Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking 1st Edition

4.4 out of 5 stars 469 ratings
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ISBN-13: 978-1449361327
ISBN-10: 1449361323
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From the Publisher

Data Science, Business Data Science from Scratch Data Science, big data R, Data Science, r programming Data Science ,Command Line Python, Data Science
Data Science for Business Data Science from Scratch Doing Data Science R for Data Science Data Science at the Command Line Python Data Science Handbook
What You Need to Know about Data Mining and Data-Analytic Thinking First Principles with Python Straight Talk from the Frontline Visualize, Model, Transform, Tidy, and Import Data Facing the Future with Time-Tested Tools Tools and Techniques for Developers

Editorial Reviews


"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 standard reading in data science.

Product details

  • Item Weight : 1.5 pounds
  • Paperback : 414 pages
  • ISBN-10 : 1449361323
  • ISBN-13 : 978-1449361327
  • Product Dimensions : 7 x 0.9 x 9.19 inches
  • Publisher : O'Reilly Media; 1st Edition (August 27, 2013)
  • Language: : English
  • Customer Reviews:
    4.4 out of 5 stars 469 ratings