Machine learning techniques are deeply rooted in our daily lives. However, human experts are heavily involved in every aspect of machine learning, since it is knowledge-intensive and labor-intensive to pursue good learning performance. To make machine learning techniques more accessible to nonexperts, automated machine learning (AutoML) has emerged as a hot topic with industrial and academic interest. In this study, we proposed an automated machine learning (AutoML) system that can be easily deployed on limited hardware such as personal computers, lab servers, university servers, etc., at optimal cost and with an easy-to-use interface. The source code for this project is continuously updated at https://github.com/optivisionlab/AutoML .