大数据/数据挖掘/推荐系统/机器学习相关资源
Share my personal resources，本文贡献者为Zhe Yu
书籍
各种书~各种ppt~更新中~ http://pan.baidu.com/s/1EaLnZ
机器学习经典书籍小结 http://www.cnblogs.com/snake-hand/archive/2013/06/10/3131145.html
机器学习&深度学习经典资料汇总 http://www.thebigdata.cn/JiShuBoKe/13299.html
视频
浙大数据挖掘系列 http://v.youku.com/v_show/id_XNTgzNDYzMjg=.html?f=2740765
用Python做科学计算 http://www.tudou.com/listplay/fLDkg5e1pYM.html
R语言视频 http://pan.baidu.com/s/1koSpZ
Hadoop视频 http://pan.baidu.com/s/1b1xYd
42区 . 技术 . 创业 . 第二讲 http://v.youku.com/v_show/id_XMzAyMDYxODUy.html
加州理工学院公开课：机器学习与数据挖掘 http://v.163.com/special/opencourse/learningfromdata.html
QQ群
机器学习&模式识别 246159753
数据挖掘机器学习 236347059
推荐系统 274750470
36大数据 80958753
Github
推荐系统
推荐系统开源软件列表汇总和评点 http://in.sdo.com/?p=1707
Mrec(Python) https://github.com/mendeley/mrec
Crab(Python) https://github.com/muricoca/crab
Python-recsys(Python) https://github.com/ocelma/python-recsys
CofiRank(C++) https://github.com/markusweimer/cofirank
GraphLab(C++) https://github.com/graphlab-code/graphlab
EasyRec(Java) https://github.com/hernad/easyrec
Lenskit(Java) https://github.com/grouplens/lenskit
Mahout(Java) https://github.com/apache/mahout
Recommendable(Ruby) https://github.com/davidcelis/recommendable
库
NLTK https://github.com/nltk/nltk
Pattern https://github.com/clips/pattern
Pyrallel https://github.com/pydata/pyrallel
Theano https://github.com/Theano/Theano
Pylearn2 https://github.com/lisa-lab/pylearn2
TextBlob https://github.com/sloria/TextBlob
MBSP https://github.com/clips/MBSP
Gensim https://github.com/piskvorky/gensim
Langid.py https://github.com/saffsd/langid.py
Jieba https://github.com/fxsjy/jieba
xTAS https://github.com/NLeSC/xtas
NumPy https://github.com/numpy/numpy
SciPy https://github.com/scipy/scipy
Matplotlib https://github.com/matplotlib/matplotlib
scikit-learn https://github.com/scikit-learn/scikit-learn
Pandas https://github.com/pydata/pandas
MDP http://mdp-toolkit.sourceforge.net/
PyBrain https://github.com/pybrain/pybrain
PyML http://pyml.sourceforge.net/
Milk https://github.com/luispedro/milk
PyMVPA https://github.com/PyMVPA/PyMVPA
博客
周涛 http://blog.sciencenet.cn/home.php?mod=space&uid=3075
Greg Linden http://glinden.blogspot.com/
Marcel Caraciolo http://aimotion.blogspot.com/
RsysChina http://weibo.com/p/1005051686952981
推荐系统人人小站 http://zhan.renren.com/recommendersystem
阿稳 http://www.wentrue.net
梁斌 http://weibo.com/pennyliang
刁瑞 http://diaorui.net
guwendong http://www.guwendong.com
xlvector http://xlvector.net
懒惰啊我 http://www.cnblogs.com/flclain/
free mind http://blog.pluskid.org/
lovebingkuai http://lovebingkuai.diandian.com/
LeftNotEasy http://www.cnblogs.com/LeftNotEasy
LSRS 2013 http://graphlab.org/lsrs2013/program/
Google小组 https://groups.google.com/forum/#!forum/resys
Journal of Machine Learning Research http://jmlr.org/
在线的机器学习社区 http://www.52ml.net/16336.html
清华大学信息检索组 http://www.thuir.cn
我爱自然语言处理 http://www.52nlp.cn/
36大数据 http://www.36dsj.com/
文章
心中永远的正能量 http://blog.csdn.net/yunlong34574
机器学习最佳入门学习资料汇总 http://article.yeeyan.org/view/22139/410514
Books for Machine Learning with R http://www.52ml.net/16312.html
是什么阻碍了你的机器学习目标？ http://www.52ml.net/16436.htm
推荐系统初探 http://yongfeng.me/attach/rs-survey-zhang-slices.pdf
推荐系统中协同过滤算法若干问题的研究 http://pan.baidu.com/s/1bnjDBYZ
Netflix 推荐系统：第一部分 http://blog.csdn.net/bornhe/article/details/8222450
Netflix 推荐系统：第二部分 http://blog.csdn.net/bornhe/article/details/8222497
探索推荐引擎内部的秘密 http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy1/index.html
推荐系统resys小组线下活动见闻2009-08-22 http://www.tuicool.com/articles/vUvQVn
Recommendation Engines Seminar Paper, Thomas Hess, 2009: 推荐引擎的总结性文章http://www.slideshare.net/antiraum/recommender-engines-seminar-paper
Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions, Adomavicius, G.; Tuzhilin, A., 2005 http://dl.acm.org/citation.cfm?id=1070751
A Taxonomy of RecommenderAgents on the Internet, Montaner, M.; Lopez, B.; de la Rosa, J. L., 2003http://www.springerlink.com/index/KK844421T5466K35.pdf
A Course in Machine Learning http://ciml.info/
基于mahout构建社会化推荐引擎 http://www.doc88.com/p-745821989892.html
个性化推荐技术漫谈 http://blog.csdn.net/java060515/archive/2007/04/19/1570243.aspx
Design of Recommender System http://www.slideshare.net/rashmi/design-of-recommender-systems
How to build a recommender system http://www.slideshare.net/blueace/how-to-build-a-recommender-system-presentation
推荐系统架构小结 http://blog.csdn.net/idonot/article/details/7996733
System Architectures for Personalization and Recommendation http://techblog.netflix.com/2013/03/system-architectures-for.html
The Netflix Tech Blog http://techblog.netflix.com/
百分点推荐引擎——从需求到架构http://www.infoq.com/cn/articles/baifendian-recommendation-engine
推荐系统 在InfoQ上的内容 http://www.infoq.com/cn/recommend
推荐系统实时化的实践和思考 http://www.infoq.com/cn/presentations/recommended-system-real-time-practice-thinking
质量保证的推荐实践 http://www.infoq.com/cn/news/2013/10/testing-practice/
推荐系统的工程挑战 http://www.infoq.com/cn/presentations/Recommend-system-engineering
社会化推荐在人人网的应用 http://www.infoq.com/cn/articles/zyy-social-recommendation-in-renren/
利用20%时间开发推荐引擎 http://www.infoq.com/cn/presentations/twenty-percent-time-to-develop-recommendation-engine
使用Hadoop和 Mahout实现推荐引擎 http://www.jdon.com/44747
SVD 简介 http://www.cnblogs.com/FengYan/archive/2012/05/06/2480664.html
Netflix推荐系统：从评分预测到消费者法则 http://blog.csdn.net/lzt1983/article/details/7696578