Ensuring Reproducibility and Robustness of ML based data processing is important to ensure business continoutity.
SERVICE DESCRIPTION
With this service, our experts offer you their expertise in defining and monitoring an end-to-end machine learning pipeline. With open source tools like MLFlow, you can adapt best practices in machine learning development and efficiently and reliably design and integrate your ML processes into your development workflows based on Git version control. You can either use your own Gitlab or Github-based project repository, or use our Gitlab server to integrate with our HPC and GPU-accelerated CI infrastructure. To monitor your workflows, we offer hosted dashboard services.
SPECIAL ACCESS CONDITIONS
Conditions and requirements for participation in an experiment within the Open Calls:
By participating in an EUHubs4Data Open Call, you are initially only applying for funding that originally comes from the European Commission and is awarded by the coordinator exclusively in its own name under the conclusion of a sub-grant agreement. This sub-grant agreement does not establish a contract with KIT, neither through your application nor through a possible positive funding decision.
KIT will therefore - also in your own interest - conclude a separate written agreement with you at the start of the experiment (based on our sample cooperation agreement.
If you decide to propose the participation of KIT and SDIL infrastructure in your experiment, you must respect the following conditions.
We provide this information in advance to ensure maximum transparency: please contact us if you have any questions. In the unlikely event that you are unable to conduct your experiment with our participation, we will attempt to assist you in selecting alternative services before the experiment begins.
Please note that contrary to the name "service", the above description is not a genuine commercial offer, but a listing of exclusive contributions as part of a genuine eye-to-eye collaboration.
For genuine commercial offerings related to the above topics, please feel free to contact us any time outside of the Open Calls.
PREREQUISITES
Having an existing ML engineering effort.
SERVICE CAN BE COMBINED WITH
This service can be combined with any other IaaS and ML infrastructure offering, that supports executing MLFlow.