ray-project

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.

Distributed XGBoost on Ray

LightGBM on Ray

A toolkit to run Ray applications on Kubernetes

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

A Pythonic Data Catalog powered by Ray that brings exabyte-level scalability and fast, ACID-compliant, change-data-capture to your big data workloads.

Pytorch Lightning Distributed Accelerators using Ray

Keeping track of RL experiments

A Ray-based data loader with per-epoch shuffling and configurable pipelining, for shuffling and loading training data for distributed training of machine learning models.