A Neophyte With AutoML: Evaluating the Promises of Automatic Machine Learning Tools. (arXiv:2101.05840v1 [cs.LG])

This paper discusses modern Auto Machine Learning (AutoML) tools from the
perspective of a person with little prior experience in Machine Learning (ML).
There are many AutoML tools both ready-to-use and under development, which are
created to simplify and democratize usage of ML technologies in everyday life.
Our position is that ML should be easy to use and available to a greater number
of people. Prior research has identified the need for intuitive AutoML tools.
This work seeks to understand how well AutoML tools have achieved that goal in
practice. We evaluate three AutoML Tools to evaluate the end-user experience
and system performance. We evaluate the tools by having them create models from
a competition dataset on banking data. We report on their performance and the
details of our experience. This process provides a unique understanding of the
state of the art of AutoML tools. Finally, we use these experiences to inform a
discussion on how future AutoML tools can improve the user experience for
neophytes of Machine Learning.

Source: https://arxiv.org/abs/2101.05840

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