ray-project/ray-educational-materials
A collection of Jupyter notebook tutorials teaching distributed ML training and serving with the Ray framework.
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Contains hands-on materials covering Ray’s ecosystem for scaling deep learning, LLM training and inference, computer vision, and time-series forecasting workloads. Topics span ray-train, ray-tune, ray-serve, and ray-data for distributed data processing, targeting practitioners who want to parallelize ML workloads across clusters.
Frequently asked
- What is ray-project/ray-educational-materials?
- A collection of Jupyter notebook tutorials teaching distributed ML training and serving with the Ray framework.
- Is ray-educational-materials open source?
- Yes — ray-project/ray-educational-materials is open source, released under the Apache-2.0 license.
- What language is ray-educational-materials written in?
- ray-project/ray-educational-materials is primarily written in Jupyter Notebook.
- How popular is ray-educational-materials?
- ray-project/ray-educational-materials has 458 stars on GitHub.
- Where can I find ray-educational-materials?
- ray-project/ray-educational-materials is on GitHub at https://github.com/ray-project/ray-educational-materials.