(M&S) ( available online, free within the Cornell network) Schuetze, Foundations of Statistical Natural Language Processing, Cambridge: MIT Press, 1999. Goldberg, Neural Network Methods in Natural Language Processing, 2017. Martin, Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, Second Edition, 2009.

Recommended: Michael Collins, Notes on Statistical NLP (on Michael's website).

Branavan (ASAPP)Īssignment 4 due, final exam out and due May 15 J&M 12.7, Nivre2003, / Amanda Stent and Anju / David Weiss J&M 5.1-5.3, 6, M&S 3.1, 9, 10.1-10.3, Collins: HMM, Collins: MEMMs (Sec 3), Collins: CRF (sec 4), Collins: Forward-backward, SOTA Taggers, TnT Tagger, Stanford Tagger J&M 25.4, 25.8, M&S 13.3, Collins: PBT, Statistical PBT, Pharaoh decoder J&M 25.5, M&S 13.1-13.2, Collins: IBM Models, IBM Models, Collins: EM (Sec 5-6), HMM alignments, IBM Model 2 EM Notebook J&M 4, M&S 6, Collins: LM, Smoothing, Char RNN W2v explained, word2vec, word2vec phrases, Hill2016, Turney2010 Primer, Back-prop, Deep Averaging Networks, Gradient Checks (briefly), Gradient Checks (in details) M&S 7.4,16.2-16.3, Collins: Naive Bayes (Sec 1-4), Collins: Log Linear (Sec 2), Ma圎nt, Baselines, CNN Classification Naive Bayes prior derivation

Short and Incomplete List of NLP Pointers.

If interested in tools and frameworks, see below for pointers to get your search started and questions answered. This course is not about using off-the-shelf NLP tools.

Possible topics include text classification, lexical semantics, language modeling, machine translation, tagging and sequence modeling, parsing, compositional semantics, summarization, question answering, language grounding, information extraction, and sentiment analysis. The goal of the course is to provide a deep understanding of the language of the field, including algorithms, core problems, methods, and data.

NLP is at the heart of many of today's most exciting technological achievements, including machine translation, automatic conversational assistants and Internet search.

This course constitutes a depth-first technical introduction to natural language processing (NLP). TA: Max Grusky, (office hours: Thursday 1pm, by Skype, coordinate via email) Instructor: Yoav Artzi, (office hours: Monday 5pm, Baron)

Index Spring 2017 CS5740: Natural Language Processing

Skype tutorial 2017