This article is part of a media partnership with PyData Berlin, a group helping support open-source data science libraries and tools. To learn more about this topic, please consider attending our fourth annual PyData Berlin conference on June 30-July 2, 2017. Miroslav Batchkarov and other experts will be giving talks

The R language is often perceived as a language for statisticians and data scientists. Quite a long time ago, this was mostly true. However, over the years the flexibility R provides via packages has made R into a more general purpose language. R was open sourced in 1995, and since

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Data Science, Data Analytics, Data Everywhere Jargon can be downright intimidating and seemingly impenetrable to the uninformed. While complicated vernacular is an unfortunate side effect of the similarly complicated world of machines, those involved in computers, data and whole host of other tech-intensive sectors don’t do themselves any favors with

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I recently stumbled across a research paper, Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US, which piqued my interest in derivative uses of data, an ongoing research interest of mine. A variety of deep learning techniques were used to draw conclusions about relationships

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