NYU Data Science newsletter – October 13, 2015

GROUP CURATION: N/A

… The success of startups like Expii helps build CMU’s reputation as a center for innovative companies and attracts more investment dollars to Pittsburgh.

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On Thursday, Expii was among the companies featured in an event called LaunchCMU, a bi-annual showcase of the university’s technology startups.

As new students have flooded the halls for the new terms at JHU Biostat, I figured I would give some recommendations to our new students, and biostatistics students in general. Some of these things may be specific to our department, but others are general, so the title should be fitting. Let’s dive in!

First Term Things … Don’t buy books

Universities are struggling to find balance between academic openness and the need for computer security across their networks.

As I spoke with friends leading up to Strata + Hadoop World NYC 2015, one topic continued to come up: metadata. It’s a topic that data engineers and data management researchers have long thought about because it has significant effects on the systems they maintain and the services they offer. I’ve also been having more and more conversations about applications made possible by metadata collection and analysis.

At the recent Strata + Hadoop World, U.C. Berkeley professor and Trifacta co-founder Joe Hellerstein outlined the reasons why the broader data industry should rally to develop open and vendor-neutral metadata services. He made the case that improvements in metadata collection and sharing can lead to interesting applications and capabilities within the industry.

Below are some of the reasons why Hellerstein believes the data industry should start focusing more on metadata:

Unicorn Data Scientists (upgraded from “sexy data scientists”) are hard to find and are paid more than $200,000 per year. A new survey finds that the rising data science tide lifts the compensation of all other data analytics professionals , even if they don’t know how to code.

The Burtch Works Study: Salaries for Predictive Analytics Professionals is based on interviews with 1,757 data analytics professionals conducted over the 12 months ending April 2015 by executive recruiting firm Burtch Works. It is a unique source of information in that it does not rely on self-reporting or data provided by human resources departments.

The 2015 NESSIS page has been created, and contains the full program, selected presentations and talk videos, and a link to pictures from the conference.

At Dataquest, we want to help our users get a better sense of how data science works in industry as part of the data science educational process. We’ve started a series where we interview experienced data scientists. We highlight their stories, advice they have for budding data scientists, and the kinds of problems they’ve worked on. The first post in this series is our interview with Trey Causey.

This is the first in a series of three blogposts about the Seeing Data project. The first post is guest written by Helen Kennedy, Professor of Digital Society at the University of Sheffield and director of Seeing Data. Part one discusses some of the findings and what this means for how we think about ‘effective’ visualisations.

Nowadays training deep learning models have become extremely easy with high-quality libraries such as Torch and Theano. These libraries are really helpful for rapidly prototyping deep learning models even without understanding much about deep learning algorithms. However, the underpinning of algorithms will help us to get maximum benefits from above deep learning libraries. Therefore, this (and upcoming) tutorials will discuss few deep learning algorithms and implement them using Python/Numpy

Data and research scientists, postdocs, faculty, and staff gathered from the University of Washington, Berkeley, New York University, and both the Moore and Sloan foundations for the annual Data Science Environment Summit. Hosted this year by UW’s eScience Institute, the gathering took place October 4th through 7th at Suncadia Resort, nestled in the eastern foothills of the Cascade Mountains.