Scaling Machine Learning Pipelines in Cloud

Scaling Machine Learning Pipelines in Cloud

NDC Conferences via YouTube Direct link

Intro

1 of 43

1 of 43

Intro

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Classroom Contents

Scaling Machine Learning Pipelines in Cloud

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  1. 1 Intro
  2. 2 About Salman
  3. 3 Giveaway
  4. 4 Agenda
  5. 5 Who is this talk for
  6. 6 Training Models
  7. 7 Docker
  8. 8 Where can we run Kubernetes
  9. 9 Benefits of Kubernetes
  10. 10 Scaling Pipelines with Kubernetes
  11. 11 Introducing Kubernetes
  12. 12 Data Science Machine Learning Engineers
  13. 13 Kubernetes tools
  14. 14 Operators
  15. 15 Fashion mnist
  16. 16 Neural Network
  17. 17 Hyper Parameters
  18. 18 Auto ML
  19. 19 Serving
  20. 20 kubeflow
  21. 21 Why Kubernetes
  22. 22 Data Science and Machine Learning
  23. 23 QFlow Pipeline
  24. 24 MiniCube
  25. 25 Python Pipeline SDK
  26. 26 GPU Pipeline
  27. 27 GPU Worker
  28. 28 Experimenting
  29. 29 Running the pipeline
  30. 30 Kale
  31. 31 Notebook
  32. 32 Kubernetes Extension
  33. 33 Adding Labels
  34. 34 Creating a Pipeline
  35. 35 Scaling Pipelines
  36. 36 Kubernetes Autoscaling
  37. 37 Considerations
  38. 38 Platform Management
  39. 39 OpenAI
  40. 40 Summary
  41. 41 References
  42. 42 Thanks
  43. 43 Outro

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