OpenML

We believe that machine learning research should be open, well-organized and easily accessible to anyone. There is amazing machine learning research going on every day in labs all over the world. What if we could easily share the latest great results (datasets, code, experiments) from all of our labs and organize them online, so that everyone can easily discover and access them, use them in myriad unexpected ways, and solve problems together on a global scale?

We strive to make as many datasets as possible easily discoverable, well documented, and frictionlessly accessible. When new models are trained and evaluated, we also make these results easily discoverable, clearly documented and reproducible, so that we can trust them, learn from them, and build on the combined results of the planet. And of course, we use machine learning on top of all this data to make new discoveries and automate our work.

We want to build the tools that we ourselves like to use, that empower us, and make our lives easier. Built around open interfaces, OpenML can be used to automatically share (and import) datasets, algorithms, and experiment results straight from the tools that we already know and love. Through our APIs, OpenML can be easily integrated into new workflows and processes, to import new data and export new results. We also believe in great standards for collecting and sharing data and for collecting and analyzing experimental results.

OpenML is being built by an awesome open source community. All code of the OpenML project carries the BSD-3 Clause license. Anyone with an interest in the project can join the community, contribute to the project design, and participate in the decision-making process, as well as meetings (e.g. hackathons) and online discussions. Dedicated contributors can be nominated to become core members, trusted to develop and maintain OpenML with care. Core members, in turn, can be nominated for the steering committee, and keep the project running smoothly with the help of the Open Machine Learning Foundation.