SUBLIME
Semantically Understanding Bias with LIME. Using the LIME-RS Algorithm to understand bias in recommender systems. (by FurkanToprak)
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. (by Trusted-AI)
SUBLIME | AIF360 | |
---|---|---|
1 | 6 | |
3 | 2,324 | |
- | 1.7% | |
10.0 | 7.2 | |
over 2 years ago | 10 days ago | |
Jupyter Notebook | Python | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
SUBLIME
Posts with mentions or reviews of SUBLIME.
We have used some of these posts to build our list of alternatives
and similar projects.
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[Q] News sites or aggregators that show engagement metrics?
curb your arrogance https://github.com/FurkanToprak/SUBLIME
AIF360
Posts with mentions or reviews of AIF360.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-10.
-
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