ANLP: Accelerated Natural Language Processing

Welcome to Accelerated Natural Language Processing

Course summary

This course synthesizes ideas from linguistics and computer science to provide students with a fast-paced introduction to the field of natural language processing. We cover a range of foundational concepts, theoretical and computational models of language, and linguistic phenomena. We focus on what makes automatic processing of language unique and challenging: its statistical properties, complex structure, and pervasive ambiguity. We use English as the primary exemplar throughout, but also discuss similarities and differences to other languages, and the implications for computational models.

As we progress from lower levels of linguistic structure (words and morphemes) through syntax to semantics and discourse, we cover formal models and algorithms for representing and analysing these different types of structure (e.g., n-gram models, HMMs, probabilistic grammar, word embeddings, and basic neural networks). These methods form the conceptual foundation for understanding state-of-the-art approaches, which are covered in depth in the Semester 2 follow-on course NLU+. We also introduce methodological and ethical considerations (e.g., evaluation, data collection, algorithmic bias) that are important for research and practice in the field.

If you're wondering whether this course is appropriate for you, please see: ANLP: should I take this course?

Where do I find things?

On this site, you will find publicly available information, including all course materials other than the assessed coursework.

On the course Learn site (linked at the top of this page) you will find information that requires a university login:

• all information about assessment, including
  • instructions and downloads
  • due dates and late policy
  • links to submission inboxes
•  a link to the course discussion forum