Add some md docs

InstallPython.md

@@ -0,0 +1,63 @@
+# Installing Python environments
+
+这章，讲解如何安装Python的环境
+
+## 1. Windows
+
+### 安装Anaconda
+
+由于Anaconda集成了大部分的python包，因此能够很方便的开始使用。由于网络下载速度较慢，因此推荐使用镜像来提高下载的速度。
+
+在这里找到适合自己的安装文件，然后下载
+https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/
+
+设置软件源 https://mirror.tuna.tsinghua.edu.cn/help/anaconda/
+```
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
+conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
+conda config --set show_channel_urls yes
+```
+
+### 安装Pytorch
+```
+conda install pytorch -c pytorch 
+pip3 install torchvision
+```
+
+
+## 2. Linux
+
+### 安装pip
+```
+sudo apt-get install python3-pip
+```
+
+### 设置PIP源
+```
+pip config set global.index-url 'https://mirrors.ustc.edu.cn/pypi/web/simple'
+```
+
+### 安装常用的包
+```
+pip install -r requirements.txt
+```
+
+或者手动安装
+```
+sudo pip install scipy
+sudo pip install scikit-learn
+sudo pip install numpy
+sudo pip install matplotlib
+sudo pip install pandas
+sudo pip install ipython
+sudo pip install jupyter
+```
+
+### 安装pytorch
+到[pytorch 官网](https://pytorch.org)，根据自己的操作系统、CUDA版本，选择合适的安装命令。
+
+例如Linux, Python3.5, CUDA 9.0：
+```
+pip3 install torch torchvision
+```
+

README.md

@@ -1,31 +1,8 @@
 # Python和机器学习的notebook
 
-本notebook教程包含了一些使用Python来学习机器学习的教程。通过本教程能够引导学习Python的基础知识和机器学习的背景和实际编程。
+本notebook教程包含了一些使用Python来学习机器学习的教程，通过本教程能够引导学习Python的基础知识和机器学习的背景和实际编程。
 
 
-## References
-更多的学习资料，可以自行在下属列表找找到适合自己的学习资料。
-
-### Python & IPython
-* [Python教程](https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000)
-* [Python-Lectures](https://github.com/rajathkmp/Python-Lectures)
-* [A gallery of interesting Jupyter Notebooks](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks)
-* [IPython tutorials](https://nbviewer.jupyter.org/github/ipython/ipython/blob/master/examples/IPython%20Kernel/Index.ipynb)
-* [Examples from the IPython mini-book](https://github.com/rossant/ipython-minibook)
-* [Code of the IPython Cookbook, Second Edition (2018)](https://github.com/ipython-books/cookbook-2nd-code)
-* [scientific-python-lectures](http://nbviewer.jupyter.org/github/jrjohansson/scientific-python-lectures/tree/master/)
-
-
-### Libs
-* [numpy](http://www.numpy.org/)
-* [matplotlib - 2D and 3D plotting in Python](http://nbviewer.jupyter.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-4-Matplotlib.ipynb)
-* [scipy](https://www.scipy.org/)
-* [pytorch](https://pytorch.org/)
-* [tensorflow](https://www.tensorflow.org/)
-
-
-### Machine learning
-
-* [ipython-notebooks: A collection of IPython notebooks covering various topics](https://github.com/jdwittenauer/ipython-notebooks)
-* [Learn Data Science](http://learnds.com/)
-* [AM207 2016](https://github.com/AM207/2016/tree/master)
+内容
+* [安装Python环境](InstallPython.md)
+* [参考资料等](References.md)

References.md

@@ -0,0 +1,52 @@
+# References
+更多的学习资料，可以自行在下属列表找找到适合自己的学习资料。
+
+## Python & IPython
+* [Python教程](https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000)
+* [Python-Lectures](https://github.com/rajathkmp/Python-Lectures)
+* [A gallery of interesting Jupyter Notebooks](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks)
+* [IPython tutorials](https://nbviewer.jupyter.org/github/ipython/ipython/blob/master/examples/IPython%20Kernel/Index.ipynb)
+* [Examples from the IPython mini-book](https://github.com/rossant/ipython-minibook)
+* [Code of the IPython Cookbook, Second Edition (2018)](https://github.com/ipython-books/cookbook-2nd-code)
+* [scientific-python-lectures](http://nbviewer.jupyter.org/github/jrjohansson/scientific-python-lectures/tree/master/)
+
+
+## Libs
+* [numpy](http://www.numpy.org/)
+* [matplotlib - 2D and 3D plotting in Python](http://nbviewer.jupyter.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-4-Matplotlib.ipynb)
+* [scipy](https://www.scipy.org/)
+* [pytorch](https://pytorch.org/)
+* [tensorflow](https://www.tensorflow.org/)
+
+
+## Machine learning
+
+* [ipython-notebooks: A collection of IPython notebooks covering various topics](https://github.com/jdwittenauer/ipython-notebooks)
+* [Learn Data Science](http://learnds.com/)
+* [AM207 2016](https://github.com/AM207/2016/tree/master)
+
+
+## Awesome series
+* [Awesome Cmputer Vision](https://github.com/jbhuang0604/awesome-computer-vision)
+* [Awesome Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning)
+* [Awesome - Most Cited Deep Learning Papers](https://github.com/terryum/awesome-deep-learning-papers)
+* [Awesome Deep Vision](https://github.com/kjw0612/awesome-deep-vision)
+* [Awesome 3D Reconstruction](https://github.com/openMVG/awesome_3DReconstruction_list)
+
+## Lectures
+* [Machine Learning](https://www.coursera.org/learn/machine-learning)
+* [CS229: Machine Learning](http://cs229.stanford.edu/)
+* [CS 20: Tensorflow for Deep Learning Research](http://web.stanford.edu/class/cs20si/index.html)
+* [CS 294: Deep Reinforcement Learning, UC Berkeley](http://rll.berkeley.edu/deeprlcourse/)
+* [Deep Learning Book](https://github.com/exacity/deeplearningbook-chinese)
+* [Machine Learning Crash Course with TensorFlow APIs](https://developers.google.cn/machine-learning/crash-course/)
+* [ Nvidia DLI](https://www.nvidia.com/zh-cn/deep-learning-ai/education/)
+* [Introduction to Machine Learning](https://webdocs.cs.ualberta.ca/~nray1/CMPUT466_551.htm)
+* [Computer Vision @ ETHZ](http://cvg.ethz.ch/teaching/compvis/)
+* [SFMedu: A Structure from Motion System for Education](http://robots.princeton.edu/courses/SFMedu/)
+* [Scene understanding of computer vision](http://vision.princeton.edu/courses/COS598/2014sp/)
+* [Autonomous Navigation for Flying Robots](http://vision.in.tum.de/teaching/ss2015/autonavx)
+* [Multiple View Geometry](http://vision.in.tum.de/teaching/ss2015/mvg2015)
+* [Deep Learning for Self-Driving Cars](https://selfdrivingcars.mit.edu/)
+* [史上最全TensorFlow学习资源汇总](https://www.toutiao.com/a6543679835670053380/)
+* [Oxford Deep NLP 2017 course](https://github.com/oxford-cs-deepnlp-2017/lectures) 

install_python.ipynb

@@ -1,94 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Chapter 2. Installing Python environments\n",
-    "\n",
-    "这章，讲解如何安装Python的环境"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Windows\n",
-    "\n",
-    "### 安装Anaconda\n",
-    "\n",
-    "由于Anaconda集成了大部分的python包，因此能够很方便的开始使用。由于网络下载速度较慢，因此推荐使用镜像来提高下载的速度。\n",
-    "\n",
-    "在这里找到适合自己的安装文件，然后下载\n",
-    "https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/\n",
-    "\n",
-    "设置软件源 https://mirror.tuna.tsinghua.edu.cn/help/anaconda/\n",
-    "```\n",
-    "conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/\n",
-    "conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/\n",
-    "conda config --set show_channel_urls yes\n",
-    "```\n",
-    "\n",
-    "### 安装Pytorch\n",
-    "```\n",
-    "conda install pytorch -c pytorch \n",
-    "pip3 install torchvision\n",
-    "```\n",
-    "\n",
-    "\n",
-    "## Linux\n",
-    "\n",
-    "### 安装pip\n",
-    "```\n",
-    "sudo apt-get install python3-pip\n",
-    "```\n",
-    "\n",
-    "### 设置PIP源\n",
-    "```\n",
-    "pip config set global.index-url 'https://mirrors.ustc.edu.cn/pypi/web/simple'\n",
-    "```\n",
-    "\n",
-    "### 安装常用的包\n",
-    "```\n",
-    "sudo pip install scipy\n",
-    "sudo pip install scikit-learn\n",
-    "sudo pip install numpy\n",
-    "sudo pip install matplotlib\n",
-    "sudo pip install pandas\n",
-    "sudo pip install ipython\n",
-    "sudo pip install jupyter\n",
-    "```\n",
-    "\n",
-    "### 安装pytorch\n",
-    "到[pytorch 官网](https://pytorch.org)，根据自己的操作系统、CUDA版本，选择合适的安装命令。\n",
-    "\n",
-    "例如Linux, Python3.5, CUDA 9.0：\n",
-    "```\n",
-    "pip3 install torch torchvision\n",
-    "```\n",
-    "\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.5.2"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}