AIF360
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| AIF360 | verifyml | |
|---|---|---|
| 6 | 1 | |
| 2,311 | 22 | |
| 2.3% | - | |
| 7.2 | 0.0 | |
| 9 days ago | about 2 years ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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AIF360
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perspective off
o https://aif360.mybluemix.net/
- How to detect and tackle bias in my data?
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Building a Responsible AI Solution - Principles into Practice
Besides the existing monitoring solution mentioned in the section above, we were also took inspiration from continuous integration and continuous delivery (CI/CD) testing tools like Jenkins and Circle CI, on the engineering front, and existing fairness libraries like Microsoft's Fairlearn and IMB's Fairness 360, on the machine learning side of things.
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Hi Reddit! I'm Milena Pribic, Advisory Designer for AI and the global design representative for AI Ethics at IBM. Ask me anything about scaling ethical AI practices at a huge company!
My advice is to remember that bias comes into the process intentionally and unintentionally! Tools like AI Fairness 360 can help you mitigate that from a development/technical perspective: https://aif360.mybluemix.net/
- [R] What are some of the best research papers to look into for ML Bias
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.
What are some alternatives?
fairlearn - A Python package to assess and improve fairness of machine learning models.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
EthicML - Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
AIX360 - Interpretability and explainability of data and machine learning models
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
interpret - Fit interpretable models. Explain blackbox machine learning.
Jenkins - Jenkins automation server
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
model-card-toolkit - A toolkit that streamlines and automates the generation of model cards
clai - Command Line Artificial Intelligence or CLAI is an open-sourced project from IBM Research aimed to bring the power of AI to the command line interface.