Eric Liang

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Announcing Ray 1.0

Dean Wampler

Pace Nathan

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Learn about Multi Armed Bandits and RL-based Recommender Systems at Ray Summit 2020

Ben Lorica

featured speakers

Trends in AI and Python Scalability: Reflections from the Ray Summit Program Chairs

Kai Fricke

PyTorch Lightning Ray

Scaling up PyTorch Lightning hyperparameter tuning with Ray Tune

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Videos and Slides for the Fourth Ray Summit Connect, August 12, 2020

Ion Stoica

Ion Stoica headshot

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Here’s what you need to look for in a model server to build ML-powered services

Sophia DeMartini

Video and Code for Anyscale Academy: Ray Tune and Ray Serve, July 22, 2020

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Forbes AI 50: America’s Most Promising Artificial Intelligence Companies

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Five Key Features for a Machine Learning Platform

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Videos and Slides for the Third Ray Summit Connect, July 8, 2020

Ray version 1.8 is here! Ray SGD has been renamed to Ray Train, Ray Datasets is now in beta, and more. Read the blog!

MLPatternsProduction

Considerations for Deploying Machine Learning Models in Production

C++ + Ray

Modern Distributed C++ with Ray

Ray 1.8

Ray version 1.8 has been released

From the creators of Ray, Anyscale is a framework for building machine learning applications at any scale originating from the UC Berkeley RISELab.

Anyscale

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Announcing Ray 1.0