深度学习背景下的“自然语言处理”课程教学研究

Research on the Teaching of Natural Language Processing Course under the Background of Deep Learning

传统“自然语言处理”课程的教学内容以基于统计学习的方法为主,与当前主流的基于深度学习的方法这一发展现状不匹配。为了培养符合市场需求的人才,应探讨深度学习背景下“自然语言处理”课程的理论和实验教学内容设计;为了提高课堂教学效果,引入对比教学法,通过与基于统计学习的方法进行对比,让学生深刻理解基于深度学习方法的优缺点。实践表明,对比教学法适合深度学习背景下“自然语言处理”课程的教学,教学效果显著提高。

The traditional Natural Language Processing course mainly focuses on methods based on statistical learning theory,which does not match the current mainstream methods based on deep learning.In order to cultivate the talents who can meet the market needs,this paper discusses the theoretical and experimental contents of the Natural Language Processing course under the background of deep learning.In order to improve the effect of classroom teaching,the comparative teaching method is introduced.By comparing with methods based on statistical learning theory,students can deeply understand the advantages and disadvantages of methods based on deep learning.The teaching practices show that the comparative teaching method is suitable for Natural Language Processing course under the background of deep learning,and the teaching effect is significantly improved.