A collection of objects and routines to help you develop your own distributed machine learning algorithm. It has two modes, federated, where a server is keeping track of the model, and decentralized, where each participant has their own local model. You can train your model directly in the browser, allowing it to run on a variety of hardware. Many extensions are in the pipeline, such as adding Byzantine resistance or training without revealing the model. Compared to other solutions, Disco is bridging the gap between people creating machine learning models and people having relevant data. By running without installation nor complex configuration, anyone can help. It's also a breeding ground for new machine learning technologies.