Machine Learning in
Political Science

POLI_SCI 490

Winter 2026

Plan for today

  • Motivation for the course

  • Introductions

  • Course overview

Motivation

What is Machine Learning?

How is this different from the methods I already learned?

Motivation 1

Data Modeling Culture

vs.

Algorithmic Modeling Culture

Real world

Data Modeling Culture

Real world

Data Modeling Culture

Algorithmic Modeling Culture

Motivation 1 (revisited)

Inference

vs.

Prediction

Any issues with this?

Motivation 1 (revisited again)

\(\widehat \beta\)-Inference

vs.

\(\widehat Y\)-Prediction

Eventually these two traditions merge

Motivation 2

\[ p > n \]

Motivation 2

\[ p \gg n \]

What this course is not about

Computational Social Science

Programming in R, Python, Julia, etc.

Web scraping

Processing unstructured data

Generative AI

 

Emphasis: Incorporating new research methods

Introductions

Me

Gustavo Diaz

Assistant Professor of Instruction in Political Science
Email:
Website: gustavodiaz.org
Office: Scott Hall 103

You

  • Name
  • Pronouns
  • Discipline + subfield/research area
  • Would you rather be covered in feathers or scales?

Course overview

Textbooks

Textbooks

Assignments

  1. Participation

  2. Explorations (3)

  3. Collaborative note taking contributions (number TBD)

  4. Final project: Data and methods paper

Grading

  • Paper: outstanding, satisfactory, unsatisfactory, failed
  • Everything else: satisfactory, unsatisfactory, failed

Questions?