MLOps library aimed at individuals and small-scale teams.
Created and maintained by Ilia Moiseev.
Github: https://t.co/wqGqfRZiIPoxid15.github.io/cascade/en/lat…Joined August 2024
Recently Cascade got its own UI!
With the help of contributors cascade-ui reached 0.2.2.
Now everyone can have their ML experiments visualized in a nice UI that is native to Cascade.
github.com/Laiserk/cascad…
Working on the development of a new experiment comparison feature for Cascade UI.
See UI features that are already available here: oxid15.github.io/cascade/en/lat…
Most of your ML side projects require experiment tracking, but none of them needs a platform for that.
With Cascade you can do everything locally, with no infra overhead.
oxid15.github.io/cascade/en/lat…
This June Cascade had 5.6% more PyPI downloads than previous months and latest 0.16.0 is dominating.
I am glad to see the growth, thank you for using Cascade!
After the big update on Metrics in Cascade I am still thinking if I should also formalize model parameters somehow...
It may simplify a lot of things on the Cascade side, but may limit the freedom of configuration.
oxid15.github.io/cascade/en/lat…
I've seen too much of "We can't spend time on experiment infrastructure, we need the results". I hope that Cascade can ease the pain of integration of MLOps tools into fast-pacing projects.
Because infrastructure matters.
We should stop running experiments without proper tracking even at a very small scale. Cascade shows that you can have reproducibility at any scale!
blog.devops.dev/enable-experim…
Did you know that you can add experiment tracking to your next ML side project without complex setups or changing too much code?
Here is how to do it using Cascade.
medium.com/@ilia.moiseev/…
Did you ever get lost in your experiments after changing hyperparameters in your script a dozen times?
You may need configuration management - now included in the Cascade 0.15.0. Read more here medium.com/@ilia.moiseev/…
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