Machine Learning and Data Science for Economists

 

October 25-26, 2018 

2 days, 8:30 AM – 4:30 PM
Federal Reserve Bank of San Francisco

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: $1,600

U.S. Government Employee: $1,675

Non-Member: $1,750


To be eligible for a refund less $50 fee, registration cancellation must be received in writing by September 12, 2018.  Questions? Please contact NABE at [email protected] or phone 202-463-6223.


REGISTER ONLINE

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and scan/email to [email protected] or fax 202-463-6239. Registration by email/fax includes a $25 processing fee.  Save $25 by registering online! 

Course Location:

Federal Reserve Bank of San Francisco
101 Market Street
San Francisco, CA 94105

Travel Information:


InterContinental San Francisco 
888 Howard Street
San Francisco, CA 94103

NOTE: NABE has secured a limited number of discounted rooms at the InterContinental San Francisco at the rate of $229/night for the nights of October 25 and 26.  Please note that this hotel is a mile from the Federal Reserve Bank of San Francisco. Unfortunately, this rate is not available for the night of October 24 due to a large convention in the city, and as a result, many of the other hotels in the area have very expensive rates for that night. For more affordable options for the night of October 24, you may want to consider looking into hotels in the Oakland area, which is connected to the Financial District area of San Francisco (where the Bank is located) by the BART transit system.  

You can make a reservation in our block at the InterContinental by using this link and entering our group code TN8 or by calling 866-781-2364 and mentioning the group code. Rooms are available until October 5, 2018, or until the room block is exhausted, whichever occurs first.  


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.