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This repository has been archived by the owner on Mar 24, 2024. It is now read-only.

This is suite of the hands-on training materials that shows how to scale CV, NLP, time-series forecasting workloads with Ray.

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Ray Educational Materials

© 2022, Anyscale Inc. All Rights Reserved

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Introductory notebooks test Ray core notebooks test Semantic segmentation notebooks test Observability notebooks test

Welcome to a collection of education materials focused on Ray, a distributed compute framework for scaling your Python and machine learning workloads from a laptop to a cluster.

Recommended Learning Path

Module Description
Overview of Ray An Overview of Ray and entire Ray ecosystem.
Introduction to Ray AI Runtime An Overview of the Ray AI Runtime.
Ray Core: Remote Functions as Tasks Learn how arbitrary functions to be executed asynchronously on separate Python workers.
Ray Core: Remote Objects Learn about objects that can be stored anywhere in a Ray cluster.
Ray Core: Remote Classes as Actors, part 1 Work with stateful actors.
Ray Core: Remote Classes as Actors, part 2 Learn "Tree of Actors" pattern.
Ray Core: Ray API best practices Learn Ray patterns & anti-patterns and best practices.
Scaling batch inference Learn about scaling batch inference in computer vision with Ray.
Optional: Batch inference with Ray Datasets Bonus content for scaling batch inference using Ray Datasets.
Scaling model training Learn about scaling model training in computer vision with Ray.
Ray observability part 1 Introducing the Ray State API and Ray Dashboard UI as tools for observing the Ray cluster and applications.
LLM model fine-tuning and batch inference Fine-tuning a Hugging Face Transformer (FLAN-T5) on the Alpaca dataset. Also includes distributed hyperparameter tuning and batch inference.
Multilingual chat with Ray Serve Serving a Hugging Face LLM chat model with Ray Serve. Integrating multiple models and services within Ray Serve (language detection and translation) to implement multilingual chat.

Connect with the Ray community

You can learn and get more involved with the Ray community of developers and researchers:

  • Ray documentation

  • Official Ray site Browse the ecosystem and use this site as a hub to get the information that you need to get going and building with Ray.

  • Join the community on Slack Find friends to discuss your new learnings in our Slack space.

  • Use the discussion board Ask questions, follow topics, and view announcements on this community forum.

  • Join a meetup group Tune in on meet-ups to listen to compelling talks, get to know other users, and meet the team behind Ray.

  • Open an issue Ray is constantly evolving to improve developer experience. Submit feature requests, bug-reports, and get help via GitHub issues.

  • Become a Ray contributor We welcome community contributions to improve our documentation and Ray framework.