Need something to distract the kids while they’re waiting to head out Trick-or-Treating? You could have them try out a Creepy Computer Game in R! Engineer and social scientist Dr Peter Provost translated one of the old BASIC games from the classic book Creepy Computer Games into R: just have them type in this file (and yes, they do need to type it character-by-character to get the full experience) and then source it into R to play the game. The goal is to move your character * to the exit at the SE corner of the graveyard populated by gravestones + while avoiding the skeletons X.

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Back in November 2010 I wrote an article that I still like, attempting to answer the question: “How could the voters have swung so much in two years? And, why didn’t Obama give Americans a better sense of his long-term economic plan in 2009, back when he still had a political mandate?”

(translated from original French version)

This past week on KDnuggets we shared a roadmap to learning GANs, offered up an introductory tutorial using Keras for deep learning, learned how to perform named entity recognition with common Python tools, got certain about uncertainty, saw consistency in poll results on the largest datasets our readers analyzed, and learned about open source automated machine learning tools. Don’t forget to participate in the latest KDnuggets poll, How Important is Understanding Machine Learning Models? Features

Need something to distract the kids while they’re waiting to head out Trick-or-Treating? You could have them try out a Creepy Computer Game in R! Engineer and social scientist Dr Peter Provost translated one of the old BASIC games from the classic book Creepy Computer Games into R: just have them type in this file (and yes, they do need to type it character-by-character to get the full experience) and then source it into R to play the game. The goal is to move your character * to the exit at the SE corner of the graveyard populated by gravestones + while avoiding the skeletons X.

In the world of data science, R is an increasingly popular programming language for a reason. It was built with statistical manipulation in mind, and there’s an incredible ecosystem of packages for R that let you do amazing things - particularly in data visualization - that would be much more difficult in Python.

By Phillip Green, Founder and CEO of Informatics4AI

This is the fourth post in our AI interpretability series. Previous posts by my colleague Ilknur Kaynar Kabul covered partial dependence, interpreting data sets and other topics.  

By Michael Nguyen, Software and Machine Learning Engineer