Automated machine learning

Automated machine learning (AutoML) refers to the process of automating the end-to-end application of machine learning to real-world problems. It encompasses tasks such as data preprocessing, feature selection, model selection, hyperparameter tuning, and model evaluation, aiming to make machine learning accessible to non-experts and improve workflow efficiency. AutoML is particularly beneficial for data scientists, business analysts, and organizations looking to leverage machine learning without extensive expertise in the field.

Automated machine learning was discovered on March 31st 2020 and it currently has a search volume of 1.9K with a growth of +146%.