Design and Practice of Linear Algebra Visualization Teaching Platform Based on Deep Learning Algorithm

In this study, a visualization teaching platform based on deep learning algorithms is designed and implemented to address the problems of abstract concepts and esoteric theories in linear algebra teaching. The platform adopts algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and its variants Long ShortTerm Memory Network (LSTM) and Generative Adversarial Network (GAN) to intelligently process the linear algebra teaching content and realize personalized recommendation and visualization display. The stability test and algorithm accuracy verification confirm the high reliability of the platform and the advantages of the deep learning algorithms in enhancing the teaching effect and students’ learning experience. This research provides useful reference for the development of intelligent education and opens up a new path for linear algebra teaching reform and innovation.