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Conference: Transform X 2021
Authors: Andrew Ng
2021-10-07
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The presentation discusses the development of data-centric AI and provides tips for its implementation, with a focus on unstructured data.
- Data-centric AI is becoming more widespread and systematic in its approach
- Consistent labeling of data is crucial for learning algorithms to work effectively
- Error analysis and engineering examples are important for structured data
- Data augmentation and noise examples can be useful for unstructured data
- Focusing on subsets of data can improve performance