I am convinced we’re at an important inflection point in the timeline of the discipline of computer science. When compared to other disciplines like mathematics, physics and biology, computer science is a very young field, starting around 1964. But something is happening now, in 2014, that is propelling the field into a new evolutionary period.
Machine learning technologies have seen many inroads into the advertising industry primarily to make for more intelligent buys and placements in order to deliver a brand message to a selected audience. Here are some compelling SLIDES from a lecture at the New York University Stern School of Business by Foster Provost, Professor of Information Systems: “Machine Learning for Display Advertising.”
FlexPod Select with Hadoop delivers enterprise class Hadoop with validated, pre-configured components for fast deployment, higher reliability and smoother integration with existing applications and infrastructure. These technical reference architectures optimize storage, networking, and servers with Cloudera and Hortonworks distributions of Hadoop.
Raising capital for a shiny new start-up company is a daunting task what with shoring up interest by funding sources like Angels and VCs, producing a compelling “pitch deck,” and stacking your management team with the right people. But the big elephant in the room is always – how much to raise? Entrepreneur Jamie Davidson recently put some science (data science that is) behind this very important question.
As social media becomes increasingly important as a data source for the purposes of machine learning, finding a brand new method for analyzing the Twitter microblogging platform is very compelling. Tauid Zaman, assistant professor at MIT’s Sloan School of Management, developed a probabilistic model for the spread of an individual tweet in the twitterverse.
Enterprise Strategy Group (ESG), a leading analyst firm, recently performed a hands-on evaluation of Hadapt Adaptive Analytical Platform for big data.
Information visualization is an increasingly important element of big data as it is the technology best able to convey the message emanating from the data. Here is a nice paper “Infovis and Statistical Graphics: Different Goals, Different Looks” (pdf) by Andrew Gelman (Professor of Statistics at Columbia University) and Antony Unwin that discusses the topic of information visualization.