@@ -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 | |||||
``` | |||||
@@ -1,31 +1,8 @@ | |||||
# Python和机器学习的notebook | # 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) |
@@ -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) |
@@ -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 | |||||
} |