The good combination of IBM coder program and code patterns motivated me to dig in into the data science area a little bit, relating to the real-world topic diversity and inclusion . Also it was interesting to see: How the AI Fairness 360 toolkit, which is an open-source library to help detect and remove bias in machine learning models, can be used for data science in this context.
The diversity and inclusion topic started with a good statement:
“Diversity and inclusion is more than a checkbox, it’s fuel for growth and success in any business or community.” IBM Coder Program.
This was one reason why I completed the challenges of the Diversity and Inclusion topic in the IBM coder program .
The IBM coder program
If you don’t know the IBM coder program, just visit this link .
The program is about:
- Growing skillset and reputation
- Discovering and transparently discuss content
- Being rewarded with various tangible and intangible rewards
The code pattern Ensure loan fairness was one of the challenges for Diversity and Inclusion topic.
Code pattern “Ensure loan fairness”
This code pattern is about machine learning with artificial intelligence, data science and python. It gives an introduction in how to use the AIF360 tool kit .
- “The AI Fairness 360 toolkit is an open-source library to help detect and remove bias in machine learning models. The AI Fairness 360 Python package includes a comprehensive set of metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models.“
In the related demo on IBM research-trusted UI, you can verify given ai models with different datasets and the bias mitigation algorithms .
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