AI explainability 360
Vijay Arya, Rachel Bellamy, Pin‐Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
Abstract
This tutorial will teach participants to use and contribute to a new open-source Python package named AI Explainability 360 (AIX360) (https://aix360.mybluemix.net), a comprehensive and extensible toolkit that supports interpretability and explainability of data and machine learning models.
Topics & Concepts
InterpretabilityPython (programming language)Computer scienceOpen sourceProgramming languageArtificial intelligenceExtensibilitySoftware engineeringSoftwareExplainable Artificial Intelligence (XAI)