Lecture 1 - Intro & Word Vectors
Lecture 2 - Neural Classifiers
Lecture 3 - Backpropagation and Neural Networks
Lecture 4 - Syntactic Structure and Dependency Parsing
Lecture 5 - Recurrent Neural Networks (RNNs)
Lecture 6 - Simple and LSTM RNNs
Lecture 7 - Translation, Seq2Seq, Attention
Lecture 8 - Self-Attention and Transformers
Lecture 10 - Prompting, Reinforcement Learning from Human Feedback
Lecture 11 - Natural Language Generation
Lecture 12 - Question Answering
Lecture 13 - Coreference Resolution
Lecture 14 - Insights between NLP and Linguistics