Where to Find ML Datasets

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A curated list of the best places to find datasets for your machine learning projects — as recommended in Hands-On Machine Learning by Aurélien Géron (Chapter 2).

📌 Note from the book: Chapter 2 uses the California Housing Prices dataset from StatLib, based on 1990 census data. It’s small, well-structured, and perfect for practicing a full ML workflow end-to-end.

🗂️ Popular Open Data Repositories

UC Irvine Machine Learning Repository

One of the oldest and most respected ML dataset collections. Maintained by UC Irvine, it hosts hundreds of datasets across classification, regression, and clustering tasks — each well-documented with attribute descriptions and usage history.

Kaggle Datasets

The go-to platform for competitive ML. Beyond competitions, Kaggle hosts thousands of community-submitted datasets on virtually every topic — complete with notebooks, public code, and discussions from other practitioners.

Amazon AWS Open Datasets

Amazon’s registry of large-scale public datasets hosted on AWS — including satellite imagery, genomics, weather, and more. Ideal when you need serious data volume and want to work directly in the cloud.


🔎 Meta Portals — They Index Other Repositories

Data Portals

A comprehensive directory of open data portals from governments, cities, research institutions, and international organizations worldwide. If you need official or civic data, this is the place to start.

OpenDataMonitor

A European initiative that tracks and monitors open data catalogs across the EU and beyond. Useful for finding government and public-sector datasets with a regional or policy focus.

Quandl (now Nasdaq Data Link)

A well-known financial and economic data platform with a generous free tier covering macro indicators, commodities, and exchange rates. Solid choice for anything finance-related.


💬 Other Useful Pages & Communities

Wikipedia — ML Datasets List

Wikipedia’s community-maintained list of datasets used in ML research, organized by domain (image, text, speech, graph, etc.). A great reference when looking for well-known benchmarks for a specific task.

Quora — Dataset Recommendations

Community Q&A threads where practitioners share lesser-known dataset sources. Useful for finding niche datasets for unusual domains that don’t appear in the standard directories.

r/datasets — The Datasets Subreddit

An active Reddit community where users share, request, and discuss datasets. Great for finding real-world, freshly scraped, or unusual datasets that haven’t made it to the major platforms yet.


📚 Source: Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow — Aurélien Géron, Chapter 2.

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