Data preparation is essential for getting good results in machine learning. Researchers developed a new framework called HAIPipe that combines human-generated and machine-generated pipelines to create a better pipeline for ML tasks. By carefully selecting the best operations from both types of pipelines, HAIPipe outperformed using either type alone in experiments with real-world data.