Learning Goals
- Effective modern methods for deep NLP
- Word vectors, FFNN, recurrent networks, attention
- Transformers, encoder/decoder, pre-training, post-training (RLHF, SFT), adaptation, interoperability, agents
- Big picture in HUMAN LANGUAGES
- why are they hard
- why using computers to deal with them are doubly hard
- Making stuff (in PyTorch)
- word meaning
- dependency parsing
- machine translation
- QA