© 2022, Anyscale. All Rights Reserved
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 | 📝 Notebook | 👩💻 Description | ⏱ Est. Time to Complete |
|---|---|---|---|
| Introductory Modules | Introduction to Ray | An Overview of Ray (Core, AIR, and Ecosystem) | 30 min |
- 💻 Minimal experience with Ray
- 🐍 Good skills in Python
- 📒 Familarity with Jupyter Notebooks
- 🧠 Working knowledge of machine learning
From here, you can learn and get more involved with our active community of developers and researchers by checking out the following resources:
- Ray's "Getting Started" Guides: A collection of QuickStart Guides for every library including installation walkthrough, examples, blogs, talks, and more!
- 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.