Practical Data Science with R (Paperback, 2nd edition)

This invaluable addition to any data scientist's library shows you how to apply the R programming language and useful statistical techniques to everyday business situations as well as how to effectively present results to audiences of all levels. To answer the ever-increasing demand for machine learning and analysis, this new edition boasts additional R tools, modeling techniques, and more. 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. Key features * Data science and statistical analysis for the business professional * Numerous instantly familiar real-world use cases * Keys to effective data presentations * Modeling and analysis techniques like boosting, regularized regression, and quadratic discriminant analysis Audience While some familiarity with basic statistics and R is assumed, this book is accessible to readers with or without a background in data science. About the technology 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 Nina Zumel and John Mount are co-founders of Win-Vector LLC, 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.

General

Imprint:	Manning Publications
Country of origin:	United States
Release date:	December 2019
First published:	2020
Authors:	Nina Zumel • John Mount
Dimensions:	380 x 240 x 40mm (L x W x T)
Format:	Paperback
Pages:	483
Edition:	2nd edition
ISBN-13:	978-1-61729-587-4
Categories:	Books > Reference & Interdisciplinary > Communication studies > Data analysis
LSN:	1-61729-587-6
Barcode:	9781617295874

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