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Practical Data Science with R, Second Edition

Practical Data Science with R, Second Edition

Practical Data Science with R, Second Edition
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Practical Data Science with R, Second Edition Paperback - 2019

by Zumel, Nina

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Description

Manning Publications. Used - Very Good. 9780979264429. . All orders guaranteed and ship within 24 hours. Your purchase supports More Than Words, a nonprofit job training program for youth, empowering youth to take charge of their lives by taking charge of a business.
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Details

  • Title Practical Data Science with R, Second Edition
  • Author Zumel, Nina
  • Binding Paperback
  • Condition Used - Very good
  • Pages 483
  • Volumes 1
  • Language ENG
  • Publisher Manning Publications
  • Publication date 2019-12-07
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # WAL-W-1b-02062
  • ISBN 9781617295874 / 1617295876
  • Weight 2 lbs (0.91 kg)
  • Dimensions 9.1 x 7.4 x 1.1 in (23.11 x 18.80 x 2.79 cm)
  • Category Computers - Data Base Management
  • Library of Congress subjects Data mining, Mathematical statistics - Data processing
  • Dewey Decimal Code 005.133

About More Than Words Inc. Massachusetts, United States

Biblio member since 2016

More Than Words empowers youth who are in foster care, court-involved, homeless or out of school to take charge of their lives by taking charge of a business. MTW believes that when system-involved youth are challenged with authentic and increasing responsibilities in a business setting, and are given high expectations and a culture of support, they can and will address personal barriers to success, create concrete action plans for their lives, and become contributing members of society. More Than Words began as an online bookselling training program for youth in DCF custody in 2004 and opened its vibrant bookstore on Moody St in Waltham in 2005 and added its Starbucks coffee bar in 2008. MTW replicated its model in the South End of Boston in 2011, thereby doubling the number of youth served annually.

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30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

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Reader reviews for Practical Data Science with R, Second Edition

From the publisher

Summary

Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology

Evidence-based decisions are crucial to success. Applying the right data analysis techniques to your carefully curated business data helps you make accurate predictions, identify trends, and spot trouble in advance. The R data analysis platform provides the tools you need to tackle day-to-day data analysis and machine learning tasks efficiently and effectively.

About the book

Practical Data Science with R, Second Edition is a task-based tutorial that leads readers through dozens of useful, data analysis practices using the R language. By concentrating on the most important tasks you'll face on the job, this friendly guide is comfortable both for business analysts and data scientists. Because data is only useful if it can be understood, you'll also find fantastic tips for organizing and presenting data in tables, as well as snappy visualizations.

What's inside

Statistical analysis for business pros
Effective data presentation
The most useful R tools
Interpreting complicated predictive models

About the reader

You'll need to be comfortable with basic statistics and have an introductory knowledge of R or another high-level programming language.

About the author

Nina Zumel and John Mount founded a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon University and blog on statistics, probability, and computer science.

About the author

Nina Zumel co-founded Win-Vector, a data science consulting firm in San Francisco. She holds a PH.D. in robotics from Carnegie Mellon and was a content developer for EMC's Data Science and Big Data Analytics Training Course. Nina also contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.

John Mount co-founded Win-Vector, a data science consulting firm in San Francisco. He has a Ph.D. in computer science from Carnegie Mellon and over 15 years of applied experience in biotech research, online advertising, price optimization and finance. He contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.

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