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For detailed codumentation,
see\ ml-dash-tutorial <https://ml-logger.readthedocs.io/en/latest/setting_up.html#ml-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.
matplotlib
figures, and images.To make sure you install the newest version of ml_dash
:
.. code-block:: bash
conda install pycurl pip install ml-logger ml-dash --upgrade --no-cache
Just doing this would not work. The landscape of python modules is a lot messier than that of javascript. The most up-to-date graphene requires the following versioned dependencies:
.. code-block:: bash
yes | pip install graphene==2.1.3 yes | pip install graphql-core==2.1 yes | pip install graphql-relay==0.4.5 yes | pip install graphql-server-core==1.1.1
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:
.. code-block:: bash
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.
.. code-block:: bash
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 <https://ml-logger.readthedocs.io/en/latest/setting_up.html#ml-dash-tutorial>
__
Implementation Notes
See `https://github.com/episodeyang/ml_logger/tree/master/ml-dash-server/notes/README.md <https://github.com/episodeyang/ml_logger/tree/master/ml-dash-server/notes/README.md>`__
.. |Downloads| image:: http://pepy.tech/badge/ml-dash
:target: http://pepy.tech/project/ml-dash
FAQs
A Beautiful Visualization Dashboard For Machine Learning
We found that ml-dash demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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