Kevin McCormick explains the story of two approaches which were used internally at AWS to accelerate new ML algorithm development, and easily package Jupyter notebooks for scheduled execution, by creating custom Jupyter kernels that automatically create Docker containers, and dispatch them to either a distributed training service or job execution environment.
This session is sponsored by AWS.
Kevin McCormick is a senior software development engineer at Amazon Web Services, where he is the lead engineer on the Amazon SageMaker notebook platform, which provides an easy-to-use Jupyter notebook experience as a first-class AWS offering. Kevin has over 15 years of software development and IT experience, including building software for everything from websites, IDEs, and web browsers to productivity applications and reusable libraries. He has contributed to a number of open source projects, including more than a dozen improvements to the Chromium project. Although he lives in Seattle, he’s a New York/New Jersey native, so he knows what a good slice of pizza is supposed to taste like.
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