AutoML

AutoML (Automated Machine Learning) automates the end-to-end ML pipeline: delivering optimized, production-ready models from raw data with minimal human intervention.

AutoML is a critical technology for democratizing data science, drastically accelerating the model development lifecycle. It systematically automates complex, iterative tasks like feature engineering, model selection, and hyperparameter tuning (HPO). For example, a system will automatically search for the best algorithm—from linear models to advanced Neural Architecture Search (NAS)—and tune parameters like learning rates to maximize a target metric. Major platforms like Microsoft Azure Machine Learning and H2O.ai's Driverless AI leverage this to deliver high-performing models for tasks such as fraud detection and sentiment analysis faster than manual methods.

https://learn.microsoft.com/en-us/azure/machine-learning/concept-automated-ml