1、用贝叶斯模型计算我的妻子是否怀孕
http://www.r-bloggers.com/a-bayesian-model-to-calculate-whether-my-wife-is-pregnant-or-not
2、在基础R中使用插值法和平滑功能
http://www.r-bloggers.com/interpolation-and-smoothing-functions-in-base-r/
3、数据兵工厂里的武器：R vs Spark 【这个链接已经挂了~】
http://www.crayondata.com/blogs/tools-in-the-data-armoury-r-vs-spark/
4、最好的大数据、数据科学、数据挖掘和机器学习播客视频大全
http://www.kdnuggets.com/2015/06/best-big-data-data-science-data-mining-machine-learning-podcasts.html
5、数据科学的线性模型导论
http://multithreaded.stitchfix.com/blog/2015/10/12/intro-linear-models/
6、黑客读物：数据统计
http://101.datascience.community/2015/10/21/statistics-for-hackers-slides-by-jake-vanderplas/
7、Apache Spark-执行概要
https://www.linkedin.com/pulse/apache-spark-executive-summary-alan-brown
8、随机vs非随机：如何叙述差异
http://www.kdnuggets.com/2015/10/random-pseudorandom.html
9、面向时间数据可视化技术的可视化调查**
http://survey.timeviz.net/
10、Python机器学习开源项目Top20
http://www.kdnuggets.com/2015/06/top-20-python-machine-learning-open-source-projects.html
11、区分付费内容（原生广告）和非付费内容
http://blog.kaggle.com/2015/10/30/dato-winners-interview-2nd-place-mortehu/
12、专业数据玩家必读：100篇开源大数据架构论文
https://www.linkedin.com/pulse/100-open-source-big-data-architecture-papers-anil-madan
文章
1、10个吸引人的数据可视化例子**
http://blog.hubspot.com/marketing/great-data-visualization-examples
2、智能应用程序（iA）-入门
https://ia.com/intelligent-applications-primer/
3、大数据-在IA中不再神秘**
https://ia.com/big-data-not-the-mystical-talisman-in-ia/
4、使用数据科学技能和科学方法的见解
http://businessoverbroadway.com/getting-insights-using-data-science-skills-and-the-scientific-method
5、算法经济
http://exchangemagazine.financial.thomsonreuters.com/articles/the-algorithm-economy
6、数据科学家……是在说我吗？！
http://thinktostart.com/a-data-scientist-who-me/
7、六种视角看人工智能的状态
https://medium.com/@VentureScanner/the-state-of-artificial-intelligence-in-six-visuals-8bc6e9bf8f32
8、大数据分析自动化
http://news.mit.edu/2015/automating-big-data-analysis-1016
9、福特如何使用大数据改变我们使用汽车的方式
http://www.forbes.com/sites/joannmuller/2015/10/22/how-ford-is-using-big-data-to-change-the-way-we-use-our-cars/
10、大地图告诉你美国如何发电**
https://www.washingtonpost.com/graphics/national/power-plants/
11、为什么DataViz会在无意中助长不平等**
http://stephanieevergreen.com/dataviz-inequality_pt1/
12、不断发展的信息图表：GIFographic来啦 **
http://immediatefuture.co.uk/blog/the-evolving-infographic-here-comes-the-gifographic/
13、数据科学的巨大创新尚未到来
http://blogs.gartner.com/alexander-linden/2015/08/27/massive-innovations-in-data-science-yet-to-come/
14、为什么Tracy-Widom的神秘统计法如此常用？
http://www.wired.com/2014/10/tracy-widom-mysterious-statistical-law/
15、我如何用Alteryx修复客户端数据库**
https://3danim8.wordpress.com/2015/10/09/how-alteryx-allowed-me-to-fix-problems-in-a-customer-created-database/
16、数据科学家并不是生来平等
http://businessoverbroadway.com/investigating-data-scientists-their-skills-and-team-makeup
17、物联网：缺失的部件
https://www.linkedin.com/pulse/20140923171256-1080580-internet-of-things-the-missing-pieces
18、招聘数据科学家：要找什么？
http://www.kdnuggets.com/2014/09/hiring-data-scientist-what-to-look-for.html
19、Nate Silver：大数据已经到达顶峰，这是一件好事
http://data-informed.com/nate-silver-big-data-has-peaked-and-thats-a-good-thing/