Application of the Iot Network and the Deep Learning Concept in Music Teaching

Abstract

In order to realize students’ in-depth understanding of music teaching content, it is necessary to reasonably allocate teaching materials according to the teaching content. Therefore, this paper puts forward the application of the concept of the Iot network and deep learning in music teaching. After the teaching resources are vectorized, the distinguishing local registration method of the DLA model is used to extract their features. Based on the dimension of the teaching content, the features of the teaching content are output in the DLA model, the music teaching resources are allocated according to the minimum matching error criterion, the hyperbolic tangent function is taken as the activation function, and the feature error is filtered by maximum aggregation. The experimental results show that the design method can, according to the music teaching content, have more than 80% accuracy in the shallow distribution and deep distribution of teaching materials, and play a positive role in promoting students’ in-depth learning.