Deep learning has enabled significant advances in a variety of domains; however, it relies heavily on large labeled datasets. Chelsea explains how we can use meta-learning, or learning to learn, to enable us to adapt deep models to new tasks with tiny amounts of data, by leveraging data from other tasks.