Update data_quickstart_tutorial.py

beginner_source/quickstart/data_quickstart_tutorial.py

@@ -1,3 +1,38 @@
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+tutorials/beginner_source/quickstart/data_quickstart_tutorial.py /
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 """
 Datasets & Dataloaders
 ===================
@@ -35,7 +70,10 @@
 # 
 # Once we have a Dataset we can index it manually like a list `clothing[index]`. 
 # 
-# Here is an example of how to load the [Fashion-MNIST](https://research.zalando.com/welcome/mission/research-projects/fashion-mnist/) dataset from torch vision. "[Fashion-MNIST](https://research.zalando.com/welcome/mission/research-projects/fashion-mnist/) is a dataset of Zalando’s article images consisting of of 60,000 training examples and 10,000 test examples. Each example is comprised of a 28×28 grayscale image, associated with a label from one of 10 classes. Read more [here](https://pytorch.org/docs/stable/torchvision/datasets.html#fashion-mnist).
+# Here is an example of how to load the `Fashion-MNIST<https://research.zalando.com/welcome/mission/research-projects/fashion-mnist/>`_ dataset from torch vision.
+# `Fashion-MNIST <https://research.zalando.com/welcome/mission/research-projects/fashion-mnist/>`_ is a dataset of Zalando’s article images consisting of of 60,000 training examples and 10,000 test examples. 
+# Each example is comprised of a 28×28 grayscale image, associated with a label from one of 10 classes. Read more `here <https://pytorch.org/docs/stable/torchvision/datasets.html#fashion-mnist>`_.
+#
 # To load the FashionMNIST Dataset we need to provide the following three parameters:
 #  - root is the path where the train/test data is stored. 
 #  - train includes the training dataset. 
@@ -194,3 +232,15 @@ def __getitem__(self, idx):
 # Next: Learn more about how to `transform that data for training <transforms_tutorial.html>`_.
 #
 # .. include:: /beginner_source/quickstart/qs_toc.txt
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