README.md · 林宇宸/PyTorch-Tutorial

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### 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](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](https://github.com/liufuyang) [**notebook files**](tutorial-contents-notebooks)
which is a great contribution to this tutorial.

* pyTorch basic
  * [torch and numpy](tutorial-contents/201_torch_numpy.py)
  * [Variable](tutorial-contents/202_variable.py)
  * [Activation](tutorial-contents/203_activation.py)
* Build your first network
  * [Regression](tutorial-contents/301_regression.py)
  * [Classification](tutorial-contents/302_classification.py)
  * [An easy way](tutorial-contents/303_build_nn_quickly.py)
  * [Save and reload](tutorial-contents/304_save_reload.py)
  * [Train on batch](tutorial-contents/305_batch_train.py)
  * [Optimizers](tutorial-contents/306_optimizer.py)
* Advanced neural network
  * [CNN](tutorial-contents/401_CNN.py)
  * [RNN-Classification](tutorial-contents/402_RNN_classifier.py)
  * [RNN-Regression](tutorial-contents/403_RNN_regressor.py)
  * [AutoEncoder](tutorial-contents/404_autoencoder.py)
  * [DQN Reinforcement Learning](tutorial-contents/405_DQN_Reinforcement_learning.py)
  * [A3C Reinforcement Learning](https://github.com/MorvanZhou/pytorch-A3C)
  * [GAN (Generative Adversarial Nets)](tutorial-contents/406_GAN.py) / [Conditional GAN](tutorial-contents/406_conditional_GAN.py)
* Others (WIP)
  * [Why torch dynamic](tutorial-contents/501_why_torch_dynamic_graph.py)
  * [Train on GPU](tutorial-contents/502_GPU.py)
  * [Dropout](tutorial-contents/503_dropout.py)
  * [Batch Normalization](tutorial-contents/504_batch_normalization.py)

**For Chinese speakers: All methods mentioned below have their video and text tutorial in Chinese.
Visit [莫烦 Python](https://mofanpy.com/tutorials/) for more.
You can watch my [Youtube channel](https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg) as well.**

### [Regression](tutorial-contents/301_regression.py)

### [Classification](tutorial-contents/302_classification.py)

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

### [RNN](tutorial-contents/403_RNN_regressor.py)

### [Autoencoder](tutorial-contents/404_autoencoder.py)

### [GAN (Generative Adversarial Nets)](tutorial-contents/406_GAN.py)
<a href="tutorial-contents/406_GAN.py">
    <img class="course-image" src="https://mofanpy.com/static/results/torch/4-6-1.gif" >
</a>

### [Dropout](tutorial-contents/503_dropout.py)
<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](tutorial-contents/504_batch_normalization.py)
<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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