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A simple tool for logging and plotting measurements during machine learning experiments

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noggin

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Noggin is a simple Python tool for ‘live’ logging and plotting measurements during experiments. Although Noggin can be used in a general context, it is designed around the train/test and batch/epoch paradigm for training a machine learning model.

Noggin’s primary features are its abilities to:

  • Log batch-level and epoch-level measurements by name
  • Seamlessly update a ‘live’ plot of your measurements, embedded within a Jupyter notebook
  • Organize your measurements into a data set of arrays with labeled axes, via xarray
  • Save and load your measurements & live-plot session: resume your experiment later without a hitch

You can read more about Noggin here

noggin