mlLang

A unified language for machine learning

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Automated conversion between machine learning code from R and Python by using mlLang

OUR TECHNOLOGY

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.

Read research paper

HOW TO USE

Simply initialize mlLang when starting your programming session.

Afterwards, all machine learning operations are recorded and written to the disk in an open XML format. This file can be later loaded to reproduce models and training processes from machine learning.

Get source form GitHub
Native integration into R and Python

VISUAL INTERFACE

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.

Visual interface facilitiates development with mlLang
News

LATEST UPDATES

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!

OUR USERS

A large user base improves mlLang with their constant feedback. Here are just a few:

  • University of Freiburg
  • Chair for Information Systems Research
  • ZF
  • TonalityTech

OUR TEAM

The work behind mlLang is led by the analytics group at the Chair for Information Systems, University of Freiburg. Our team secures the maintenance and on-going development.

Visit our research group
Building

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
Freiburg, Germany

Mail:
Phone: +49 761 203 2400