Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
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Updated
Jun 17, 2024 - Jupyter Notebook
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
H2O.ai Machine Learning Interpretability Resources
A library that implements fairness-aware machine learning algorithms
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
youtube & tiktok analysis + youchoose recommendation custmizer. backend, extensions, and tooling
A national archive of police data collected by journalists, lawyers, and activists around the country.
Project Lockdown (an initiative from The IO Foundation) is a civic tech, interactive platform providing an overview of the state of Human and Digital Rights around the globe. It evaluates policies obtained from official sources that may impact their observance. It provides, among other tools, a layered map interface that allows for a visual repr…
SenateTrades: what stocks are your senators buying?
A Python wrapper for the OpenFEC API.
Chilean Municipalities Information System (SINIM) Wrapper 📈🏛🇨🇱
WordPress plugin that enables updates to published content to be held in a draft state, or to be submitted for moderation and approval before they go live. It makes WP’s native Revisions more accountable by extending the system’s tracking of changes to taxonomy items and featured images, and improves the ‘Compare Revisions’ interface.
A curated list of tools and resources for online adult content/porn filtering
Custom Python/Django CMS - Transparency for Public Projects (used for BERwatch/BLBwatch)
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
Plugin to make WordPress more Wiki-like by allowing more than one person to edit the same Post, Page, or Custom Post Type at the same time. When there are conflicting edits, it helps users to view, compare, and merge changes before saving.
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
Open source for https://starcitizentracker.github.io/
The OpenPoliceData (OPD) Python library is the most comprehensive centralized public access point for incident-level police data in the United States. OPD provides easy access to 425+ incident-level datasets for about 4800 police agencies. Types of data include traffic stops, use of force, officer-involved shootings, and complaints.
Unofficial pdf/epub of the content of "re:Work" from Google Inc. Pdf/epub can be found here: https://github.com/daniperez/rework/releases
Data on Digital Media and Technology Expenditures in the United States Congress
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