Sara is a research scholar at the Google-Brain team working on building interpretable machine learning models for reliability and robustness. We talk about how she transitioned from economics to now pure research at the Brain team. We also talk in detail about what interpretability means, what are the state-of-art techniques, and what are some of the most important things any machine learning researcher must know.
About the Host:
Jay is a Ph.D. student at Arizona State University, doing research on building Interpretable AI models for Medical Diagnosis.
Jay Shah: https://www.linkedin.com/in/shahjay22/
You can reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
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