Core Topics
Below is a list of core topics that will be covered during the semester. The schedule is tentative and subject to change.
- NLP Basics
- Text Processing basics + Empirical laws
- Language Modeling + Smoothing
- Parts of Speech Tagging
- Syntax, Dependency Parsing
- Distributional Semantics, Word Embeddings
- Combining Logical and distributional semantics
- Introduction to Neural Networks
- Seq2Seq models, RNNs, LSTMs
- Introduction to attention mechanism, Transformers
- Large-scale pre-training and related models (BERT, GPT)
- Prompting, Debugging
- Neurosymbolic NLP