What is an AutoML tool used for?

An AutoML tool is specifically designed to automate the machine learning process, which streamlines and simplifies the various stages involved in building machine learning models. It typically encompasses tasks such as data preprocessing, feature selection, model selection, hyperparameter tuning, and even model evaluation—all of which are essential parts of the machine learning workflow.

By automating these processes, AutoML tools allow users, even those without extensive machine learning expertise, to build effective models more easily and quickly. This capability is especially valuable in scenarios where time and expertise are limited, and it helps organizations leverage machine learning without needing in-depth knowledge of the algorithms and their nuances.

In contrast, the other options relate to more manual or specific tasks that do not encompass the broad automation functions that an AutoML tool performs. For instance, manual tuning requires a hands-on approach that AutoML specifically seeks to minimize, and tasks like data visualization and cleaning, while important, are not the primary focus of AutoML tools.