Introduction to Machine Learning and Computational Models in the Social Sciences
Our goal as social scientists is to build models of the world and provide advice to policy makers. Given that human actors are often strategic and the games they play are complex, building and testing these models is difficult and distinct from common examples of machine learning. A task that is often used to motivate introductions to machine learning is teaching a model to recognize hand-written characters using MNIST data (https://www.tensorflow.org/datasets/catalog/mnist). Our task is harder: we must build models that involve forecasting human behavior ranging from votes in a legislature to changes in stock prices.