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Homework assignments

See Gradescope for the most up to date due dates.

Course topics outline


Make sure to reload this page to ensure you’re seeing the latest version. Readings should be done before the indicated class. The main textbooks are available free online:

Tentative schedule follows.

Thu 9/2: Introduction

Tue 9/7: Words, regexes, tokenization

Thu 9/9: Word probs and N-gram language models

Tue 9/14: Naive Bayes Text Classification

Thu 9/16: Naive Bayes Text Classification, continued

Tue 9/21: Logistic Regression Classification

Thu 9/23: Annotation and Labeling

Tue 9/28: On Data - Collection and Creation

Thu 9/30: On Data - Considerations

Tue 10/5: Classification Applications

Thu 10/7: Classification Applications, Final Project Discussion

Tue 10/12: Tagging, part 1: Parts of Speech and Named Entities

Thu 10/14: Tagging, part 2

Tue 10/19: Grammars and Syntactic Parsing

Thu 10/21: Syntactic Parsing Applications

Tue 10/26: Word Embeddings (I)

Thu 10/28: Word Embeddings (II)

Tue 11/2: Neural Networks

Thu 11/4: Midterm Review and Misc. Topics

Tue 11/9: In-class midterm

No class Thu 11/11 (holiday)

11/16-11/18: Pretrained Neural Language Models (BERT)

11/23-12/2: NLP Applications

Tue 12/7: Final presentations

Rest of semester

Tentative future dates. Subject to revision.

Tue 12/7: Posters/presentations

Last day of class! The poster or presentation session will take place during and around the standard lecture time.

Thu 12/16: Final project due (last day of finals)

Final project reports are due by the last day of the final exam period. Late days cannot be used.