NYU Data Science newsletter – May 13, 2015

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… I recently started my third “real” job since finishing school; at my first and third jobs I have been a “data scientist”. I was a math major in college (and pretty good at it) and spent a year in the math Ph.D. program at the University of Virginia (and performed well there as well). These two facts alone would not have equipped me for a career in data science. In fact, it remains unclear to me that those two facts alone would have prepared me for any career (with the possible exception of teaching) without significantly more training.

pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.

With 672 million Tweets about the 2014 World Cup in Brazil, and over one billion fans reached, FIFA’s Twitter strategy certainly wasn’t an own goal. It was a veritable screamer. But there’s more to running the football governing body’s accounts than just posting up pictures of players and goals. With events going on all over the planet throughout the year, and numerous corporate initiatives to boot, FIFA’s social strategy continues even when the players’ 90 minutes are up.

We spoke to FIFA’s Social Media Manager, Alex Stone, about what it takes to tactically mastermind an award-winning social strategy for an event of the magnitude of the World Cup, how they plan to use Twitter in the future, and the peculiar story about their most successful social post. On top of this, we also dug into his strategy for the upcoming Women’s World Cup, which kicks off in June.

After 1.7 million miles we’ve learned a lot?—?not just about our system but how humans drive, too.

Amazon ML (Machine Learning) made a lot of noise when it came out last month. Shortly afterwards, someone posted a link to Google Prediction API on HackerNews and it quickly became one of the most popular posts. Google’s product is quite similar to Amazon’s but it’s actually much older since it was introduced in 2011. Anyway, this gave me the idea of comparing the performance of Amazon’s new ML API with that of Google. For that, I used the Kaggle “give me some credit” challenge. But I didn’t stop there: I also included startups who provide competing APIs in this comparison — namely, PredicSis and BigML. In this wave of new ML services, the giant tech companies are getting all the headlines, but bigger companies do not necessarily have better products.

Since its inception in the 1960s, the modern computer has offered humans the same “pull computing” paradigm: make a query, get a response. Or, as we often experience it: Go to the haystack, try to find the needle.

But that’s quickly changing. As software grows more intelligent and learns more about our preferences and behavior, it seemingly gets to know us. That knowledge makes software more valuable because it means that it can deliver things to us, perhaps even before we know we want it. We are at the start of the era of push computing.

Data from Spotify appear to confirm why your parents are so out of it: As people get older, they listen to less hot music of the moment, and instead just queue up the oldies.

This statistical crunch comes via Ajay Kalia, who calculated a popularity score for all songs that we streamed in 2014, and then examined who listened to them, and how old they were.

Authorities dig through prescription med databases thanks to pre-digital age precedent.

Topic 26: Student Loans

What should people who are interested in accountability and algorithms be thinking about? Here is one answer: My [Christian Sandvig] eleven-minute remarks are now online from a recent event at NYU. I’ve edited them to intersperse my slides.

Victor Gorbenko (NYU) gave an absolutely excellent PhD defense. Congratulations Dr Gorbenko.