AutoML System

AutoML systems automate the process of building machine learning models, aiming to reduce human effort and expertise required for tasks ranging from data preprocessing to model deployment and ensembling. Current research emphasizes integrating large language models (LLMs) for improved user interaction and full-pipeline automation, as well as incorporating hardware awareness to optimize model efficiency and addressing issues like imbalanced datasets and fairness. This field is significant because it promises to democratize machine learning by making it more accessible to non-experts and to improve the efficiency and effectiveness of model development across diverse applications.