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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.
| 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. |
| Scaling batch inference | Learn about scaling batch inference in computer vision with Ray. |
You can learn and get more involved with the Ray community of developers and researchers:
- Ray documentation
- Official Ray Website: 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