Session

Case Study: The Road to Simple ML Training and Deploying in Azure

Often machine learning training and production deployment of machine learning have been two different and distinct challenges. Data Scientist do not often consider the constraints of production deployment and Engineers are weary of debugging often lengthy code base that go along with models. Over the years, Azure has developed tools to minimize the gap between these two processes – allowing Data Scientist to focus on machine learning and Engineers to interface cleanly without having to inherit large code bases. In this session we will cover how these Azure tools accelerated our machine learning development and how these tools have changed over the years to help us move even faster.

Jeffrey Wu

Manager, Enterprise Data and Advanced Analytics at Carbonite

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