To get started with learning PyTorch, start with our Beginner Tutorials. The :doc:`60-minute blitz </beginner/deep_learning_60min_blitz>` is the most common starting point, and gives you a quick introduction to PyTorch. If you like learning by examples, you will like the tutorial :doc:`/beginner/pytorch_with_examples`
If you would like to do the tutorials interactively via IPython / Jupyter, each tutorial has a download link for a Jupyter Notebook and Python source code.
We also provide a lot of high-quality examples covering image classification, unsupervised learning, reinforcement learning, machine translation and many other applications at https://github.com/pytorch/examples/
You can find reference documentation for PyTorch's API and layers at http://docs.pytorch.org or via inline help. If you would like the tutorials section improved, please open a github issue here with your feedback: https://github.com/pytorch/tutorials
.. customgalleryitem:: :figure: /_static/img/thumbnails/pytorch-logo-flat.png :tooltip: Understand PyTorch’s Tensor library and neural networks at a high level. :description: :doc:`/beginner/deep_learning_60min_blitz`
.. customgalleryitem:: :tooltip: Understand similarities and differences between torch and pytorch. :figure: /_static/img/thumbnails/torch-logo.png :description: :doc:`/beginner/former_torchies_tutorial`
.. customgalleryitem:: :tooltip: This tutorial introduces the fundamental concepts of PyTorch through self-contained examples. :figure: /_static/img/thumbnails/examples.png :description: :doc:`/beginner/pytorch_with_examples`
.. galleryitem:: beginner/transfer_learning_tutorial.py
.. galleryitem:: beginner/data_loading_tutorial.py
.. customgalleryitem::
:tooltip: I am writing this tutorial to focus specifically on NLP for people who have never written code in any deep learning framework
:figure: /_static/img/thumbnails/babel.jpg
:description: :doc:`/beginner/deep_learning_nlp_tutorial`
.. toctree:: :maxdepth: 2 :hidden: :includehidden: :caption: Beginner Tutorials beginner/deep_learning_60min_blitz beginner/former_torchies_tutorial beginner/pytorch_with_examples beginner/transfer_learning_tutorial beginner/data_loading_tutorial beginner/deep_learning_nlp_tutorial
.. galleryitem:: intermediate/char_rnn_classification_tutorial.py
.. galleryitem:: intermediate/char_rnn_generation_tutorial.py :figure: _static/img/char_rnn_generation.png
.. galleryitem:: intermediate/seq2seq_translation_tutorial.py :figure: _static/img/seq2seq_flat.png
.. galleryitem:: intermediate/reinforcement_q_learning.py
:figure: _static/img/cartpole.gif
.. customgalleryitem:: :tooltip: Writing Distributed Applications with PyTorch. :description: :doc:`/intermediate/dist_tuto` :figure: _static/img/distributed/DistPyTorch.jpg
.. galleryitem:: intermediate/spatial_transformer_tutorial.py
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Intermediate Tutorials intermediate/char_rnn_classification_tutorial intermediate/char_rnn_generation_tutorial intermediate/seq2seq_translation_tutorial intermediate/reinforcement_q_learning intermediate/dist_tuto intermediate/spatial_transformer_tutorial
.. galleryitem:: advanced/neural_style_tutorial.py
:intro: This tutorial explains how to implement the Neural-Style algorithm developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge.
.. galleryitem:: advanced/numpy_extensions_tutorial.py
.. galleryitem:: advanced/super_resolution_with_caffe2.py
.. customgalleryitem:: :tooltip: Implement custom extensions in C++ or CUDA. :description: :doc:`/advanced/cpp_extension` :figure: _static/img/cpp_logo.png
.. toctree:: :maxdepth: 2 :includehidden: :hidden: :caption: Advanced Tutorials advanced/neural_style_tutorial advanced/numpy_extensions_tutorial advanced/super_resolution_with_caffe2 advanced/cpp_extension