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PyTorch Tutorial for Deep Learning Researchers
| Date | Stars |
|---|---|
| 2026-07-24 | 32432 |
| 2026-07-25 | 32434 |
| 2026-07-28 | 32434 |
| 2026-07-30 | 32434 |
| 2026-07-31 | 32443 |
| 2026-08-06 | 32445 |
Today
+2 stars today
This week
+11 stars this week
This month
— stars this month
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growth rate 0.03%/day
<p align="center"><img width="40%" src="logo/pytorch_logo_2018.svg" /></p> -------------------------------------------------------------------------------- This repository provides tutorial code for deep learning researchers to learn [PyTorch](https://github.com/pytorch/pytorch). In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish [Official Pytorch Tutorial](http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html). <br/> ## Table of Contents #### 1. Basics * [PyTorch Basics](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/pytorch_basics/main.py) * [Linear Regression](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/linear_regression/main.py#L22-L23) * [Logistic Regression](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/logistic_regression/main.py#L33-L34) * [Feedforward Neural Network](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/01-basics/feedforward_neural_network/main.py#L37-L49) #### 2. Intermediate * [Convolutional Neural Network](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/convolutional_neural_network/main.py#L35-L56) * [Deep Residual Network](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/deep_residual_network/main.py#L76-L113) * [Recurrent Neural Network](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/recurrent_neural_network/main.py#L39-L58) * [Bidirectional Recurrent Neural Network](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/bidirectional_recurrent_neural_network/main.py#L39-L58) * [Language Model (RNN-LM)](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/02-intermediate/language_model/main.py#L30-L50) #### 3. Advanced * [Generative Adversarial Networks](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/generative_adversarial_network/main.py#L41-L57) * [Variational Auto-Encoder](https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/03-advanced/variational_autoencoder/main.py#L38-L65) * [Neural Style Transfer](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/neural_style_transfer) * [Image Captioning (CNN-RNN)](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/image_captioning) #### 4. Utilities * [TensorBoard in PyTorch](https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/04-utils/tensorboard) <br/> ## Getting Started ```bash $ git clone https://github.com/yunjey/pytorch-tutorial.git $ cd pytorch-tutorial/tutorials/PATH_TO_PROJECT $ python main.py ``` <br/> ## Dependencies * [Python 2.7 or 3.5+](https://www.continuum.io/downloads) * [PyTorch 0.4.0+](http://pytorch.org/)
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:648d69f99f66f153, topic:deep-learning, topic:pytorch
matched fp:648d69f99f66f153, name:tutorial, desc:tutorial, readme:tutorial