NYUAD CS-AD 220 – Spring 2017
Natural Language Processing
Slides and Handouts
All slides and handouts will be available online HERE.
The field of natural language processing (NLP), also known as computational linguistics, is interested in the modeling and processing of human (i.e., natural) languages. This course covers foundational NLP concepts and ideas, such as finite state methods, n-gram modeling, hidden Markov models, part-of-speech tagging, context free grammars, syntactic parsing and semantic representations. The course will survey a range of NLP applications such as information retrieval, summarization and machine translation. Concepts taught in class will be reinforced in practice by hands-on assignments.
J+M: Daniel Jurafsky and James H. Martin. "Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition." (2nd Edition). Pearson Prentice Hall, 2008. The book is available at the bookstore.
NH: Nizar Habash. "Introduction to Arabic Natural Language Processing." Synthesis Lectures on Human Language Technologies. Morgan & Claypool Publishers, 2010. This book is available online (click HERE or HERE).
Components of the Final Grade: There will be four homework assignments and two exams (one mid-term and one final). The assignments are varied in form including on-paper exercises (such as walking through algorithms), hands-on programming, building systems using off-the-shelf tools, and data analysis. Assignments count for 55% (one earns 10% and three earn 15% each); exams count for 40% (20% midterm and 20% final); and class participation (asking questions and participating in discussions that demonstrate having read the assigned readings) earns 5%.
Participation and Attendance Policies: Attendance is required. Every unexcused absence (i.e., not pre-cleared with instructor, or not with medical documentation provided to instructor) will automatically cause one grade level drop. Participation is expected in class discussions of specific NLP problems and solutions in a way that demonstrates preparedness.
Assignment Submission Policies: All assignments are due at 11:59pm on the due date specified in syllabus. For late submissions, 10% will be deducted from the homework grade per each late day.
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