What to expect:
This is a hands-on course for linguists or CS majors new to NLP. It will provide the general overview of the field and cover the basic text processing pipelines (corpus collection, tokenization, stemming, POS-tagging, chunking, syntactic and semantic parsing). It will also introduce the basics of machine learning, including hands-on sentiment classification experiments with scikit-learn, and statistical analysis and visualization of the results.
Pre-requisites:
The first week of the course will provide a hands-on introduction to the basics of NLP. We will cover corpus pre-processing pipelines, basic machine learning experiments on text classification, and analysis of their results. The course is aimed at linguists with only basic programming skills in Python, and will highlight in particular the problems with the current evaluation paradigms, dataset design, and general methodological challenges — the interdisciplinary areas in which their expertise is much needed.
Monday: Introduction to NLP: a brief overview of the field: [tutorial] [slides]
Tuesday: Basic NLP pipeline with Python (NLTK, SpaCy): [tutorial] [slides]
Wednesday: Lexical resources in Python: [tutorial] [slides]
Thursday: Count-based vector space models with Python [tutorial] [slides]
Friday: Introduction to machine learning with Python [tutorial] [slides]
