OpenML is readily integrated into a large and growing number of machine learning libraries and environments, so you can easily download and upload OpenML datasets, train models, and share the results. If you want to integrate your own machine learning tool, see the available APIs, or join us in one of our hackathons!
Most scikit-learn machine learning algorithms, pipelines, and optimization procedures (e.g. RandomSearchCV) are readily supported through the Python API. Also any algorithm that can be wrapped as an scikit-learn estimator (e.g. xgboost) is supported.
Documentation Jupyter Notebook Online demo
In all integrations, you can easily authenticate by setting your API key once (and then forget about it). See the tool-specific instructions above on how to do this. You can find your API key in your profile (after logging in).