Speed up model development by 100x via distributed training and best-in-class hyperparameter search.
Manage and share GPU resources, on premises, in the cloud, or both.
Run unmodified TensorFlow, Keras, and PyTorch code on Kubernetes or bare-metal.
Track, share, and reproduce experiments and metrics automatically.
Optimize models through automated architecture search for constrained deployments.
Explore and visualize results using GPU-powered notebooks.