OpenML
Collaborative machine learning platform for sharing datasets, tasks, algorithms, and experiments. Create reproducible ML benchmarks with standardized evaluation protocols and seamless scikit-learn integration.
About OpenML
OpenML is a collaborative machine learning platform that shares datasets, tasks, algorithms and experiments in one place. The point of it is reproducibility: standardised evaluation protocols so results can be compared rather than merely reported, with scikit-learn integration so running against a shared task is not a project in itself.
We track it rather than use it daily. We list it as the option for the moment the question stops being "does this work" and becomes "did this actually beat the baseline, and can someone else confirm it" — the point at which informal experiment notes stop being enough for anyone but you.
Weights & Biases and MLflow solve an adjacent problem: tracking your own runs rather than comparing against a shared public benchmark. Most teams need one of those regardless. Hugging Face is where modern model distribution and leaderboards live. Kaggle brings community and competition pressure to the same kind of data. The UCI repository remains the source for many of the classical benchmark sets OpenML organises around. OpenML is the wrong call if your work is large language models; that conversation happens elsewhere. It is right for classical machine learning, where a defined task and a comparable evaluation are exactly what you need.
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OpenML alternatives
Other Data Science & ML Datasets tools we use alongside OpenML.
Kaggle
World's largest data science community platform offering datasets, competitions, and machine learning models. Access millions of public datasets and participate in ML competitions with real-world problems.
View toolGoogle Dataset Search
Search engine for datasets across the web, making it easy to find datasets stored anywhere online. Discover publicly available datasets from government agencies, research institutions, and other organizations.
View tool
Frequently asked questions
- What is OpenML?
- Collaborative machine learning platform for sharing datasets, tasks, algorithms, and experiments. Create reproducible ML benchmarks with standardized evaluation protocols and seamless scikit-learn integration. OpenML is a collaborative machine learning platform that shares datasets, tasks, algorithms and experiments in one place. The point of it is reproducibility: standardised evaluation protocols so results can be compared rather than merely reported, with scikit-learn integration so running against a shared task is not a project in itself.
- What category does OpenML fall into?
- OpenML is a Data Science & ML Datasets tool. Replace Works tracks it in the Tool Lab, our public catalogue of the AI tools we evaluate and ship with.
- What are the best alternatives to OpenML?
- The closest alternatives we track in the same Data Science & ML Datasets category are Kaggle and Google Dataset Search. All of them are listed in the Replace Works Tool Lab with our notes on where each one fits.
- Does Replace Works use OpenML?
- OpenML is listed in our Tool Lab as a tool we have evaluated and recommend, but it is not currently in our day-to-day rotation.