Column directory (including video introduction)

Everyone is welcome to ask questions, discuss and correct in the video bulletin and comments! Enter from here old version

Deep learning development

Note video and note document series

Explore deep learning that passers-by can understand (video update)

Deep learning questions and answers summary

Deep learning summary in the summary (welcome questions and corrections)

Wu Enda is the best start!


Deep learning flower book notes (Read only when you are not reading)

Build a good intuition: Mathematical intuition Physical intuition

Jade of his mountain

amazing people

Reading a paper, maybe not as horrible as you think.

I have been looking up to deep study papers and feel that way out of my reach, so I have been trying to avoid reading papers or even textbooks;

However, when I learned the CNN course, Wu Enda said that I can understand it, then try it, in case I really understand it…

Although the textbooks are very good, the authors who wrote the Deep Learning Book are all growing up…

In this content, Not only the notes for reading the paper, but also the notes for reading and interpreting the papers.

Read the source code of the deep learning library

Toolbox application

demos, resources

Learn the numpy library

Learn the tangent library

Learning the autograd library

Taking pytorch as an example, when we need to write a function that pytorch does not have, we need to provide forward and reverse transfer functions. The inverse function requires us to write the derivative calculation process ourselves; autograd can help us solve the problem of reverse homing. We only need to provide a forward function.

Learn the pytorch library

previous works

Learn the tensorflow library

Learning keras library

Learning chainer library

Learning mxnet library

Learning scipy library

Learning the matplotlib library

Learning seaborn library

Learn the Jupyter / IPython library

Work platform construction and maintenance

Exploring the method of video notes


C programming

C basics

joinquant uqer programming

How to use online quantification python write strategy

What are the benefits of making your own tools?


Time-consuming, inefficient, full of mistakes, no use, no practical value


Self-education, figure out how each tool comes from, what are the characteristics, what are the specific small problems that can be solved; you can always debug to the bottom

my treasure box