NYU Data Science newsletter – August 14, 2015

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We are extremely pleased to announce that Data Carpentry has received $750,000 in funding from the Gordon and Betty Moore Foundation.

… in spite of our recent data-driven achievements, the evidence suggests that humans may well be in the dark ages of data. McKinsey, in their broadly read Big Data report, estimates that there will be only 2.5 million data-literate professionals in the United States in 2018 — less than 1% of the projected population. Surveys show that professionals today still take action the old-fashioned way — based on gut instinct, personal experience and what they think they know.

On Aug. 8 at the International Neural Network Society conference on big data in San Francisco, Baidu senior research engineer Awni Hannun presented on a new model that the Chinese search giant has developed for handling voice queries in Mandarin. The model, which is accurate 94 percent of the time in tests, is based on a powerful deep learning system called Deep Speech that Baidu first unveiled in December 2014.

In this lightly edited interview, Hannun explains why his new research is important, why Mandarin is such a tough language to learn and where we can expect to see future advances in deep learning methods.

Here are two things we know about the weather: We have tons of data about it, and we care very deeply about it.

It’s those two factors that led Microsoft researchers Ashish Kapoor and Eric Horvitz to turn to the latest advances in artificial intelligence to try to find a better answer to that age-old question: What’s the weather forecast?

Flu season had just begun in October 2013 when the federal government abruptly shut down because Congress had failed to pass a budget. Among the many public services that suddenly went dark was the Centers for Disease Control’s nationwide “FluView” program which provides crucial flu data to public health officials. Sorry kids. … As the federal government risks heading into another shutdown this fall, Congress should ensure that highly valuable open data will not again fall victim to politics.

At the beginning of July, I traveled to Austin for SciPy 2015, the annual conference dedicated to scientific computing in Python. Python is a powerful, easy-to-use programming language which has become very popular in the data science community. I was at the conference because the data science department at Civis Analytics uses Python to write all of the predictive modeling which goes into the new Civis platform – it’s been a wonderful tool for us.

It wasn’t long after the ink dried on the Verizon acquisition of AOL before Seth Demsey formed a plan to make the companies’ technology work together. … But as Mr. Demsey, a veteran in the field, seeks additional staff to fuel what he expects to be a continual process of building tools and integrating technologies, the term “data science” on prospective employee’s resume doesn’t always mean what he thinks it should.

We get to meet lots of exciting data innovators at Extract, so we decided to use our knowledge to create the first Data Mavericks list. A lot of thought went in to choosing people who are truly making a difference in the data scene.

It was no easy task narrowing our list down, but 40 under 40 seemed like a good place to start. Here they are. In alphabetical order, please enjoy our list of the Top 40 Data Mavericks under 40.

We are excited to announce the 6^th annual WIN Workshop, 2015, taking place October 2-3 in New York City. The last five years have seen the development of an intimate and influential community, around topics which at their core involve ‘information in networks‘—its distribution, its diffusion, its value, and its influence on social and economic outcomes. Scholars from fields as diverse as computer science, economics, physics, political science and sociology have come together to lay the foundation for ongoing relationships and to build a multidisciplinary research community. The sixth year of WIN will bring innovative new content and an even more vibrant discussion to the forum. More information: http://www.winworkshop.net/ and http://winworkshop.net/win2015/WINCALL2015.pdf

Deadline for Abstract Submissions: Friday, August 21