A comprehensive collection of data quality resources, tools, papers, and projects across various data types including traditional data, LLM pretraining/fine-tuning data, multimodal data, and more. Essential reference for researchers and practitioners in data-centric AI.
| Stars | 26 |
| Forks | 7 |
| Category | AI Tool |
| License | CC0-1.0 |
| Quality Score | 35.3/100 |
| Last Updated | 2026-04-18 |
| Created | 2025-03-03 |
| Est. Tokens | ~8k |
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awesome-data-quality is A comprehensive collection of data quality resources, tools, papers, and projects across various data types including traditional data, LLM pretraining/fine-tuning data, multimodal data, and more. Ess. It is categorized as a AI Tool with 26 GitHub stars.
You can find installation instructions and usage details in the awesome-data-quality GitHub repository at github.com/MigoXLab/awesome-data-quality. The project has 26 stars and 7 forks, indicating an active community.
awesome-data-quality is released under the CC0-1.0 license, making it free to use and modify according to the license terms.