machine learning

Active learning is great, but what if you don’t already have a model? You can bootstrap your way to a machine learning model with majority-vote deterministic rules. Human labeled data is often the primary bottleneck in building good machine learning models.

Reproducible methods like knitr and version control using git are on their way toward being standard for academic code, even in social science disciplines such as political science. knitr, Rmarkdown, and Jupyter notebooks make it easy to verify that your findings and figures come from the most recent version of your code and that it runs without errors.