Ray RLlib

Ray Train

Ray Datasets

RayDP

Retail

Gaming

Government

Financial

Ray Serve

Anyscale

Ray Core

Healthcare

Technology

Here you can find where the Anyscale and Ray teams will be in attendance at industry events across the globe. 

Industry Event

Press Interview

On-Demand Webinar

Webinar

RL Summit

Weekly Demo

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

dawn

Dawn Song

Dawn Song 2

Towards Building a Responsible Data Economy

tianqi

Tianqi Chen

Tianqi Chen, Assistant Professor, ML & CS Department, Carnegie Mellon University | CTO, OctoML | Creator of Apache TVM, XGBoost, and the co-creator of Apache MXNet

Elements of Learning Systems

eric b

Eric Brewer

Eric Brewer, VP Infrastructure & Google Fellow, Google | Professor, UC Berkeley

Lessons from the Kubernetes Adventure

panel

Zhe Zhang

Xu Ning, PhD

Xu Ning

Azeem Ahmed

Bhavya Agarwal

Zhe Zhang (Open Source Engineering Lead), Anyscale; Xu Ning, PhD, (Senior Engineering Manager), Uber; Azeem Ahmed (Director of Data Platform Engineering), Shopify; Bhavya Agarwal (ML Engineer), Robinhood

Panel: ML Platform on Ray

dong li

Dong Li

Dong Li, PMC Member, Apache Kylin | Founding Member & Product Head, Kyligence

Simplify Big Data & AI on Spark and Ray with MLSQL

k & l

Kai Huang

Luyang Wang

Luyang Wang 2

Kai Huang, Software Engineer, Intel & Luyang Wang, Director of Machine Learning Engineering & Data Science, Restaurant Brands International

Mobile Order Click-Through Rate (CTR) Recommendation with Ray on Apache Spark at Burger King

stefan

 Stefan Schneider

Stefan Schneider, PhD Candidate & Researcher, Paderborn University

DeepCoMP: Multi-agent Reinforcement Learning for Multi-cell Selection in 5G and Beyond

Hao Chen

Improving Ray for Large-scale Applications

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

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

hero2

Thumbnail: Webinar: Getting Started with Distributed Training at Scale

Getting Started with Distributed Training at Scale

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 Live Virtual Hands On Lab: Building Scalable AI with Ray 

Lineage Tracking webinar cover photo

From Unity Catalog to MLflow: Experiment Tracking and Lineage for Ray

Virtual Hands on Lab

 Live Virtual Hands On Lab: Building Scalable AI with Ray

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

Event Types

All Products / Libraries

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Events