skip to content
Practical data science with R Preview this item
ClosePreview this item
Checking...

Practical data science with R

Author: Nina Zumel; John Mount, (Computational scientist)
Publisher: Shelter Island, NY : Manning Publications Co., [2014] ©2014
Edition/Format:   Print book : EnglishView all editions and formats
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  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

 

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Document Type: Book
All Authors / Contributors: Nina Zumel; John Mount, (Computational scientist)
ISBN: 9781617291562 1617291560
OCLC Number: 862790245
Description: xxv, 389 pages : illustrations ; 24 cm
Contents: Part 1. Introduction to data science: The data science process --
Loading data into R --
Exploring data --
Managing data --
Part 2. Modelling methods: Choosing and evaluating models --
Memorization methods --
Linear and logistic regression --
Unsupervised methods --
Exploring advanced methods --
Part 3. Delivering results: Documentation and deployment --
Producing effective presentations.
Responsibility: Nina Zumel, John Mount.

Abstract:

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. 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--Publisher website.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.

Similar Items

Related Subjects:(3)

User lists with this item (4)

Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


Primary Entity

<http://www.worldcat.org/oclc/862790245> # Practical data science with R
    a schema:Book, schema:CreativeWork ;
    library:oclcnum "862790245" ;
    library:placeOfPublication <http://id.loc.gov/vocabulary/countries/nyu> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/1415384267#Topic/data_mining> ; # Data Mining
    schema:about <http://dewey.info/class/006.3/> ;
    schema:about <http://experiment.worldcat.org/entity/work/data/1415384267#Topic/r_computer_program_language> ; # R (Computer program language)
    schema:about <http://experiment.worldcat.org/entity/work/data/1415384267#Topic/mathematical_statistics_data_processing> ; # Mathematical statistics--Data processing
    schema:author <http://experiment.worldcat.org/entity/work/data/1415384267#Person/zumel_nina> ; # Nina Zumel
    schema:author <http://experiment.worldcat.org/entity/work/data/1415384267#Person/mount_john_computational_scientist> ; # (Computational scientist) John Mount
    schema:bookFormat bgn:PrintBook ;
    schema:copyrightYear "2014" ;
    schema:datePublished "2014" ;
    schema:description "Part 1. Introduction to data science: The data science process -- Loading data into R -- Exploring data -- Managing data -- Part 2. Modelling methods: Choosing and evaluating models -- Memorization methods -- Linear and logistic regression -- Unsupervised methods -- Exploring advanced methods -- Part 3. Delivering results: Documentation and deployment -- Producing effective presentations."@en ;
    schema:description "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. 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--Publisher website."@en ;
    schema:exampleOfWork <http://worldcat.org/entity/work/id/1415384267> ;
    schema:inLanguage "en" ;
    schema:name "Practical data science with R"@en ;
    schema:productID "862790245" ;
    schema:workExample <http://worldcat.org/isbn/9781617291562> ;
    wdrs:describedby <http://www.worldcat.org/title/-/oclc/862790245> ;
    .


Related Entities

<http://experiment.worldcat.org/entity/work/data/1415384267#Person/mount_john_computational_scientist> # (Computational scientist) John Mount
    a schema:Person ;
    schema:familyName "Mount" ;
    schema:givenName "John" ;
    schema:name "(Computational scientist) John Mount" ;
    .

<http://experiment.worldcat.org/entity/work/data/1415384267#Person/zumel_nina> # Nina Zumel
    a schema:Person ;
    schema:familyName "Zumel" ;
    schema:givenName "Nina" ;
    schema:name "Nina Zumel" ;
    .

<http://experiment.worldcat.org/entity/work/data/1415384267#Topic/mathematical_statistics_data_processing> # Mathematical statistics--Data processing
    a schema:Intangible ;
    schema:name "Mathematical statistics--Data processing"@en ;
    .

<http://experiment.worldcat.org/entity/work/data/1415384267#Topic/r_computer_program_language> # R (Computer program language)
    a schema:Intangible ;
    schema:name "R (Computer program language)"@en ;
    .

<http://worldcat.org/isbn/9781617291562>
    a schema:ProductModel ;
    schema:isbn "1617291560" ;
    schema:isbn "9781617291562" ;
    .


Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.