AIF360
model-card-toolkit
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| AIF360 | model-card-toolkit | |
|---|---|---|
| 6 | 1 | |
| 2,311 | 402 | |
| 2.3% | 0.5% | |
| 7.2 | 5.4 | |
| 9 days ago | 9 months 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
model-card-toolkit
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Building a Responsible AI Solution - Principles into Practice
We explored various solutions in the machine learning space as well as in the neighbouring software development space for inspiration and learning. Some notable ones include Git and Github, Google Model Cardsand IBM's Factsheets. One of the main design decisions we faced was whether to go with a plain-text git-based solution or a structured schema approach. Eventually, we decided to build on top of Google Model Card (structured protobuf schema). This sacrifices immediate readability of the file, but makes it easy to be processed across different systems in a predictable manner.
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]
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
AIX360 - Interpretability and explainability of data and machine learning models
Jenkins - Jenkins automation server
interpret - Fit interpretable models. Explain blackbox machine learning.
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
DALEX - moDel Agnostic Language for Exploration and eXplanation
verifyml - Open-source toolkit to help companies implement responsible AI workflows.