You may notice that I often recommend excellent Github repositories to you. You may have questions: how to find excellent Github repositories? How do I find great repositories on Github?

In general, to find excellent repositories on Github, is to enter keywords, search, and see github’s recommendation results, which are sorted by match, relatively accurate.

This article introduces another method, which I often use:

Take a look at what the best users have in their warehouse.

First, take a look at github’s star rankings:

gitstar-ranking.com

In general, star users, there are always some good warehouses.

gitstar-ranking.com/users

I usually went through them one by one and found many treasures:

This method is based on an assumption:

A good user, if has a good warehouse, usually his other warehouses are not bad.

These warehouses may have just been established, there are not many stars, and the search results may not be the top, but using the method I recommend to search from the top user rankings can often have a lot of surprises!

Finally, post the AD. My Github user star ranks 125:

Making address:

github.com/fengdu78

Github is on the second page:

Gitstar-ranking.com/users?page=…

Site introduction ↓↓↓

“Machine Learning Beginners” is a personal public account to help artificial intelligence enthusiasts get started (founder: Huang Haiguang)

Beginners on the road to entry, the most need is “help”, rather than “icing on the cake”.

ID: 92416895\

Currently, the planet of Knowledge in the direction of machine learning ranks no. 1.

Past wonderful review \

  • Conscience recommendation: Introduction to machine learning information summary and learning recommendations \

  • Github Image download by Dr Hoi Kwong (Machine learning and Deep Learning Notes and Resources)

  • Machine Learning Cheat Sheet – (Understanding machine learning like reciting TOEFL Vocabulary) \

  • Introduction to Deep Learning – Python Deep Learning, annotated version of the original code in Chinese and ebook

  • Machine learning – “Statistical learning methods” python code implementation, ebook and courseware \

  • Blockbuster | complete AI learning course, the most detailed resources arrangement! \

  • Word2vec

  • Fundamentals of Mathematics for Stanford CS229 Machine Learning (Probability and Linearity)

Note: This site’S QQ groups: 659697409 (a total of 8 groups, do not add repeatedly).

To join the wechat group of this site, please add the assistant wechat of Huang Bo, explanation: public number user group.

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