A collection of contents studied about "Mathematics for Machine Learning".
Easily learn from GitHub Pages with high-quality content.
All of them participated in this study with high-quality content!
Thanks goes to these wonderful people :
Seongjun Jang |
Woojung Han |
Jihyun Bae |
Eunbi Park |
Junghun Kim |
Sangeun Park |
---|---|---|---|---|---|
WonJoon Choi |
ChanHee Kang |
Ian Na |
Lim SuHyeong |
Kim Juwon |
Kim YoonJong |
JuYoung Suk |
Wonhyeong Seo |
Jinyoung Son |
Minjeong Yoo |
Bug reports and pull requests are welcome on GitHub at https://github.com/junnei/mml.
Feel free to contribute with high-quality contents!
(If Docker you don't need to install all, just run it and Open your browser at http://localhost:4000/mml/kr
)
$ docker-compose up
First, we need to install ruby (v2.7.3 in my case) [Home page]
If Windows OS, Download RubyInstaller
## Linux
$ sudo apt install ruby ruby-dev build-essential
## MacOS
$ brew install ruby
And then install jekyll
:
$ gem install bundler:2.1.4 jekyll
First, fork this repository and clone to your local machine.
$ git clone https://github.com/[YOUR_GITHUB_ID]/mml
$ cd mml
Install gem dependencies by :
$ bundle install
## if bundler version error, 'bundle _2.1.4_ install'
If Ruby >= 3.0.0, before install gem dependencies :
$ bundle add webrick
## if bundler version error, 'bundle _2.1.4_ add webrick'
You should preview the site contents before contributing, so just run it by:
$ bundle exec jekyll serve
This starts a Jekyll server, and now you could test whatever you added.
Open your browser at http://localhost:4000/mml/kr
Add your information in _data/writers.yml
.
#ex)
junnei:
kr:
name: 장성준
en:
name: Seongjun Jang
[YOUR_GITHUB_ID]:
kr:
name: [YOUR_NAME/KR](홍길동)
en:
name: [YOUR_NAME/EN](John Doe)
- Open a Pull Request
- Await code review
- Ta-da! You've become a contributor!😆
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.