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The best data science is “human-in-the-loop” data science—blending the strengths of human and machine. As the human, your time is best spent thinking deeply about data and crafting Machine Learning (ML) models, while the machine efficiently cranks on your models. In this talk, the speakers will present a fresh paradigm—interactive data science at scale. The speakers will merge two open-source tools, Jupyter and Kubeflow to demonstrate a unique, “human-in-the-loop” AI/ML workflow. They will leverage Jupyter’s world-class interactive computing tools and Kubeflow’s innovative, cloud-native scaling technologies to develop, tune, train, and deploy massive ML models. The speakers will highlight key features in both projects that dramatically enhance and simplify the way humans do data science. Finally, they will end with demonstrating Jupyter’s new real-time collaboration experience—because two (or more) “humans-in-the-loop” are better than one.
Andrey Velichkevich is a Senior Software Engineer at Apple and is a key contributor to the Kubeflow open-source project. He is a member of Kubeflow Steering Committee and a co-chair of Kubeflow AutoML and Training WG. Additionally, Andrey is an active member of the CNCF WG AI. He... Read More →
Zach Sailer is an Senior Software Engineer at Apple and a member of Jupyter's Software Steering Council. He's been a core contributor to Jupyter's open-source community (and one its earliest developers) for over a decade. Fun fact: Zach spent his graduate days in an evolutionary biophysics... Read More →
