Automated machine learning systems for non-experts could be critical for
industries to adopt artificial intelligence to their own applications. This
paper detailed the engineering system implementation of an automated machine
learning system called YMIR, which completely relies on graphical interface to
interact with users. After importing training/validation data into the system,
a user without AI knowledge can label the data, train models, perform data
mining and evaluation by simply clicking buttons. The paper described: 1) Open
implementation of model training and inference through docker containers. 2)
Implementation of task and resource management. 3) Integration of Labeling
software. 4) Implementation of HCI (Human Computer Interaction) with a rebuilt
collaborative development paradigm. We also provide subsequent case study on
training models with the system. We hope this paper can facilitate the
prosperity of our automated machine learning community from industry
application perspective. The code of the system has already been released to
GitHub (this https URL).

该论文详细介绍了自动化机器学习系统 - YMIR 的开发和实现，通过图形界面与用户交互，使非 AI 专业人士可以轻松地进行数据标记、模型训练、数据挖掘和模型评估。该系统的特点包括：使用 docker 容器进行模型训练和推断；任务和资源管理；标签软件集成；以及使用重建的协作开发范式实现 HCI（人机交互）。此外，该论文还提供了使用该系统训练模型的案例研究。