139e2bb139ce823c9)** API. Back up these utterances before deletion by **[exporting the log files](https://westus.dev.cognitive.microsoft.com/docs/services/5890b47c39e2bb17b84a55ff/operations/5890b47c39e2bb052c5b9c36)**.
 
+## Enable active learning
+
+To enable active learning, you must log user queries. This is accomplished by calling the [endpoint query](luis-get-started-create-app.md#query-the-v3-api-prediction-endpoint) with the `log=true` querystring parameter and value.
+
 ## Next steps
 
 * Learn how to [review](luis-how-to-review-endpoint-utterances.md) endpoint utterances

articles/cognitive-services/LUIS/luis-how-to-review-endpoint-utterances.md

@@ -9,7 +9,7 @@ ms.custom: seodec18
 ms.service: cognitive-services
 ms.subservice: language-understanding
 ms.topic: conceptual
-ms.date: 12/17/2019
+ms.date: 01/23/2020
 ms.author: diberry
 ---
 

articles/cosmos-db/how-to-use-stored-procedures-triggers-udfs.md

@@ -125,6 +125,7 @@ asyncClient.executeStoredProcedure(sprocLink, requestOptions, storedProcedureArg
         successfulCompletionLatch.countDown();
         System.out.println(storedProcedureResponse.getActivityId());
     }, error -> {
+        successfulCompletionLatch.countDown();
         System.err.println("an error occurred while executing the stored procedure: actual cause: "
                 + error.getMessage());
     });

articles/industry/agriculture/get-sensor-data-from-sensor-partner.md

@@ -67,8 +67,13 @@ You can generate the above information by following these steps: (Please note th
 
 ### Integrate device data by using the generated credentials
 
-Go to the device partner portal to link FarmBeats by using the set of credentials you generated in the previous section:
+Go to the device partner portal to link FarmBeats. Currently the following device partners are supported:
 
+1. [Davis Instruments](https://weatherlink.github.io/azure-farmbeats/setup)
+2. [Teralytic](https://app.teralytic.com/login)
+3. [Pessl Instruments](https://ng.fieldclimate.com/user-api-services)
+
+You will need to provide the following information which you have generated in the previous section:
  - API endpoint
  - EventHub connection string
  - Client ID

articles/industry/agriculture/ingest-historical-telemetry-data-in-azure-farmbeats.md

@@ -67,7 +67,7 @@ Follow these steps.
 
  Now that you have the required credentials, you can define the device and sensors. To do this, create the metadata by calling FarmBeats APIs. Please note you will need to call the APIs as the client app that you created in the above section
 
- FarmBeats Datahub has the following APIs that enable creation and management of device or sensor metadata.
+ FarmBeats Datahub has the following APIs that enable creation and management of device or sensor metadata. Please note that as a partner you have access to only read, create and update the metadata; **Delete is not allowed by a partner.**
 
 - /**DeviceModel**: DeviceModel corresponds to the metadata of the device, such as the manufacturer and the type of device, which is either a gateway or a node.
 - /**Device**: Device corresponds to a physical device present on the farm.
@@ -379,6 +379,41 @@ Here's an example of a telemetry message:
 }
 ```
 
+## Troubleshooting
+
+### Can't view telemetry data after ingesting historical/streaming data from your sensors
+
+**Symptom**: Devices or sensors are deployed, and you've created the devices/sensors on FarmBeats and ingested telemetry to the EventHub, but you can't get or view telemetry data on FarmBeats.
+
+**Corrective action**:
+
+1. Ensure you have done the partner registration correctly - you can check this by going to your datahub swagger, navigate to /Partner API, Do a Get and check if the partner is registered. If not, please follow the [steps here](get-sensor-data-from-sensor-partner.md#enable-device-integration-with-farmbeats) to add partner.
+2. Ensure that you have created the metadata (DeviceModel, Device, SensorModel, Sensor) using the partner client credentials.
+3. Ensure that you have used the correct Telemetry message format (as specified below):
+
+```json
+{
+"deviceid": "<id of the Device created>",
+"timestamp": "<timestamp in ISO 8601 format>",
+"version" : "1",
+"sensors": [
+    {
+      "id": "<id of the sensor created>",
+      "sensordata": [
+        {
+          "timestamp": "< timestamp in ISO 8601 format >",
+          "<sensor measure name (as defined in the Sensor Model)>": <value>
+        },
+        {
+          "timestamp": "<timestamp in ISO 8601 format>",
+          "<sensor measure name (as defined in the Sensor Model)>": <value>
+        }
+      ]
+    }
+ ]
+}
+```
+
 
 ## Next steps
 

articles/machine-learning/team-data-science-process/agile-development.md

@@ -2,12 +2,12 @@
 title: Agile development of data science projects - Team Data Science Process
 description: Execute a data science project in a systematic, version controlled, and collaborative way within a project team by using the Team Data Science Process.
 author: marktab
-manager: cgronlun
-editor: cgronlun
+manager: marktab
+editor: marktab
 ms.service: machine-learning
 ms.subservice: team-data-science-process
 ms.topic: article
-ms.date: 09/05/2019
+ms.date: 01/10/2020
 ms.author: tdsp
 ms.custom: seodec18, previous-author=deguhath, previous-ms.author=deguhath
 ---
@@ -82,13 +82,13 @@ After your project and project code repository are created, you can add a Featur
 
    You can also link the Feature to the project's Azure Repos code repository by selecting **Add link** under the **Development** section. 
 
-   After you finish editing the Feature, select **Save & Close**.
+   After you edit the Feature, select **Save & Close**.
 
    ![Edit Feature and select Save & Close](./media/agile-development/3a-add-link-repo.png)
 
 ## <a name='AddStoryunderfeature-4'></a>Add a User Story to the Feature 
 
-Under the Feature, you can add User Stories to describe major steps needed to finish the project. 
+Under the Feature, you can add User Stories to describe major steps needed to complete the project. 
 
 To add a new User Story to a Feature: