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https://github.com/jonathandinu/spark-ray-data-science
Supporting content (slides and exercises) for the Pearson video series covering best practices for developing scalable applications with Spark and Ray in the context of a data scientist's standard workflow.
https://github.com/jonathandinu/spark-ray-data-science
artificial-intelligence data-science distributed-computing machine-learning python ray spark
Last synced: about 2 months ago
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Supporting content (slides and exercises) for the Pearson video series covering best practices for developing scalable applications with Spark and Ray in the context of a data scientist's standard workflow.
- Host: GitHub
- URL: https://github.com/jonathandinu/spark-ray-data-science
- Owner: jonathandinu
- Created: 2021-05-21T22:44:12.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-09-06T02:19:11.000Z (about 2 years ago)
- Last Synced: 2024-05-15T13:22:58.995Z (4 months ago)
- Topics: artificial-intelligence, data-science, distributed-computing, machine-learning, python, ray, spark
- Language: Jupyter Notebook
- Homepage: http://jonathans.estate/scaling-ds-videos
- Size: 105 MB
- Stars: 44
- Watchers: 2
- Forks: 4
- Open Issues: 0
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Metadata Files:
- Readme: README.md