How to Set Up an ML Data Labeling Pipeline - Best Practices and Examples

How to Set Up an ML Data Labeling Pipeline - Best Practices and Examples

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Labeled data: the missing pillar of Al

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3 of 22

Labeled data: the missing pillar of Al

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How to Set Up an ML Data Labeling Pipeline - Best Practices and Examples

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  1. 1 Intro
  2. 2 Agenda
  3. 3 Labeled data: the missing pillar of Al
  4. 4 ML production pipeline
  5. 5 Data labelling requirements
  6. 6 Crowdsourcing - ML
  7. 7 Toloka platform
  8. 8 Crowdsourcing for ML data labelling
  9. 9 Instructions
  10. 10 Interface
  11. 11 Tolokers around the world
  12. 12 Filters Toloka example
  13. 13 Train your performers
  14. 14 Behavior checks
  15. 15 Fast responses example
  16. 16 Quality checks
  17. 17 Tips for control tasks
  18. 18 Control tasks example
  19. 19 Overlap and majority vote example
  20. 20 Pricing - Performance-based payment
  21. 21 Aggregation
  22. 22 Easy integration with other ML tools

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