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# %matplotlib inline

#
# **Learn the Basics** ||
# `Quickstart <quickstart_tutorial.html>`_ || 
# `Tensors <tensorqs_tutorial.html>`_ || 
# `Datasets & DataLoaders <data_tutorial.html>`_ ||
# `Transforms <transforms_tutorial.html>`_ ||
# `Build Model <buildmodel_tutorial.html>`_ ||
# `Autograd <autogradqs_tutorial.html>`_ ||
# `Optimization <optimization_tutorial.html>`_ ||
# `Save & Load Model <saveloadrun_tutorial.html>`_
#
# Learn the Basics
# ===================
#
# Authors: 
# `<NAME> <https://github.com/suraj813>`_,
# `<NAME> <https://github.com/sethjuarez/>`_, 
# `<NAME> <https://github.com/cassieview/>`_, 
# `<NAME> <https://soshnikov.com/>`_, 
# `<NAME> <https://github.com/aribornstein/>`_ 
#
# Most machine learning workflows involve working with data, creating models, optimizing model 
# parameters, and saving the trained models. This tutorial introduces you to a complete ML workflow 
# implemented in PyTorch, with links to learn more about each of these concepts.
#
# We'll use the FashionMNIST dataset to train a neural network that predicts if an input image belongs 
# to one of the following classes: T-shirt/top, Trouser, Pullover, Dress, Coat, Sandal, Shirt, Sneaker, 
# Bag, or Ankle boot. 
#
# `This tutorial assumes a basic familiarity with Python and Deep Learning concepts.`
#
#
# Running the Tutorial Code
# ------------------
# You can run this tutorial in a couple of ways:
#
# - **In the cloud**: This is the easiest way to get started! Each section has a Colab link at the top, which opens a notebook with the code in a fully-hosted environment. Pro tip: Use Colab with a GPU runtime to speed up operations *Runtime > Change runtime type > GPU*
# - **Locally**: This option requires you to setup PyTorch and TorchVision first on your local machine (`installation instructions <https://pytorch.org/get-started/locally/>`_). Download the notebook or copy the code into your favorite IDE.
#
#
# How to Use this Guide
# ----------------- 
# If you're familiar with other deep learning frameworks, check out the `0. Quickstart <quickstart_tutorial.html>`_ first
# to quickly familiarize yourself with PyTorch's API.
#
# If you're new to deep learning frameworks, head right into the first section of our step-by-step guide: `1. Tensors <tensor_tutorial.html>`_.
#
#
# .. include:: /beginner_source/basics/qs_toc.txt
#
# .. toctree::
#    :hidden:
#
#
#

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