NYU Data Science newsletter – October 29, 2015

NYU Data Science Newsletter features journalism, research papers, events, tools/software, and jobs for October 29, 2015

GROUP CURATION: N/A

 
Data Science News



Analytics vs Data Science

Data Science 101


from October 24, 2015

The lines between analytics and data science can definitely be very blurry. Different companies might call the same position by two different names, but at their core, they do have some differences. … In my opinion, a true data scientist should spend more time creating and programming new algorithms while a business analyst should spend more time applying existing algorithms.

 

Software Carpentry: Code Review – a Needed Habit in Science

Software Carpentry


from October 28, 2015

More than a year ago, Marian Petre and Greg Wilson wrote an article about reviewing code, but I was not aware of it until last week when Greg talked about their findings in a workshop in London (though it had been mentioned here before). I have been reviewing code for years, however I have not realised that I was doing so till GitHub made it easy. Reading code from others feels the same as proofreading a Spanish text (or any other text), where you have to pay attention to the orthography, the grammar and whether it says what it’s meant to say (or it does what it’s meant to do).

Since I started my PhD I’ve organised programming clubs in the institutes where I’ve been as a way of sharing knowledge between the colleagues. But in these last 10 years I’ve just done a “code review” session twice. The first one involved external people (from industry) reading scientific code, whereas the second time (last week) were done between the researchers.

 

Future Of Big Data: Meet Five MBAs Blazing A Trail In Business Analytics

BusinessBecause


from October 28, 2015

If there is one topic that gets business school graduates’ pulses racing, it is the big data scene.

Data is creating countless new career paths and is slowly reshaping the way executives gain insights and develop strategy. It is a much-hyped area that will pique the interest of any aspiring business leader, who will need to use advanced analytics to manage risk, improve controls and, ultimately, enhance operational performance.

“The way big data is changing what’s going on in business is like life scientists having a microscope for the first time,” says Mark Kennedy, associate professor of strategy and director of the KPMG Centre for Business Analytics at Imperial College Business School. Frankly, he says, it is hard to image an industry that isn’t going to be “fundamentally disrupted” by big data.

 

Open Software Initiative (OSI) day – Keynote Speech 2: Software and engineering efforts at NYU Center for Datascience – 2015-10-26 (Webcast CC-IN2P3/CNRS )

Paris-Saclay Center for Data Science


from October 28, 2015

Paris-Saclay Center for Data Science – Open Software Initiative (OSI) day

Keynote Speech 2: Software and engineering efforts at NYU Center for Datascience by Andreas Mueller [video, 42:46]

 

5 tips for working with data science interns | CIO

CIO


from October 26, 2015

Interns want valuable experience, and with a little effort, an internship can become just as fruitful for your department as it is for their resume. Here are five tips on how to get the best out of your data science interns.

 

NetFridge and Energy Globe Win Top Prizes at Third Annual BERC Cleanweb Hackathon

Berkeley Institute for Data Science


from October 27, 2015

Nearly 50 participants from UC Berkeley, Berkeley Lab, and the Bay Area gathered for the third annual BERC Cleanweb Hackathon. The event was a huge success, and 10 teams made pitches at the end of the 24-hour event in front of a panel of judges, including Anna Schneider of WattTime, Elena Lucas of UtilityAPI, and Kate Knox of Advanced Microgrid Solutions.

 

Mapping the 3-D structure of DNA

MIT News


from October 26, 2015

For graduate student Abe Weintraub, the magic and intrigue of DNA is all in the packaging.

Imagine trying to fit 24 miles of string into a tennis ball, the PhD student in biology says: That is, in essence, what it’s like inside every cell nucleus in the human body, each of which contains about 2 meters’ worth of DNA strands. But, as Weintraub is finding, this packaging sometimes goes awry, which may be the basis for disease.

Although the genetic code that resides in DNA has traditionally been thought of as linear, Weintraub is contributing to a body of knowledge about its 3-D organization.

 

Icahn School of Medicine at Mount Sinai Researchers Map Genetic Diversity of New York City, Advancing Precision Medicine

CityLab


from October 27, 2015

The genetic makeup of New York City is a vast web of stories and relationships—migrations, couplings, clusterings, undetected syndromes, and bodily boons. That’s what makes the city an incredible laboratory for the next frontier of healthcare: medicine tailored to you and your genes.

So says Eimear Kenny, professor and genetic researcher at the Icahn School of Medicine at Mount Sinai. Kenny and PhD candidate Gillian Belbin study neighborhood-level human movement patterns across New York City, using, among other things, the genetic samples of 32,000 New Yorkers.

 

[1510.07211] On End-to-End Program Generation from User Intention by Deep Neural Networks

arXiv, Computer Science > Software Engineering


from October 25, 2015

This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding code in a characterby-by-character fashion. We demonstrate its feasibility through a case study and empirical analysis. To fully make such technique useful in practice, we also point out several cross-disciplinary challenges, including modeling user intention, providing datasets, improving model architectures, etc. Although much long-term research shall be addressed in this new field, we believe end-to-end program generation would become a reality in future decades, and we are looking forward to its practice.

 
Events



Election Mapping Bonanza



Election season is coming fast! In the first of a series of process events, this session will center on visualizing election results at different scales, ensuring data is normalized, and taking advantage of custom cartography and basemaps. We will use CartoDB, CartoCSS and basic SQL to build a demonstration map that should get everyone started.

Tuesday, November 10, at 7 p.m., CartoDB (201 Moore St, Brooklyn)

 

Leave a Comment

Your email address will not be published.