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(This article was first published on <strong><a href="http://r-addict.com/2016/10/03/Rocker-Presentation-eRka10.html"> http://r-addict.com</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p><img src="https://i2.wp.com/r-addict.com/images/fulls/docker2.png?w=456" data-recalc-dims="1"> <strong>What is R?</strong> I was asked at the end of my presentation on the <a target="_blank" href="http://www.meetup.com/Cracow-R-User-Group/events/233624341/">10th Cracow R Users Meetup</a> that was held last Friday (30.09.2016). I felt strange but absolutely confirmed that <strong>R is the language of Data Science and is designed to performed the statistical data analysis</strong>. Later I found out that few of listeners came to the meetup to listen more about Docker than R, as my topic was <strong>Rocker – explanation and motivation for Docker containers usage in applications development</strong>. In this post I present the overview of my presentation. If you are not familiar with using Dockers in R applications development, then this is a must read for you!</p>
<h1>Presentation</h1>
<p>The presentation is available at my <a target="_blank" href="http://r-addict.com/eRka10/#/">website</a> and (as many people ask) was prepared with the help of <a target="_blank" href="http://rmarkdown.rstudio.com/revealjs_presentation_format.html">revealjs::revealjs_presentation</a>, a great tool from <a target="_blank" href="https://github.com/rstudio/revealjs">RStudio</a>. The front page wasn’t entirely specified in regular <a target="_blank" href="http://rmarkdown.rstudio.com/">rmarkdown</a> YAML, as I put few <a target="_blank" href="http://fontawesome.io/icons/">font awesome icons</a> so I think you would also like to see the code of the presentation at my <a target="_blank" href="https://github.com/MarcinKosinski/eRka10/blob/master/index.Rmd">GitHub’s repository</a>.</p>
<p><img src="https://i1.wp.com/r-addict.com/images/fulls/erka10_2.jpg?w=456" data-recalc-dims="1"></p>
<h1>Overview</h1>
<p>Below I present the description of the presentation.</p>
<p>As R users we mostly perform analysis, produce reports and create interactive shiny applications. Those are rather one-time performances. Sometimes, however, the R developer enters the world of the real software development, where R applications should be built once and then distributed and maintained on many machines.</p>
<p>What are the best practices in distributing the software? How can we ensure the code will always run the same regardless of its environment? Is there a way to skip the manual and long-lasting installation process if the software have been built once? Why using Docker in shipping the software is crucial?</p>
<p>Docker is the world’s leading software containerization platform. Docker containers wrap a piece of software in a complete file system that contains everything needed to run: code, runtime, system tools, system libraries – anything that can be installed on a server. This guarantees that the software will always run the same, regardless of its environment.</p>
<p>In my presentation I’ll give a brief introduction to Docker and provide a full motivation for using this technology in a regular R work. I strongly belief Docker can improve the data analysis to be more reproducible and can facilitate the software development so that the distribution and maintenance can be easier.</p>
<p>The presentation will be said by the person with the R background, assuming that the audience is also experienced in R. Get motivated: http://r-addict.com/2016/05/13/Docker-Motivation.html</p>
<p>### Acknowledgement</p>
<p>I would like to say thank you to <a target="_blank" href="https://github.com/zzawadz">Zygmunt Zawadzki</a> and <a target="_blank" href="https://github.com/bsekiewicz">Bartosz Sękiewicz</a>, organizators of this meetup and <a target="_blank" href="http://r-addict.com/2016/10/03/Rocker-Presentation-eRka10.html">Marta Karaś</a>, the second speaker with a great presentation on <em>Convex Clustering and Biclustering with application in R</em> that can be found <a target="_blank" href="https://rawgit.com/statsox/Convex-Clustering-slides/master/slides.html#/">here</a></p>
<p><img src="https://i0.wp.com/r-addict.com/images/fulls/erka10_1.jpg?w=456" data-recalc-dims="1"></p>
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