BBVA - Giters

mercury-robust is a framework to perform robust testing on ML models and datasets. It provides a collection of test that are easy to configure and helpful to guarantee robustness in your ML processes.

Language:Jupyter NotebookApache-2.012 30

ust2dsa

Improves Ubuntu security feed compatibility allowing it to be consumed by Debian vulnerability report tool, debsecan.

Language:HaskellApache-2.012 60

mercury-dataschema

Utility package that, given a Pandas DataFrame, it uses the DataSchema class which auto-infers feature types and automatically calculates different statistics depending on the types.

Language:PythonApache-2.011 50

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.

Language:Jupyter NotebookApache-2.011 30

waf-benchmark

Web Application Firewall Benchmark

Language:PythonApache-2.011 50

mercury-reels

Reels is a library for analyzing sequences of events from transactional data to predict when related target events may occur in the future.

Language:C++NOASSERTION10 30

contract-testing

An experiment of contract testing using pact

Language:ScalaApache-2.09 70

mercury-settrie

A Python 3 library developed in C++ that enables efficient storage and querying of sets of sets. It can be used to perform fast document search. Uses the Settrie algorithm: https://osebje.famnit.upr.si/~savnik/papers/cdares13.pdf

Language:C++NOASSERTION9 3 9