Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Build your neural network easy and fast, 莫烦Python中文教学
| Date | Stars |
|---|---|
| 2026-07-24 | 8458 |
| 2026-07-25 | 8458 |
| 2026-07-28 | 8458 |
| 2026-07-30 | 8458 |
| 2026-07-31 | 8461 |
| 2026-08-01 | 8464 |
| 2026-08-02 | 8466 |
| 2026-08-05 | 8465 |
| 2026-08-06 | 8465 |
Today
— stars today
This week
+7 stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.08%/day
<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](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)
<a href="tutorial-contents/301_regression.py">
<img class="course-image" src="https://mofanpy.com/static/results/torch/1-1-2.gif">
</a>
### [Classification](tutorial-contents/302_classification.py)
<a href="tutorial-contents/302_classification.py">
<img class="course-image" src="https://mofanpy.com/static/results/torch/1-1-3.gif">
</a>
### [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)
<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](tutorial-contents/404_autoencoder.py)
<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)](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="courExcerpt of 4,851 characters
Read on GitHub
Morvan
66
8
Jerome · National Chiao Tung University · Taiwan
4
2
1
1
jingege315
1
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:93134126b176597d, topic:neural-network, topic:pytorch
matched fp:93134126b176597d, topic:gan
matched fp:93134126b176597d, topic:reinforcement-learning, readme:reinforcement learning
matched fp:93134126b176597d, topic:tutorial, name:tutorial, readme:tutorial