Machine learning for social scientists
Given the knowledge and practice as a social scientist (e.g., the understanding of regression methods), what would be the most useful information about Machine learning?
- The goal is different. yhat or beta?
- Because of the different focus, there are different emphasis. For instance, in ML, we focus more on preventing overfitting by employing dataset split, Cross validation, Regularization, and so on.
- ML is omnivorous. It doesn’t have to be a ‘statistical’ model. A good example would be the Genetic algorithm (see CGP Grey‘s ML video).