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晒出你见过最好的”机器学习“资源!有没有优秀经管资源,是牛人和弱逼的最大区别!   [推广有奖]

111
我为统计而来 学生认证  发表于 2016-11-29 17:42:33
需要具备扎实的数学、统计、优化、计算机等多门交叉学科的理论与实践!

112
jgchen1966 发表于 2016-11-29 19:54:53
http://web.stanford.edu/~hastie/pub.htm
        Books
        Papers - 2016
        Papers - 2015
        Papers - 2014
        Papers - 2013
        Papers - 2012
        Papers - 2011
        Papers - 2010
        Papers - 2009
        Papers - 2008
        Papers - 2007
        Papers - 2006
        Papers - 2005
        Papers - 2004
        Papers - 2003
        Papers - 2002
        Papers - 2001
        Papers - 2000
        Papers - 1999
        Papers - 1998
        Papers - 1997
        Papers - 1996
        Papers - 1995
        Papers - 1994
        Papers - 1993
        Papers - 1992
        Papers - 1991
        Papers - 1990
        Papers - 1987
        Papers - 1986
        Thesis - 1984

113
jgchen1966 发表于 2016-11-29 19:59:34
要读,就读大师的原文原著,既使读懂一分,也比读其它收获大,再列两位大师级的个人网页:
http://is.tuebingen.mpg.de/person/bs
Bernhard Schölkopf
My scientific interests are in the field of machine learning and inference from empirical data. In particular, I study kernel methods for extracting regularities from possibly high-dimensional data. These regularities are usually statistical ones, however, in recent years I have also become interested in methods for finding causal structures that underly statistical dependences. I have worked on a number of different applications of machine learning - in data analysis, you get "to play in everyone's backyard." Most recently, I have been trying to play in the backyard of astronomers and photographers.

I am heading the Department of Empirical Inference; to learn more about our work, take a look at the Department Overview.

Many of my papers can downloaded if you click on the tab "publications;" alternatively, from http://www.kernel-machines.org/ or from arxiv.  Some additional links:

First chapter of our book Learning with Kernels.
Review paper on kernel methods in the Annals of Statistics.
Short high-level introduction on statistical learnig theory (in German) that appeared in the 2004 Jahrbuch of the Max Planck Society.
Obituary for Alexej Chervonenkis (NIPS 2014).
With the growing interest in (how to make money with) big data, machine learning has significantly gained in popularity. We have published an article in the German newspaper FAZ, discussing some of the implications. Disclaimer: the text that appears above our names was neither written nor approved by us.
A children's book
Photographs: view of the Alps from the southern black forest, a rainbow in La Palma, a lunar eclipse in 2007, the Andromeda galaxy, the Milky Way on the Roque de los Muchachos, the North America Nebula, the constellation Orion with Barnard's loop, and finally a picture of a beautiful northern light, which I took a few years ago from the plane, on the way home from a conference in Vancouver. I always try to get a window seat when flying home from the North American west coast - it is surprizingly common to see northern lights. Looking at the night sky is a fascinating and humbling experience.
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114
jgchen1966 发表于 2016-11-29 20:01:49
最后,最值得纪念的:Leo Breiman,randomForest 创始人。
http://www.stat.berkeley.edu/~breiman/papers.html
513.pdf
518.pdf
adaptbag99.pdf
arc97.pdf
arcall.pdf
arcall96.pdf
arcing-the-edge.pdf
bagging.pdf
BAtrees.pdf
curds-whey-all.pdf
curds-whey-justfigs.pdf
curds-whey-justtables.pdf
curds-whey-justtext.pdf
DB-CART.pdf
games.pdf
half&half.pdf
nldiscanace.pdf
notes_on_random_forests_v2.pdf
OOBestimation.pdf
pastebite.pdf
pcart.pdf
random-forests.pdf
randomforest2001.pdf
randomforests-rev.pdf
SF_Manual.pdf
siamtalk2003.pdf
some_theory2000.pdf
some_theory2001.pdf
Using_random_forests_V3.0.pdf
Using_random_forests_v3.00.pdf
Using_random_forests_V3.1.pdf
Using_random_forests_v4.0.old.pdf
Using_random_forests_v4.0.pdf
wald2002-1.pdf
wald2002-2.pdf
wald2002-3.pdf
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115
karst 发表于 2016-11-29 21:24:45

116
蜗牛1328 发表于 2016-11-29 23:16:07

回帖奖励 +5

系统的学习方法也很重要

117
怡红公子下凡 发表于 2016-11-30 09:48:21

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互相学习

118
recardo 发表于 2016-11-30 10:24:45 来自手机
中华励志网www.zhlzw.com中名著阅读,有古今中外各类经典图书在线阅读资源,比如弗里德曼《资本主义与自由》,马歇尔《经济学原理》,哈耶克《个人主义与经济秩序》,同时也有亚里士多德《形而上学》黑格尔《精神现象学》等经典名著。进入网页后搜索书名或作者即可。祝你读书愉快学有所成!

119
建宇 发表于 2016-12-1 11:13:46
[tongue]

120
xuyan12311 发表于 2016-12-1 15:33:17

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