Linguistic, mathematical, and computational fundamentals of natural language processing (NLP).
Topics include part of speech tagging, Hidden Markov models, syntax and parsing, lexical semantics, compositional semantics, machine translation, text classification, discourse and dialogue processing. Additional topics such as sentiment analysis, text generation, and deep learning for NLP.
Introduction to Natural Language Processing Jacob Eisenstein First Edition, October 2019 MIT Press ISBN: 9780262042840 https://github.com/jacobeisenstein/gt-nlp-class/blob/master/notes/eisenstein-nlp-notes.pdf
Speech and Language Processing Daniel Jurafsky and James Martin Third Edition, 2019 Prentice Hall https://web.stanford.edu/~jurafsky/slp3/
Approximately 50 pages of the textbooks
(CPSC 202 and CPSC 223) OR "permission of the instructor". All programming assignments are in Python.
Class logistics, Why is NLP hard, Methods used in NLP, Mathematical and probabilistic background, Linguistic background, Python libraries for NLP, NLP resources, Word distributions, NLP tasks, Preprocessing
Language Modeling, Noisy Channel, Hidden Markov Models, The Viterbi Algorithm, Statistical Part of Speech Tagging, Syntax and Parsing, Context-Free Grammars, CKY Parsing, the Penn Treebank, Parsing Evaluation, Dependency Syntax, Dependency Parsing, Features and Unification, Tree-Adjoining Grammars, Combinatory Categorial Grammars, Noun sequence parsing
Text Similarity, Stemming, WordNet, Word Similarity, Vector Semantics, Dimensionality Reduction, Representing Meaning, First Order Logic, Inference, Semantic Parsing, Abstract Meaning Representation, Sentiment Analysis
Question Answering, Text Summarization, Text Generation, Discourse Analysis, Dialogue Systems, Machine Translation, Syntax-based Machine Translation
Text Classification, Vector Classification, Linear Models, Text clustering
Perceptron, Word Embeddings, word2vec, Deep Neural Networks, Sentence Representations, Neural approaches to question answering, parsing, machine translation, summarization, etc., Transformers, BERT.
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