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Welcome to PyTorch Tutorials
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To get started with learning PyTorch, start with our Beginner Tutorials.
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To learn how to use PyTorch, start with our Getting Started Tutorials.
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The :doc:`60-minute blitz </beginner/deep_learning_60min_blitz>` is the most common
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starting point, and gives you a quick introduction to PyTorch.
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If you like learning by examples, you will like the tutorial
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:doc:`/beginner/pytorch_with_examples`
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starting point, and provides a broad view into how to use PyTorch from basics all the way to constructing deep neural networks.
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If you would like to do the tutorials interactively via IPython / Jupyter,
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Some considerations:
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- If you would like to do the tutorials interactively via IPython / Jupyter,
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each tutorial has a download link for a Jupyter Notebook and Python source code.
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We also provide a lot of high-quality examples covering image classification,
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- Additional high-quality examples are available including image classification,
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unsupervised learning, reinforcement learning, machine translation and
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many other applications at https://github.com/pytorch/examples/
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You can find reference documentation for PyTorch's API and layers at
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- You can find reference documentation for PyTorch's API and layers at
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http://docs.pytorch.org or via inline help.
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If you would like the tutorials section improved, please open a github issue
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- If you would like the tutorials section improved, please open a github issue
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here with your feedback: https://github.com/pytorch/tutorials
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Lastly, some of the tutorials are marked as requiring the *Preview release*. These are tutorials that use the new functionality from the PyTorch 1.0 Preview. Please use the *getting started* section to get instructions on how to install the latest Preview build before trying these tutorials.
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Getting Started
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------------------
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