Broken link removed

Author: pritamso

articles/machine-learning/how-to-train-pytorch.md

@@ -103,7 +103,7 @@ AzureML allows you to either use a curated (or ready-made) environment or create
 In this section, we'll begin by introducing the data for training. We'll then cover how to run a training job, using a training script that we've provided. You'll learn to build the training job by configuring the command for running the training script. Then, you'll submit the training job to run in AzureML.
 
 ### Obtain the training data
-You'll use data that is stored on a public blob as a [zip file](https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip). This dataset consists of about 120 training images each for two classes (turkeys and chickens), with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We'll download and extract the dataset as part of our training script `pytorch_train.py`.
+You'll use data that is stored on a public blob as a zip file. This dataset consists of about 120 training images each for two classes (turkeys and chickens), with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We'll download and extract the dataset as part of our training script `pytorch_train.py`.
 
 ### Prepare the training script
 
@@ -256,4 +256,4 @@ In this article, you trained and registered a deep learning neural network using
 
 - [Track run metrics during training](how-to-log-view-metrics.md)
 - [Tune hyperparameters](how-to-tune-hyperparameters.md)
-- [Reference architecture for distributed deep learning training in Azure](/azure/architecture/reference-architectures/ai/training-deep-learning)
+- [Reference architecture for distributed deep learning training in Azure](/azure/architecture/reference-architectures/ai/training-deep-learning)