Practical Data Science with R
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Narrated by:
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Josef Gagnier
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By:
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Nina Zumel
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John Mount
About this listen
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.
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.
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
This book is accessible to listeners without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed.
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.
PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2014 Manning Publications (P)2018 Manning PublicationsCritic reviews
"A unique and important addition to any data scientist’s library." (Jim Porzak, cofounder, Bay Area R Users Group)
What listeners say about Practical Data Science with R
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- Lucas
- 26-04-20
A paper copy is essential
I’m less than two chapters in and it’s become very clear that a paper copy of this book is essential in order to get the most out of it. Flipping back and forth to the supplier figures is ok, but they lack the context that comes with having them next to the text they are being discussed in.
I’d really hoped this could be a commute listen, but sadly it’s not.
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