Automated machine learning (AutoML) is a process of applying machine learning models to real-world problems using automation. More specifically, it automates the selection and composition/parameterization for these systems which can reduce time constraints when developing them in order that they may be more efficiently applied across diverse datasets with varying input formats


A Primer on Data Labeling Approaches To Building Real-World Machine Learning Applications