The Current State of Automated Machine Learning

This post will provide a brief explanation of AutoML, argue for its justification and adoption, present a pair of contemporary tools for its pursuit, and discuss AutoML's anticipated future and direction.

Randy Olson, whose research focuses on hyperparameter optimization, says the following:

In the near future, I see automated machine learning (AutoML) taking over the machine learning model-building process: once a data set is in a (relatively) clean format, the AutoML system will be able to design and optimize a machine learning pipeline faster than 99% of the humans out there.

There was a lot of new information in this post for me—I hadn't realized how far along some of this R&D had gotten. Highly recommended if you're not already familiar with this world.

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