Ray - A Framework for Scaling and Distributing Python and ML Applications

Ray - A Framework for Scaling and Distributing Python and ML Applications

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Demo

20 of 28

20 of 28

Demo

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Classroom Contents

Ray - A Framework for Scaling and Distributing Python and ML Applications

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  1. 1 Introduction
  2. 2 Agenda
  3. 3 Industry Trends
  4. 4 Distributed Computing
  5. 5 Distributed Applications
  6. 6 Ray Ecosystem
  7. 7 Ray Internals
  8. 8 Ray Design Patterns
  9. 9 The Ray Ecosystem
  10. 10 Ray Tune
  11. 11 Ray Tune Search Algorithms
  12. 12 Hyperparameter Tuning
  13. 13 Hyperparameter Tuning Challenges
  14. 14 exhaustive search
  15. 15 Bayesian optimization
  16. 16 Early stop
  17. 17 Sample code
  18. 18 Worker processes
  19. 19 XCBoost Ray
  20. 20 Demo
  21. 21 Training
  22. 22 XRBoost Array
  23. 23 Hyperparameter Training
  24. 24 Example
  25. 25 Summary
  26. 26 Reinforcement Learning
  27. 27 Ray Community
  28. 28 Contact Jules

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