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Accelerating Model Development and Deployment with the right API Abstraction — Dallin Akagi (DataRobot)

The amount of value that we can get out of our data depends on both the accuracy of the models built around them and the speed with which these can be built, tested, and deployed. In this talk we present the API of DataRobot, focusing on the reasons why we focus on a higher-level modeling abstraction than other APIs. We will also share a use case illustrating how this abstraction level makes it possible to accelerate model deployment development.


Dallin is a data scientist and engineer at DataRobot, building a REST API for automated machine learning. He previously worked in a computer vision lab for the Department of Defense studying neural networks and deep learning. He studied Computer Science at CalTech.