An Updated History of R

Here’s a refresher on the history of the R project: 1992: R development begins as a research project in Auckland, NZ by Robert Gentleman and Ross Ihaka  1993: First binary versions of R published at Statlib [see update, below] 1995: R first distributed as open-source software, under GPL2 license 1997: R core group formed 1997: CRAN founded (by Kurt Hornik and Fritz Leisch) 1999: The R website, r-project.org, founded 2000: R 1.0.0 released (February 29)  2001: R News founded (later to become the R Journal) 2003: R Foundation founded 2004: First UseR! conference (in Vienna) 2004: R 2.0.0 released 2009: First edition of the R Journal 2013: R 3.0.0 released 2015: R Consortium founded, with R Foundation participation 2016: New R logo adoptedt I’ve added some additional dates gleaned from the r-announce mailing list archives and a 1998 paper on the history of R…
Original Post: An Updated History of R

An Updated History of R

Here’s a refresher on the history of the R project: 1992: R development begins as a research project in Auckland, NZ by Robert Gentleman and Ross Ihaka  1993: First binary versions of R published at Statlib  1995: R first distributed as open-source software, under GPL2 license 1997: R core group formed 1997: CRAN founded (by Kurt Jornik and Fritz Leisch) 1999: The R website, r-project.org, founded 2000: R 1.0.0 released (February 29)  2001: R News founded (later to become the R Journal) 2003: R Foundation founded 2004: First UseR! conference (in Vienna) 2004: R 2.0.0 released 2009: First edition of the R Journal 2013: R 3.0.0 released 2015: R Consortium founded, with R Foundation participation 2016: New R logo adopted I’ve added some additional dates gleaned from the r-announce mailing list archives and a 1998 paper on the history of R written by co-founder…
Original Post: An Updated History of R

Top 10 Machine Learning Algorithms for Beginners

[unable to retrieve full-text content]A beginner’s introduction to the Top 10 Machine Learning (ML) algorithms, complete with figures and examples for easy understanding.
Original Post: Top 10 Machine Learning Algorithms for Beginners

The ways that AI can change your business

[unable to retrieve full-text content]AI technology involves a change in the value chain and represents a major challenge and opportunity for businesses. Managers are directly involved in this challenge, by accompanying the teams through this transition: vanquish fears, embracing innovation, transforming businesses, training teams.
Original Post: The ways that AI can change your business

5 Free Resources for Furthering Your Understanding of Deep Learning

[unable to retrieve full-text content]This post includes 5 specific video-based options for furthering your understanding of neural networks and deep learning, collectively consisting of many, many hours of insights.
Original Post: 5 Free Resources for Furthering Your Understanding of Deep Learning

Install Useful Eclipse Plugins in Bio7 for R, Data Science and Programming

20.10.2017 Beside a massive of amount of R packages and ImageJ plugins Bio7 can be extended with Eclipse plugins useful for data science and programming. Some of them could also be very useful for R related developments (e.g., to develop R packages or distribute Shiny apps). Installation of Eclipse Plugins One  way to install Eclipse plugins is by using the Update Manager in the help menu (Help->Install New Software). Thus the first step to install a plugin is to open the Update Manager and selecting the category “Eclipse Repository – http://download.eclipse.org/releases/neon” (see screenshot below!) Another handy way of searching and installing Eclipse plugins is by using the Marketplace Client plugin which must be installed firstly with the Update Manager. Search for the Marketplace Client (e.g., “marketplace”) plugin to filter, select and install the Marketplace Client. The following plugins can be…
Original Post: Install Useful Eclipse Plugins in Bio7 for R, Data Science and Programming