fixes

Author: aahill

articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/language-studio/deploy-model.md

@@ -16,14 +16,14 @@ To deploy your model from within the [Language Studio](https://aka.ms/LanguageSt
 
 2. Click on **Add deployment** to start a new deployment job.
 
-    :::image type="content" source="../../media/deploy-model.png" alt-text="A screenshot showing the deployment button" lightbox="../../media/deploy-model.png":::
+    :::image type="content" source="../../media/deploy-model.png" alt-text="A screenshot showing the deployment button in Language Studio." lightbox="../../media/deploy-model.png":::
 
 3. Select **Create new deployment** to create a new deployment and assign a trained model from the dropdown below. You can also **Overwrite an existing deployment** by selecting this option and select the trained model you want to assign to it from the dropdown below.
 
     > [!NOTE]
     > Overwriting an existing deployment doesn't require changes to your [prediction API](https://aka.ms/ct-runtime-swagger) call but the results you get will be based on the newly assigned model.
     
-   :::image type="content" source="../../media/add-deployment.png" alt-text="A screenshot showing the deployment screen" lightbox="../../media/add-deployment.png":::
+   :::image type="content" source="../../media/add-deployment.png" alt-text="A screenshot showing the model deployment options in Language Studio." lightbox="../../media/add-deployment.png":::
 
 4. Click on **Deploy** to start the deployment job.
 

articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/language-studio/test-model.md

@@ -23,5 +23,5 @@ To test your deployed models from within the [Language Studio](https://aka.ms/La
 
 6. In the **Result** tab, you can see the extracted entities from your text and their types. You can also view the JSON response under the **JSON** tab. <!--[learn more](../rest-api/get-results.md#response-body) about the structure of the JSON response.-->
 
-    :::image type="content" source="../../media/test-model-results.png" alt-text="View the test results" lightbox="../../media/test-model-results.png":::
+    :::image type="content" source="../../media/test-model-results.png" alt-text="A screenshot showing the deployment testing screen in Language Studio." lightbox="../../media/test-model-results.png":::
 

articles/cognitive-services/language-service/custom-text-analytics-for-health/includes/language-studio/train-model.md

@@ -18,7 +18,7 @@ To start training your model from within the [Language Studio](https://aka.ms/La
 
 3. Select **Train a new model** and type in the model name in the text box. You can also **overwrite an existing model** by selecting this option and choosing the model you want to overwrite from the dropdown menu. Overwriting a trained model is irreversible, but it won't affect your deployed models until you deploy the new model.
 
-    :::image type="content" source="../../media/train-model.png" alt-text="Create a new training job" lightbox="../../media/train-model.png":::
+    :::image type="content" source="../../media/train-model.png" alt-text="A screenshot showing the training job creation screen in Language Studio." lightbox="../../media/train-model.png":::
 
 4. Select data splitting method. You can choose **Automatically splitting the testing set from training data** where the system will split your labeled data between the training and testing sets, according to the specified percentages. Or you can **Use a manual split of training and testing data**, this option is only enabled if you have added documents to your testing set.
 

articles/cognitive-services/language-service/custom-text-analytics-for-health/overview.md

@@ -35,22 +35,22 @@ Similarly to Text Analytics for health, custom Text Analytics for health can be
 
 Using custom Text Analytics for health typically involves several different steps. 
 
-:::image type="content" source="media/development-lifecycle.png" alt-text="The development lifecycle" lightbox="media/development-lifecycle.png":::
+:::image type="content" source="media/development-lifecycle.png" alt-text="A diagram showing the project development lifecycle when working with custom models." lightbox="media/development-lifecycle.png":::
 
-1. **Define your schema**: Know your data and define the new entities you want extracted on top of the existing Text Analytics for health entity map. Avoid ambiguity.
+* **Define your schema**: Know your data and define the new entities you want extracted on top of the existing Text Analytics for health entity map. Avoid ambiguity.
 
-2. **Label your data**: Labeling data is a key factor in determining model performance. Label precisely, consistently and completely.
-    1. **Label precisely**: Label each entity to its right type always. Only include what you want extracted, avoid unnecessary data in your labels.
-    2. **Label consistently**:  The same entity should have the same label across all the files.
-    3. **Label completely**: Label all the instances of the entity in all your files.
+* **Label your data**: Labeling data is a key factor in determining model performance. Label precisely, consistently and completely.
+    * **Label precisely**: Label each entity to its right type always. Only include what you want extracted, avoid unnecessary data in your labels.
+    * **Label consistently**:  The same entity should have the same label across all the files.
+    * **Label completely**: Label all the instances of the entity in all your files.
 
-3. **Train the model**: Your model starts learning from your labeled data.
+* **Train the model**: Your model starts learning from your labeled data.
 
-4. **View the model's performance**: After training is completed, view the model's evaluation details, its performance and guidance on how to improve it. 
+* **View the model's performance**: After training is completed, view the model's evaluation details, its performance and guidance on how to improve it. 
 
-6. **Deploy the model**: Deploying a model makes it available for use via the [Analyze API](https://aka.ms/ct-runtime-swagger).
+* **Deploy the model**: Deploying a model makes it available for use via the [Analyze API](https://aka.ms/ct-runtime-swagger).
 
-7. **Extract entities**: Use your custom models for entity extraction tasks.
+* **Extract entities**: Use your custom models for entity extraction tasks.
 
 ## Reference documentation and code samples