Scitator/animus
Minimalistic framework to run machine learning experiments.
This framework helps machine learning researchers design and run highly customized experiments. It provides a flexible structure to define how data batches are processed across epochs and datasets, allowing deep control over the entire training pipeline. The output is a precisely configured and executed ML experiment, ideal for researchers who need to test novel approaches or integrate diverse components.
No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning researcher who needs granular control over every step of your experimental pipeline, from data transformation to hardware integration and model training logic.
Not ideal if you are a practitioner looking for a quick way to build standard machine learning models with off-the-shelf components and minimal customization.
Stars
27
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 14, 2022
Commits (30d)
0
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