Reference books
- There is no official textbook for the course, but if you would like to read further about NLP, here are some good reference books on NLP:
- To learn more about deep learning
Debugging and learning about neural networks
Podcasts
- NLP highlights (from 2017 to 2023) with Matt Gardner, Pradeep Dasigi, and Waleed Ammar
- Deep learning for NLP
- Sequence models
- Static Word Embeddings
- Pretrained language models
- Using LLMs
- NLP pipelines
Tasks and datasets
A list of shared task datasets are provided below.
In some cases you can also extend your homework code to produce innovative project ideas for these tasks.
Shared Task Collections
Embeddings
Language models
Multitask Benchmarks
Question Answering
Math questions
Commonsense reasoning
CoNLL Shared Tasks
SemEval Shared Tasks
Classification Tasks
Parsing
Machine Translation
Unlabeled Data for Clustering, Language Models, etc.
Sentiment and Opinion Mining