NYU Data Science newsletter – April 30, 2015

NYU Data Science Newsletter features journalism, research papers, events, tools/software, and jobs for April 30, 2015

GROUP CURATION: N/A

 
Data Science News



Hadoop and beyond: A primer on Big Data for the little guy – SD Times

SD Times


from April 28, 2015

“Here’s a credible angle on why Big Data could implode,” began Gary Nakamura, CEO of Concurrent, which makes Cascading, an open-source data application development platform that works with Hadoop, and Driven, a tool for visualizing data pipeline performance. “A CTO could walk into a data center, and when they say, ‘Here is your 2,000-node Hadoop cluster,’ the CTO says, ‘What the hell is that and why am I paying for it?’ That could happen quite easily. I predicted last year that this would be the ‘show me the money’ year for Hadoop.”

 

Statistics: P values are just the tip of the iceberg

Nature News & Comment


from April 28, 2015

Ridding science of shoddy statistics will require scrutiny of every step, not merely the last one, say Jeffrey T. Leek and Roger D. Peng.

 

Open Source Data Science Masters

Fraser Campbell and Sabine Crevoisier


from April 28, 2015

On May 21st 2014, we flew out to Thailand with loaded backpacks, this time for a different reason than the holidays which came before. We were taking 6 months out of our lives to study Data Science online.

After four years in industry, the still young world of open source and open access education inspired us to test courses that re-ignited our interest in science. Blown away by the quality of courses available, comparable to a reputable Master degree, we decided to create a tailored curriculum with the aim of becoming Data Scientists.

This website showcases some of the skills we have acquired on this journey.

 

More tools for managing and reproducing complex data projects – O’Reilly Radar

O'Reilly Radar, Ben Lorica


from April 29, 2015

… As I survey the landscape, the types of tools remain the same, but interfaces continue to improve, and domain specific languages (DSLs) are starting to appear in the context of data projects. One interesting trend is that popular user interface models are being adapted to different sets of data professionals (e.g. workflow tools for business users).

 

SurveyMonkey Has Quizzed Us Since 1999. Now It Has Answers | WIRED

WIRED, Business


from April 28, 2015

When Dave Goldberg stepped into the role of CEO at SurveyMonkey in 2009, he saw an opportunity to transform the company. Back then, the company behind the world’s leading online survey platform was made up of just 14 people. It was profitable and successful, Goldberg remembers, with lots of happy customers. But Goldberg believed SurveyMonkey could do more than ask questions. It also has a lot of answers.

 

Surprisingly Amazing: The Words Associated with Every Kind of Music | Evolver.fm

Evolver.fm


from April 29, 2015

The latest in time-sucking music data entertainment: ‘Genres In Their Own Words’

This is a massive list that pairs over 1400 genres with the words that are most distinctive to the song titles from each genre, from Spotify data alchemist Glenn McDonald. If you’re anything like us, it will make for surprisingly compelling reading — we say “surprising,” because nobody wrote these words; they simply emerged out of the data, as being associated with certain genres of music.

 

DARPA Seeks to Create Software Systems That Could Last 100 Years

DARPA News


from April 08, 2015

As modern software systems continue inexorably to increase in complexity and capability, users have become accustomed to periodic cycles of updating and upgrading to avoid obsolescence—if at some cost in terms of frustration. In the case of the U.S. military, having access to well-functioning software systems and underlying content is critical to national security, but updates are no less problematic than among civilian users and often demand considerable time and expense. That is why today DARPA announced it will launch an ambitious four-year research project to investigate the fundamental computational and algorithmic requirements necessary for software systems and data to remain robust and functional in excess of 100 years.

 
Events



NYU Data Science Social Tickets, New York | Eventbrite



As we approach the end of this academic year, we would like to invite all graduate students, researchers, staff and faculty members at NYU working on data science to a university wide social event sponsored by The Center for Data Science.

This is an opportunity for all data scientists across the university to get together in a casual setting and talk about cool data science initiatives around campus.

Come celebrate what we have achieved over the past year and meet other awesome data scientists at NYU! Come early and your first drink is on us! H’ordeuvres will be served.

Friday, May 1, at 5 p.m., West 3rd Common

 

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