# Kind-PyTorch-Tutorial

**Repository Path**: lg21c/Kind-PyTorch-Tutorial

## Basic Information

- **Project Name**: Kind-PyTorch-Tutorial
- **Description**: Kind PyTorch Tutorial for beginners
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-10-03
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<p align="center">
<img src="./logo/PyTorch.jpg" width="60%">
</p>

Requirements
-------------------------
- python 3.5.2
- Pytorch (http://pytorch.org/)
- Numpy
- matplotlib

Optional
--------------------------
- visdom (https://github.com/facebookresearch/visdom)

Table of contents
--------------------------
- [Pytorch Tensor Basics](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/01_Tensor_Basics/pytorch_tensor_basic.ipynb)
- [Variable and Automatic Gradient Calculation](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/02_Variable_Autograd/Variable_Autograd.ipynb)
- [Linear Regression Example (Loss & Optimizer)](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/03_Linear_Regression/Linear_Regression.ipynb)
- [MNIST CNN (cpu & gpu)](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/04_MNIST_CNN/MNIST_CNN.ipynb)
- [Input Pipeline & Pretrained Model](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/05_Input_Pipeline_Pretrained/Input_Pipeline_Pretrained.ipynb)
- [Autoencoder & Model Save](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/06_Autoencoder_Model_Save)
- [Denoising Autoencoder](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/tree/master/07_Denoising_Autoencoder)
- [Simple Character RNN](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/blob/master/08_Simple_Char_RNN/Simple_Char_RNN.ipynb)
- [Vanilla GAN (Layer naming & Multi gpu)](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/tree/master/09_GAN_LayerName_MultiGPU)
- [InfoGAN using Least Squares loss](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/tree/master/10_InfoGAN_Least_Squares_Loss)
- [Image Style Transfer using ResNet](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/tree/master/11_StyleTransfer_ResNet)
- [Semantic Segmentation (U-Net & Fusion-Net)](https://github.com/GunhoChoi/Kind_PyTorch_Tutorial/tree/master/12_Semantic_Segmentation)