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ml.cern.ch

ml.cern.ch is a Kubeflow based ML solution provided by CERN.

Kubeflow

Kubeflow is a Kubernetes based ML toolkits aiming at making deployments of ML workflows simple, portable and scalable. In Kubeflow, pipeline is an important concept. Machine Learning workflows are discribed as a Kubeflow pipeline for execution.

How to access

ml.cern.ch only accepts connections from within the CERN network. Therefore, if you are outside of CERN, you will need to use a network tunnel (eg. via ssh -D dynamic port forwarding as a SOCKS5 proxy)... The main website are shown below.

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Examples

After logging into the main website, you can click on the Examples entry to browser a gitlab repository containing a lot of examples. For instance, below are two examples from that repository with a well-documented readme file.

  1. mnist-kfp is an example on how to use jupyter notebooks to create a Kubeflow pipeline (kfp) and how to access CERN EOS files.
  2. katib gives an example on how to use the katib to operate hyperparameter tuning for jet tagging with ParticleNet.
Last update: September 27, 2022