Code & ML research
GitHub
github.com
Code & ML researchfree
READMEs, docs folders and wikis are strong sources for how a tool actually works — paste the rendered page URL.
A maintainer's own README explains how a tool is meant to be used more reliably than a third-party blog tutorial written around it, and wikis or docs folders often carry detail that never made it into official documentation. That makes it a strong source for a notebook built around a specific library's real behavior. Check the repository's last commit date before trusting a README, since abandoned projects' docs can describe options that no longer exist.
Import into Gemini Notebook
- 1Copy the link above (or a specific page from the site).
- 2In your notebook, click Add source → Website.
- 3Paste the link and confirm — several links can be pasted at once, one per line.
Documentation pages import better than repositories: paste a project's docs URL or README page, not the repo root.
More code & ml research sources
- Papers with CodeML papers matched to their implementations and benchmarks — import the paper page and the README together.
- Hugging Face PapersA daily-curated feed of AI research, each paper with a discussion page that adds context.
- MDN Web DocsThe reference for web platform APIs — reliable ground truth for a web-dev notebook.
- Stack ExchangeAccepted answers on the technical sites make good targeted sources for narrow questions.