朴素贝叶斯与伯特:入门NLP课程的Jupyter笔记本作业

Proceedings of the Fifth Workshop on Teaching NLP Pub Date : 2021-06-01 DOI:10.18653/V1/2021.TEACHINGNLP-1.20

Jennifer Foster, Joachim Wagner

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引用次数: 1

摘要

我们描述了两本Jupyter笔记本，它们构成了都柏林城市大学最后一年级本科生自然语言处理(NLP)入门模块中两项作业的基础。笔记本向学生展示了如何使用多项朴素贝叶斯训练词袋极性分类器，以及如何使用BERT微调极性分类器。学生们将代码作为自己实验的起点。

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Naive Bayes versus BERT: Jupyter notebook assignments for an introductory NLP course

We describe two Jupyter notebooks that form the basis of two assignments in an introductory Natural Language Processing (NLP) module taught to final year undergraduate students at Dublin City University. The notebooks show the students how to train a bag-of-words polarity classifier using multinomial Naive Bayes, and how to fine-tune a polarity classifier using BERT. The students take the code as a starting point for their own experiments.

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Proceedings of the Fifth Workshop on Teaching NLP

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