NYU Data Science newsletter – July 5, 2016

GROUP CURATION: N/A

“We need to get drunk, go home, have a bit of a cry, and then do something about it tomorrow,” said John M. Greally, one of the authors and an epigenetics expert at the Albert Einstein College of Medicine in New York.

Among other criticisms, he and his co-authors — Ewan Birney of the European Bioinformatics Institute and George Davey Smith of the MRC Integrative Epidemiology Unit at the University of Bristol in England — argue that in some cases, changes to epigenetic marks don’t cause disease, but are merely consequences of disease.

Some studies, for example, have found that people with a high body mass index have unusual epigenetic marks on a gene called HIF3A. Some researchers have suggested that those marks change how HIF3A functions, perhaps reprogramming fat cells to store more fat.

Once the realm of science fiction, smart machines are rapidly becoming part of our world—and these technologies offer amazing potential to improve the way we live. Imagine intelligent, autonomous vehicles that reduce crashes and alleviate congestion in crowded cities. Imagine robots that can help your aged grandma move around safely or instructors that can assist special-needs children in classrooms. Gil Pratt, former head of the Robotics Challenge at DARPA, now heads up the $1 billion Silicon Valley-based, Toyota Research Institute where he and his team are pushing the boundaries of human knowledge in autonomous vehicles and robotics. This session will explore the breakthrough technologies on the horizon and the unprecedented issues we will face in this brave new world.

… What’s needed for AI’s wide adoption is an understanding of how to build interfaces that put the power of these systems in the hands of their human users. What’s needed is a new hybrid design discipline, one whose practitioners understand AI systems well enough to know what affordances they offer for interaction and understand humans well enough to know how they might use, misuse, and abuse these affordances.

More on data & design:

A framework for evaluating electronic health record vendor user-centered design and usability testing processes (July 03, Journal of the American Medical Informatics Association; Raj M Ratwani et al)

Mike Kuniavsky on the mindshift needed to design for ecosystems (July 07, O’Reilly Radar, Mary Treseler and Mike Kuniavsky)

Ambient Computing by Mike Barlow (July 08, O’Reilly Media, Mike Barlow)

Data Visualization, Design and Information Munging (November 2015, Martin Krzywinski/ Genome Sciences Center)

How Fast Food Chains Use Data to Test New Products and Drive Sales (July 07, Eater)

In Silicon Valley, where companies big and small are at work on self-driving cars, there have been a variety of approaches, and even some false starts.

The most divergent paths may be the ones taken by Tesla, which is already selling cars that have some rudimentary self-driving functions, and Google, which is still very much in experimental mode.

More on cars:

The autonomous car as a driving partner (July 05, O’Reilly Radar, David Beyer and Daniela Rus)

Self-Driving Laws (July 05, SSRN; Anthony J. Casey and Anthony Niblett)

Without legislation, robotic cars can’t be tested on Mass. roads (July 04, The Boston Globe)

As Self-Driving Cars Hit the Road, Innovation Is Outpacing Insurance (July 03, The New York Times)

BMW strikes autonomous car deal with Intel, Mobileye (July 05, ReadWrite)

To Mark Abraham, executive director of DataHaven, data is not simply information.

“Each data point is like one person’s story,” said Abraham, who has led the 25-year-old nonprofit organization since 2009. “So data put together is really putting together everyone’s story in a way that’s scientific.”

DataHaven has been indispensable to other nonprofits, such as the Community Foundation for Greater New Haven and Yale New Haven Health, say officials at those agencies. Whether it’s the Greater New Haven Community Index, first issued in 2013 with an update coming out this summer, or the Community Wellbeing Survey, Abraham’s group of five staffers sifts through the ever-growing wealth of information to present a picture of Connecticut and Greater New Haven that’s unavailable elsewhere.

We use genetics to understand human health and disease and spend our lives analyzing genomic data and developing tools to make these analyses more informative. Tackling some of the big challenges in human genetics and genomics requires engaging 100,000s of volunteers and collecting rich information about their health, behavior and environment.

Last year, we launched Genes for Good, a study of genes, health and behavior through a Facebook app. Volunteers complete health history surveys, daily health tracking surveys, and behavioral tasks.

There’s not much traffic on the streets of Devens. The community’s manager, Thatcher Kezer, likes it that way, and not just because it makes for a fast commute. Kezer thinks the lightly traveled roads of this former Army base make it an ideal place for automakers to conduct real-world road tests of self-driving cars.

“We want Devens to be the center of the development of this industry,” said Kezer, senior vice president of MassDevelopment, the state-funded economic development agency that manages Devens. “And we have the space to do it.”

There’s just one problem: Testing autonomous cars on public roads isn’t legal yet in Massachusetts, and there’s no telling when it will be.

Advances in self-driving car technology have gotten ahead of insurers’ ability to factor the systems into auto premiums.

So at least for now, coverage for cars using self-driving technology works the same way as coverage for traditional vehicles, according to the insurance industry.

A recent fatality involving a Tesla Model S electric sedan using the company’s Autopilot system has focused attention on the risks of new “autonomous driving” technology. But the insurance claims process for cars using the systems generally works the same way as for cars without them, said Robert Hartwig, president of the Insurance Information Institute, an industry group.

As the use of data science techniques continues to grow across disciplines, a group of University of Michigan researchers are working to build a community of social scientists with skills in Big Data through a week-long summer camp for faculty and graduate students.

In January, Google’s AlphaGo crossed a major artificial intelligence threshold by besting human grandmaster Lee Sedol at the famously complex game of Go. The win prompted a flood of news stories about whether humans will become obsolete in a world of increasingly intelligent machines that don’t just follow instructions embedded in code, but actually learn. At Credit Suisse’s 2016 Thought Leader Forum, University of Washington computer science professor Pedro Domingos addressed the state of the art in machine learning, its current limitations and future potential, and what it all means for the economy.

The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats.

Pandas has got to be one of my most favourite libraries… Ever.
Pandas allows us to deal with data in a way that us humans can understand it; with labelled columns and indexes. It allows us to effortlessly import data from files such as csvs, allows us to quickly apply complex transformations and filters to our data and much more. It’s absolutely brilliant.

Along with Numpy and Matplotlib I feel it helps create a really strong base for data exploration and analysis in Python. Scipy (which will be covered in the next post), is of course a major component and another absolutely fantastic library, but I feel these three are the real pillars of scientific Python.