July 31, 2020 @ 9:30am
Aditi Singhal, Vivek Kumar
Historically agile software development teams have adopted Continuous Integration and Continuous Deployment aka CI/CD strategy for publishing code in production. Whereas in the world of Machine Learning, in addition to traditional software, the delivery of ML systems requires updating data and models as well. This requires extending conventional CI/CD pipelines to include ML workflows such as collecting data, training, and evaluation. In this workshop, we will go over a sample workflow demonstrating a CI/CD pipeline for ML first applications. We will also look at some of the best practices such as model versioning, continuous training, and automated model evaluation.
Aditi Singhal is an ML Engineer in the Azure Machine Learning team at Microsoft. She recently graduated with a Masters in Data Science from the University of Washington, Seattle.
Vivek is a Software Engineer in the Advertising team at Walmart Labs. He also graduated with a Masters in Data Science from the University of Washington, Seattle.
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