AutoML
Expanded definition
Automated machine learning (AutoML) tries to reduce manual trial-and-error in training classical or neural models. It does not replace problem framing, data contracts, or production monitoring. In generative-AI stacks, AutoML is a different job from prompt evals, RAG tuning, or LLM fine-tuning. Use AutoML when you are fitting a tabular or classical model; use a golden set and task metrics when you are shipping an LLM feature.
Related terms
Explore adjacent ideas in the knowledge graph.
AutoML FAQ
What is AutoML?
AutoML automates parts of the machine-learning workflow such as preprocessing, model selection, and hyperparameter search.
How is AutoML used in AI systems?
Automated machine learning (AutoML) tries to reduce manual trial-and-error in training classical or neural models. It does not replace problem framing, data contracts, or production monitoring. In generative-AI stacks, AutoML is a different job from prompt evals, RAG tuning, or LLM fine-tuning.
Related
Comparisons, tools, and models that connect to this idea.