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International Journal of Neural Network, 2022, 3(4); doi: 10.38007/NN.2022.030409.

Appliance of Deep Learning in Intelligent Education


Yang Wang and Shangbin Li

Corresponding Author:
Shangbin Li

Physical Education Department, Harbin Engineering University, Harbin 150001, China


Intelligent education is the main direction of China's future development. In the information age, the traditional teaching mode can no longer meet the higher requirements for information and knowledge quality in students' learning. Based on this, this paper proposes a method to help improve neural network training speed, reduce training time and improve memory efficiency. First, it introduces the relevant theories of intelligent pedagogy through literature analysis, and then designs a set of experimental scheme according to the actual situation, and verifies its effectiveness and accuracy. Finally, the feasibility of the design scheme is verified by the experimental results. The test results show that the data processing time of the model is relatively fast, the delay time is relatively low, and the compatibility rate of the model is up to more than 90%. This provides a reference for further exploration of AI education in the future, and also contributes to the future development of China.


Deep Learning, Intelligent Education, Intelligent Appliance, Deep Education

Cite This Paper

Yang Wang and Shangbin Li. Appliance of Deep Learning in Intelligent Education. International Journal of Neural Network (2022), Vol. 3, Issue 4: 69-76. https://doi.org/10.38007/NN.2022.030409.


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