Practical Data Science With R by Nina ZumelPractical Data Science With R by Nina Zumel

Practical Data Science With R

byNina Zumel, John Mount

Paperback | April 13, 2014

Pricing and Purchase Info

$55.68 online 
$64.95 list price save 14%
Earn 278 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

Summary

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll 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 Book

Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics.

Practical Data Science with R shows you how to apply the R programming language and useful statistical techniques to everyday business situations. Using examples from marketing, business intelligence, and decision support, it shows you how to design experiments (such as A/B tests), build predictive models, and present results to audiences of all levels.

This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.

What's Inside

  • Data science for the business professional
  • Statistical analysis using the R language
  • Project lifecycle, from planning to delivery
  • Numerous instantly familiar use cases
  • Keys to effective data presentations

About the Authors

Nina Zumel and John Mount are cofounders of a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at win-vector.com.

Table of Contents

    PART 1 INTRODUCTION TO DATA SCIENCE
  1. The data science process
  2. Loading data into R
  3. Exploring data
  4. Managing data
  5. PART 2 MODELING METHODS
  6. Choosing and evaluating models
  7. Memorization methods
  8. Linear and logistic regression
  9. Unsupervised methods
  10. Exploring advanced methods
  11. PART 3 DELIVERING RESULTS
  12. Documentation and deployment
  13. Producing effective presentations
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, ...
Loading
Title:Practical Data Science With RFormat:PaperbackDimensions:416 pages, 9.25 × 7.38 × 0.68 inPublished:April 13, 2014Publisher:Manning PublicationsLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1617291560

ISBN - 13:9781617291562

Look for similar items by category:

Reviews