Dexa/Practical AI

Data Labeling Challenges

Michael discusses the future of data labeling, emphasizing the need for quality control and addressing challenges like weak supervision and identifying edge cases. Automation and AI augmentation are key in improving the labeling process.

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Practical AI
Open source data labeling tools
Related Questions
- What are the challenges in machine learning as discussed in the episode Data Selection for Data-Centric AI: Data Quality Over Quantity // Cody Coleman // Coffee Sessions #59 and the clip Data Labeling Challenges?