Data & official records

UCI ML Repository

archive.ics.uci.edu

Data & official recordsfree

Long-running archive of benchmark datasets for machine learning. Each dataset page documents variables and provenance — import the page, not the raw CSV.

Each dataset page documents the variables, collection method, and known issues, which is what you want in a notebook explaining a classic dataset like Iris or Adult Income rather than just handing over numbers with no context. It fits teaching notebooks that walk through a specific algorithm or feature-engineering problem. Most of the datasets are small, tabular, and decades old at this point, so it won't help with anything needing modern-scale or unstructured data.

Open UCI ML Repository

Import into Gemini Notebook

  1. 1Copy the link above (or a specific page from the site).
  2. 2In your notebook, click Add source → Website.
  3. 3Paste the link and confirm — several links can be pasted at once, one per line.

Gemini Notebook is a reading tool, not a spreadsheet engine — feed it the written reports and summary pages, not raw CSVs, and ask about what the documents say.

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