Ray RLlib

Ray Train

Ray Datasets

RayDP

Retail

Gaming

Government

Financial

Ray Serve

Anyscale

Ray Core

Healthcare

Technology

Ray Tune

Press Interview

On-Demand Webinar

Webinar

RL Summit

Weekly Demo

Anyscale's webinars provide Ray users the opportunity to connect and learn from the global community of Ray experts.

Anyscale flavicon new white

Anyscale Connect

Ray Meetup

Anyscale GA Launch

Anyscale Academy provides training on the Ray ecosystem, tailored for data scientists, data engineers, and MLOps engineers.

Anyscale Academy Logo

Anyscale Academy

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.

Ray Summit

feng

Fengbin Fang

Fengbin Fang, Software Engineer, Ant Group

Application of Online Resource Allocation Based on Ray

joseph

Joseph Suarez

Joseph Suarez, PhD Student, MIT | Creator, Neural MMO

Neural MMO: Building a Massively Multiagent Research Platform with Ray and RLlib

sang

SangBin Cho

Data Processing on Ray

jaeyun

Jaehyun Sim

Amar Shah

Jaehyun Sim (Software Engineering Manager) & Amar Shah (Cloud Architect/Infrastructure Engineer), Ikigai Labs

Achieving Scalability and Interactivity with Ray Serve

carson wang

Carson Wang

Carson Wang, Software Engineering Manager, Intel Data Analytics Software Group

RayDP: Build Large-scale End-to-end Data Analytics and AI Pipelines Using Spark and Ray

richard decal

Richard Decal

Richard Decal, Lead ML Engineer, Dendra Systems

How Ray and Anyscale Make it Easy to do Massive-scale ML on Aerial Imagery

stephanie and yi

Stephanie Wang

Yi Cheng

Stephanie Wang, PhD Student, UC Berkeley | Software Engineer, Anyscale & Yi Cheng, Software Engineer, Anyscale

Ray Internals: Object Management with the Ownership Model

tengwei

Tengwei Cai

Tengwei Cai, Software Engineer, Ant Group

Building High Availability and Scalability Online Computing Applications on Ray

domingo

Juan Roberto Honorato

Domingo Ortuzar

Juan Roberto Honorato, AI Tech Lead, Anastasia

The Quick Journey to Using Ray: How We Implement Ray and Anyscale to Speed up our ML Processes

srini

Srinivasa Rao Aravilli

Srinivasa Rao Aravilli, Director of Engineering & Data Platforms, AI/ML & Privacy Engineering, Visa

Detection of Sensitive Personal Data in Large Data Sets Using Ray with Deep Learning

rob and dan

Daniel Imberman

Rob Deeb

Daniel Imberman (PMC Member, Apache Airflow | Software Engineer) & Rob Deeb (Senior Data Analytics Engineer), Astronomer.io

Data Science at Scale: From Notebook to Production with Airflow and Ray

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

NAME

EMAIL

COMPANY

Register to watch

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

A one stop shop for all events, past and future, to connect and learn from the global community of Ray experts.

hero2

Robert Nishihara on theCUBE

Watch the interview with Anyscale CEO Robert Nishihara and John Walls from theCUBE as part of their coverage of AWS re:Invent 2022 

TheCube Interviews Anyscale CEO at AWS re:Invent 2022 

Ray Meetup-July 25

Through a demo using XGBoost for classification, we will demonstrate how you can scale training, hyperparameter tuning, and inference with Ray — all from a single node to a cluster, with tangible improvements in performance.

Ray Meetup @ SF Bay ACM: Scaling ML/AI workloads with the Ray Ecosystem

Ray Meetup-June 22

It’s time for our June meetup, a monthly series, where we get together to discuss Ray and Ray’s native libraries for scaling machine learning workloads. This month, we have invited Ray community speakers from IBM and Stanford/ETH to share how they use Ray to solve challenging ML problems. Join us to learn about Ray community use cases.

Ray Community Talks: IBM Research and Stanford

Ray Meetup-May 25

Each month we get together to discuss Ray and Ray’s native libraries for scaling machine learning workloads. For May’s meetup, we have invited Ray community members Stanley Bishop (DeepChem.io), Jiaxin Shan (ByteDance), and Aniket Maurya (Grid.ai) to share how they use Ray to solve challenging ML problems.

Ray Community Talks: Grid.ai, DeepChem.io, and ByteDance

This section is used to order the "Types" and "Tags" that show up for filters on the Event Index

Event Types

All Products / Libraries

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

Events

Scalable AI and Python

Events

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