Machine Learning and Data Science for Economists

 

July 26-27, 2018 

2 days, 8:30 AM – 4:30 PM
U.S. Bureau of Labor Statistics - Boston Regional Office

This course aims to speak to the value of using methods from machine learning and data science for the applied business economist.  More course information

Registration Details

NABE Member Early-Bird*: $1,600

U.S. Government Employee Early-Bird*: $1,675

Non-Member Early-Bird*: $1,750


To be eligible for a refund less $50 fee, registration cancellation must be received in writing by June 20, 2018.  Questions? Please contact NABE at [email protected] or phone 202-463-6223.


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Location

U.S. Bureau of Labor Statistics Boston Regional Office
JFK Federal Building
25 New Sudbury Street
Boston, MA 02203


Travel Information

Nearby Hotels:

Kimpton Onyx Hotel
155 Portland Street
Boston, MA 02114

Holiday Inn Express & Suites Boston Garden
280 Friend Street
Boston, MA 02114

Ames Boston Hotel - Curio Collection by Hilton
1 Court Street
Boston, MA 02108

About the Instructor



Matthew Harding is an Econometrician and Data Scientist who develops machine learning and artificial intelligence techniques to answer Big Data questions related to individual consumption and investment decisions in areas such as health, energy, and finance. He is an Associate Professor of Economics and Statistics at UC Irvine. He holds a PhD in Economics from MIT and an MPhil in Economics from Oxford University. He directs the Deep Data Lab which conducts research into cutting edge econometric methods for the analysis of “deep data”, large and information-rich data sets derived from many seemingly unrelated sources to provide novel economic insights. At the same time his research emphasizes solutions for achieving triple-win strategies.  These are solutions that not only benefit individual consumers, but are profitable for firms, and have a large positive impact on society at large. Professor Harding advised a number of companies and agencies on economics and data science problems, including Apple, US Commodity Futures Commission, World Bank, Electric Power Research Institute (EPRI), and the Department of Justice. He is also an advisor to a number of technology startups.