We have developed mlLang as an XML-based, unified language for machine learning. It standardizes all relevant steps to train superior models: preprocessing operations, model specification, and the tuning process.
Our simple converters support R and Python. Now, changes between languages have become simple and effortless. Plus: all steps are now documented and reproducible.
A visual interface brings machine learning to everyone. Predictive models are no longer miracles of individuals. Instead, everyone can unleash the power of forecasting with simple drag-and-drop.
Our graphical user interface generates model descriptions in mlLang. These are optionally trained with either R and Python. The unified language for machine learning makes it afterwards straightforward to deploy trained models.
Stay in the loop: our desktop application is under development and will become open source in late 2017.
We are continuously improving mlLang to make machine learning reproducible. Our R package has just been released. We soon expect to publish a first stable version for Python. Await more news soon!
A large user base improves mlLang with their constant feedback. Here are just a few:
Need more details? Contact us
We are here to assist. We look forward to get in touch with potential users, receive their feedback or collaborate with our research deparments. Contact us by phone or email.
Dr Stefan Feuerriegel
Chair for Information Systems Research
University of Freiburg
Phone: +49 761 203 2400