Ray is an open-source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. Ray provides a simple, universal API for building distributed applications.
Ray is packaged with the following libraries for accelerating machine learning workloads:
Tune: Scalable Hyperparameter Tuning RLlib: Scalable Reinforcement Learning RaySGD: Distributed Training Wrappers Ray Serve: Scalable and Programmable Serving Datasets: Distributed Arrow on Ray (preview)
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Ray is an open-source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Ray provides a simple, universal API for building distributed applications.
Ray is packaged with the following libraries for accelerating machine learning workloads:
Tune: Scalable Hyperparameter Tuning
RLlib: Scalable Reinforcement Learning
RaySGD: Distributed Training Wrappers
Ray Serve: Scalable and Programmable Serving
Datasets: Distributed Arrow on Ray (preview)