update

Author: openpublishbuild

articles/machine-learning/how-to-image-processing-batch.md

@@ -26,7 +26,7 @@ You can use batch model deployments for processing tabular data, but also any ot
 
 ## About this sample
 
-This article uses a model that was built using TensorFlow along with the RestNet architecture. For more information, see [Identity Mappings in Deep Residual Networks](https://arxiv.org/abs/1603.05027). You can download [a sample of this model](https://azuremlexampledata.blob.core.windows.net/data/imagenet/model.zip). The model has the following constraints:
+This article uses a model that was built using TensorFlow along with the RestNet architecture. For more information, see [Identity Mappings in Deep Residual Networks](https://arxiv.org/abs/1603.05027). You can download `https://azuremlexampledata.blob.core.windows.net/data/imagenet/model.zip`. The model has the following constraints:
 
 - It works with images of size 244x244 (tensors of `(224, 224, 3)`).
 - It requires inputs to be scaled to the range `[0,1]`.

articles/machine-learning/how-to-use-batch-azure-data-factory.md

@@ -143,8 +143,8 @@ To create this pipeline in your existing Azure Data Factory and invoke batch end
 
 1. Select a *.zip* file.
 
-   - To use managed identities, select [this file](https://azuremlexampledata.blob.core.windows.net/data/templates/batch-inference/Run-BatchEndpoint-MI.zip).
-   - To use a service principle, select [this file](https://azuremlexampledata.blob.core.windows.net/data/templates/batch-inference/Run-BatchEndpoint-SP.zip).
+   - To use managed identities, select `https://azuremlexampledata.blob.core.windows.net/data/templates/batch-inference/Run-BatchEndpoint-MI.zip`.
+   - To use a service principle, select `https://azuremlexampledata.blob.core.windows.net/data/templates/batch-inference/Run-BatchEndpoint-SP.zip`.
 
 1. A preview of the pipeline shows up in the portal. Select **Use this template**.
 

articles/machine-learning/how-to-use-batch-fabric.md

@@ -34,7 +34,7 @@ In this article, you learn how to consume Azure Machine Learning batch deploymen
         - Create/manage batch endpoints and deployments: Use roles Owner, contributor, or custom role allowing `Microsoft.MachineLearningServices/workspaces/batchEndpoints/*`.
         - Create ARM deployments in the workspace resource group: Use roles Owner, contributor, or custom role allowing `Microsoft.Resources/deployments/write` in the resource group where the workspace is deployed.
 - A model deployed to a batch endpoint. If you don't have one, use the steps in [Deploy models for scoring in batch endpoints](how-to-use-batch-model-deployments.md) to create one.
-- Download the [_heart-unlabeled.csv_](https://azuremlexampledata.blob.core.windows.net/data/heart-disease-uci-unlabeled/heart-unlabeled.csv) sample dataset to use for scoring.
+- Download the `https://azuremlexampledata.blob.core.windows.net/data/heart-disease-uci-unlabeled/heart-unlabeled.csv` sample dataset to use for scoring.
 
 ## Architecture