Mercury's explainability is a library with implementations of different state-of-the-art methods in the field of explainability
Project description
mercury-explainability
mercury-explainability is a library with implementations of different state-of-the-art methods in the field of explainability. They are designed to work efficiently and to be easily integrated with the main Machine Learning frameworks.
Mercury project at BBVA
Mercury is a collaborative library that was developed by the Advanced Analytics community at BBVA. Originally, it was created as an InnerSource project but after some time, we decided to release certain parts of the project as Open Source.
That's the case with the mercury-explainability
package.
If you're interested in learning more about the Mercury project, we recommend reading this blog post from www.bbvaaifactory.com
User installation
The easiest way to install mercury-explainability
is using pip
:
pip install -U mercury-explainability
Help and support
This library is currently maintained by a dedicated team of data scientists and machine learning engineers from BBVA AI Factory.
Documentation
website: https://bbva.github.io/mercury-explainability/
Project details
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Source Distribution
Hashes for mercury-explainability-0.0.2.tar.gz
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