PyTorch-basic-tutorial

PyTorch-basic-tutorial

basic tutorial for pytorch1.x

How to read these tutorials

This tutorial is divided into 12 parts, from linear regression to logistic regression. The framework used includes PyTorch 1.x version Each part is described in detail on my corresponding CSDN blog

Pytorch 笔记Ⅰ——Pytorch 张量与基本操作

Pytorch 笔记Ⅱ——Pytorch 自动求导机制

Pytorch 笔记Ⅲ——Pytorch 神经网络

Pytorch基础笔记 Ⅳ——单变量线性回归

Pytorch 笔记Ⅴ——多元线性回归

Pytorch 笔记Ⅵ——Titanic 及 breast_cancer 分类应用

Pytorch 笔记Ⅶ——mnist手写数字识别

Pytorch 笔记Ⅷ——cifar10卷积神经网络

Pytorch 笔记Ⅸ——数据增强

Pytorch 笔记Ⅹ——迁移学习ResNet18_&_VGG16

Pytorch 笔记Ⅺ——Autoencoder

Pytorch 笔记Ⅻ——DQN Reinforcement Learning

Result from tutorials

The compilation environment is win10, which uses the PyTorch-GPU version, of which PyTorch1.7.0 used by PyTorch1.x, some of the larger models are trained by Google Colab, and all corresponding notebooks are all Given, this part is mainly GAN and CGAN, the following will show some of the results obtained in this tutorial

PyTorch

Visualization of Encoder

MNIST

How to contact me

If you encounter any problems in this tutorial notebook, you can contact me, my common QQ mailbox: [email protected] and my Google mailbox [email protected], you can also privately mail me on my CSDN blog or Raise issues on github

Finally, I briefly introduce myself as follows: My name is Guo Quanhao, winner of the national first prize in the National University Optoelectronic Design Competition, 2016 postgraduate recommendation of the University of Electronic Science and Technology, a member of the Momi Visual Lab, familiar with C, Python, stm32, deep learning, if my blog Helpful to everyone, welcome everyone’s attention