Machine learning

Machine learning is simply an extension of statistics. The basics are the same:

• learn from training data
• evaluate in test data
• pick the learner that does the best
• predict for new cases!

The only difference with machine learning is that a huge number of candidate learners are available to you. The pages that follow introduce a few of those learners.

Optional resources

Grimmer, Justin, Margaret E. Roberts, and Brandon M. Stewart. 2022. Machine learning for social science: An agnostic approach. Annual Review of Political Science 24: 395-419.

Molina, Mario, and Filiz Garip. 2019. Machine learning for sociology. Annual Review of Sociology 45: 27-45.

Athey, Susan, and Guido W. Imbens. 2019. Machine learning methods that economists should know about. Annual Review of Economics 11: 685-725.

Lundberg, Ian, Jennie E. Brand, and Nanum Jeon. 2022. Researcher reasoning meets computational capacity: Machine learning for social science. Social science research 108: 102807.