We want this resource to grow with contributions from readers and data enthusiasts. Make a pull request if you want to add resources. All PRs will be reviewed and approved by the repository maintainers (Karan Goel, Laurel Orr) before merging.
- For making edits to existing areas and area pages, submit a PR containing the relevant changes. Many existing pages and areas are stubs where we could use help!
- We welcome changes such as missed subtopics, clarifying discussion, additional resources and links such as citations, paper links, blogs, videos, code, workshops, classes, tutorials, figures, pictures, recipes, tweets and books.
If you'd like to add a new area page, use the Area Page Issue to suggest a new area: your request will need to be approved by admins before you make any PRs that add a new area page.
- If writing a new area page, write a summary for the area and how it relates to data-centric AI in README.md.
- Add a new area page. In the area page, add subheaders for different subtopics that might be important. Add a few critical links (citations, paper links, blogs, videos, code, workshops, classes, tutorials, figures, pictures, recipes, tweets, books), and a short description for each sub-topic and how it relates to the section.
- Please only include and focus on work that is data-centric: our goal is not to build a general ML resource!
We want to gather interesting lists of resources and content that are related to data-centric AI. Please submit a PR if you'd like to add a new list or grow an existing one. We've included a list of workshops as an example.
- Use
h1orh2headers for all major headings (other subheadings can be in standard markdown). So, use<h1 id="sec:my-h1-section"></h1>or<h2 id="subsec:my-h2-section"></h2>to tag sections instead of standard markdown hashes.
Once you've made a contribution, please add your name, organization and what you contributed to the list of contributors at the end of README.md.