kaggle 冠军 owen zhang 关于kaggle比赛数据处理的ppt

一本经典的误差分析的教材。本书是《物理科学中的数据处理和误差分析》对应的英文版，是清晰版，电子书格式为pdf。DOI： 10.1063/1.4823194

资源包主要内容： （1）各个步骤需要的实验源码 （2）各个步骤生成的text、xml以及csv文件 （3）实验过程的大致说明，帮助更好的理解实验 包含整个实验过程的所有资源，代码完整，附带实验说明，易于理解。 原reviews.xml有点不合适，用资源包里的替换掉就好。 最后，祝大家能早日做完实验，早回家。

2016级山东大学软件工程数据科学导论崔院长实验课，包含实验一，二，五，六，七，九

山东大学数据科学导论上课全部课件及复习资料。

三元闭包现象的数据验证，1.整个实验以矩阵为操作对象，邻接矩阵还是很有作用的，也便于理解 2.R语言中有network数据结构，有IGraph包，计算聚集系数与介数都有已封装得函数。

Data Science for Business英文原版PDF Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Review, 'A must-read resource for anyone who is serious about embracing the opportunity of big data.', -- Craig Vaughan, Global Vice President at SAP, 'This book goes beyond data analytics 101. It's the essential guide for those of us (all of us?) whose businesses are built on the ubiquity of data opportunities and the new mandate for data-driven decision-making.', --Tom Phillips, CEO of Media6Degrees and Former Head of Google Search and Analytics, 'Data is the foundation of new waves of productivity growth, innovation, and richer customer insight. Only recently viewed broadly as a source of competitive advantage, dealing well with data is rapidly becoming table stakes to stay in the game. The authors' deep applied experience makes this a must read--a window into your competitor's strategy.', -- Alan Murray, Serial Entrepreneur; Partner at Coriolis Ventures, 'This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data.', -- Ron Bekkerman, Chief Data Officer at Carmel Ventures, 'A great book for business managers who lead or interact with data scientists, who wish to better understand the principles and algorithms available without the technical details of single-disciplinary books.', -- Ronny Kohavi, Partner Architect at Microsoft Online Services Division, About the Author, Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs. His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing., Tom Fawcett holds a Ph.D. in machine learning and has worked in industry R&D for more than two decades for companies such as GTE Laboratories, NYNEX/Verizon Labs, and HP Labs. His published work has become standar