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This session will talk about to evaluate and add trustworthiness and fairness to your multi-cloud Kubeflow workflows. The session will describe the following: * Overview of responsible AI & fairness. * What are the different aspects of fairness. * How to evaluate fairness in the input data & the model. * Demo: Using open source tools such as MinDiff/Tensorflow/ai-widgets for fair model learning * Demo: Including fairness as a parameter in HyperParameter tuning in Kubeflow * Transition from experimentation in Notebooks to ML production pipelines. * Recommendations to ensure your AI workflows are trustworthy and fair. Suggestions for enhancements in Kubeflow that can accelerate this evolution.
Meenakshi leads Kubernetes and AI/ML product offerings at Cisco. Meenakshi has interest in AI/ML space and is excited about how the technology can enhance human well-being and productivity.
