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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.