Machine Learning in the Social Sciences:

Intermediate

June 15, 2023

2:00 p.m. - 6:20 p.m. (EST)

 

Dr. Jeff Gill

Distinguished Professor in the Department of Government and the Department of Mathematics, American University

 

Whether you are taking this workshop as a standalone session or as a follow up to Machine Learning in the Social Sciences: An Accessible Introduction, this workshop is ideal for anyone interested in digging deeper into the application of machine learning techniques. In this workshop, Dr. Gill will build on the basics of machine learning, presenting the various models and exploring the various challenges that present themselves when using such models in the context of big data. Using sample data and freely accessible software, participants will work through a series of short exercises that will train them to better handle big data problems. Upon completing this session, participants will also be aware of the various resources available for further learning in this area.

 

Outline

• Where can machine learning help?

• Models

• Solving big data problems

  • Exercises

• Further learning

 

Readings & Resources

Gill, Jeff. 2021. “Political Science Is a Data Science.” The Journal of Politics 83 (1): 1–7.

Alpaydin, Ethem. 2014. Introduction to Machine Learning. Cambridge: MIT Press.

Bishop, Christopher. 2006. Pattern Recognition and Machine Learning. New York: Springer.

 

Audience & Prerequisites

Participants must have some familiarity with probability, statistics, linear algebra and calculus. In this workshop, participants will work with different models to gain a better understanding of the ways in which machine learning can be practically applied. In order to get the most out of this workshop, participants are expected to have familiarized themselves with the content presented in the assigned readings.