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A Beautiful Visualization Dashboard For Machine Learning

Project description

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For detailed codumentation, seeml-dash-tutorial

ML-dash replaces visdom and tensorboard. It allows you to see real-time updates, review 1000+ of experiments quickly, and dive in-depth into individual experiments with minimum mental effort.

  • Parallel Coordinates

  • Aggregating Over Multiple Runs (with different seeds)

  • Preview Videos, ``matplotlib`` figures, and images.

Usage

To make sure you install the newest version of ml_dash:

pip install ml-logger ml-dash --upgrade --no-cache

There are two servers:

  1. a server that serves the static web-application files ml_dash.app

    This is just a static server that serves the web application client.

    To run this:

    python -m ml_dash.app
  2. the visualization backend ml_dash.server

    This server usually lives on your logging server. It offers a graphQL API backend for the dashboard client.

    python -m ml_dash.server --logdir=my/folder

    Note: the server accepts requests from ``localhost`` only by default for safety reasons. To overwrite this, see the documentation here: ml-dash-tutorial

Implementation Notes

See https://github.com/episodeyang/ml_logger/tree/master/ml-dash-server/notes/README.md

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ml-dash-0.3.4.tar.gz (4.0 MB view hashes)

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