Skill UI

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

This resource guides authors on positioning their research for the International Conference on Automated Machine Learning (AutoML). It helps evaluate if a manuscript—especially those involving NAS, HPO, or meta-learning—is a suitable fit for the venue. The focus is on framing contributions that enhance the automated search process, robust methodologies, and system pipelines, rather than solely relying on final leaderboard scores.