MML Study

A collection of contents studied about "Mathematics for Machine Learning".

Easily learn from GitHub Pages with high-quality content.

Go to Project Page!

Group Member

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`

Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/junnei/mml.

Feel free to contribute with high-quality contents!

Requirements

(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

Installation

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

Submitting code changes:

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!😆

Progress of Studying

Progress	Contents	Assigned to	Update Date	Status
Chapter 2.1 - 2.5	Linear Algebra (선형대수)	`Seongjun Jang(장성준)`	2022-07-10	✔️
Chapter 2.6 - 2.9	Linear Algebra (선형대수)	`Woojung Han(한우정)` `Sangeun Park(박상은)` `Junghun Kim(김정훈)`	2022-07-17	♻️
Chapter 3.1 - 3.10	Analytic Geometry (해석기하학)	`Lim SuHyeong(임수형)` `Wonhyeong Seo(서원형)` `JuYoung Suk(석주영)`	2022-07-17	♻️
Chapter 4.1 - 4.8	Matrix Decompositions (행렬분해)	`Wonhyeong Seo(서원형)` `Ian Na(나경훈)`	2022-07-24	♻️
Chapter 5.1 - 5.9	Vector Calculus (벡터 미적분학)		2022-07-31	❌
Chapter 6.1 - 6.8	Probability and Distributions (확률과 분포)		2022-08-07	❌
Chapter 7.1 - 7.4	Continuous Optimizations (연속 최적화)		2022-08-14	❌
Chapter 8.1 - 8.6	When Models Meet Datas (모델과 데이터)		2022-08-14	❌
Chapter 9.1 - 9.5	Linear Regression (선형회귀)		2022-08-21	❌
Chapter 10.1 - 10.8	Dimensionality Reduction with Principal Component Analysis (차원 축소 w/ PCA)		2022-08-21	❌
Chapter 11.1 - 11.5	Density Estimation with Gaussian Mixture Models (밀도 추정)		2022-08-28	❌
Chapter 12.1 - 12.6	Classification with Support Vector Machines (분류 w/ SVM)		2022-08-28	❌

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CheezEun/mml