Teaching Design of Online Ideological and Political Course Based on Deep Learning Model Evaluation

In practical terms, teachers are supported to use more straightforward teaching methods, such as creating real-life contextual problems, to help students develop deep learning skills. In this paper, using Bayesian theory and Bayesian classifier research methods, a machine learning model was constructed using Python to establish the correspondence between online teaching of civics and high-level semantic features and to achieve computer learning through text and teaching design evaluation research that can identify high-frequency knowledge points. The inter-relationship model knowledge mapping, the accuracy is 90%, and the continuous knowledge update help to improve the model accuracy.