EthicML
AIF360
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EthicML | AIF360 | |
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1 | 6 | |
24 | 2,281 | |
- | 1.8% | |
9.3 | 7.3 | |
4 days ago | 9 days ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
EthicML
We haven't tracked posts mentioning EthicML yet.
Tracking mentions began in Dec 2020.
AIF360
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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!
AI Factsheets: https://www.ibm.com/blogs/watson/2020/12/how-ibm-is-advancing-ai-governance-to-help-clients-build-trust-and-transparency/ AI Fairness 360: https://aif360.mybluemix.net/ AI Explainability 360: https://aix360.mybluemix.net/
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/
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]
AIX360 - Interpretability and explainability of data and machine learning models
thinc - 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
interpret - Fit interpretable models. Explain blackbox machine learning.
model-card-toolkit - A toolkit that streamlines and automates the generation of model cards
verifyml - Open-source toolkit to help companies implement responsible AI workflows.
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.
DALEX - moDel Agnostic Language for Exploration and eXplanation
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.
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]
pygod - A Python Library for Graph Outlier Detection (Anomaly Detection)