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Optimization of Ideological and Political Education Strategies in Colleges and Universities Based on Deep Learning
1School of Marxism, Hunan City University, Yiyang 413000, Hunan, China.
Abstract:
In the current technological world, artificially intelligent deep learning techniques are adapted in many fields. This advanced technology is also used in the field of education. In this study, people will conduct research on the optimization of ideological and political education strategies in colleges and universities based on deep learning. Deep learning is often a machine learning technique that uses artificial neural networks that allow a machine to imitate human behaviour. Ideological and political education deals with the social studies implied by the political scenario. Ideological and political education aims to teach the younger generation social, economic, and political awareness. In our proposed system, people will deploy the deep learning algorithm named brute force algorithm to optimize ideological and political education in colleges and universities. The teaching optimization is performed by automating the training of the deep learning model. The results were compared with the existing K-means algorithm, and it is observed that the proposed system has achieved a higher accuracy of 99.12% in optimizing the educational strategies.
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