OpenML

Spec sheet

Purpose

OpenML is an open platform for sharing datasets, algorithms, and experiments for machine learning.Read 4 Oct 2026 · beta.openml.org

API

OpenML offers a REST API for uploading and downloading machine learning resources, with XML and JSON endpoints.Read 4 Oct 2026 · docs.openml.org

Integrations

The documentation lists integrations for Python/scikit-learn, PyTorch, TensorFlow, R, Julia, Rust, and .NET.Read 4 Oct 2026 · docs.openml.org

Support

OpenML lists its community discussions and the contact address [email protected].Read 4 Oct 2026 · beta.openml.org

Access limit

Data can be accessed without an account, subject to rate limits; an account is required to upload and manage resources.Read 4 Oct 2026 · docs.openml.org

Authentication

API authentication uses a key available from a signed-in user's profile.Read 4 Oct 2026 · docs.openml.org

Benchmarking

OpenML provides standardized tasks with predefined train/test splits and fixed evaluation protocols.Read 4 Oct 2026 · beta.openml.org

Citations

OpenML supports DOI generation for datasets, flows, and runs so they can be cited.Read 4 Oct 2026 · beta.openml.org

Datasets

OpenML says its datasets are uniformly formatted, versioned, and ready to load.Read 4 Oct 2026 · beta.openml.org

Experiment tracking

OpenML supports automatic tracking and sharing of pipelines, called flows, and experiment runs.Read 4 Oct 2026 · beta.openml.org

Reproducibility

OpenML tracks experiment metadata including algorithms, hyperparameters, datasets, metrics, and hardware.Read 4 Oct 2026 · beta.openml.org

Who it serves

OpenML describes its community as researchers, developers, data scientists, educators, and enthusiasts.Read 4 Oct 2026 · beta.openml.org

Plans and prices

Every OpenML plan and price →

Where Specifiction places it

• Experiment Tracking#10 of 227.4
• ML Experiment Tracking Software#22 of 397.3
• Machine Learning Data Catalog Software#8 of 147.1