Personalized Recommendation Method of College Art Education Resources Based on Deep Learning

In order to solve the problem of uneven distribution of educational resources and enable the campus network host to complete the recommendation of art education resources according to students’ learning interests, the personalized recommendation method of art education resources in colleges and universities based on in-depth learning is studied. Design the deep learning architecture of art education in colleges and universities, and determine the basic architecture, upgrade architecture and complete architecture layout of the campus network learning algorithm. According to the principle of educational weight distribution, the similarity degree of educational resource information is calculated; Based on the in-depth learning algorithm and the resource vector to be allocated, the solution expression of the recommendation table is derived, the personalized recommendation list of college art education resources is formulated, and the design of personalized recommendation method of college art education resources based on in-depth learning is completed. The implementation results show that under the effect of the deep learning recommendation method, the proportion of learning allocation of the selected art education resources exceeds 90%, and the uneven distribution of education resources has been well solved.