We sat down with Cristian Borcea, PhD from the New Jersey Institute of Technology to discuss the IoT and Big Data applications. “New machine learning techniques could help us extract knowledge from these data – this happens especially for knowledge that we don’t expect and we don’t even know exists – we cannot search for something that we don’t know exists.”
I’ve been monitoring a curious and lively discussion over on LinkedIn – “Is it necessary to have a Masters Degree to become a data scientist?” The comments I’ve seen have exhibited a number of points of view on the matter that I think are reflective of the questions on many people’s minds – both those wanting to become a data scientist and those wanting to hire a data scientist.
I recently got an e-mail with the salutation “Hi Data Scientist.” Pretty smart e-mail marketing campaign because, lo-and-behold, I am a data scientist and I actually was interested in the e-mail! It was from a company called DataCamp which I learned later used to be DataMind. I knew them from their R-Fiddle tool for learning R online.
The video below comes to us from the Strata Conference 2014: How Companies are Using Spark, and Where the Edge in Big Data Will Be. While the first big data systems made a new class of applications possible, organizations must now compete on the speed and sophistication with which they can draw value from data. […]
Last week saw evidence for the big data industry steamroller effect as the Strata Conference 2014 in Santa Clara came and went. With thousands of attendees, an abundance of informative presentations, and a very healthy exhibitor ecosystem, the show defined the current state-of-the-art for all that is big data. If you missed the big event, O’Reilly Media has graciously made available the slides and videos for some of the presentations.
Get your complimentary copy of the Hadoop Buyer’s Guide, from Robert D. Schneider, the author of Hadoop for Dummies.
The father of the S language which ultimately became R, Dr. John Chambers, sits down with Professor Trevor Hastie of the Stanford University Statistics Department to discuss the long and fascinating history of the R language.