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Practical Data Science with R
book

Practical Data Science with R

by John Mount, Nina Zumel
March 2014
Beginner to intermediate
416 pages
13h 36m
English
Manning Publications
Content preview from Practical Data Science with R

Appendix C. More tools and ideas worth exploring

In data science, you’re betting on the data and the process, not betting on any one magic technique. We advise designing your projects to be the pursuit of quantifiable goals that have already been linked to important business needs. To concretely demonstrate this work style, we emphasize building predictive models using methods that are easily accessible from R. This is a good place to start, but shouldn’t be the end.

There’s always more to do in a data science project. At the least, you can

  • Recruit new partners
  • Research more profitable business goals
  • Design new experiments
  • Specify new variables
  • Collect more data
  • Explore new visualizations
  • Design new presentations
  • Test old assumptions ...
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Publisher Resources

ISBN: 9781617291562Publisher SupportPublisher WebsiteErrata Page