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Author by : Malcolm Gladwell Languange Used : en Release Date : 2008-11-18 Publisher by : Penguin UK ISBN : 9780141903491 File Size : 46,8 Mb Total Download : 721
From the bestselling author of Blink and The Tipping Point, Malcolm Gladwell's Outliers: The Story of Success overturns conventional wisdom about genius to show us what makes an ordinary person an extreme overachiever. Why do some people achieve so much more than others? Can they lie so far out of the ordinary? In this provocative and inspiring book, Malcolm Gladwell looks at everyone from rock stars to professional athletes, software billionaires to scientific geniuses, to show that the story of success is far more surprising, and far more fascinating, than we could ever have imagined. He rev
Author by : Bruce Schneier Languange Used : en Release Date : 2012-01-27 Publisher by : John Wiley & Sons ISBN : 9781118239018 File Size : 50,5 Mb Total Download : 841
In today's hyper-connected society, understanding the mechanisms of trust is crucial. Issues of trust are critical to solving problems as diverse as corporate responsibility, global warming, and the political system. In this insightful and entertaining book, Schneier weaves together ideas from across the social and biological sciences to explain how society induces trust. He shows the unique role of trust in facilitating and stabilizing human society. He discusses why and how trust has evolved, why it works the way it does, and the ways the information society is changing everything.
Author by : Charu C. Aggarwal Languange Used : en Release Date : 2016-12-10 Publisher by : Springer ISBN : 9783319475783 File Size : 53,5 Mb Total Download : 772
This book provides comprehensive coverage of the field of outlier analysis from a computer science point of view. It integrates methods from data mining, machine learning, and statistics within the computational framework and therefore appeals to multiple communities. The chapters of this book can be organized into three categories: Basic algorithms: Chapters 1 through 7 discuss the fundamental algorithms for outlier analysis, including probabilistic and statistical methods, linear methods, proximity-based methods, high-dimensional (subspace) methods, ensemble methods, and supervised methods.