
Show HN: Comet Panels – Custom visualizations for your ML experiments - gidim
https://www.comet.ml/demo/gallery/view/new#select-panel?gallery-tab=Public
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gidim
Hi HN! Really excited to share this with with those of you training ML models.
Comet Panels is an easy and free way to build visualizations, widgets and apps
in HTML/JS/CSS _on top_ of your ML experiment data and a gallery where you can
share your work with the world.

Panels is built on our experiment management platform (100% free for
individuals). Essentially as a user you can report all of your metrics,
params, assets, data samples etc. Everything stored is also accessible via our
JS SDK so it's really easy to fetch data for your panels.

The main idea is that visualizations aren't stale. Every time a new
experiments is reported your visualization will update with that additional
data.

Docs available here: [https://www.comet.ml/docs/javascript-sdk/getting-
started/](https://www.comet.ml/docs/javascript-sdk/getting-started/)

Blogpost with more information: [https://www.comet.ml/site/introducing-panels-
custom-visualiz...](https://www.comet.ml/site/introducing-panels-custom-
visualizations-for-machine-learning/)

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amrrs
Is it like Streamlit with Gallery?

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gidim
Streamlit is awesome but solves a different use case. There's definitely
similarities but also a few core differences. 1. Comet Panels reads the
experimentation data from our API/Database. Streamlit is much more like
Jupyter notebooks where you'd have to setup your own data store and implement
logic to update it with new experiment data. This also means that if you pull
a visualization from the gallery it should work out of the box as the API is
standard among everyone! 2\. Comet Panels is freely hosted so no need to setup
a webserver 3\. Comet Panels is natively written in JS/HTML/CSS so you can use
any JS library out of the box. Streamlit is written in Python and you might be
limited to the built in UI components (or you can build a custom on which is
also in JS/HTML/CSS)

