HazyResearch/data-centric-ai resource

Health v2 · maintenance only

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1147 stars · 120 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated, opinionated collection of resources, papers, and progress on Data-Centric AI from the Hazy Research group at Stanford. It organizes topics like weak supervision, data augmentation, data cleaning, robustness, and MLOps into a structured reading guide.

Use cases

• learn about data-centric ai
• find papers on weak supervision and data programming
• study data augmentation and cleaning techniques for machine learning
• prepare a course or reading list on data quality for ML
• explore mlops and data selection resources
• understand why data matters more than models in production ai

When to choose

• you want a curated starting point for data-centric AI research and concepts
• you are building a curriculum or self-study plan around data quality in ML
• you want links to papers, case studies, and related awesome lists in one place

When to avoid

• you need runnable code, libraries, or tools rather than reading material
• you need up-to-date coverage, as several sections are stubs or under construction
• you want an unbiased survey rather than an opinionated viewpoint

Facets

learning-resource · maturity maintenance

documentation machine-learning machine-learning data-science artificial-intelligence tutorials cross-platform data-centric-ai curated-list awesome-list research-resources mlops data-quality

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markdown · JSON · MCP: product_card(name="HazyResearch/data-centric-ai")