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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-project/ray-educational-materials
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© 2022, Anyscale Inc. All Rights Reserved
Welcome to a collection of education materials focused onRay, 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. |
| 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. |
You can learn and get more involved with the Ray community of developers and researchers:
Official Ray siteBrowse 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 SlackFind friends to discuss your new learnings in our Slack space.
Use the discussion boardAsk questions, follow topics, and view announcements on this community forum.
Join a meetup groupTune in on meet-ups to listen to compelling talks, get to know other users, and meet the team behind Ray.
Open an issueRay is constantly evolving to improve developer experience. Submit feature requests, bug-reports, and get help via GitHub issues.
Become a Ray contributorWe welcome community contributions to improve our documentation and Ray framework.
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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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