Merge pull request #185714 from nibaccam/patch-18

AutoML Images | link edit

Author: PRMerger12

articles/machine-learning/reference-automl-images-hyperparameters.md

@@ -16,7 +16,7 @@ ms.date: 01/18/2022
 
 Learn which hyperparameters are available specifically for computer vision tasks in automated ML experiments.
 
-With support for computer vision tasks, you can control the model algorithm and sweep hyperparameters. These model algorithms and hyperparameters are passed in as the parameter space for the sweep. While many of the hyperparameters exposed are model-agnostic, there are instances where hyperparameters are task-specific or model-specific.
+With support for computer vision tasks, you can control the model algorithm and sweep hyperparameters. These model algorithms and hyperparameters are passed in as the parameter space for the sweep. While many of the hyperparameters exposed are model-agnostic, there are instances where hyperparameters are model-specific or task-specific.
 
 ## Model-specific hyperparameters
 
@@ -82,7 +82,7 @@ The following table summarizes hyperparmeters for image classification (multi-cl
 The following hyperparameters are for object detection and instance segmentation tasks.
 
 > [!WARNING]
-> These parameters are not supported with the `yolov5` algorithm.
+> These parameters are not supported with the `yolov5` algorithm. See the [model specific hyperparameters](#model-specific-hyperparameters) section for `yolo5` supported hyperparmeters.
 
 | Parameter name       | Description           | Default  |
 | ------------- |-------------|-----|
@@ -100,4 +100,4 @@ The following hyperparameters are for object detection and instance segmentation
 
 * Learn how to [Set up AutoML to train computer vision models with Python (preview)](how-to-auto-train-image-models.md).
 
-* [Tutorial: Train an object detection model (preview) with AutoML and Python](tutorial-auto-train-image-models.md).
+* [Tutorial: Train an object detection model (preview) with AutoML and Python](tutorial-auto-train-image-models.md).