Ray Summit brings together the community of architects, machine learning engineers, researchers, and other developers building the next generation of scalable, distributed, high-performance Python and machine learning applications. The conference will include those who are already using Ray platform and those who are interested in learning how Ray can meet their needs.

devin

Devin Petersohn

Devin Petersohn, PhD Student, UC Berkeley

Scaling Interactive Data Science with Modin and Ray

chris van p

Chris Van Pelt

Chris Van Pelt, Co-founder, Weights & Biases

W&B Tables and Ray

clark

Clark Zinzow

Clark Zinzow, Software Engineer, Anyscale

Per-epoch Shuffling Data Loader: Mix It Up As You Train!

wildlife

Emiliano Castro

Vinicius Alves

Felipe Antunes

Emiliano Castro (Principal Data Scientist), Vinicius Alves
(Data Scientist), & Felipe Antunes (Staff Data Scientist), Wildlife Studios

Using Reinforcement Learning to Optimize IAP Offer Recommendations in Mobile Games

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travis

Travis Addair

End-to-End AutoML with Ludwig on Ray

patrick 

Patrick Ames

Patrick Ames, Senior Software Engineer, Amazon

Petabyte Scale Datalake Table Management with Ray, Arrow, Parquet, and S3

simon

Simon Mo

Ray Serve: Patterns of ML Models in Production

kai and michael

Michael Mui

Kai Fricke

Michael Mui, Senior Software Engineer, Uber ML & Kai Fricke, Software Engineer, Anyscale

Distributed XGBoost on Ray

edi 

Edi Palencia

Edi Palencia, Principal AI Engineer, Microsoft

Offline RL with RLlib

raoul

Raoul Khouri

Raoul Khouri, Quantitative Software Engineer, Two Sigma

A 24x Speedup for Reinforcement Learning with RLlib + Ray

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

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