I enthusiastically read Kush Varshney's book when it was released for free to the world several months back. Trustworthy Machine Learning is a concise and clear overview of many of the ways that machine learning can go wrong, and so I was especially keen to get Kush on to talk more about his work and research.

I also got a stronger sense of appreciation for how good MLOps practices and workflows offered a clear path to ensuring that your machine learning models and behaviours could become more trustworthy. Kush has done a lot of interesting work, particularly with the AI Fairness 360 and AI Explainability 360 toolkits that I'm sure listeners of this podcast would find worth checking out.

Special Guest: Kush Varshney.

Links:

• Trustworthy Machine Learning by Kush R. Varshney
• Home - AI Explainability 360
• Home - AI Fairness 360
• Kush Varshney
• Kush Varshney (@krvarshney) / Twitter
• Kush Varshney | LinkedIn
• Trustworthy Machine Learning: Varshney, Kush R.: 9798411903959: Amazon.com: Books