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https://github.com/abaofromcug/i-love-python
this reponsitory is for python or Jupyder
https://github.com/abaofromcug/i-love-python
jupyter-notebook machine-learning matplotlib numpy python3 scipy
Last synced: about 1 month ago
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this reponsitory is for python or Jupyder
- Host: GitHub
- URL: https://github.com/abaofromcug/i-love-python
- Owner: AbaoFromCUG
- Created: 2017-05-24T16:03:08.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-03-13T01:32:16.000Z (almost 7 years ago)
- Last Synced: 2024-10-12T23:11:44.014Z (3 months ago)
- Topics: jupyter-notebook, machine-learning, matplotlib, numpy, python3, scipy
- Language: Jupyter Notebook
- Size: 11.7 MB
- Stars: 2
- Watchers: 0
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# I-love-python
this reponsitory is for python or Jupyder
### about jupyder
> IPython is a command shell for interactive computing in multiple programming languages,
> originally developed for the Python programming language, that offers introspection,
> rich media, shell syntax, tab completion, and history. IPython provides the following features:1. Interactive shells (terminal and Qt-based).
2. A browser-based notebook with support for code, text, mathematical expressions, inline plots and other media.
3. Support for interactive data visualization and use of GUI toolkits.
4. Flexible, embeddable interpreters to load into one's own projects.
5. Tools for parallel computing.
-----wikipedia> IPython是用于多种编程语言的交互式计算的命令外壳,最初是为Python编程语言开发的,它提供了内省,
> 富媒体,shell语法,制表符和历史记录。IPython提供以下功能:1. 交互式shell(基于终端和基于Qt的)。
2. 基于浏览器的笔记本,支持代码,文本,数学表达,内联绘图和其他媒体。
3. 支持交互式数据可视化和GUI工具包的使用。
4. 灵活的,可嵌入的解释器加载到自己的项目中。
5. 并行计算工具。在jupyder 中,正在做100道python题目来提高我的python水平,python太重要了,但是目前我还是不够熟悉这门语言的结构
但是在jupyder中我接触了makedown,感觉用起来超级赞
### about python
天啊,这个没什么好说的貌似,辣鸡的一匹啊
本来想做数据挖掘的,但是数学逻辑不过硬啊,想着先学了数据结构再说吧### 新开始学的爬虫(貌似之前学了爬虫但是中途跑丢了)
这次是我第一次用python3写的东西,天啊感觉python3和2的差距好大,之前的东西都要修改了大概·### 开始了深入的爬虫学习
在某网站上爬下了约300张的图片,尽管设置了timeout,但是貌似jupyter到最后仍然挂了### 掉入数据挖掘的坑
无聊的时候就是喜欢不停的尝试新的东西,
#### 安装Numpy(含有mkl),Scipy,以及scikit-learn等轮子,建议去http://www.lfd.uci.edu/~gohlke/pythonlibs/ 下载对于文件,
然后本地用pip安装,注意路径,还有就是32位的选择32,64位的选择amd64的,这是pip 或者easy_install的分发源头(我是这么想的)
参考了http://www.cnblogs.com/LuffySir/p/6054238.html 感谢原作者,通俗易懂,当然StackOverflow也有讲这个,奈何理解力有限