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👉 Tip #21: Five sources for interesting datasets

Let’s say that you need to find a dataset for a Data Science project. Perhaps this is a project for school, or a practice project to build up your portfolio and showcase your skills.

Where should you look? Here are 5 sources I recommend checking out:

  1. Kaggle Datasets: It’s fun to browse, and the upvoting system makes it easy to discover higher-quality datasets. Also, its Data Explorer lets you see a preview of the raw data.
  2. Data Is Plural: This is a fascinating weekly newsletter (since 2015!) that highlights “useful/curious datasets.” Search its archive via a Google Sheet or web app.
  3. Awesome Public Datasets: A gigantic list (on GitHub) of high-quality datasets grouped by topic.
  4. Data.gov: Open data from the US government. It’s huge, well-organized, and more interesting than you would think!
  5. Google Dataset Search: This is a great way to search for a dataset, especially if you already have a specific topic in mind. Also, the autocomplete feature is quite nice!

Want even more options? Sebastian Raschka compiled this list of dataset repositories for Machine Learning and Deep Learning.


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See you next Tuesday!

- Kevin

P.S. If toddlers had lawyers (video)

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