AutoML Overview

AutoML, short for automated machine learning, is a set of techniques and tools that aim to automate various aspects of the ML pipeline, making it easier and faster for individuals without extensive ML expertise to build and deploy ML models. AutoML systems automate tasks such as data preprocessing, feature engineering, model selection, hyperparameter tuning, and model evaluation.

AutoML aims to reduce the time and effort required for developing ML models by automating repetitive and time-consuming tasks. It democratizes ML by enabling nonexperts to leverage the power of ML in their respective domains, allowing them to focus on domain-specific problems rather than the intricacies of model building and optimization.

AutoML workflow