verifyml
EthicML
| verifyml | EthicML | |
|---|---|---|
| 1 | 1 | |
| 22 | 24 | |
| - | - | |
| 0.0 | 9.3 | |
| about 2 years ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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verifyml
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Building a Responsible AI Solution - Principles into Practice
Interested readers should check out the VerifyML website, docs or Github code. Feel free to create a Github issue and drop any suggestions or feedback over there! VerifyML is proudly open-sourced and created by a small tech startup. I would like to think that more companies are going to see responsible AI as a comparative advantage or requirement and having an ecosystem of solutions that are not controlled by the interests of large tech companies would be key in driving the sector forward. I look forward to improving the user experience and integration with more machine learning tools over the next year, as well as sharing more thoughts in the space.
EthicML
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[R] An overview of some available Fairness Frameworks & Packages
These are all great tools. I found though that there wasn't one package with the flexibility of what we needed in my research group for work in this area, so we wrote EthicML. Some of you may also find it useful too.
What are some alternatives?
fairlearn - A Python package to assess and improve fairness of machine learning models.
responsible-ai-toolbox - Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
DALEX - moDel Agnostic Language for Exploration and eXplanation
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
Jenkins - Jenkins automation server
pygod - A Python Library for Graph Outlier Detection (Anomaly Detection)
model-card-toolkit - A toolkit that streamlines and automates the generation of model cards