# THU-Coursework-Machine-Learning-for-Big-Data
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
This file will become your README and also the index of your
documentation.
## Developer Guide
如果你想加入我们一起开源作业，请阅读以下指南。
If you are new to using `nbdev` here are some useful pointers to get you
started.
### 关于Quarto和nbdev一些需要配置的地方
``` sh
nbdev_install_quarto
quarto install tinytex
quarto install chromium
sudo apt-get install librsvg2-bin
```
### 关于nbdev、quarto+pandoc 这一套系统支持和不支持的markdown与latex语法
- latex公式：
- 不能用””
- 对于align公式,似乎都失败了 align, aligned和aligned\*,
[参考](https://tex.stackexchange.com/questions/256920/package-amsmath-error-beginaligned-allowed-only-in-math-mode)
- MathJax引擎支持的应该支持。https://quarto.org/docs/output-formats/html-basics.html
- VSCode也用的是 MathJax
https://stackoverflow.com/questions/62879232/how-do-i-use-latex-in-a-jupyter-notebook-inside-visual-studio-code
- markdown语法：
### Install THU_Coursework_Machine_Learning_for_Big_Data in Development mode
``` sh
# make sure THU_Coursework_Machine_Learning_for_Big_Data package is installed in development mode
$ pip install -e .
# make changes under nbs/ directory
# ...
# compile to have changes apply to THU_Coursework_Machine_Learning_for_Big_Data
$ nbdev_prepare
```
## Usage
我们在学习清华大学《大数据机器学习》以及《大数据分析》两门课程完成作业的同时，也形成了一个简单的机器学习与数据分析库，对李航《统计学习方法》上的部分代码做了实现和可视化，你可以通过安装我们的库来复用我们写的代码逻辑。
### Installation
Install latest from the GitHub
[repository](https://github.com/Open-Book-Studio/THU-Coursework-Machine-Learning-for-Big-Data):
``` sh
$ pip install git+https://github.com/Open-Book-Studio/THU-Coursework-Machine-Learning-for-Big-Data.git
```
<!--
or from [conda][conda]
```sh
$ conda install -c yecanming6666 thu_big_data_ml
``` -->
or from
[pypi](https://pypi.org/project/THU-Coursework-Machine-Learning-for-Big-Data/)
``` sh
$ pip install thu_big_data_ml
```
### Documentation
Documentation can be found hosted on this
https://thu-coursework-machine-learning-for-big-data-docs.vercel.app/ .
Additionally you can find package manager specific guidelines on
[pypi](https://pypi.org/project/THU-Coursework-Machine-Learning-for-Big-Data/)
respectively.
<!-- [conda][conda] and -->
<!-- [conda]: https://anaconda.org/Open-Book-Studio/THU-Coursework-Machine-Learning-for-Big-Data -->
## How to use
Fill me in please! Don’t forget code examples:
``` python
1+1
```
2
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