AutoML Pipeline

AutoML pipelines automate the process of building machine learning models, aiming to reduce the need for expert intervention and accelerate AI development. Current research focuses on improving the efficiency and effectiveness of these pipelines, including the use of large language models for task management and automated debugging, and exploring optimal transport methods for model selection in diverse learning scenarios like clustering. This work is significant because it democratizes access to advanced machine learning techniques and improves the reliability and performance of AI systems across various applications.