AutoML
Automated Machine Learning -- tools and techniques that automate the process of building machine learning models, from feature engineering to model selection and hyperparameter tuning.
What It Automates
AutoML can handle data preprocessing, feature engineering, algorithm selection, hyperparameter optimization, and model ensembling. It democratizes ML by reducing the need for deep expertise.
Popular Tools
Google AutoML, H2O AutoML, Auto-sklearn, FLAML, and AutoGluon. These range from cloud services to open-source libraries.
Limitations
AutoML excels at tabular data but is less mature for NLP and computer vision. It cannot replace domain expertise for problem framing, data quality assessment, or interpreting results in context.