== 人工智能和机器学习 AI&ML ==

我关心的AI、ML的分支领域：

我的csdn博客：== Deep Learning 和 Knowledge Graph ==

（有关DL&KG的资料都在这里）

http://blog.csdn.net/yyhustim/article/details/8558665

重要的链接：

AI on the Web

http://aima.cs.berkeley.edu/ai.html

Best Papers vs. Top Cited Papers in Computer Science (since 1996)

http://arnetminer.org/conferencebestpapers%3Bjsessionid=E0A30E1D0F6EBD1F713AB5C29B79D8F7.tt

Machine Learning Surveys

http://www.mlsurveys.com/

UC Irvine Machine Learning Repository

http://archive.ics.uci.edu/ml/

水木社区 → 学术科学 → AI（人工智能）版

http://www.newsmth.net/bbsdoc.php?board=AI&ftype=6

大家：

John McCarthy's Home Page

http://www-formal.stanford.edu/jmc/frames.html

Marvin Minsky's Home Page

http://web.media.mit.edu/~minsky/

Patrick Henry Winston's Home Page

http://people.csail.mit.edu/phw/index.html

Peter Norvig 

http://norvig.com/index.html

Andrew Ng's homepage

http://ai.stanford.edu/~ang/index.html

阅读列表：

How to do Research At the MIT AI Lab

http://dspace.mit.edu/handle/1721.1/41487

READING LIST FOR THE QUALIFYING EXAMINATION IN ARTIFICIAL INTELLIGENCE

http://www-cs-students.stanford.edu/~pdoyle/quail/syllabus/syllabus.html

http://www-formal.stanford.edu/eyal/qual/revised-list.ps （对应的ps文档）

Intelligent Systems - PhD Qualifying Exam Reading List

http://www.cc.gatech.edu/is/is-qual/readings/index.html

AI FAQ Index

http://www.faqs.org/faqs/ai-faq/

著作：

Artificial Intelligence: A Modern Approach

http://aima.cs.berkeley.edu/

（A practical guide to the AIMA Python code -1: http://blog.youxu.info/2007/10/04/a-practical-guide-to-the-aima-python-code-1/）

Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp

http://norvig.com/paip.html

Pattern Recognition and Machine Learning

http://research.microsoft.com/en-us/um/people/cmbishop/PRML/index.htm

Machine Learning, Tom Mitchell, McGraw Hill, 1997.

http://www.cs.cmu.edu/~tom/mlbook.html

Artificial Intelligence: Foundations of Computational Agents

http://www.cs.ubc.ca/~poole/aibook/html/ArtInt.html

Machine Learning: a Probabilistic Perspective

http://www.cs.ubc.ca/~murphyk/MLbook/index.html

期刊和会议：

Foundations and Trends in Machine Learning

http://www.nowpublishers.com/journals/Foundations%20and%20Trends%C2%AE%20in%20Machine%20Learning/5

- 豆瓣上的一个总结：http://www.douban.com/note/255373634/

编程：

scikit-learn: machine learning in Python

http://projects.scipy.org/scikits（这是developer site，官网似乎被墙了）

Orange，使用Python脚本语言的机器学习组件和可视化编程接口

http://orange.biolab.si/

机器学习软件Weka

http://www.cs.waikato.ac.nz/~ml/

Machine Learning Open Source Software

http://jmlr.org/mloss/

http://mloss.org/software/

The Mobile Robot Programming Toolkit

http://www.mrpt.org/

== 一些LISP资源的链接 ==（我收集在csdn上的）

http://blog.csdn.net/yyhustim/article/details/8163704

What is the best way to get started in artificial intelligence programming?

http://stackoverflow.com/questions/4006793/what-is-the-best-way-to-get-started-in-artificial-intelligence-programming

Language Requirements for AI Development [closed]

http://stackoverflow.com/questions/3522064/language-requirements-for-ai-development

Good Programming Languages for AI

http://cseweb.ucsd.edu/classes/sp00/cse151/q1/crocha.html

a list of some machine learning software. Many of them are open source (the linked page shows the licenses).

http://www.dmoz.org/Computers/Artificial_Intelligence/Machine_Learning/Software/

The Apache Mahout™ machine learning library's goal is to build scalable machine learning libraries.

http://mahout.apache.org/

OpenPR Planning - sourceforge 

http://sourceforge.net/projects/openpr/files/code%20for%20an%20individual%20algorithm/

课程：

CS229  Machine Learning  Autumn 2012 

http://cs229.stanford.edu/

网易公开课 ：机器学习课程（CS229  Machine Learning）

http://v.163.com/special/opencourse/machinelearning.html

CS 188: Artificial Intelligence, Fall 2007

http://inst.eecs.berkeley.edu/~cs188/fa07/lectures.html

Computer Science 294 Practical Machine Learning (Spring 2008)

http://www.cs.berkeley.edu/~pliang/cs294-spring08/

【百度文库课程】机器学习 - 余凯&张潼

http://wenku.baidu.com/course/view/49e8b8f67c1cfad6195fa705

71237Z 统计学习基础 —2008年秋季

http://www.jdl.ac.cn/user/lyqing/statlearning/StatlLearning_handout.html

网站和博客：

Free Mind

http://freemind.pluskid.org/

丕子

http://www.zhizhihu.com/

谷子粒-Guzili

http://www.guzili.com/

leftnoteasy

http://www.cnblogs.com/LeftNotEasy/

JerryLead

http://www.cnblogs.com/jerrylead/tag/Machine%20Learning/default.html?page=1

Rachel Zhang

http://blog.csdn.net/abcjennifer/article/category/1173803

dreamcatcher 

http://stochasticquant.com/

v_JULY_v

http://blog.csdn.net/v_july_v/article/category/1061301

demonstrate

http://remonstrate.wordpress.com/ （要用梯子）

liulixiang.info

http://liulixiang.info/wiki/index.php?title=%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E6%8E%A8%E8%8D%90%E8%AE%BA%E6%96%87%E5%92%8C%E4%B9%A6%E7%B1%8D(%E8%BD%AC%E8%87%AA%E6%B0%B4%E6%9C%A8)

一些机器学习（Machine Learning）的网站总结

http://scienceroom.net/machine-learning-websites-collection-1370.html