Achieving AutoML

How can AutoML achieve the goal of end-to-end automatization? Well, you are probably already guessing that a natural choice is to use machine learning – that's very cool – AutoML uses ML for automating ML pipelines.

What are the benefits? Automating the creation and tuning of the machine learning end-to-end offers produces simpler solutions, reduces the time to produce them, and ultimately might produce architectures that could potentially outperform the models that were crafted by hand.

Is this a closed research area? Quite the opposite. At the beginning of 2020, AutoML is a very open research field, which is not surprising, as the initial paper drawing attention to AutoML was published at the end of 2016.