<p align="center"> <a href="http://pytorch.org/" target="_blank"> <img width="40%" src="logo.png" style="max-width:100%;"> </a> </p> <br>

If you'd like to use Tensorflow, no worries, I made a new Tensorflow Tutorial just like PyTorch. Here is the link: https://github.com/MorvanZhou/Tensorflow-Tutorial

pyTorch Tutorials

In these tutorials for pyTorch, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years.

Thanks for liufuyang's notebook files
which is a great contribution to this tutorial.

• pyTorch basic
  • torch and numpy
  • Variable
  • Activation
• Build your first network
  • Regression
  • Classification
  • An easy way
  • Save and reload
  • Train on batch
  • Optimizers
• Advanced neural network
  • CNN
  • RNN-Classification
  • RNN-Regression
  • AutoEncoder
  • DQN Reinforcement Learning
  • A3C Reinforcement Learning
  • GAN (Generative Adversarial Nets) / Conditional GAN
• Others (WIP)
  • Why torch dynamic
  • Train on GPU
  • Dropout
  • Batch Normalization

For Chinese speakers: All methods mentioned below have their video and text tutorial in Chinese.
Visit 莫烦 Python for more.
You can watch my Youtube channel as well.

Regression

<a href="tutorial-contents/301_regression.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/1-1-2.gif"> </a>

Classification

<a href="tutorial-contents/302_classification.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/1-1-3.gif"> </a>

CNN

<a href="tutorial-contents/401_CNN.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/4-1-2.gif" > </a>

RNN

<a href="tutorial-contents/403_RNN_regressor.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/4-3-1.gif" > </a>

Autoencoder

<a href="tutorial-contents/403_RNN_regressor.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/4-4-1.gif" > </a> <a href="tutorial-contents/403_RNN_regressor.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/4-4-2.gif" > </a>

GAN (Generative Adversarial Nets)

<a href="tutorial-contents/406_GAN.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/4-6-1.gif" > </a>

Dropout

<a href="tutorial-contents/503_dropout.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/5-3-1.gif" > </a>

Batch Normalization

<a href="tutorial-contents/504_batch_normalization.py"> <img class="course-image" src="https://mofanpy.com/static/results/torch/5-4-2.gif" > </a>

Donation

If this does help you, please consider donating to support me for better tutorials. Any contribution is greatly appreciated!

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