3 Open-Source Python Packages to Track Data Science Experiments

Author(s): Cornellius Yudha Wijaya

Originally published on Towards AI.

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Photo by Kelly Sikkema on Unsplash

Experimentation is at the heart of the data science process, as the activity defines the science of data science. It is also much easier in the modern era, as the introduction of computational power makes data science experimentation more powerful, can be reproduced, and is easy to track.

However, I have seen many data scientists yet to track their data science experiments. It’s not a fatal error, but tracking has many benefits. The benefit includes but is not limited to below:

Easier times to evaluate metrics based on the changes; model, hyperparameter, feature engineering, etc.,Help to keep… Read the full blog for free on Medium.

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Published via Towards AI