Very minor changes . . .

Author: fbsolo-ms1

articles/machine-learning/how-to-add-users.md

@@ -108,7 +108,7 @@ To add users to your workspace, you must be an owner of the workspace.
 
 ## For your labelers
 
-Now, your labelers can begin labeling in your project. However, they still need information from you to access the project. 
+Now, your labelers can begin labeling in your project. However, they still need information from you to access the project.
 
 Be sure to create your labeling project before you contact your labelers.
 
@@ -120,7 +120,7 @@ Send the following information to your labelers, after you fill in your workspac
 1. Accept the invite from **Microsoft Invitations ([email protected])**.
 1. Follow the steps on the web page after you accept. Don't worry if, at the end, you find yourself on a page that says you don't have any apps.
 1. Open [Azure Machine Learning studio](https://ml.azure.com).
-1. Use the dropdown to select the workspace **\<workspace-name\>**. 
+1. Use the dropdown to select the workspace **\<workspace-name\>**.
 1. Select the **Label data** tool for **\<project-name\>**.
     :::image type="content" source="media/how-to-add-users/label-data.png" alt-text="Screenshot showing the label data tool.":::
 1. For more information about how to label data, see [Labeling images and text documents](how-to-label-data.md).

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

@@ -8,7 +8,7 @@ ms.reviewer: franksolomon
 ms.service: machine-learning
 ms.subservice: mldata
 ms.topic: how-to
-ms.date: 02/03/2023
+ms.date: 02/07/2023
 ms.custom: data4ml, ignite-fall-2021, ignite-2022
 ---
 
@@ -162,7 +162,7 @@ Since the final labels still rely on input from the labeler, this technology is
 
 After submission of some labels, the classification machine learning model starts to group together similar items. These similar images are presented to the labelers on the same screen to speed up manual tagging. Clustering is especially useful when the labeler views a grid of four, six, or nine images.
 
-Once a machine learning model has been trained on your manually labeled data, the model is truncated to its last fully connected layer. Unlabeled images are then passed through the truncated model in a process commonly known as "embedding" or "featurization." This process embeds each image in a high-dimensional space defined by this model layer. Images that are nearest neighbors in the space are used for clustering tasks. 
+Once a machine learning model has been trained on your manually labeled data, the model is truncated to its last fully connected layer. Unlabeled images are then passed through the truncated model in a process commonly known as "embedding" or "featurization." This process embeds each image in a high-dimensional space defined by this model layer. Images that are nearest neighbors in the space are used for clustering tasks.
 
 The clustering phase doesn't appear for object detection models, or for text classification.