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Practical Data Science with R

Practical Data Science with R - Free Ebook Download

Book Detail

Author/Editor(s): Nina Zumel, John Mount, Jim Porzak
Publication Date: April 13, 2014
ISBN-10: 1617291560
ISBN-13: 978-1617291562
Language: English
Edition: 1
Publisher: Manning
Size: 36.2 MB
Format: pdf, epub, mobi

Book Description

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.

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.

Reviews

This Book is full of practical tips. Absolutely wonderful for a data science beginner to read. The codes are explained so well. Of of the best data science book in the market.

--Zhiyao Pei, Amazon Customer Reviews

Successfully practicing data science is not just about fitting statistical models to data, but about solving business problems. This requires practitioners to be able to translate business questions into quantitative goals, communicate technical results, manage models as software artifacts, etc. Describing these needs, and providing an overview of tools and examples for each, is the differentiating angle of this book. Ms. Zumel and Mr. Mount run a successful data-science consulting practice, and thus are uniquely qualified to speak from that perspective. Their advanced analytical background also allowed them to provide a very inviting presentation of the most common modeling methods, with the right amount of detail for an introductory book, the intuition behind them, and compelling examples and sample R code. The formatting of the entire book is super clear; the placement/color of the comments, as well as lots of screen shots, make reading it a smooth experience. I highly recommend this book to beginner and intermediate practitioners.

--Giovanni Seni, Amazon Customer Reviews
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