Skip to main content

The bias and fairness audit toolkit.

Project description

Aequitas is an open-source bias audit toolkit for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive tools.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aequitas-0.38.1-py3.6.egg (2.3 MB view details)

Uploaded Egg

File details

Details for the file aequitas-0.38.1-py3.6.egg.

File metadata

  • Download URL: aequitas-0.38.1-py3.6.egg
  • Upload date:
  • Size: 2.3 MB
  • Tags: Egg
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/49.6.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.9

File hashes

Hashes for aequitas-0.38.1-py3.6.egg
Algorithm Hash digest
SHA256 7220f1cc5c34e131f1d959e5b55526a43ded6162492469573e62ed4f0cf1f78f
MD5 ea57fd8f539e21d9b354c6deab766b14
BLAKE2b-256 63bfdbed26cfa48a28d804ea12d6866c34aabc5e39fbbb1b8818683b5c7afced

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page