Abstract
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.- Anthology ID:
- 2021.teachingnlp-1.20
- Volume:
- Proceedings of the Fifth Workshop on Teaching NLP
- Month:
- June
- Year:
- 2021
- Address:
- Online
- Editors:
- David Jurgens, Varada Kolhatkar, Lucy Li, Margot Mieskes, Ted Pedersen
- Venue:
- TeachingNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 112–114
- Language:
- URL:
- https://aclanthology.org/2021.teachingnlp-1.20
- DOI:
- 10.18653/v1/2021.teachingnlp-1.20
- Cite (ACL):
- Jennifer Foster and Joachim Wagner. 2021. Naive Bayes versus BERT: Jupyter notebook assignments for an introductory NLP course. In Proceedings of the Fifth Workshop on Teaching NLP, pages 112–114, Online. Association for Computational Linguistics.
- Cite (Informal):
- Naive Bayes versus BERT: Jupyter notebook assignments for an introductory NLP course (Foster & Wagner, TeachingNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2021.teachingnlp-1.20.pdf