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Machine Learning for Hackers : Case Studies and Algorithms to Get You Started

Machine Learning for Hackers : Case Studies and Algorithms to Get You Started Paperback - 2012

by John Myles White; Drew Conway

  • Used
  • very good
  • Paperback

Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data. Readers learn machine learning and statistics tools in a practical fashion, using black-box solutions and case studies instead of a traditional math-heavy presentation.

Description

O'Reilly Media, Incorporated, 2012. Paperback. Very Good. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.Dust jacket quality is not guaranteed.
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Details

  • Title Machine Learning for Hackers : Case Studies and Algorithms to Get You Started
  • Author John Myles White; Drew Conway
  • Binding Paperback
  • Edition INTERNATIONAL ED
  • Condition Used - Very Good
  • Pages 320
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media, Incorporated
  • Date 2012
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Price on Product - Canadian, Table of Contents
  • Bookseller's Inventory # G1449303714I4N00
  • ISBN 9781449303716 / 1449303714
  • Weight 1.14 lbs (0.52 kg)
  • Dimensions 9.2 x 7.06 x 0.75 in (23.37 x 17.93 x 1.91 cm)
  • Library of Congress subjects Computer algorithms, Electronic data processing - Automation
  • Dewey Decimal Code 005.1

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Citations

  • Reference and Research Bk News, 04/01/2012, Page 190

About the author

Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.

John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.