Automated Machine Learning (AutoML) in Azure is the process of automating the end-to-end task of applying machine learning to real-world problems. It enables users—regardless of coding or ML expertise—to train, tune, and deploy models efficiently.
Key Capabilities:
- Automatically selects algorithms, features, and hyperparameters
- Supports classification, regression, time-series forecasting, computer vision, and natural language processing (NLP)
- Offers both code-first (SDK/CLI) and no-code (Azure ML Studio) interfaces
- Handles feature engineering, validation, testing, and ensemble modeling
- Produces deployable models, including export to ONNX for cross-platform use (e.g., in .NET)
Learn how Azure Machine Learning can automatically generate a model by using the parameters and criteria you provide with automated machine learning.