Metadata-Version: 2.1
Name: etiq
Version: 1.6.0
Summary: ETIQ.ai ML Testing library
Home-page: https://etiq.ai/
Author: ETIQ AI
Author-email: devops@etiq.ai
License: UNKNOWN
Keywords: ai,bias,etiq,fairness
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: MacOS X
Classifier: Environment :: Win32 (MS Windows)
Classifier: Framework :: IPython
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8,<3.13
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: platformdirs
Requires-Dist: numpy<=1.26.4,>=1.21
Requires-Dist: pandas<2,>=1.3.5
Requires-Dist: sqlalchemy<2,>=1.4
Requires-Dist: scikit-learn
Requires-Dist: xgboost>1.5.1
Requires-Dist: requests
Requires-Dist: shortuuid
Provides-Extra: all
Requires-Dist: great-expectations; extra == "all"

# ETIQ AI

Etiq helps companies test and monitor ML models. For data science & ML teams, Etiq tests ML algorithms, identifying issues and preventing accuracy loss in both development & production stages. Etiq helps identify the following issue types in the dataset/model: Bias, Data Leakage, Data Fingerprinting, Accuracy Issues, Drift, across both pre-production and production stages. Additionally, Etiq helps identify which segments are impacted by each issue type and provides modular tests that you can plug at different points in your pipeline.

With the release of Etiq 1.6.0 the package is now compatible with Apple Silicon processors. Due to dependencies (xgboost)
in the package you may need to install libomp via homebrew

If you haven't already, install homebrew on your computer: **https://brew.sh/**

Then run the following in your terminal: **brew install libomp**

## Getting Started

To get started with this package, view our quickstart guide at https://docs.etiq.ai/

## Licence

The current licensing terms are available on this page;

https://docs.etiq.ai/faq-and-other/faq#licensing-terms


