#
R (Computer program language)
Resource Information
The concept ** R (Computer program language)** represents the subject, aboutness, idea or notion of resources found in **Mid-Continent Public Library**.

The Resource
R (Computer program language)
Resource Information

The concept

**R (Computer program language)**represents the subject, aboutness, idea or notion of resources found in**Mid-Continent Public Library**.- Label
- R (Computer program language)

## Context

Context of R (Computer program language)#### Subject of

No resources found

No enriched resources found

- 25 recipes for getting started with R
- A data scientist's guide to acquiring, cleaning, and managing data in R
- Adaptive tests of significance using permutations of residuals with R and SAS
- Advanced R
- Advanced R : data programming and the cloud
- Advanced analytics with R and Tableau : advanced visual analytical solutions for your business
- Advanced object-oriented programming in R : statistical programming for data science, analysis and finance
- An introduction to bootstrap methods with applications to R
- Applied data visualization with R and ggplot2 : Create useful, elaborate, and visually appealing plots
- Applied probabilistic calculus for financial engineering : an introduction using R
- Automated trading with R : quantitative research and platform development
- Basic data analysis for time series with R
- Beginning R : an introduction to statistical programming
- Beginning R : an introduction to statistical programming
- Beginning R : the statistical programming language
- Big data analytics with R and Hadoop
- Bioinformatics with R cookbook : over 90 practical recipes for computational biologists to model and handle real-life data using R
- Building a recommendation system with R : learn the art of building robust and powerful recommendation engines using R
- Business analytics using R : a practical approach
- Business case analysis with R : simulation tutorials to support complex business decisions
- Computational actuarial science with R
- Customer and business analytics : applied data mining for business decision making using R
- Data analysis with R : a comprehensive guide to manipulating, analyzing, and visualizing data in R
- Data analysis with R : load, wrangle, and analyze your data using the world's most powerful statistical programming language
- Data manipulation with R : efficiently perform data manipulation using the split-apply-combine strategy in R
- Data manipulation with R : perform group-wise data manipulation and deal with large datasets using R efficiently and effectively
- Data mashups in R
- Data mashups in R
- Data mining applications with R
- Data science in R : a case studies approach to computational reasoning and problem solving
- Data science in the cloud with Microsoft Azure machine learning and R : 2015 update
- Deep learning with R
- Doing Bayesian data analysis : a tutorial with R and BUGS
- Domain-specific languages in R : advanced statistical programming
- Dynamic documents with R and knitr
- Efficient R optimization
- Efficient R programming : a practical guide to smarter programming
- Efficient data processing with R
- Exploring everyday things with R and Ruby
- Financial risk modelling and portfolio optimization with R
- Foundational and applied statistics for biologists using R
- Functional data structures in R : advanced statistical programming in R
- Getting started with Greenplum for big data analytics : a hands-on guide on how to execute an analytics project from conceptualization to operationalization using Greenplum
- Getting started with RStudio
- Graphing data with R : an introduction
- Hands-on data science with R : techniques to perform data manipulation and mining to build smart analytical models using R
- Hands-on ensemble learning with R : a beginner's guide to combining the power of machine learning algorithms using ensemble techniques
- Hands-on geospatial analysis with R and QGIS : a beginner's guide to manipulating, managing, and analyzing spatial data using R and QGIS 3.2.2
- Hands-on programming with R
- Instant R starter
- Instant heat maps in R how-to
- Introduction to R for business intelligence : learn how to leverage the power of R for business intelligence
- Introduction to R for quantitative finance : solve a diverse range of problems with R, one of the most powerful tools for quantitative finance
- Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R
- Introduction to scientific programming and simulation using R
- Jupyter cookbook : over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more
- Jupyter for data science : exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter
- Learn R for applied statistics : with data visualizations, regressions, and statistics
- Learning Bayesian models with R : become an expert in Bayesian machine learning methods using R and apply them to solve real-world big data problems
- Learning R
- Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks
- Learning R programming : become an efficient data scientist with R
- Learning RStudio for R statistical computing
- Learning data mining with R : develop key skills and techniques with R to create and customize data mining algorithms
- Learning predictive analytics with Python : gain practical insights into predictive modelling by implementing predictive analytics algorithms on public datasets with Python
- Learning predictive analytics with R : get to grips with key data visualization and predictive analytic skills using R
- Learning shiny : make the most of R's dynamic capabilities and create web applications with Shiny
- Learning social media analytics with R : transform data from social media platforms into actionable insights
- Machine learning and data science : an introduction to statistical learning methods with R
- Machine learning using R : a comprehensive guide to machine learning
- Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R
- Machine learning with R cookbook : analyze data and build predictive models
- Machine learning with R cookbook : explore over 110 recipes to analyze data and build predictive models with the simple and easy-to-use R code
- Marketing data science : modeling techniques in predictive analytics with R and Python
- Mastering R for quantitative finance : use R to optimize your trading strategy and build up your own risk management system
- Mastering RStudio : develop, communicate, and collaborate with R : harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizations
- Mastering data analysis with R : gain clear insights into your data and solve real-world data science problems with R--from data munging to modeling and visualization
- Mastering machine learning with R : master machine learning techniques with R to deliver insights for complex projects
- Mastering predictive analytics with R : machine learning techniques for advanced models
- Mastering predictive analytics with R : master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential concepts
- Mastering scientific computing with R : employ professional quantitative methods to answer scientific questions with a powerful open source data analysis environment
- Mastering social media mining with R : extract valuable data from social media sites and make better business decisions using R
- Mastering text mining with R : master text-taming techniques and build effective text-processing applications with R
- Mathematical statistics with resampling and R
- Metaprogramming in R : advanced statistical programming for data science, analysis and finance
- Modeling techniques in predictive analystics with Python and R : a guide to data science
- Modeling techniques in predictive analytics : business problems and solutions with R
- Modern R programming cookbook : recipes to simplify your statistical applications
- Modern analysis of customer surveys : with applications using R
- Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles
- Nonlinear parameter optimization using R tools
- Nonparametric hypothesis testing : rank and permutation methods with applications in R
- Option pricing and estimation of financial models with R
- Oracle R Enterprise : harnessing the power of R in Oracle Database
- Parallel R
- Parallel computing for data science : with examples in R, C++ and CUDA
- Practical data science cookbook : 89 hands-on recipes to help you complete real-world data science projects in R and Python
- Practical data science cookbook : practical recipes on data pre-processing, analysis and visualization using R and Python
- Practical data science with R
- Practical graph mining with R
- Practical predictive analytics : back to the future with R, Spark, and more!
- Pro data visualization using R and Javascript
- Pro machine learning algorithms : a hands-on approach to implementing algorithms in Python and R
- Programming skills for data science : start writing code to wrangle, analyze, and visualize data with R
- Python for R users : a data science approach
- Python vs. R for data science
- R : mining spatial, text, web, and social media data : create and customize data mioning algorithms : a course in three modules
- R : recipes for analysis, visualization and machine learning : get savvy with R language and actualize projects aimed at analysis, visualization and machine learning
- R : unleash machine learning techniques : find out how to build smarter machine learning systems with R : follow this three module course to become a more fluent machine learning practitioner : a course in three modules
- R Graph essentials : use R's powerful graphing capabilities to design and create professional-level graphics
- R Graphs cookbook : over 70 recipes for building and customizing publication-quality visualizations of powerful and stunning R graphs
- R and MATLAB
- R cookbook
- R data analysis cookbook : a journey from data computation to data-driven insights
- R data analysis cookbook : over 80 recipes to help you breeze through your data analysis projects using R
- R data analysis projects : build end to end analytics systems to get deeper insights from your data
- R data mining : implement data mining techniques through practical use cases and real-world datasets
- R data science essentials : learn the essence of data science and visualization using R in no time at all
- R data structures and algorithms : increase speed and performance of your applications with efficient data structures and algorithms
- R data visualization cookbook : over 80 recipes to analyze data and create stunning visualizations with R
- R data visualization recipes : a cookbook with 65+ data visualization recipes for smarter decision-making
- R deep learning cooking : solve complex neural net problems with TensorFlow, H2O and MXNet
- R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet
- R deep learning projects : master the techniques to design and develop neural network models in R
- R for Microsoft Excel users : making the transition for statistical analysis
- R for data analysis
- R for data science
- R for data science : import, tidy, transform, visualize, and model data
- R for dummies
- R for everyone : advanced analytics and graphics
- R for everyone : advanced analytics and graphics
- R for medicine and biology
- R graphics
- R graphics cookbook
- R graphs cookbook : detailed hands-on recipes for creating the most useful types of graphs in R, starting from the simplest versions to more advanced applications
- R high performance programming : overcome performance difficulties in R with a range of exciting techniques and solutions
- R in a nutshell
- R in a nutshell
- R in action : data analysis and graphics with R
- R in action : data analysis and graphics with R
- R machine learning essentials : gain quick access to the machine learning concepts and practical applications using the R development environment
- R object-oriented programming : a practical guide to help you learn and understand the programming techniques necessary to exploit the full power R
- R packages
- R programming by example : practical, hands-on projects to help you get started with R
- R programming for bioinformatics
- R programming fundamentals : deal with data using various modeling techniques
- R projects for dummies
- R quick syntax reference
- R recipes : a problem-solution approach
- R statistical application development by example : learn R statistical application development from scratch in a clear and pedagogical manner
- R web scraping quick start guide : techniques and tools to crawl and scrape data from websites
- Regression analysis with R : design and develop statistical nodes to identify unique relationships within data at scale
- Robust nonlinear regression : with applications using R
- Sams teach yourself R in 24 hours
- Social media mining with R : deploy cutting-edge sentiment analysis techniques to real-world social media data R
- Statistical analysis with R : beginner's guide : take control of your data and produce superior statistical analyses with R
- Statistical application development with R and Python : power of statistics using R and Python
- Statistical computing in C++ and R
- Statistical hypothesis testing with SAS and R
- Statistical programming With SAS/IML software
- Statistical rethinking : a Bayesian course with examples in R and Stan
- Statistics and data analysis for microarrays using R and Bioconductor
- Statistics for machine learning : build supervised, unsupervised, and reinforcement learning models using both Python and R
- Text mining with R : a tidy approach
- The R book
- The art of R programming : tour of statistical software design
- Understanding and applying basic statistical methods using R
- Unsupervised learning with R : work with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data
- Using R for statistics
- Using R to unlock the value of big data : big data analytics with Oracle R Enterprise and Oracle R Connector for Hadoop
- Web application development with R using Shiny
- Web application development with R using Shiny : build stunning graphics and interactive data visualizations to deliver cutting-edge analytics
- Web application development with R using Shiny : integrate the power of R with the simplicity of Shiny to deliver cutting-edge analytics over the Web
- Writing code for R packages
- ggplot2 essentials : explore the full range of ggplot2 plotting capabilities to create meaningful and spectacular graphs

## Embed

### Settings

Select options that apply then copy and paste the RDF/HTML data fragment to include in your application

Embed this data in a secure (HTTPS) page:

Layout options:

Include data citation:

<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.mymcpl.org/resource/nDejP-oRiaw/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.mymcpl.org/resource/nDejP-oRiaw/">R (Computer program language)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.mymcpl.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.mymcpl.org/">Mid-Continent Public Library</a></span></span></span></span></div>

Note: Adjust the width and height settings defined in the RDF/HTML code fragment to best match your requirements

### Preview

## Cite Data - Experimental

### Data Citation of the Concept R (Computer program language)

Copy and paste the following RDF/HTML data fragment to cite this resource

`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.mymcpl.org/resource/nDejP-oRiaw/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.mymcpl.org/resource/nDejP-oRiaw/">R (Computer program language)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.mymcpl.org/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.mymcpl.org/">Mid-Continent Public Library</a></span></span></span></span></div>`