Merge pull request #109220 from diberry/diberry/0326-per-quickfix

[Cogsvcs] Personalizer - quick fix, create resource

Author: American-Dipper

articles/cognitive-services/personalizer/how-to-create-resource.md

@@ -2,7 +2,7 @@
 title: Create Personalizer resource
 description: Service configuration includes how the service treats rewards, how often the service explores, how often the model is retrained, and how much data is stored.
 ms.topic: conceptual
-ms.date: 02/19/2020
+ms.date: 03/26/2020
 ---
 
 # Create a Personalizer resource
@@ -24,28 +24,32 @@ Create a Personalizer resource for each feedback loop.
 
 1. Select **Create** to create the resource.
 
-1. Once your resource has deployed, select the **Go to Resource** button to go to your Personalizer resource. Go to the **Configuration** page for the new resource to [configure the learning loop](how-to-settings.md).
+1. After your resource has deployed, select the **Go to Resource** button to go to your Personalizer resource.
+
+1. Select the **Quick start** page for your resource, then copy the values for your endpoint and key. You need both the resource endpoint and key to use the Rank and Reward APIs.
+
+1. Select the **Configuration** page for the new resource to [configure the learning loop](how-to-settings.md).
 
 ## Create a resource with the Azure CLI
 
 1. Sign in to the Azure CLI with the following command:
 
-    ```bash
+    ```azurecli-interactive
     az login
     ```
 
 1. Create a resource group, a logical grouping to manage all Azure resources you intend to use with the Personalizer resource.
 
 
-    ```bash
+    ```azurecli-interactive
     az group create \
         --name your-personalizer-resource-group \
         --location westus2
     ```
 
 1. Create a new Personalizer resource, _learning loop_, with the following command for an existing resource group.
 
-    ```bash
+    ```azurecli-interactive
     az cognitiveservices account create \
         --name your-personalizer-learning-loop \
         --resource-group your-personalizer-resource-group \
@@ -54,6 +58,19 @@ Create a Personalizer resource for each feedback loop.
         --location westus2 \
         --yes
     ```
+
+    This returns a JSON object, which includes your **resource endpoint**.
+
+1. Use the following Azure CLI command to get your **resource key**.
+
+    ```azurecli-interactive
+        az cognitiveservices account keys list \
+        --name your-personalizer-learning-loop \
+        --resource-group your-personalizer-resource-group
+    ```
+
+    You need both the resource endpoint and key to use the Rank and Reward APIs.
+
 ## Next steps
 
 * [Configure](how-to-settings.md) Personalizer learning loop

articles/cognitive-services/personalizer/troubleshooting.md

@@ -57,7 +57,7 @@ If you are unsure about how your learning loop is currently behaving, run an [of
 
 **Answer**: Personalizer returns the same probabilities in a Rank API result when it has just started and has an _empty_ model, or when you reset the Personalizer Loop, and your model is still within your **Model update frequency** period.
 
-When the new update period begins, the updated model is used, and you’ll see the probabilities change.
+When the new update period begins, the updated model is used, and you'll see the probabilities change.
 
 </details>
 
@@ -88,7 +88,7 @@ When the new update period begins, the updated model is used, and you’ll see t
 </details>
 
 <details>
-<summary><b>I created an offline evaluation and it succeeded almost instantly. Why is that? I don’t see any results?</b></summary>
+<summary><b>I created an offline evaluation and it succeeded almost instantly. Why is that? I don't see any results?</b></summary>
 
 **Answer**: The offline evaluation uses the trained model data from the events in that time period. If you did not send any data in the time period between start and end time of the evaluation, it will complete without any results. Submit a new offline evaluation by selecting a time range with events you know were sent to Personalizer.