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