Taming Large Scale Deep Learning

Building practical applications powered by deep learning remains an enormous challenge. This talk describes how deep learning workflows are supported by existing software tooling and several promising opportunities to improve these workflows via automated hyperparameter optimization, efficient utilization of distributed resources, and reproducible workflow management.