NYU Data Science newsletter – September 9, 2015

GROUP CURATION: N/A

In this entry, we briefly summarize several thought-provoking findings from the Good Judgment Project. These findings helped us improve our aggregated forecasts and win the Aggregative Contingent Estimation (ACE) forecasting tournament, sponsored by IARPA. We also provide references to the original papers for curious readers.

Videos from Startup.ML @Bloomberg #mlearning for #fintech event are up. Great talks about mortgage portfolio risk & fraud

Activision allowed two of their most credentialed employees to host a PAX ’15 panel on the role users play in game development. PhDs Justin Shacklette and Spencer Stirling spent nearly an hour explaining how the company is constantly, intelligently collecting data referred to as “Smart Data.”

Facebook is overhauling its Pages feature to make it more useful for businesses in its biggest update since 2012, the company announced Tuesday afternoon.

It’s adding new call-to-action buttons that will let businesses encourage potential customers to do things like book appointments at a spa, peruse a resturant’s menu, or browse the products a store offers.

The National Science Foundation (NSF) has awarded $3 million to researchers at NYU Steinhardt School of Culture, Education, and Human Development and Stanford University Graduate School of Education to create a language-focused science curriculum for fifth graders.

The four-year project, which began Sept. 1, will pay particular attention to developing science education that supports English language learners.

This repo contains code to transform Hillary’s emails from raw PDF documents to a SQLite database.

This is a work in progress – any help normalizing and extracting this data’s much appreciated!

… It’s presentation day at SAILORS, the Stanford Artificial Intelligence Laboratory’s Outreach Summer program, the country’s first AI summer camp for girls. Backed by more than forty university professors, postdoctoral scholars, and graduate students from the lab, as well as big-name corporate sponsors like Google, the camp aims to remove the Achilles heel of AI research and, indeed, computer science as a whole: there aren’t enough women.

… One study, by three scientists from Germany’s Alfred Wegener Institute, uses computers to model how Greenland’s rapid thawing could affect the Atlantic meridional overturning circulation, the system that pushes cold, dense saltwater into the deep ocean and helps transport warm water northward, helping to warm Europe’s climate.

Their report, in the journal Geophysical Research Letters, says previous research may have underestimated changes to the ocean from the huge influx of fresh, cold water from melting ice sheets. Using new methods, the German scientists were able to estimate more precisely how much ice would melt and how all that added freshwater would affect ocean circulation.

We introduce the participant to modern distributed file systems and MapReduce, including what distinguishes good MapReduce algorithms from good algorithms in general. The rest of the course is devoted to algorithms for extracting models and information from large datasets. Participants will learn how Google’s PageRank algorithm models importance of Web pages and some of the many extensions that have been used for a variety of purposes. We’ll cover locality-sensitive hashing, a bit of magic that allows you to find similar items in a set of items so large you cannot possibly compare each pair. When data is stored as a very large, sparse matrix, dimensionality reduction is often a good way to model the data, but standard approaches do not scale well; we’ll talk about efficient approaches. Many other large-scale algorithms are covered as well, as outlined in the course syllabus.

Course begins on Saturday, September 12

We are currently accepting applications for the Data Science MS program and Non-Degree program (deadlines below). Please review the frequently asked questions prior to starting your application. Detailed admission requirements are also available on this website.

Application Deadlines

November 1st, 2014: Non-degree seeking students for Spring 2016

February 4th, 2016: Degree (MS in Data Science) seeking students for Fall 2016

August 1st, 2016: Non-degree seeking students for Fall 2016