Machine learning (ML) is a data-driven modeling approach that has become popular in recent years, thanks to major advances in software and hardware. Given enough data about a complex system, ML allows a computer model to imitate that system and predict its behavior. Unlike a deductive modeling approach, which requires some understanding of a system to be able to predict its behavior, the inductive approach of ML can predict the behavior of a system without ever understanding it in a traditional sense. Climate is a complex system, but there is not enough observed data describing an unprecedented event like global warming on which a computer model can be trained. Instead, it may be more fruitful to use ML to imitate a climate model, or a component of it, to greatly speed up computations. This will allow the parameter space of climate models to be explored more efficiently.