Natural Language Processing (CS 445)

2021 Spring
Faculty of Engineering and Natural Sciences
Computer Sci.& Eng.(CS)
3
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Reyyan Yeniterzi reyyan@sabanciuniv.edu,
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English
Undergraduate
CS204 CS210
Formal lecture
Interactive,Learner centered,Project based learning
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CONTENT

This course studies the theory, design and implementation of natural language processing systems. Topics include text processing, regular expressions, statistical properties of text, edit distance, language modeling, text classification, sequence modeling, topic modeling, computational morphology, neural networks for NLP, chatbots, transfer learning for NLP.

OBJECTIVE

A student who succesfully fulfills the course requirements will be able to demonstrate:
1) To describe the statistical properties of text in natural language.
2) To implement programs that can process textual data and extract valuable information from it.
3) To apply well-known language processing techniques to text.
4) To explain the significance and principles of language modeling.
5) To develop machine learning models to classify documents, sub-documents or terms.
6) To assess the quality of natural language processing models applied to text.

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Midterm 30
Participation 15
Individual Project 55

RECOMENDED or REQUIRED READINGS

Optional Readings

Speech and Language Processing by Daniel Jurafsky and James Martin.
Foundations of Statistical Natural Language Processing by Christopher Manning and Hinrich Sch├╝tze
Natural Language Processing with Python by Steven Bird, Ewan Klein and Edward Loper