Creating complex models from scratch requires vast amounts of compute resources, data, and time. Transfer learning accelerates the process by leveraging commonalities between tasks (such as detecting edges in images) and applying those learning to a new task. Training time for a model can go from weeks to hours, making machine learning more commercially viable for many businesses.