PaddlePaddle-basic-tutorial

A basic tutorial for paddlepaddle2.0 version

How to read these tutorials

This tutorial is divided into 9 parts, from linear regression to logistic regression. The framework used includes PaddlePaddle2.x low-level API and advanced API.

Each part is described in detail on my corresponding CSDN blog

PaddlePaddle tutorial Ⅰ——Multiple linear regression

PaddlePaddle tutorial Ⅱ——Multiple linear classification

PaddlePaddle tutorial Ⅲ——Fashion-Mnist Full Connect Networks

PaddlePaddle tutorial Ⅳ——AutoEncoder

PaddlePaddle tutorial Ⅴ——Cifar10 Convolutional Neural Networks

PaddlePaddle tutorial Ⅵ——VGG transfer Learning

PaddlePaddle tutorial Ⅶ——Augmentation for Image

PaddlePaddle tutorial Ⅷ——UNet of Segmentation

PaddlePaddle tutorial Ⅸ——LSTM for Classification & Regression

Result from tutorials

PaddlePaddle Architecture

Visualization of loss values in AutoEncoder

Visualization of Data distribution

VisualDL of UNet Segmentation

How to contact me

If you encounter any problems in this tutorial notebook, you can contact me, my common QQ mailbox: 876270200@qq.com and my Google mailbox cybergodhao@gmail.com, 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 and second prize of mathematical modeling contest for Postgraduates, 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