NYU Data Science newsletter – October 23, 2015

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Happy Open Access week! As usual, I’m celebrating the Open Data portion of Open Access, but my special focus this year is on getting credit for your research data. My library did an in-person workshop on the topic earlier this week and I want to share the idea out more widely on the blog because I think it’s important.

Could it be that machine learning in particular is the next natural step for all the companies and end users who have climbed aboard the data express? Indeed, the attention around large-scale, complex analytics and the systems and frameworks to support them spurred some of that evolution. But ultimately, one could make the argument that for some analytical workloads, in both the research and enterprise spaces, those advances have hit their own peak. All of the new methods and approaches that grew from the fertile “big data” soils have been sown and tested.

An international research team led by Yale University postdoctoral researcher Hakim Atek recently discovered more than 250 distant galaxies, including some of the faintest, smallest galaxies in the universe. The team relied upon new images from the Hubble Space Telescope, focusing on a trio of cosmic magnifying glasses.

Getting into the back of a black taxi is the quintessential London experience. Name any spot in Britain’s capital and the driver knows exactly where to go and how to get there as fast as possible. This is “The Knowledge.” Every cabbie must master it, and it takes years to learn.

A week ago, Amazon Web Services chief Andy Jassy stood onstage at the company’s annual tech conference and promised “freedom” to frustrated Oracle users. Now Amazon says that over 1,000 customers have already taken him up on the offer.

In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.

Yelp hosts tens of millions of photos uploaded by Yelpers from all around the world. The wide variety of these photos provides a rich window into local businesses, a window we’re only just peeking through today.

One way we’re trying to open that window is by developing a photo understanding system which allows us to create semantic data about individual photographs.

There is a 99.9 percent chance of a magnitude-5 or greater earthquake striking within three years in the greater Los Angeles area, where a similar sized temblor caused more than $12 million in damage last year, according to a study by NASA and university researchers.

As federal agencies start implementing the 2014 Digital Accountability and Transparency Act — which requires them to publish spending data in standard formats — a few tech startups see an opportunity to make money.

One of those companies is 8-year-old Seattle-based tech company Socrata, whose customers include the Centers for Medicare and Medicaid Services, the state of Maryland and the City of Austin. Socrata sells software products designed to help governments upload datasets.

Join us for a day-long dive into healthcare data! You will work in small groups to tackle one part of the data analysis pipeline: data wrangling, descriptive analytics, or predictive modeling. Project managers and technical experts will be on hand to keep your momentum going. If you need a break and want to learn something new, there will be plenty of cool speakers discussing topics in healthcare and data science. We will also have a kick-off event the evening before to meet your group and set up your system so that the next morning you can all dive into the data right away.

Deadline to Apply: Sunday, October 25. Data Dive takes place Friday-Saturday, November 6-7, at Insight Data Science, 45 W 25th St, 9th Floor, NYC.

There is life in data, if you know how where to look: the number of steps from your apartment to the coffee shop, the cost of a latte, the levels of pollution in the October air you’re breathing in. As we move through the world, we leave thousands of other signals behind us that speak volumes about our health and well-being. Now, a new project in New York City will gather and process those signals on an unprecedented scale.

The ambitious scheme, named the Kavli HUMAN Project, will track every last scrap of data generated by 10,000 New Yorkers. Taken together, that data will weave a detailed narrative of each person’s life – where they go, what they do, how they’re feeling, how they walk the line between sickness and health. [No cost site registration required to read.]