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conda-forge.org : pydrift
How do we measure the degradation of a machine learning process? Why does the performance of our predictive models decrease? Maybe it is that a data source has changed (one or more variables) or maybe what changes is the relationship of these variables with the target we want to predict. `pydrift` tries to facilitate this task to the data scientist, performing this kind of checks and somehow measuring that degradation.
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Source
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purl: pkg:conda/pydrift
License: MIT
Latest release: over 2 years ago
First release: about 4 years ago
Stars: 32 on GitHub
Forks: 9 on GitHub
See more repository details: repos.ecosyste.ms
Last synced: about 14 hours ago