Achieving AutoML
How can AutoML achieve the goal of end-to-end automatization? Well, you have probably already guessed 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 machine learning end to end offers simpler solutions, reduces the time to produce them, and ultimately might produce architectures that could potentially outperform models that were crafted by hand.
Is this a closed research area? Quite the opposite. At the beginning of 2022, 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.
