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

4.5 out of 5 stars 386 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

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
--This text refers to an alternate kindle_edition edition.

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.
--This text refers to an alternate kindle_edition edition.

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Customer reviews

4.5 out of 5 stars
4.5 out of 5
386 customer ratings
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Reviewed in the United States on October 4, 2016
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Reviewed in the United States on February 23, 2020
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Reviewed in the United States on February 4, 2016
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Reviewed in the United States on March 10, 2015
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Reviewed in the United States on March 20, 2018
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Top international reviews

Daniel Bryant
5.0 out of 5 stars A perfect introduction to the data science, which helped me fully understand and pull-together lots of related concepts
Reviewed in the United Kingdom on January 16, 2014
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53 people found this helpful
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FireTV is unreliable as HELL !
2.0 out of 5 stars Waffles on and takes forever to get to the point
Reviewed in the United Kingdom on April 17, 2017
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6 people found this helpful
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Varzoth
4.0 out of 5 stars A good book for a business person to learn about data ...
Reviewed in the United Kingdom on March 19, 2018
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KattyBent
5.0 out of 5 stars A clear and well put together book.
Reviewed in the United Kingdom on January 31, 2016
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Steve Koll
5.0 out of 5 stars Great easy-reading book on datascience for manager
Reviewed in Germany on August 4, 2016
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21 people found this helpful
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Alvaro Flores
5.0 out of 5 stars Para aspirantes a analista de datos es muy bueno
Reviewed in Mexico on July 20, 2016
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Jim-C
5.0 out of 5 stars Great intro and quick refresher course
Reviewed in Germany on November 24, 2019
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Lawrence Sanjay
5.0 out of 5 stars The perfect book to get into ai for any middle manager business and IT
Reviewed in India on July 21, 2016
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Derecj J Toker
5.0 out of 5 stars Incredible book
Reviewed in Canada on March 10, 2020
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bhaskar mishra
5.0 out of 5 stars Good Read
Reviewed in India on March 8, 2020
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Adriano
5.0 out of 5 stars Perfetto per iniziare, ma anche per chi ha già esperienza
Reviewed in Italy on October 27, 2017
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CustomerKing
5.0 out of 5 stars Molto ben fatto ed quilibrato
Reviewed in Italy on January 9, 2014
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Amazon Customer
4.0 out of 5 stars Good for knowledge structuring, not for solving problems
Reviewed in Canada on February 3, 2016
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sv
2.0 out of 5 stars Not a good read. The language is long winded
Reviewed in India on February 13, 2018
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Martin Sykora
4.0 out of 5 stars Four Stars
Reviewed in Canada on June 7, 2018
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