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

Ray Meetup-July 25

Jules Damji

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

Gi-Joon Nam

Jinwook Jung

Tomasz Zaluska

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

Dmitri Gekhtman

Dmitri 

Stanley Bishop

Stanley Bishop-Rosal

Jiaxin Shan

Aniket Maurya

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

Ray Meetup-Data Science DC

Modern machine learning workloads are compute-intensive and require distributed execution. Ray is an open-source, general-purpose, distributed framework that easily scales Python applications and ML workloads from a laptop to a cluster. 


Ray Meetup @ Data Science DC: Scaling and distributing Python & ML applications with Ray

Ray Meetup-Ray Serve

Edward Oakes

Jiao Dong

Shreyas Krishnaswamy

Shreyas

It’s time for April's Ray Meetup, a monthly series where we get together to discuss Ray and Ray’s native libraries for scaling machine learning workloads. This month we will discuss Ray Serve, Ray’s ML framework-agnostic, production-ready, operational, and scalable model serving library.

Productionizing ML at scale with Ray Serve

Ray Meetup-Ray Train

Will Drevo

Amog Kamsetty

Matthew Deng

Mark Saroufim

Welcome to our second Ray meetup, where we focus on Ray’s native libraries for scaling machine learning workloads. 

We'll discuss Ray Train, a production-ready distributed training library for deep learning workloads. And will present TorchX and Ray Integration. Through this integration, PyTorch developers can submit PyTorch-based scripts and workloads to a Ray Cluster using TorchX’s SDK and CLI via its new Ray Scheduler.

Ray Train, PyTorch, TorchX, and distributed deep learning

Ray Meetup-BAyPIGgies

Today, AI applications are becoming pervasive across all sectors of our industry. Driven by a few fundamental trends, there is no indication of slowing down. In fact, the trend continues rapidly, making distributed computing at scale a norm and necessity.

Ray Meetup @ BAyPIGgies: Scaling AI workloads with the Ray Ecosystem

Ray Meetup-Data+AI Denver

Modern machine learning (ML) workloads, such as deep learning and large-scale model training, are compute-intensive and require distributed execution. Ray is an open-source, distributed framework from U.C. Berkeley’s RISELab that easily scales Python applications and ML workloads from a laptop to a cluster, with an emphasis on the unique performance challenges of ML/AI systems. It is now used in many production deployments.

Ray Meetup @ Data + AI Denver Meetup: Ray, a framework for scaling and distributing Python & ML applications

Welcome to our first Ray meetup in the New Year 2022, after two years of absence due to the Covid-19 pandemic. We are super excited to be back.


Ray Meetup is Back in the New Year 2022

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

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kubecon-2024

Meet Anyscale at Kubecon 2024

anyscale-reinvent2024

Meet Anyscale at AWS re:Invent

ray-singapore-meetup

[Ray Meetup] Exploring the Ray Framework for accelerating AI/ML Applications

ray compiled graphs

[Ray Meetup] Ray Compiled Graphs Deep Dive

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Event Types

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Events