OpenML
OpenML is a free, open platform for sharing machine-learning datasets, algorithms, and experiments through the web and an API.
What OpenML is
OpenML is a free, open platform for sharing machine-learning datasets, algorithms, and experiments through the web and an API. Its datasets are uniformly formatted, versioned, and ready to load, while standardized tasks provide predefined train/test splits and fixed evaluation protocols. OpenML tracks experiment details such as algorithms, hyperparameters, datasets, metrics, and hardware. It can automatically track and share pipelines, called flows, and experiment runs. Integrations are listed for Python with scikit-learn, PyTorch, TensorFlow, R, Julia, Rust, and .NET. A REST API supports uploading and downloading resources through XML and JSON endpoints. Datasets, flows, and runs can receive DOIs for citation. Data can be accessed without an account, though rate limits apply; uploading and managing resources requires an account, and API authentication uses a key from a signed-in profile. OpenML describes its community as including researchers, developers, data scientists, educators, and enthusiasts.
Good
- Free access to datasets and other resources.
- Versioned datasets use a uniform format.
- Standard tasks specify splits and evaluation protocols.
- Tracks and shares flows and experiment runs.
- DOIs support citation of datasets, flows, and runs.
Watch out
- Unauthenticated access is subject to rate limits.
- Uploading and managing resources requires an account.
- API authentication requires a signed-in user's key.
Who it suits
OpenML suits people who need to share or reproduce machine-learning experiments and datasets. It may also fit educators and developers working with its listed language and framework integrations.
Verdict
OpenML combines dataset sharing, experiment tracking, and standardized benchmarking in one platform. Public data access does not require an account, but uploads and resource management do.
Plans and prices
From OpenML's own pricing page, checked 4 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Free | Free | Open access; account required to upload resources; rate limits apply to unauthenticated data access |
The facts
Each one read from OpenML's own pages, with the date it was checked.
What it does
- Access limit
- Data can be accessed without an account, subject to rate limits; an account is required to upload and manage resources.checked 4 Oct 2026
- API
- OpenML offers a REST API for uploading and downloading machine learning resources, with XML and JSON endpoints.checked 4 Oct 2026
- Authentication
- API authentication uses a key available from a signed-in user's profile.checked 4 Oct 2026
- Benchmarking
- OpenML provides standardized tasks with predefined train/test splits and fixed evaluation protocols.checked 4 Oct 2026
- Citations
- OpenML supports DOI generation for datasets, flows, and runs so they can be cited.checked 4 Oct 2026
- Datasets
- OpenML says its datasets are uniformly formatted, versioned, and ready to load.checked 4 Oct 2026
- Experiment tracking
- OpenML supports automatic tracking and sharing of pipelines, called flows, and experiment runs.checked 4 Oct 2026
- Integrations
- The documentation lists integrations for Python/scikit-learn, PyTorch, TensorFlow, R, Julia, Rust, and .NET.checked 4 Oct 2026
- Purpose
- OpenML is an open platform for sharing datasets, algorithms, and experiments for machine learning.checked 4 Oct 2026
- Reproducibility
- OpenML tracks experiment metadata including algorithms, hyperparameters, datasets, metrics, and hardware.checked 4 Oct 2026
- Support
- OpenML lists its community discussions and the contact address [email protected].checked 4 Oct 2026
- Who it serves
- OpenML describes its community as researchers, developers, data scientists, educators, and enthusiasts.checked 4 Oct 2026
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