Date Lecture Topic Slides Homework Quiz
Jan 18 Intro to NLP lecture 1, GPT-3 demo Setting up the environment  
Jan 25 Lexical embeddings ML review, lecture 2 Sentiment analysis with logistic regression quiz 1
Feb 1 Neural networks 101 lecture 3 Neural networks from scratch quiz 2
Feb 8 Neural networks 201 lecture 4 Fully-connected neural networks for text classification quiz 3
Feb 15 Attention mechanism lecture 5, notes Language modeling quiz 4
Feb 22 No Class, Monday schedule      
Mar 1 Sequence to sequence networks lecture 6   quiz 5
Mar 8 No Class, Spring break      
Mar 15 Transfer Learning in NLP lecture 7 Machine Translation  
Mar 22 Guest Lecture, Alexey Romanov, Neural Ranking search, NLP over OCR   quiz 6
Mar 29 Pre-training Variants
Topics: Knowledge Representation in BERT		 lecture 8
lecture 8b		 BERT for classification, BERT for QA (optional, extra points)  
Apr 5 Effect of scale in NLP lecture 9 Research paper presentations  
Apr 12 Paper presentations   Supervised project work  
Apr 19 Guest Lecture, Albert Webson, Multitask Prompted Training   Supervised project work  
Apr 26 Guest Lecture, Mikhail Galkin, Graph neural networks   Supervised project work  
May 3 Presentations      
  • Homeworks are due at midnight on the day before the next lecture.
  • Quizzes are due immediately before the next lecture.
  • Homeworks must be submitted via Blackboard; you must submit a PDF of your homework and a link to a Github repository with your code.