For our latest installment of the insideBIGDATA Data Science 101 series, I thought I’d do something a bit different. Here is a sample analysis by data scientist and blogger Dan Goldin who published some nice results using R to assess the web requests originating from the top 100 Internet sites.
Stephen Wolfram, founder of Wolfram Research and creator of Mathematica, just announced the new Wolfram Programming Language. This new knowledge-based language could be a game changer in data science.
Microsoft Research, the research arm of the software giant, is a hotbed of data science and machine learning research. Microsoft has the resources to hire the best and brightest researchers from around the globe. A recent publication is available for download (PDF): “Deep Learning: Methods and Applications” by Li Deng and Dong Yu, two prominent researchers in the field.
Big Data will change the way your organization responds to business opportunities. But to reap its full benefits, you have to move from proof of concept into full production. Here is an informative, 52-minute presentation that provides the guidelines for successfully integrating Hadoop into your standard data center processes.
Jeremy Howard made a presentation to the Melbourne R meetup group, where he gave a brief overview of his “data scientist’s toolbox” (using a few Kaggle competitions as practical examples), and also provided an introduction to ensembles of decision trees (including the well-known Random Forest™ algorithm).
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.