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Viser: Data Science in R

Beginning Data Science in R
Søgbar e-bog

Beginning Data Science in R Vital Source e-bog

Thomas Mailund
(2017)
Springer Nature
399,00 kr.
Leveres umiddelbart efter køb
Beginning Data Science in R

Beginning Data Science in R Vital Source e-bog

Thomas Mailund
(2017)
Springer Nature
299,00 kr.
Leveres umiddelbart efter køb
Data Science in R

Data Science in R

Thomas Mailund
(2017)
Sprog: Engelsk
Apress L. P.
444,00 kr.
Print on demand. Leveringstid vil være ca 2-3 uger.

Detaljer om varen

  • Vital Source searchable e-book (Fixed pages)
  • Udgiver: Springer Nature (Marts 2017)
  • ISBN: 9781484226711
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.  This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming.  What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Vital Source 365 day rentals (fixed pages)
  • Udgiver: Springer Nature (Marts 2017)
  • ISBN: 9781484226711R365
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this.  This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming.  What You Will Learn Perform data science and analytics using statistics and the R programming language Visualize and explore data, including working with large data sets found in big data Build an R package Test and check your code Practice version control Profile and optimize your code Who This Book Is For Those with some data science or analytics background, but not necessarily experience with the R programming language.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: 5 år fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • Paperback
  • Udgiver: Apress L. P. (Marts 2017)
  • ISBN: 9781484226704
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.
Beginning Data Science in R details how data science is a combination of statistics, computational science, and machine learning. You'll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. 
This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. 
What You Will Learn
  • Perform data science and analytics using statistics and the R programming language
  • Visualize and explore data, including working with large data sets found in big data
  • Build an R package
  • Test and check your code
  • Practice version control
  • Profile and optimize your code

Who This Book Is For
Those with some data science or analytics background, but not necessarily experience with the R programming language.

1. Introduction to R programming.
2. Reproducible analysis.
3. Data manipulation.
4. Visualizing and exploring data.
5. Working with large data sets.
6. Supervised learning.
7. Unsupervised learning.
8. More R programming.
9. Advanced R programming.
10. Object oriented programming.
11. Building an R package.
12. Testing and checking.
13. Version control.
14. Profiling and optimizing.
De oplyste priser er inkl. moms

Senest sete

Polyteknisk Boghandel

har gennem mere end 50 år været studieboghandlen på DTU og en af Danmarks førende specialister i faglitteratur.

 

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