Metadata-Version: 2.1
Name: etiq-spark
Version: 1.5.1rc2
Summary: This is an optional, extension to the etiq library to provide spark datasets
Author-email: ETIQ AI <devops@etiq.ai>
Project-URL: homepage, https://etiq.ai
Keywords: ai,bias,etiq,fairness
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 :: 3.7
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: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: <3.12,>=3.7
Description-Content-Type: text/markdown
Requires-Dist: etiq ==1.5.1rc2
Requires-Dist: pyspark[pandas_on_spark] >=3.3.2

# 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 building & production stages. Etiq helps identify the following issue
types in the dataset/model: Bias, Data Leakage, 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.

## Getting Started

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


## Licence

This library is distributed under the Creative Commons "Attribution-NoDerivatives 4.0
International (CC BY-ND 4.0)":

https://creativecommons.org/licenses/by-nd/4.0/
