Merge pull request #178422 from sdgilley/sdg-update-dl

minor review changes

Author: PRMerger12

articles/machine-learning/how-to-create-text-labeling-projects.md

@@ -34,10 +34,10 @@ Azure Machine Learning data labeling is a central place to create, manage, and m
 > [!Important]
 > Text data must be available in an Azure blob datastore. (If you do not have an existing datastore, you may upload files during project creation.)
 
-Text data can be either ".txt" or ".csv" files.
+Data formats available for text data:
 
-* For ".txt" files, each file represents one item to be labeled.
-* For ".csv" files, each row represents one item presented to the labeler.  You can display one or more columns to use when labeling that row.
+* **.txt**: each file represents one item to be labeled.
+* **.csv** or **.tsv**: each row represents one item presented to the labeler.  You decide which columns the labeler can see in order to label the row.
 
 ## Prerequisites
 
@@ -78,7 +78,7 @@ To create a dataset from data that you've already stored in Azure Blob storage:
 1. Select **Create a dataset** > **From datastore**.
 1. Assign a **Name** to your dataset.
 1. Choose the **Dataset type**:
-    * Select **Tabular** if you're using a .csv file, where each row contains a response.
+    * Select **Tabular** if you're using a .csv or .tsv file, where each row contains a response.
     * Select **File** if you're using separate .txt files for each response.
 1. (Optional) Provide a description for your dataset.
 1. Select **Next**.
@@ -96,16 +96,16 @@ To directly upload your data:
 1. Select **Create a dataset** > **From local files**.
 1. Assign a **Name** to your dataset.
 1. Choose the **Dataset type**.
-    * Select **Tabular** if you're using a .csv file, where each row is a response.
+    * Select **Tabular** if you're using a .csv or .tsv file, where each row is a response.
     * Select **File** if you're using separate .txt files for each response.
 1. (Optional) Provide a description of your dataset.
 1. Select **Next**
 1. (Optional) Select or create a datastore. Or keep the default to upload to the default blob store ("workspaceblobstore") of your Machine Learning workspace.
 1. Select **Upload** to select the local file(s) or folder(s) to upload.
 1. Select **Next**.
-1. If uploading .csv files:
+1. If uploading .csv or .tsv files:
     * Confirm the settings and preview, select **Next**.
-    * Include all columns of text you'd like the labeler to see when classifying that row.
+    * Include all columns of text you'd like the labeler to see when classifying that row.  If you'll be using ML assisted labeling, adding numeric columns may degrade the ML assist model.
     * Select **Next**.
 1.  Confirm the details. Select **Back** to modify the settings or **Create** to create the dataset.
 
@@ -114,6 +114,9 @@ To directly upload your data:
 
 [!INCLUDE [refresh](../../includes/machine-learning-data-labeling-refresh.md)]
 
+> [!NOTE]
+> Incremental refresh isn't available for projects that use tabular (.csv or .tsv) dataset input.
+
 ## Specify label classes
 
 [!INCLUDE [classes](../../includes/machine-learning-data-labeling-classes.md)]

articles/machine-learning/how-to-label-data.md

@@ -63,6 +63,8 @@ Machine learning algorithms may be triggered during your labeling. If these algo
 
 Especially early in a labeling project, the machine learning model may only be accurate enough to prelabel a small subset of images. Once these images are labeled, the labeling project will return to manual labeling to gather more data for the next round of model training. Over time, the model will become more confident about a higher proportion of images, resulting in more prelabel tasks later in the project.
 
+When there are no more prelabled tasks, you'll stop confirming or correcting labels and go back to manually tagging the items.
+
 ## <a name="image-tasks"></a> Image tasks
 
 For image-classification tasks, you can choose to view multiple images simultaneously. Use the icons above the image area to select the layout.