A Beautiful Visualization Dashboard For Machine Learning
Project description
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:
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
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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