Transforming Embedded Systems: Constructing a Deep Learning Environment for Nonlinear Data Analysis in the Creation of an Experiential Composite Bookstore Space Design Model

Abstract

In the era of global knowledge informatization, the field of education is facing a comprehensive and profound reform. With the reform of educational paradigm, "transformation of teaching methods" and "realization of deep learning" have become the key words of this reform. As a learning paradigm, deep learning is a core topic of general concern in the field of machine learning and learning science. Therefore, in the trend of the deep integration of information technology and education, we use the deep learning environment to improve the learning quality of scholars by designing the learning space of the experiential composite bookstore in the deep learning environment. In order to better analyze the spatial design model of experiential composite bookstore with nonlinear data, using the analysis and research of the design in the deep learning environment can more effectively analyze the spatial design and model construction of experiential composite bookstore with nonlinear data in the deep learning environment. The design of characteristic bookstores has more humanistic feelings, meets readers' reading and spiritual needs, and lays a theoretical foundation for the better development of physical bookstores and characteristic bookstores.