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VW cracks down on executive pay after diesel scandal
German car maker returns to profit and posts record sales in 2016 despite emissions testing furore.


BA owner IAG's profits hit by weak pound
The owner of British Airways and Iberia reports higher profits, despite the impact of sterling's weakness.


East Africa to track trucks from Mombasa port to stop theft
Uganda, Kenya and Rwanda adopt a truck-tracking system to prevent theft and speed up goods in transit.


Royal Bank of Scotland losses more than treble to £7bn
The bank, which is 72%-owned by taxpayers, reports its ninth consecutive year of losses.


Trump's Treasury Secretary targets tax reform 'by August'
In his first TV interview Steven Mnuchin promises deregulation and tax cuts to boost growth.



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Death and Tax Cuts
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Data Smart: Using Data Science to Transform Information into Insight

by John W. Foreman

Published by Wiley


Most people are approaching data science all wrong. Here's how to do it right.

Not to disillusion you, but data scientists are not mystical practitioners of magical arts. Data science is something you can do. Really. This book shows you the significant data science techniques, how they work, how to use them, and how they benefit your business, large or small. It's not about coding or database technologies. It's about turning raw data into insight you can act upon, and doing it as quickly and painlessly as possible.

Roll up your sleeves and let's get going.

Relax -- it's just a spreadsheet

Visit the companion website at www.wiley.com/go/datasmart to download spreadsheets for each chapter, and follow them as you learn about:

  • Artificial intelligence using the general linear model, ensemble methods, and naive Bayes
  • Clustering via k-means, spherical k-means, and graph modularity
  • Mathematical optimization, including non-linear programming and genetic algorithms
  • Working with time series data and forecasting with exponential smoothing
  • Using Monte Carlo simulation to quantify and address risk
  • Detecting outliers in single or multiple dimensions
  • Exploring the data-science-focused R language


pub date: 2013-11-04 | Paperback | 9781118661468