NYU Data Science newsletter – October 21, 2015

GROUP CURATION: N/A

It takes a sharp manager to figure out who on a team really clicks with whom—and then carefully coordinate their interactions so that both employees feel good about work, thereby boosting their productivity.

At Concentrix, a customer-service provider, executives think that they may have found the secret to orchestrating group behavior: Make the manager a machine.

Information theory can seem kind of intimidating. I don’t think there’s any reason it should be. In fact, many core ideas can be explained completely visually! … Let’s focus on one variable like the weather. We know how probable it is that it’s sunny or raining. For both cases, we can look at the conditional probabilities. How likely am I to wear a t-shirt if it’s sunny? How likely am I to wear a coat if it’s raining?

“F.D.R.’s War Plans!” reads a headline from a 1941 Chicago Daily Tribune. Had this article been written today, it might rather have said “21 War Plans F.D.R. Does Not Want You To Know About. Number 6 may shock you!”. Modern writers have become very good at squeezing out the maximum clickability out of every headline. But this sort of writing seems formulaic and unoriginal. What if we could automate the writing of these, thus freeing up clickbait writers to do useful work?

If this sort of writing truly is formulaic and unoriginal, we should be able to produce it automatically. Using Recurrent Neural Networks, we can try to pull this off.

… Networks of related objects, be they nodes or wedding guests, are known to mathematicians as “graphs,” and graph coloring is the much-studied act of partitioning these objects into conflict-free sets. Most graphs, with their tangle of interconnections, are impossible to color with a limited palette. The larger they are, the more colors you need. Moving from node to node, alternating between colors, you inevitably get into traffic jams that force you to pull new hues out of the box. Likewise, in the real world, seating charts, meeting schedules and delivery routes can seldom be made optimal. But since the 1960s, mathematicians have escaped these coloring frustrations by working with so-called perfect graphs, which “behave very nicely with respect to coloring,” said Chudnovsky, a 38-year-old math professor at Princeton University.

… I love OpenStreetMap. It’s the best. In my opinion, it’s the most important thing to have happened to the geo community since Dr. Tomlinson started working with map overlays in the 1960s.

Geo-tech has rapidly grown and matured over the past two decades. Not long ago, most things GIS and geo-tech were reserved for governments (local to national) and academic institutions. Thankfully, that isn’t the case in today’s world. Geo-thinking and geo-tech is everywhere and OpenStreetMap is a major reason why.

But how has OpenStreetMap helped make location and geo so prevalent to a growing variety of industries and institutions outside of government and academia? Why is that story that Bill linked to so important?

Ed Cunningham is the front man and fiddle player for the Comet Bluegrass All-Stars, a band that has been playing every Sunday since 1996 (“except Easter,” he says) at the Comet, a bar in the Northside neighborhood of Cincinnati, Ohio. Thus the name. The All-Stars can be heard, along with Roseanne Cash, on a new album from the Cincinnati Pops Orchestra called “American Originals.”

He is also the head of the building code enforcement shop for the City of Cincinnati. That is not necessarily a likely launch pad for a thrilling data initiative that portends a tech renaissance that will shape the future of cities. But I’m here to tell you about Cunningham’s role in a project that does indeed provide that promise. With some help from an amazing program from the University of Chicago.

Our IT4BI Master studies finished, and the next logical step after graduation is finding a job. I was interested in Data Science jobs and this post is a summary of my interview experience and preparation.

The term “Data Science” is not yet well establish, so interviews for Data Science jobs might include a very broad range of questions, depending on the interpretation of the term by a particular company. In this post I attempt to organize Data Science interview questions in some usable form, but it might also be biased by how I see Data Science myself. I hope you also can find it useful.

The exponential growth of the Internet of Things (IoT) is far outpacing the ability of stakeholders to address safety standards and security concerns. This is not unusual as rapidly developing technology often challenges regulators and standards organizations to develop a framework for consensus governance. However, because the IoT transcends so many industries, there will be unprecedented difficulties with respect to harmonization of standards that will apply from one industry sector to another.

The efforts to develop and implement safety standards and government regulations have been taking place globally, albeit in fits and starts and not necessarily in synchronization among the developed countries. Nonetheless, as governments take note of the IoT, the number of threats identified continues to multiply.