Construction Method of Network Teaching Resources Based on Deep Learning

Abstract

In this paper, the construction method of network teaching resources based on deep learning is researched. In this
paper, a teaching resource integration method based on convolutional neural network is designed, including the
design of Arduino device identification program based on convolutional neural network and the construction of
Arduino device learning resource library. Based on this, this paper proposes a network multimedia teaching
resource integration system based on constrained clustering algorithm. In order to realize the system, the use
cases of the system are analyzed. On the basis of use case analysis, the function and overall architecture of the
system are designed respectively, and the collaborative recommendation module is mainly designed. In order to
improve the accuracy of recommendation, this paper uses constrained clustering algorithm to complete the
integration of network teaching resources. The experimental results show that the system can improve the
accuracy of recommendation matching and the integration efficiency of network teaching resources.