数据挖掘相关资料

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

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/

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