Agents5h ago
Five-Agent System Automates ML Pipeline Generation
A new five-agent architecture automates end-to-end machine learning pipelines from natural-language goals. The system uses code-grounded RAG and a self-healing mechanism to interpret errors and adapt from execution history. Tested on 150 tasks, it reduces manual DAG construction. This allows practitioners to deploy complex ML workflows via simple text prompts.